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Immune-surveillance over EBV and EBV-associated Burkitt lymphoma How does malaria alter immune- surveillance and how might this impact immunotherapeutic efficacy? Ann Moormann, PhD, MPH Associate Professor Department of Medicine

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Page 1: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Immune-surveillance over EBV and EBV-associated Burkitt lymphoma

How does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy

Ann Moormann PhD MPHAssociate Professor

Department of Medicine

OutlinePart I EBV and Cancers

Part II Translational ScienceEpidemiology of endemic Burkitt lymphomaWhat is the role of T cellsWhat is the role of NK cellsImplications for immunotherapy

I have no conflicts of interest to declare

EBV (HHV-4)

EBV was the first virus to be directly implicated in oncogenesis (endemic Burkitt lymphoma)

gt90 of adults worldwide are EBV infected (life-long herpes virus)

20 of human cancers are caused by an infectious agent and 80 of those are viral

EBV is associated with 1-2 of all cancers

List of EBV-associated malignancies (not always B cells)

Burkitt lymphoma (BL) non-Hodgkinrsquos lymphomas (NHL) Hodgkin lymphoma (HL) Nasopharyngeal carcinoma (NPC) Gastric adenocarcinoma (GC) Post-transplant lymphoproliferative disorder

(PTLD) Immuno-deficiency related cancers (IDL) TNK cell lymphomas

Is EBV important or incidental

EBV is not always present

Thompson AACR 2004

Part II endemic Burkitt lymphomaA tale of two infections

First described by Denis Burkitt in 1958

A COMBINED MEDICAL AND SURGICAL STAFF MEETING

will be held

on Wednesday 22nd March 1961 at 515 pm

IN THE COURTAULD LECTURE THEATRE

Mr DP Burkitt from Makerere College Uganda will talk on The Commonest Childrens Cancer in Tropical Africa A Hitherto Unrecognised Syndrome

Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong

Human Herpes Virus 4 (HHV4)

EBV

Primary infectionB cell

Blasting B cell

Latent infection

Reactivation

1

2

3

4

Epstein Barr virus (EBV)bull Herpesvirus (Herpesviridae HHV4)

Double strain DNA virusbull Latent proteins (5 EBNAs amp 2

LMPs)bull EBV type 1 and type 2 common in

African populations (EBNA-3 variants)

bull Transmitted in salivabull Asymptomatic infection young

children but causes Acute Infectious Mononucleosis in adolescents

bull Lytic reactivation (~44 proteins)bull EBV used to transform B cells into

lymphoblastoid cell line (LCL)bull Life long latent infection in B

cells (excellent immune evasion strategies)

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 2: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

OutlinePart I EBV and Cancers

Part II Translational ScienceEpidemiology of endemic Burkitt lymphomaWhat is the role of T cellsWhat is the role of NK cellsImplications for immunotherapy

I have no conflicts of interest to declare

EBV (HHV-4)

EBV was the first virus to be directly implicated in oncogenesis (endemic Burkitt lymphoma)

gt90 of adults worldwide are EBV infected (life-long herpes virus)

20 of human cancers are caused by an infectious agent and 80 of those are viral

EBV is associated with 1-2 of all cancers

List of EBV-associated malignancies (not always B cells)

Burkitt lymphoma (BL) non-Hodgkinrsquos lymphomas (NHL) Hodgkin lymphoma (HL) Nasopharyngeal carcinoma (NPC) Gastric adenocarcinoma (GC) Post-transplant lymphoproliferative disorder

(PTLD) Immuno-deficiency related cancers (IDL) TNK cell lymphomas

Is EBV important or incidental

EBV is not always present

Thompson AACR 2004

Part II endemic Burkitt lymphomaA tale of two infections

First described by Denis Burkitt in 1958

A COMBINED MEDICAL AND SURGICAL STAFF MEETING

will be held

on Wednesday 22nd March 1961 at 515 pm

IN THE COURTAULD LECTURE THEATRE

Mr DP Burkitt from Makerere College Uganda will talk on The Commonest Childrens Cancer in Tropical Africa A Hitherto Unrecognised Syndrome

Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong

Human Herpes Virus 4 (HHV4)

EBV

Primary infectionB cell

Blasting B cell

Latent infection

Reactivation

1

2

3

4

Epstein Barr virus (EBV)bull Herpesvirus (Herpesviridae HHV4)

Double strain DNA virusbull Latent proteins (5 EBNAs amp 2

LMPs)bull EBV type 1 and type 2 common in

African populations (EBNA-3 variants)

bull Transmitted in salivabull Asymptomatic infection young

children but causes Acute Infectious Mononucleosis in adolescents

bull Lytic reactivation (~44 proteins)bull EBV used to transform B cells into

lymphoblastoid cell line (LCL)bull Life long latent infection in B

cells (excellent immune evasion strategies)

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 3: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

EBV (HHV-4)

EBV was the first virus to be directly implicated in oncogenesis (endemic Burkitt lymphoma)

gt90 of adults worldwide are EBV infected (life-long herpes virus)

