análisis automático. estudio inicial (lst) y clasificación
TRANSCRIPT
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Análisis automático. Estudio inicial (LST) de los
síndromes linfoproliferativos crónicos T y NK
Teoría
Julia Almeida MD PhDCentro de Investigación del Cáncer, Universidad de Salamanca / IBSAL & CIBERONC
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Análisis automático. Estudio inicial (LST) de los síndromes linfoproliferativos crónicos T y NK
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Análisis automático. Estudio inicial (LST) de los síndromes linfoproliferativos crónicos T y NK
Chronic lymphoproliferative disorders
Large and heterogeneous group of disorders characterized by
proliferation and accumulation of morphologic and
immunophenotypic mature lymphocytes in diverse locations
Classification is initially based on lymphoid lineage
assessment
B-cell
CD19+
CD20+
Igs+
T- & NK- cells
CD3+
CD7+
CD4+/CD8+
CD3-
CD7+
CD56+
CD16+
Consequently, build upon morphologic, pathologic, immunophenotypic, genetic,
epidemiologic and clinical features (WHO2017 Classification)
Courtesy of Juan Flores MD PhD
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Chronic lymphoproliferative disorders: WHO2017 classificationCLL/small lymphocytic lymphoma
B-cell prolymphocytic leukaemia
Splenic marginal zone lymphoma
Hairy cell leukaemia
Splenic B-cell lymphoma/leukaemia, unclassifiable
Lymphoplasmacytic lymphoma
IgM MGUS
Heavy chain diseases
Plasma cell neoplasms
Extranodal marginal zone lymphoma of MALT tissues
Nodal marginal zone lymphoma
Follicular lymphoma
Paediatric-type follicular lymphoma
Large B-cell lymphoma with IRF4 rearrangement
Primary cutaneous follicle centre lymphoma
Mantle cell lymphoma
Diffuse large B-cell lymphoma (DLBCL), NOS
T-cell/histiocyte-rich large B-cell lymphoma
Primary diffuse large B-cell lymphoma of the CNS
Primary cutaneous diffuse large B-cell lymphoma, leg type
EBV-positive diffuse large B-cell lymphoma, NOS
EBV-positive mucocutaneous ulcer
DLBCL associated with chronic inflammation
Lymphomatoid granulomatosis
Primary mediastinal (thymic) large B-cell lymphoma
Intravascular large B-cell lymphoma
ALK-positive large B-cell lymphoma
Plasmablastic lymphoma
Primary effusion lymphoma
HHV8-associated lymphoproliferative disorders
Burkitt lymphoma
Burkitt-like lymphoma with 11q aberration
High-grade B-cell lymphoma
B-cell lymphoma, unclassifiable,
with features intermediate between DLBCL and classic Hodgkin lymphoma
T-cell prolymphocytic leukaemia
T-cell large granular lymphocytic leukaemia
Chronic lymphoproliferative disorder of NK cells
Aggressive NK-cell leukaemia
EBV-positive T-cell and NK-cell LPDs of childhood
Systemic EBV+ T-cell lymphoma of childhood
Chronic active EBV infection of T- and NK-cell type, systemic form
Hydroa vacciniforme-like lymphoproliferative disorder
Severe mosquito bite allergy
Adult T-cell leukaemia/lymphoma
Extranodal NK/T-cell lymphoma, nasal type
Intestinal T-cell lymphoma
Enteropathy-associated T-cell lymphoma
Monomorphic epitheliotropic intestinal T-cell lymphoma
Intestinal T-cell lymphoma, NOS
Indolent T-cell lymphoproliferative disorder of the GIT
Hepatosplenic T-cell lymphoma
Subcutaneous panniculitis-like T-cell lymphoma
Mycosis fungoides
Sézary syndrome
Primary cutaneous CD30-positive T-cell LPDs
Lymphomatoid papulosis
Primary cutaneous anaplastic large cell lymphoma
Primary cutaneous peripheral T-cell lymphomas, rare subtypes
Primary cutaneous gamma delta T-cell lymphoma
Primary cutaneous CD8-positive aggressive epidermotropic cytotoxic T-cell lymphoma
Primary cutaneous acral CD8-positive T-cell lymphoma
Primary cutaneous CD4+ small/medium T-cell LPD
Peripheral T-cell lymphoma, NOS
Angioimmunoblastic T-cell lymphoma and other nodal lymphomas of T follicular