20 of human cancers are caused by an infectious agent and 80 of those are viral

EBV is associated with 1-2 of all cancers

List of EBV-associated malignancies (not always B cells)

Burkitt lymphoma (BL) non-Hodgkinrsquos lymphomas (NHL) Hodgkin lymphoma (HL) Nasopharyngeal carcinoma (NPC) Gastric adenocarcinoma (GC) Post-transplant lymphoproliferative disorder

(PTLD) Immuno-deficiency related cancers (IDL) TNK cell lymphomas

Is EBV important or incidental

EBV is not always present

Thompson AACR 2004

Part II endemic Burkitt lymphomaA tale of two infections

First described by Denis Burkitt in 1958

A COMBINED MEDICAL AND SURGICAL STAFF MEETING

will be held

on Wednesday 22nd March 1961 at 515 pm

IN THE COURTAULD LECTURE THEATRE

Mr DP Burkitt from Makerere College Uganda will talk on The Commonest Childrens Cancer in Tropical Africa A Hitherto Unrecognised Syndrome

Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong

Human Herpes Virus 4 (HHV4)

EBV

Primary infectionB cell

Blasting B cell

Latent infection

Reactivation

1

2

3

4

Epstein Barr virus (EBV)bull Herpesvirus (Herpesviridae HHV4)

Double strain DNA virusbull Latent proteins (5 EBNAs amp 2

LMPs)bull EBV type 1 and type 2 common in

African populations (EBNA-3 variants)

bull Transmitted in salivabull Asymptomatic infection young

children but causes Acute Infectious Mononucleosis in adolescents

bull Lytic reactivation (~44 proteins)bull EBV used to transform B cells into

lymphoblastoid cell line (LCL)bull Life long latent infection in B

cells (excellent immune evasion strategies)

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 4: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

List of EBV-associated malignancies (not always B cells)

Burkitt lymphoma (BL) non-Hodgkinrsquos lymphomas (NHL) Hodgkin lymphoma (HL) Nasopharyngeal carcinoma (NPC) Gastric adenocarcinoma (GC) Post-transplant lymphoproliferative disorder

(PTLD) Immuno-deficiency related cancers (IDL) TNK cell lymphomas

Is EBV important or incidental

EBV is not always present

Thompson AACR 2004

Part II endemic Burkitt lymphomaA tale of two infections

First described by Denis Burkitt in 1958

A COMBINED MEDICAL AND SURGICAL STAFF MEETING

will be held

on Wednesday 22nd March 1961 at 515 pm

IN THE COURTAULD LECTURE THEATRE

Mr DP Burkitt from Makerere College Uganda will talk on The Commonest Childrens Cancer in Tropical Africa A Hitherto Unrecognised Syndrome

Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong

Human Herpes Virus 4 (HHV4)

EBV

Primary infectionB cell

Blasting B cell

Latent infection

Reactivation

1

2

3

4

Epstein Barr virus (EBV)bull Herpesvirus (Herpesviridae HHV4)

Double strain DNA virusbull Latent proteins (5 EBNAs amp 2

LMPs)bull EBV type 1 and type 2 common in

African populations (EBNA-3 variants)

bull Transmitted in salivabull Asymptomatic infection young

children but causes Acute Infectious Mononucleosis in adolescents

bull Lytic reactivation (~44 proteins)bull EBV used to transform B cells into

lymphoblastoid cell line (LCL)bull Life long latent infection in B

cells (excellent immune evasion strategies)

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 5: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Is EBV important or incidental

EBV is not always present

Thompson AACR 2004

Part II endemic Burkitt lymphomaA tale of two infections

First described by Denis Burkitt in 1958

A COMBINED MEDICAL AND SURGICAL STAFF MEETING

will be held

on Wednesday 22nd March 1961 at 515 pm

IN THE COURTAULD LECTURE THEATRE

Mr DP Burkitt from Makerere College Uganda will talk on The Commonest Childrens Cancer in Tropical Africa A Hitherto Unrecognised Syndrome

Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong

Human Herpes Virus 4 (HHV4)

EBV

Primary infectionB cell

Blasting B cell

Latent infection

Reactivation

1

2

3

4

Epstein Barr virus (EBV)bull Herpesvirus (Herpesviridae HHV4)

Double strain DNA virusbull Latent proteins (5 EBNAs amp 2

LMPs)bull EBV type 1 and type 2 common in

African populations (EBNA-3 variants)

bull Transmitted in salivabull Asymptomatic infection young

children but causes Acute Infectious Mononucleosis in adolescents

bull Lytic reactivation (~44 proteins)bull EBV used to transform B cells into

lymphoblastoid cell line (LCL)bull Life long latent infection in B

cells (excellent immune evasion strategies)

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 6: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

EBV is not always present

Thompson AACR 2004

Part II endemic Burkitt lymphomaA tale of two infections

First described by Denis Burkitt in 1958

A COMBINED MEDICAL AND SURGICAL STAFF MEETING

will be held

on Wednesday 22nd March 1961 at 515 pm

IN THE COURTAULD LECTURE THEATRE

Mr DP Burkitt from Makerere College Uganda will talk on The Commonest Childrens Cancer in Tropical Africa A Hitherto Unrecognised Syndrome

Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong

Human Herpes Virus 4 (HHV4)

EBV

Primary infectionB cell

Blasting B cell

Latent infection

Reactivation

1

2

3

4

Epstein Barr virus (EBV)bull Herpesvirus (Herpesviridae HHV4)

Double strain DNA virusbull Latent proteins (5 EBNAs amp 2

LMPs)bull EBV type 1 and type 2 common in

African populations (EBNA-3 variants)

bull Transmitted in salivabull Asymptomatic infection young

children but causes Acute Infectious Mononucleosis in adolescents

bull Lytic reactivation (~44 proteins)bull EBV used to transform B cells into

lymphoblastoid cell line (LCL)bull Life long latent infection in B

cells (excellent immune evasion strategies)

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 7: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Part II endemic Burkitt lymphomaA tale of two infections

First described by Denis Burkitt in 1958

A COMBINED MEDICAL AND SURGICAL STAFF MEETING

will be held

on Wednesday 22nd March 1961 at 515 pm

IN THE COURTAULD LECTURE THEATRE

Mr DP Burkitt from Makerere College Uganda will talk on The Commonest Childrens Cancer in Tropical Africa A Hitherto Unrecognised Syndrome

Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong

Human Herpes Virus 4 (HHV4)

EBV

Primary infectionB cell

Blasting B cell

Latent infection

Reactivation

1

2

3

4

Epstein Barr virus (EBV)bull Herpesvirus (Herpesviridae HHV4)

Double strain DNA virusbull Latent proteins (5 EBNAs amp 2

LMPs)bull EBV type 1 and type 2 common in

African populations (EBNA-3 variants)

bull Transmitted in salivabull Asymptomatic infection young

children but causes Acute Infectious Mononucleosis in adolescents

bull Lytic reactivation (~44 proteins)bull EBV used to transform B cells into

lymphoblastoid cell line (LCL)bull Life long latent infection in B

cells (excellent immune evasion strategies)

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 8: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

First described by Denis Burkitt in 1958

A COMBINED MEDICAL AND SURGICAL STAFF MEETING

will be held

on Wednesday 22nd March 1961 at 515 pm

IN THE COURTAULD LECTURE THEATRE

Mr DP Burkitt from Makerere College Uganda will talk on The Commonest Childrens Cancer in Tropical Africa A Hitherto Unrecognised Syndrome

Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong

Human Herpes Virus 4 (HHV4)

EBV

Primary infectionB cell

Blasting B cell

Latent infection

Reactivation

1

2

3

4

Epstein Barr virus (EBV)bull Herpesvirus (Herpesviridae HHV4)

Double strain DNA virusbull Latent proteins (5 EBNAs amp 2

LMPs)bull EBV type 1 and type 2 common in

African populations (EBNA-3 variants)

bull Transmitted in salivabull Asymptomatic infection young

children but causes Acute Infectious Mononucleosis in adolescents

bull Lytic reactivation (~44 proteins)bull EBV used to transform B cells into

lymphoblastoid cell line (LCL)bull Life long latent infection in B

cells (excellent immune evasion strategies)

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 9: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong

Human Herpes Virus 4 (HHV4)

EBV

Primary infectionB cell

Blasting B cell

Latent infection

Reactivation

1

2

3

4

Epstein Barr virus (EBV)bull Herpesvirus (Herpesviridae HHV4)

Double strain DNA virusbull Latent proteins (5 EBNAs amp 2

LMPs)bull EBV type 1 and type 2 common in

African populations (EBNA-3 variants)

bull Transmitted in salivabull Asymptomatic infection young

children but causes Acute Infectious Mononucleosis in adolescents

bull Lytic reactivation (~44 proteins)bull EBV used to transform B cells into

lymphoblastoid cell line (LCL)bull Life long latent infection in B

cells (excellent immune evasion strategies)

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 10: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

EBV

Primary infectionB cell

Blasting B cell

Latent infection

Reactivation

1

2

3

4

Epstein Barr virus (EBV)bull Herpesvirus (Herpesviridae HHV4)

Double strain DNA virusbull Latent proteins (5 EBNAs amp 2

LMPs)bull EBV type 1 and type 2 common in

African populations (EBNA-3 variants)

bull Transmitted in salivabull Asymptomatic infection young

children but causes Acute Infectious Mononucleosis in adolescents

bull Lytic reactivation (~44 proteins)bull EBV used to transform B cells into

lymphoblastoid cell line (LCL)bull Life long latent infection in B

cells (excellent immune evasion strategies)

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 11: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Geographic overlap with malariafirst cancer to be mapped

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 12: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Sporozoites

Merozoites

Ring

RBCRuptured iRBC

Gametocytes

Plasmodium falciparum malariabull Complex life cycle ndash infects

liver cells and red blood cells (RBC)

bull 228 Mb genome 14 chromosomes amp 2400 proteins (allelic variants)

bull Common parasitic infection for children living in Africa

bull Number one cause of death for children under 5 years of age

bull Semi-protective immunity develops after repeated infections which allows an acute infection to become a chronic infection of mature RBC (no APC)