helper (TFH) cell originAngioimmunoblastic T-cell lymphoma
Follicular T-cell lymphoma
Nodal peripheral T-cell lymphoma with TFH phenotype
Anaplastic large cell lymphoma, ALK-positive
Anaplastic large cell lymphoma, ALK-negative
Breast implant-associated anaplastic large cell lymphoma
Matu
re B
-cell n
eopla
sms
Matu
re T
-and N
K-c
ell n
eopla
sms
Courtesy of Juan Flores MD PhD
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Chronic lymphoproliferative disorders: WHO2017 classificationCLL/small lymphocytic lymphoma
B-cell prolymphocytic leukaemia
Splenic marginal zone lymphoma
Hairy cell leukaemia
Splenic B-cell lymphoma/leukaemia, unclassifiable
Lymphoplasmacytic lymphoma
IgM MGUS
Heavy chain diseases
Plasma cell neoplasms
Extranodal marginal zone lymphoma of MALT tissues
Nodal marginal zone lymphoma
Follicular lymphoma
Paediatric-type follicular lymphoma
Large B-cell lymphoma with IRF4 rearrangement
Primary cutaneous follicle centre lymphoma
Mantle cell lymphoma
Diffuse large B-cell lymphoma (DLBCL), NOS
T-cell/histiocyte-rich large B-cell lymphoma
Primary diffuse large B-cell lymphoma of the CNS
Primary cutaneous diffuse large B-cell lymphoma, leg type
EBV-positive diffuse large B-cell lymphoma, NOS
EBV-positive mucocutaneous ulcer
DLBCL associated with chronic inflammation
Lymphomatoid granulomatosis
Primary mediastinal (thymic) large B-cell lymphoma
Intravascular large B-cell lymphoma
ALK-positive large B-cell lymphoma
Plasmablastic lymphoma
Primary effusion lymphoma
HHV8-associated lymphoproliferative disorders
Burkitt lymphoma
Burkitt-like lymphoma with 11q aberration
High-grade B-cell lymphoma
B-cell lymphoma, unclassifiable,
with features intermediate between DLBCL and classic Hodgkin lymphoma
T-cell prolymphocytic leukaemia
T-cell large granular lymphocytic leukaemia
Chronic lymphoproliferative disorder of NK cells
Aggressive NK-cell leukaemia
EBV-positive T-cell and NK-cell LPDs of childhood*
Systemic EBV+ T-cell lymphoma of childhood
Chronic active EBV infection of T- and NK-cell type, systemic form
Hydroa vacciniforme-like lymphoproliferative disorder
Severe mosquito bite allergy
Adult T-cell leukaemia/lymphoma
Extranodal NK/T-cell lymphoma, nasal type
Intestinal T-cell lymphoma
Enteropathy-associated T-cell lymphoma
Monomorphic epitheliotropic intestinal T-cell lymphoma*
Intestinal T-cell lymphoma, NOS
Indolent T-cell lymphoproliferative disorder of the GIT*
Hepatosplenic T-cell lymphoma
Subcutaneous panniculitis-like T-cell lymphoma
Mycosis fungoides
Sézary syndrome
Primary cutaneous CD30-positive T-cell LPDs
Lymphomatoid papulosis
Primary cutaneous anaplastic large cell lymphoma
Primary cutaneous peripheral T-cell lymphomas, rare subtypes
Primary cutaneous gamma delta T-cell lymphoma
Primary cutaneous CD8-positive aggressive epidermotropic cytotoxic T-cell lymphoma
Primary cutaneous acral CD8-positive T-cell lymphoma*
Primary cutaneous CD4+ small/medium T-cell LPD*
Peripheral T-cell lymphoma, NOS
Angioimmunoblastic T-cell lymphoma and other nodal lymphomas of T follicular
helper (TFH) cell originAngioimmunoblastic T-cell lymphoma
Follicular T-cell lymphoma*
Nodal peripheral T-cell lymphoma with TFH phenotype*
Anaplastic large cell lymphoma, ALK-positive
Anaplastic large cell lymphoma, ALK-negative*
Breast implant-associated anaplastic large cell lymphoma*
Matu
re B
-cell n
eopla
sms
Matu
re T
-and N
K-c
ell n
eopla
sms
Provisional entities are shown in Italics
* Changes from the 2008 classification
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CD8 - FITC
CD
4 -
PEC
y5
WHO DISEASE ENTITIES
ImmunophenotypeClinical features
Morphology Genetics & molecular
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How can multiparametric
flow cytometry (FCM)
help for the study of
of T- and NK-cell CLPD
in the clinical setting?