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 13: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

The face of Burkitt lymphoma todayo Most common pediatric cancer in equatorial

Africao Annual incidence 2-5 per 100000 childreno Peak incident age 5-9 yearso Extranodal monoclonal B cell tumoro High tumor proliferation indexo Tumor presentation in abdomen as well as

jawo Conventional chemotherapy used without

the need for surgery or radiotherapyo Endemic BL in Africa gt 90 EBV-associated

tumoro Curious note ~10 of eBL are EBV-negative

tumors if you only counted the incidence of non-EBV BL in Africa it would be the same as sporadic BL in the US

Rochford Cannon Moormann NatRevMicro 2005

Buckle IJC 2017

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 14: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Old Literature in support of malaria-induced immuno-suppression model

Gambian patients with acute malaria were unable to control outgrowth of EBV-transformed cells measured by an in vitro regression assay (Whittle Nature 1984)

Healthy adults living in malaria holoendemic regions of Papua New Guinea had impaired EBV-specific T cells responses measured by regression assay (Moss Int J Canc 1983)

Both were cross-sectional studies

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 15: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Focus on testing the immune ldquosuppressionrdquo hypothesis

Children who have had chronic malaria infections develop qualitative and quantitative differences in their immune control over EBV compared to those who have not been exposed to malariaMy immunology studies started in 2002 ~ 20 years since last publications on this topic

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 16: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Study design Healthy children with and without malaria exposure

Kisumu

Nandi

Nandi CountyHypoendemic malaria transmissionLow incidence of eBLSample size = 130 children ages 1-14 years

Kisumu CountyHoloendemic malariaHigh incidence eBL Sample size = 106 children ages 1-14 years

Rainey TMIH 2007

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 17: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Village-based age-structured cross-sectional studies

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 18: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

UMMS-KEMRI labin Kisumu

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 19: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

How do you measure EBV infections

IgM and IgG antibody titers to a panel of EBV antigens1 Viral Capsid Antigen (VCA)2 Early Antigen (EA)3 EBV Nuclear Antigen 1 (EBNA1)4 Zta Reactive Antigen (ZEBRA)

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 20: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control

Moormann JID 2005

(-198 +- 046)

(034 +- 056)

(1 +- 029)

(210 +- 038)

(569 +- 131)

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 21: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria

Reynaldi et al JID 2016Piriou et al JID 2012

Kisumu Nandi

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 22: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Anemia Cerebral malaria

Anti-disease immunity

Immune protection threshold achieved

Anti-infection immunity

Eve

nt fr

eque

ncy

How do you measure malaria infections in children

Malaria morbidity and mortality highest lt 5 years

BL incidence highest in children 5-9 years old

Modified from Stoute Trends Parastiology 2005

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 23: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Luminex serology profiles unsupervised hierarchical clustering

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 24: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Early-age primary EBV infection and malaria-associated EBV reactivation

Highest prevalence of symptomatic Pf-malaria

Peak age-incidence of eBL

Age in years

What is the cumulative impact of Plasmodium falciparum malaria co-infections on immunity to Epstein Barr virus

Development of premunition to malaria semi-protective immunity permissive of asymptomatic parasitemia

Erosion of EBV-specific T cell immunosurveillance

Rochforld and Moormann Curr Trop Microbiol Immunol 2015

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 25: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

How is EBV-specific T cell immunity influenced by malaria exposure

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 26: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies

bull Immunodominant epitopes to EBV lytic and latent antigens

bull HLA Class I restricted IFN-γ responses mediated by CD8+ T cells

bull Stable IFN-γ responses in healthy adults who are EBV seropositive with low to no detectable virus in peripheral circulation

bull EBNA1 induces IFN-γ responses primarily from CD4+ T cells but also cross-priming for CD8 + T cells

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 27: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

T cell immunity to EBV antigens

bull Latent genes bull 2 non-translated small RNAs (EBER-1 and -2) bull 6 nuclear proteins (EBNA-1 EBNA-2 EBNA-

3A -3B -3C and EBNA-LP)bull 3 latent membrane proteins (LMP-1 -2A and -

2B) bull Lytic genes ~70 (Bam H1 fragments) BZLF1

BMLF1 BMRF1 BRLF1 BARF0 BHRF1 gp85 gp110 gp350

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 28: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Demographics of Kenyan study population

Age Group (years) 1-4 5-9 10-14 All ages n () n () n () n ()

Kisumu No of subjects 34 (32) 37 (35) 35 (33) 106 (100) EBV seropositive 32 (94) 37 (100) 35 (100) 104 (98) Mean hemoglobin (gdl) 972 1225 1251 1153 Subjects with Pf positive smear 26 (77) 27 (73) 29 (83) 82 (77) Mean body temperature (oC) 3680 3676 3689 3682

Nandi No of subjects 39 (30) 50 (38) 41 (32) 130 (100) EBV seropositive 36 (92) 50 (100) 41 (100) 127 (98) Mean hemoglobin (gdl) 1218 1282 1329 1277 Subjects with Pf positive smear 3 (8) 7 (14) 11 (26) 21 (16) Mean body temperature (oC) 3721 3718 3709 3716

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent

Age Group (years)

1-4

5-9

10-14

All ages

n ()

n ()

n ()

n ()

Kisumu

No of subjects

34 (32)

37 (35)

35 (33)

106 (100)

EBV seropositive

32 (94)

37 (100)

35 (100)

104 (98)

Mean hemoglobin (gdl)

972

1225

1251

1153

Subjects with Pf positive smear

26 (77)

27 (73)

29 (83)

82 (77)

Mean body temperature (oC)

3680

3676

3689

3682

Nandi

No of subjects

39 (30)

50 (38)

41 (32)

130 (100)

EBV seropositive

36 (92)

50 (100)

41 (100)

127 (98)

Mean hemoglobin (gdl)

1218

1282

1329

1277

Subjects with Pf positive smear

3 (8)

7 (14)

11 (26)

21 (16)

Mean body temperature (oC)

3721

3718

3709

3716

Page 29: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

HLA Class I-restricted EBV peptide selection for IFN-γ ELISPOT assays

EBV protein Cycle Amino Acids Peptide Sequence HLA-restriction

BZLF1 Lytic 190-197 RAK FKQ LL HLA B8

BMLF1 Lytic 280-288 GLC TLV AML HLA A2

BRLF1 Lytic 148-156 RVR AYT YSK HLA A3

BRLF1 Lytic 28-37 DYC NVL NKE F HLA A24

EBNA 3A Latent 379-387 RPP IFI RRL HLA B7

EBNA 3C Latent 258-266 RRI YDL IEL HLA B27

EBNA 3B Latent 217-225 TYS AGI VQI HLA A24

EBNA 3A Latent 325-333 FLR GRA YGL HLA B8

EBNA 3A Latent 596-604 SVR DRL ARL HLA A2

EBNA 3A Latent 603-611 RLR AEA QVK HLA A3

EBNA 3B Latent 657-666 VEI TPY KPT W HLA B44

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 30: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area

1-4 years

5-9 years

10-14 years

Holoendemic malariaHypoendemic malaria

84 8778

94

50

3444

31

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

92 94 9488

22

53

19

41

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

8997

86 89

3442

2631

0

20

40

60

80

100

PHA PPD EBV lytic EBV latent

p-value lt 003

Moormann et al JID 2007

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 31: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Chart6

Kisumu
Nandi
84
87
78
94
50
34
44
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 32: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
Page 33: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Page 34: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Page 35: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Page 36: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Page 37: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 82 97 31 22
Nandi 76 85 59 45
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Page 38: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 39: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 40: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 41: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 42: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 43: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 44: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Chart7

Kisumu
Nandi
92
94
94
88
22
53
19
41

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 45: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
Page 46: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Page 47: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Page 48: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Page 49: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Page 50: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 91 89 40 31
Nandi 85 78 34 27
Page 51: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 52: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 53: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 54: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 55: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 56: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 57: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Chart8

Kisumu
Nandi
89
97
86
89
34
42
26
31

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
PHA PHA
PPD PPD
EBV lytic EBV lytic
EBV latent EBV latent
Page 58: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

demographics

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Age group (years)
1-4 5-9 10-14 all ages
Holoendemic malaria site n () n () n () n ()
No of study participants 34 36 36 106
EBV seropositive 32 (94) 35 (97) 36 (100) 104 (98) 94 97 100 98
P falciparum parasitemia 26 (81) 26 (74) 30 (83) 82 (79) 81 74 83 79
Mean hemoglobin (gdl) 98 122 125 116
Mean body temperature 369 367 370 369
Highland malaria site
No of study participants 39 48 43 130
EBV seropositive 36 (92) 48 (100) 43 (100) 127 (98) 92 100 100 98
P falciparum parasitemia 3 (8) 7 (15) 11 (26) 21 (16) 8 15 26 16
Mean hemoglobin (gdl) 12 129 135 128
Mean body temperature 372 373 37 372
Endemic Burkitts lymophoma patients
No of study participants 19 61 13 93
EBV seropositive 19 61 13 93
P falciparum parasitemia 10 22 3 35 53 36 23 38
Mean hemoglobin (gdl) 103 102 105 103
Page 59: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

nice table s1s2BL

ampA
Page ampP

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Nandi Kisumu BL patients
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value positive (responderstotal) responders total chi-square p-value (BL v Kisumu)
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458 41 7 17 025 061
5-9 59 29 49 31 11 36 6827 00151 41 26 64 100 032
10-14 34 14 41 40 14 35 0278 06394 42 5 12 001 091
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187 53 9 17 146 023
5-9 45 22 49 22 8 37 5028 00390 45 29 64 567 0017
10-14 27 11 41 31 11 35 0194 08005 25 3 12 032 057
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529 93
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years EBV lytic EBV latent
Kisumu 47 35
Nandi 29 29
BL 41 53
5-9 years EBV lytic EBV latent
Kisumu 31 22
Nandi 59 45
BL 41 45
10-14 years EBV lytic EBV latent
Kisumu 40 31
Nandi 34 27
BL 42 25
Page 60: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