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Sequential FCM strategy to diagnose and characterize T/NK-CLPD
Leukemia 2012; 26, 1908–1975 (van Dongen et al on behalf of EuroFlow)
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Clinical questions
1st step: LYMPHOCYTE SCREENING TUBE
Sequential FCM strategy to diagnose and characterize T/NK-CLPD
Leukemia 2012; 26, 1908–1975 (van Dongen et al on behalf of EuroFlow)
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FCM in T/NK-cell CLPD
1. Diagnostic screening
- Normal reactive/regenerating clonal
2. Classification
- Definition of biologic and clinical entities
- Risk group definition
- Prognostic stratification
3. Assessment of response to treatment
Increased T cell population
Normal / residual
T cells
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Clinical questions
1st step: LYMPHOCYTE SCREENING TUBE
2nd step: T-CLPD CLASSIFICATION
Sequential FCM strategy to diagnose and characterize T/NK-CLPD
Leukemia 2012; 26, 1908–1975 (van Dongen et al on behalf of EuroFlow)
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FCM in T/NK-cell CLPD
1. Diagnostic screening
- Normal reactive/regenerating clonal
2. Classification
- Definition of biologic and clinical entities
- Risk group definition
- Prognostic stratification
3. Assessment of response to treatment
Normal / residual T cells
T-PLL
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EuroFlow Lymphoid Screening Tube (LST)
PacB PacO FITC PEPerCp
Cy5.5PE Cy7 APC
APC
H7
LSTCD4
CD20CD45
CD8
sIgl
CD56
sIgkCD5
CD19
TCRgdCD3 CD38
• Identification of targeted cell populations: mature B-, T- & NK-cells
• Subsetting into major subpopulations
• Detection of abnormal cell populations requiring further evaluation
• Altered (distribution or absolute cell) concentration
• Aberrant immunophenotypic pattern
• B-cell clonality
Leukemia 2012; 26, 1908–1975 (van Dongen et al on behalf of EuroFlow)
AIMS
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Rapid immunophenotypic screening of T/NK lymphocytosis
Normal PB
CD4/CD8 ratio = 2.5
CD20 + CD4 - PacBCD20 + CD4 - PacB CD5 - PerCP-Cy5.5
CD
3 -
APC
CD
8 +
anti
-sIg
l-
FIT
C
CD
8 +
anti
-sIg
l-
FIT
C
Only mature lymphoid
cells are shown
EuroFlow Lymphoid Screening Tube (LST)
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Rapid immunophenotypic screening of T/NK lymphocytosis
Normal PB
T-CLPD PB
CD4/CD8 ratio = 2.5
CD20 + CD4 - PacBCD20 + CD4 - PacB CD5 - PerCP-Cy5.5
CD
3 -
APC
CD
8 +
anti
-sIg
l-
FIT
C
CD
8 +
anti
-sIg
l-
FIT
C
CD20 + CD4 - PacBCD20 + CD4 - PacB CD5 - PerCP-Cy5.5
CD
3 -
APC
CD
8 +
anti
-sIg
l-
FIT
C
CD
8 +
anti
-sIg
l-
FIT
C
Only mature lymphoid
cells are shown
EuroFlow Lymphoid Screening Tube (LST)
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Rapid immunophenotypic screening of T/NK lymphocytosis
Normal PB
T-CLPD PB
CD4/CD8 ratio = 2.5
CD20 + CD4 - PacBCD20 + CD4 - PacB CD5 - PerCP-Cy5.5
CD
3 -
APC
CD
8 +
anti
-sIg
l-
FIT
C
CD
8 +
anti
-sIg
l-
FIT
C
CD20 + CD4 - PacBCD20 + CD4 - PacB CD5 - PerCP-Cy5.5
CD
3 -
APC
CD
8 +
anti
-sIg
l-
FIT
C
CD
8 +
anti
-sIg
l-
FIT
C
Only mature lymphoid
cells are shown
EuroFlow Lymphoid Screening Tube (LST)
CD4/CD8 ratio = 22
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Rapid immunophenotypic screening of T/NK lymphocytosis
Normal PB
CD4/CD8 ratio = 2.5
CD20 + CD4 - PacBCD20 + CD4 - PacB CD5 - PerCP-Cy5.5
CD
3 -
APC
CD
8 +
anti
-sIg
l-
FIT
C
CD
8 +
anti
-sIg
l-
FIT
C
EuroFlow Lymphoid Screening Tube (LST)
T-CLPD PB
CD20 + CD4 - PacBCD20 + CD4 - PacB CD5 - PerCP-Cy5.5
CD
3 -
APC
CD
8 +
anti
-sIg
l-
FIT
C
CD
8 +
anti
-sIg
l-
FIT
C
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Rapid immunophenotypic screening of T/NK lymphocytosis
Normal PB