nice table s1s2BL

Kisumu
Nandi
BL

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Page 61: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

nice table s1s2

Kisumu
Nandi
BL
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Page 62: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi
BL
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Page 63: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
ampA
Page ampP
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Nandi Kisumu
Stimulant Age group (yrs) positive (responderstotal) responders total percent positive responders total chi-square p-value
EBV lytic peptide pool 0-4 29 11 38 47 16 34 2511 01458
5-9 59 29 49 31 11 36 6827 00151 128
10-14 34 14 41 40 14 35 0278 06394 105
EBV latent peptide pool 0-4 29 11 38 35 12 34 0332 06187
5-9 45 22 49 22 8 37 5028 00390
10-14 27 11 41 31 11 35 0194 08005
PHA 0-4 76 29 38 82 28 34 0397 05740
5-9 92 45 49 89 33 37 0175 07208
10-14 85 35 41 91 32 35 0665 04938
PMA+I 0-4 32 12 38 47 16 34 1809 02284
5-9 41 20 49 46 17 37 0226 06654
10-14 49 20 41 54 19 35 0229 06529
PPD 0-4 84 31 37 79 27 34 0226 07617
5-9 85 41 48 97 36 37 3459 01300
10-14 78 32 41 89 31 35 1474 03600
significant p-value lt005
Percent population responding
0-4 years PHA PPD EBV lytic EBV latent
Kisumu 84 78 50 44
Nandi 87 94 34 31
5-9 years PHA PPD EBV lytic EBV latent
Kisumu 92 94 22 19
Nandi 94 88 53 41
10-14 years PHA PPD EBV lytic EBV latent
Kisumu 89 86 34 26
Nandi 97 89 42 31
Page 64: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Nandi
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 65: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Nandi
Kisumu
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 66: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Nandi
Kisumu
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 67: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 68: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 69: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins
Kisumu
Nandi

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 70: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

HLA Class I Tetramer specificity of T cells

Tube 1 FLY (LMP2) CMV (pp65) YLL (LMP1) CLG (LMP2)Tube 2 FLY (LMP2) YVL (BRFL1) GLC (BMLF1) LLD

(EBNA3C)

Or another way to think about the HLA-A2 panelLatent antigen peptides to LMP1 LMP2 x 2 and EBNA3CLytic antigen peptides to BRLF1 and BMFL1

Collaboration with Pratip Chattopadhyay and David Price

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 71: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0017

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0079

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

981e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 691e-3

0 103 104 105

ltG560-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 795e-3

0 103 104 105

ltV605-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8

0029

0 103 104 105

ltV800-Agt tetramer

0

103

104

105

ltG61

0-A

gt c

d8

0017

0 103 104 105

ltV565-Agt tet

0

103

104

105

ltG61

0-A

gt c

d8 0037

FLY YLL CMV CLG

FLY GLC YVL LLD

Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 72: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

0

0

0

0

0

0

0

0

0

0

0

0

PD1

CD

27

CC

R7

CD

127

CD45RO CD45RO CD57 CD45RO

Overlay of EBV-specific CD8 T cells by phenotype

Each color dot represents a CD8 T cell specific for an EBV-peptide HLA-A2 Tetramer

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 73: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Qualitative differences exists between EBV-specific lytic and latent T cellsubsets

Chattopadhyay JV 2013

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 74: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Chattopadhyay JV 2013

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 75: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Conclusion from tetramer studies

bull Children exposed to chronic malaria infections had fewer memory EBV-specific T-cells that were more differentiated and less capable of homeostatic proliferation compared to those from the hypoendemic malaria area

bull Malaria has a specific effect on EBV-T cells in contrast to CMV or bulk T cells which did not differ between groups (data not shown)

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 76: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Persistent malaria exposure is associated with the generation of adistinct population of CD8dim T cells

Yves FalangaFalanga JCI Insight 2018

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 77: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

What is the impact of chronic malaria exposure on CD8 T cell function

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 78: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 79: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Summary of T cell studies to date

bull The phenotype and function of CD8 T cells change over time in malaria exposed children compared to non-malaria exposed children

bull CD4 T cells seem to be influenced by age but not by malaria exposure

Next stepsbull Functional implications for EBV immune surveillancebull Are they present as Tumor infiltrating lymphocytes in

eBL patients

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 80: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Which cells are making IFN-γ to EBVin young children if not T cells

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 81: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

each color represents a marker

each shade represents the intensity of the marker

Dimensionality reduction clustering t-SNE visualization

Step 1 ACCENSE ndash multidimensional principal components analysis (PCA) that clustering cells by expression of surface and intracellular markers