CD4/CD8 ratio = 2.5
CD20 + CD4 - PacBCD20 + CD4 - PacB CD5 - PerCP-Cy5.5
CD
3 -
APC
CD
8 +
anti
-sIg
l-
FIT
C
CD
8 +
anti
-sIg
l-
FIT
C
EuroFlow Lymphoid Screening Tube (LST)
T-CLPD PB
CD20 + CD4 - PacBCD20 + CD4 - PacB CD5 - PerCP-Cy5.5
CD
3 -
APC
CD
8 +
anti
-sIg
l-
FIT
C
CD
8 +
anti
-sIg
l-
FIT
CCD4/CD8 ratio = 0.32
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EuroFlow Lymphoid Screening Tube (LST)
PacB PacO FITC PEPerCp
Cy5.5PE Cy7 APC
APC
H7
LSTCD4
CD20CD45
CD8
sIgl
CD56
sIgkCD5
CD19
TCRgdCD3 CD38
• Identification of targeted cell populations: mature B-, T- & NK-cells
• Subsetting into major subpopulations
• Detection of abnormal cell populations requiring further evaluation
• Altered (distribution or absolute cell) concentration
• Aberrant immunophenotypic pattern (≥94% of T-CLPD and NK-CLPD)
• B-cell clonality
Leukemia 2012; 26, 1908–1975 (van Dongen et al on behalf of EuroFlow)
AIMS
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EuroFlow strategy in CLPD
LST validation
B-cells CD8hi T-cells NK-cellsCD4+ T-
cells
Principal component analysis
Principal component 1
Pri
ncip
al com
ponent
2
Lymphoid cells abnormality N
Immunophenotypic profile (n=227) 227/233 (97.4%)
Altered numbers /distribution (n=172) 172/233 (73.8%)
Total (n=233) 233/233 (100%)
Conventional vs reference data base interpretation
Courtesy of Juan Flores MD PhD Leukemia 2012; 26, 1908–1975 (van Dongen et al on behalf of EuroFlow)
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EuroFlow strategy in CLPD
LST validation
B-cells CD8hi T-cells NK-cellsCD4+ T-
cells
Principal component 1
Pri
ncip
al com
ponent
2
Lymphoid cells abnormality N
Immunophenotypic profile (n=227) 227/233 (97.4%)
Altered numbers /distribution (n=172) 172/233 (73.8%)
Total (n=233) 233/233 (100%)
Conventional vs reference data base interpretation
Courtesy of Juan Flores MD PhD
Principal component analysis
Leukemia 2012; 26, 1908–1975 (van Dongen et al on behalf of EuroFlow)
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Rationale for using automation for the analysis of the EuroFlow LST
Classical expert-based manual gating strategies for interpreting flow cytometry data
depend on individual expertise ( = subjectivity)
Manual analysis strategies used by (individual) experts based on each
individual cell population via bivariate dot plots are hardly reproducible
Need for simpler, less laborious, less time-consuming,
more reproducible gating strategies
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Rationale for using automation for the analysis of the EuroFlow LST
Classical expert-based manual gating strategies for interpreting flow cytometry data
depend on individual expertise ( = subjectivity)
Manual analysis strategies used by (individual) experts based on each
individual cell population via bivariate dot plots are hardly reproducible
Need for simpler, less laborious, less time-consuming,
more reproducible gating strategies
For this purpose, the EuroFlow consortium has designed, constructed and
validated an automated gating and identification (AGI) strategy, based on:
i) Clustering techniques to define groups of events in a sample
ii) A data base comparison step, to (objectively) classify each individual group of events in
a sample against pre-defined cell populations in a data base (matched for sample type,
antibody panel, age and/or disease condition)
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EuroFlow LST PB data base construction
Key steps:
Flores-Montero J et al. J Immunol Methods. 2019 Dec;475:112662
1. Selection / Staining and acquisition of normal-
reactive samples
2. Inspection of technical quality
3. Check for biological and/or technical outliers
4. Analysis and identification of all cell populations in
the sample
5. Samples incorporation to the data base
6. Prospective validation
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EuroFlow LST PB data base construction
Key steps:
LST sample selected (n=119)
QC check for technical and
biologic variables (n=73)
Samples included in
the data base (n=46)
Flores-Montero J et al. J Immunol Methods. 2019 Dec;475:112662
1. Selection / Staining and acquisition of normal-
reactive samples
2. Inspection of technical quality
3. Check for biological and/or technical outliers
4. Analysis and identification of all cell populations in
the sample
5. Samples incorporation to the data base
6. Prospective validation
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EuroFlow LST data base construction
Key steps: Gating strategy for normal PB populations
Flores-Montero J et al. J Immunol Methods. 2019 Dec;475:112662
1. Selection / Staining and acquisition of normal-
reactive samples
2. Inspection of technical quality
3. Check for biological and/or technical outliers
4. Analysis and identification of all cell populations in
the sample
5. Samples incorporation to the data base
6. Prospective validation
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EuroFlow LST data base construction
Key steps:
Flores-Montero J et al. J Immunol Methods. 2019 Dec;475:112662
1. Selection / Staining and acquisition of normal-
reactive samples
2. Inspection of technical quality
3. Check for biological and/or technical outliers
4. Analysis and identification of all cell populations in
the sample
5. Samples incorporation to the data base
6. Prospective validation
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EuroFlow LST data base construction
Key steps: Tumor cell populations
Normal (residual) cell populations
% c
ells
manu
al ana
lysis
% cells AGI
% cells AGIFlores-Montero J et al. J Immunol Methods. 2019 Dec;475:112662
1. Selection / Staining and acquisition of normal-
reactive samples
2. Inspection of technical quality
3. Check for biological and/or technical outliers
4. Analysis and identification of all cell populations in
the sample
5. Samples incorporation to the data base
6. Prospective validation
% c
ells
manu
al ana
lysis
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EuroFlow LST AGI data base
LST data base(s) requirements:
• Mature aberrant lymphocytes can
infiltrate various tissues
• Peripheral blood
• Bone marrow
• Lymph node
• Other fluids
• Wide range of patients’ age:
• Normal <-> reactive <-> clonal
• Boarder variability in:
• Lymphoid cell (sub) populations presence
and distribution
Flores-Montero J et al. J Immunol Methods. 2019 Dec;475:112662
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EuroFlow automated analysis LST data bases
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Automated analysis LST in PB sample
File selection
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Automated analysis LST in PB sample
Data base selection
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Automated analysis LST in PB sample
Data base selection
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Automated analysis LST in PB sample
Data base selection
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Automated analysis LST in PB sample
Data base selection
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Automated analysis LST in PB sample
Data base selection
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Automated gaiting & identification (AGI) process
Clustering
Classification
Output
Evaluation of CHKs
Reporting
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Automated analysis LST in PB sample
AGI output
12%
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Automated analysis LST in PB sample