Step 2 Interrogate phenotype of cell clusters by multiparameter flow cytometry

Step 3 Isolate populations of interest for single cell RNAseq

Step 4 Link immune cell type and function with clinical status and epidemiology Track changes in immune profile as child ages or during course of chemotherapy

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 82: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Iterated heat map for every single markers

ACCENSE Automated Classification of Cellular Expression by Nonlinear Stochastic Embedding Shekhar PNAS 2014

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 83: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

WHAT IS THE ROLE OF NATURAL KILLER (NK) CELLS IN EBV IMMUNOSURVEILLANCE IN YOUNG CHILDREN

bull How do Natural Killer (NK) cells contribute to control of EBV during early-age primary infections and during lytic reactivation in young children

bull How do Plasmodium falciparum malaria co-infections influence the balance between NK and T cell control over EBV-infected B cells

bull What is the role of NK cells in eBL pathogenesis versus survival

Catherine Forconipost-doc

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 84: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

What is the functional capacity of NK cells in children with BL

NK cells and Cancer Morvan and Lanier 2016

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 85: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Nandi (normal control group)=gt Children EBV+Malaria-

Kisumu=gt Children EBV+Malaria+

Burkitt lymphoma (BL) patients (cases) Red dots indicate home of children diagnosed with Burkitt Lymphoma=gt BL+EBV+Malaria+

Kenya

Buckle et al International Journal of Cancer 2016 Sep 15139(6)1231-40

Study Design BL cases matched to 2 controls

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 86: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

CHARACTERIZATION OF NK CELLS (CD56+CD3-) WITHIN OUR STUDY POPULATIONS

bull KIRs (Inhibition and Activation)bull Natural Cytotoxicity Receptors (NCRs)

bull CD16 bull NKp46 NKp30

bull CD94NKG2 familly receptorsbull NKG2A (Inhibition)bull NKG2C (Activation)

bull NK cell Activation Receptors (NARs)bull NKG2Dbull 2B4(CD244) et NKTBNKTAbull DNAM-1(CD226)bull CRACCbull CD160bull CD161

bull Activating NK cellsbull CD57 (memory-like NK subset when associated with NKG2C)bull CD69 bull CD25bull NKp44

IFNgMIP1bTNFaCD107aPerforinGranzyme ab

Phenotypic markers Functional markers

Collaboration with Galit Alter

Four panel flow experiments

she used for CMV (Cosgrove et Al 2014)

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 87: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

NATURAL KILLER CELLSbull Commonly described as CD3- lymphocytes NK cells are usually gated

on CD56+ cells bull Can be supplemented by CD16 or NKp46 staining in flow cytometry

CD56brightCD16neg

CD56brightCD16pos

CD56dimCD16pos

CD56dimCD16neg

ldquoimmaturerdquo NK cells

ldquomaturerdquo NK cells

FCyIII Antibody-Dependent Cellular Cytotoxicity

NCA

M-1

Adh

esio

n m

olec

ule

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 88: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

INNATE BUT WITH ADAPTIVE FEATURES

Multiple ldquosubsetsrdquo within CD56dimCD16pos NK cells

Canonical NK cells Cytotoxic Immunoregulatory subset

Adaptive NK cells Effector subset trained for Immuno-surveillance

ldquoMemory-likerdquo NK cells Faster cytokinic and cytotoxic responses

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 89: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

NK CELLS IN KENYAN CHILDREN

Forconi et al Blood Advances 2018

EBV+Malaria- EBV+Malaria+

After phenotype analysis neither canonical neither ldquomemory-likerdquo profile

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 90: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Picture for BL survivorsNK CD56brightCD16neg increased andNK CD56negCD16pos decreased (restoration to lsquonormalrsquo)

CD5

6

CD16

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 91: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

CD56NEGCD16POS

HIGHEST PROPORTION IN

BL PATIENTS WITH HIGHER EBV LOADS

CD56

CD16

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 92: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

KIR3DL1 (NK inhibition signal) increases with malariaEBV and BL diagnosis

Inhibition signal

Farag 2002 Blood

Saunders 2015 Imm Reviews

NKG2A

CD94

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

o

f po

siti

ve c

ells

NKG2A important for AIM

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 93: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

NK activation

Inhibition of NK cells

Exhaustion of NK cells

Strong similarities in genes expression between CD56negCD16pos and CD56dimCD16pos NK cells

NK cytotoxicity

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 94: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

The ultimate clinical question How do we design NK immunotherapy for these children

Pahl ImmunoBio 2017

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 95: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL

1What cell types control EBV infections in young childrenbull Relative contributions by Innate unconventional T cells and

effector-memory T cellsbull Does this shift as child ages (and DC mature) to become more

adult-like EBV-specific immunity2When do malaria (or other immune-modulating)

infections adversely impact EBV immunitybull Malaria prevents efficient priming to EBV or does it

incrementally eroded anti-virial immunity3What mediates EBV-specific immunity in children

diagnosed with eBL bull Are immune-defects specific to EBVbull Do they persist or can they be lsquorebootedrsquo after chemotherapy

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 96: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Itrsquos Treg

Itrsquos NK cells

Itrsquos antibodies

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 97: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL

Hyper-responsive

Hypo-responsive

Pathogen clearance but risk of immuno-pathologyorchronic infection with lsquomutedrsquo immunity

Malaria

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 98: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Questions to ponder for treating eBL in Africa

bull Which immuno-therapeutic approaches should be taken for this EBV-associated cancer

bull Are there special considerations related to immune response and regulation in children that differ from adults

bull Which parasitic infections are immune modulating enough to be able to influence response to an immunotherapy for eBL(is this a pre-existing condition)

bull What are the implications for immunotherapies for eBL and EBV vaccines to prevent this pediatric cancer in Africa

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60
Page 99: Immune-surveillance over EBV and EBV-associated Burkitt ... · Healthy adults living in malaria holoendemic regions of ... 3A, -3B, -3C and EBNA-LP). • 3 latent membrane proteins

Ragon Institute of MGH MIT and Harvard Cormac Cosgrove Galit AlterUMass Moormann Lab

Catherine (Cat) Forconi

Priya Shaikumar Lakshmi

Joslyn Foley (City of Hope)

Geoff Buckle (UCSF)

Kenya Medical Research Institute John Michael Ongrsquoecha

Cliff Oduor

Peter Oluoch

Erastmus Kirwa

Research funded byNIH NCI CA134051 (Moormann)NIH NCI CA108609 CA101741 (Muumlnz)Thrasher Research Fund (Moormann)Denis Burkitt Fellowship (Moormann)University of Massachusetts Center for Clinical and Translational Science (UL1TR001453)(AMM and JAB)

Direct Relief International Andrew Schroeder

Kenya Ministry of Health (JOORTH) Juliana Otieno

Pamella Omollo

Nursing staff and parents of BL patients

University of Zurich Christian Muumlnz

All the children their family and the medical staff

UMass collaborators Burkittrsquos Project Jeff Bailey Yasin Kaymaz Leslie Berg Rachel Gerstein

  • Immune-surveillance over EBV and EBV-associated Burkitt lymphomaHow does malaria alter immune-surveillance and how might this impact immunotherapeutic efficacy
  • Outline
  • EBV (HHV-4)
  • List of EBV-associated malignancies (not always B cells)
  • Is EBV important or incidental
  • EBV is not always present
  • Slide Number 7
  • First described by Denis Burkitt in 1958
  • Virus isolated from BL tumor in 1964 by Tony Epstein Yvonne Barr and Bert Achong
  • Slide Number 10
  • Geographic overlap with malariafirst cancer to be mapped
  • Slide Number 12
  • The face of Burkitt lymphoma today
  • Old Literature in support of malaria-induced immuno-suppression model
  • Focus on testing the immune ldquosuppressionrdquo hypothesis
  • Study design Healthy children with and without malaria exposure
  • Village-based age-structured cross-sectional studies
  • UMMS-KEMRI labin Kisumu
  • How do you measure EBV infections
  • Higher EBV loads in Kisumu and eBL children by qPCR surrogate for immune control
  • Longitudinal studies reveal higher cumulative EBV burden in children with chronic malaria
  • How do you measure malaria infections in children
  • Luminex serology profiles unsupervised hierarchical clustering
  • Slide Number 24
  • Slide Number 25
  • Characteristics of T cell mediatedEBV immunosurveillance learned from adult studies
  • T cell immunity to EBV antigens
  • Demographics of Kenyan study population
  • HLA Class I-restricted EBV peptide selection for IFN- ELISPOT assays
  • EBV-specific IFN-γ ELISPOT responses deficient in children 5-9 yrs old from malaria holoendemic area
  • HLA Class I Tetramer specificity of T cells
  • Example of EBV-specificity and frequency of CD8 T cells by tetramer staining for an individual
  • Slide Number 33
  • Qualitative differences exists between EBV-specific lytic and latent T cell subsets
  • Slide Number 35
  • Conclusion from tetramer studies
  • Persistent malaria exposure is associated with the generation of a distinct population of CD8dim T cells
  • What is the impact of chronic malaria exposure on CD8 T cell function
  • CD8 T cell effector function is significantly diminished in children after prolonged exposure to malaria
  • Summary of T cell studies to date
  • Slide Number 41
  • Dimensionality reduction clustering t-SNE visualization
  • Iterated heat map for every single markers
  • What is the role of Natural Killer (NK) cells in EBV immunosurveillance in young children
  • Slide Number 45
  • Slide Number 46
  • Characterization of NK cells (CD56+CD3-) within our study populations
  • Natural Killer Cells
  • Innate but with adaptive features
  • Slide Number 50
  • Slide Number 51
  • CD56negCD16poshighest proportion in BL patients with higher EBV loads
  • Slide Number 53
  • Slide Number 54
  • Slide Number 55
  • Immune surveillance (anti-viral and anti-tumor) questions to ponder for eBL
  • Slide Number 57
  • Is there an immunologic balance achieved to protect children against malaria that puts children at risk for EBV-associated BL
  • Questions to ponder for treating eBL in Africa
  • Slide Number 60