After evaluation of CHKs
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Automated analysis LST in PB sample
Report
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EuroFlow Automated analysis in CLPD (LST)
Concluding remarks
Automated analysis is a robust and accurate tool to
support cytometrists in the diagnosis and classification of
CLPD which contributes to the systematic, more
standardized and fast analysis and reporting
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Clinical questions
1st step: LYMPHOCYTE SCREENING TUBE
2nd step: ASSESSMENT OF CLONALITY
Sequential FCM strategy to diagnose and characterize T/NK-CLPD
Leukemia 2012; 26, 1908–1975 (van Dongen et al on behalf of EuroFlow)
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Clonality assessment for T-CLPD
Langerak et al, Blood 2001; Van Dongen et al, Leukemia 2003; Langerak et al, Leukemia 2012
TCRVβ repertoire by FCM
Expensive
Labor-intense
Difficult to interpret
Limited sensitivity
Restricted diversity of TCRγ
Complex
Lack of clone quantification or Immunophenotypic characterization
High levels of background noise amplification
(requiring sorting of the suspicious clonal cell population)
Not available in many laboratories
Molecular clonality by PCR
Aberrant TCD8+ cells
100% Vb13.2+
Normal TCD8+ cells
Limitations / disadvantages
Limitations / disadvantages
Not available in many laboratories
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T-cell receptor β chain constant region (TRBC1) reagent
Tunnacliffe et al, Proc. Natl. Acad. Sci. 1985; Shi et al, Cytom. Part B 2020; Horna et al, Int. J. Mol. Sci. 2021
Anti-TRBC1:
• Against one of two mutually exclusive TRBC genes
• Randomly selected during TCR gene rearrangement
Flow cytometry TRBC1 marker (clone JOVI-1):A. Normal and virus-specific (“reactive”) Tαβ-cells: polytypic TRBC1 expression
B. Monoclonal Tαβ-CLPD: monotypic TRBC1 expression
CD4+ Tαβ-cells
37-51%
CD8+ Tαβ-cells
36-52%
Clonal
Tαβ-cells
TRBC1-
Clonal
Tαβ-cells
TRBC1+
Clonal
Tαβ-cells
TRBC1lo
A B
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FCM-based clonality assay for T-CLPD
OBJECTIVES
1.- To optimize a flow cytometric method for routine use of anti-
TRBC1 to assess T-cell clonality
2.- To validate it in a large series of normal and pathological
samples
• TRBC1-expression of normal Tαβ-cells and Tαβ-cell subsets
(ranges for normality)
• Evaluation of specificity and sensitivity for detection of clonal
Tαβ-cells present at minimal disease levels
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0 20 40 60 80 100
CD3 - 10’ - TRBC1
CD3 + TRBC1
TRBC1 - 10’ - CD3
Without CD3TRBC1 only
TRBC1 10’
and then CD3
CD3 + TRBC1
CD3 10’ and
then TRBC1
0 20 40 60 80 100
CD3 - 10’ - TRBC1
CD3 + TRBC1
TRBC1 - 10’ - CD3
Without CD3
% TRBC1+
0 10 20 30 40
CD3 10’ and then TRBC1
CD3 + TRBC1
TRBC1 10’ and then CD3
TRBC1 only
0 10 20 30 40
CD3 10’ and then TRBC1
CD3 + TRBC1
TRBC1 10’ and then CD3
TRBC1 only
TRBC1 Stain Index
*
*
* p≤0.05 vs TRBC1 only
# p≤0.05 vs CD3 10’ and then TRBC1
#
#
TRBC1 only
TRBC1 10’
and then CD3
CD3 + TRBC1
CD3 10’ and
then TRBC1
Optimization of the approach
% TRBC1+ of Tαβ cells TRBC1 Stain Index on Tαβ cells
TRBC1 labeling significantly improved in the presence of CD3; the best resolution to identify
TRBC1+ cells was achieved by adding CD3 either simultaneously or after TRBC1
○ TRBC1 in BV421
X CD3-APC (SK7)
X CD3-APC (REA613)
X CD3-APC (UCHT1)
∆ TRBC1 in FITC
X CD3-PECy7 (SK7)
X CD3-PEVio770
(REA613)
X Any CD3 reagent
Sta
inin
g c
ondit
ions
Sta
inin
g c
ondit
ions
Optimization and validation of the TRBC1-FCM approach for detecting
clonal Tαβ-cells (n=211 normal, reactive and pathological samples)
Muñoz-García N et al, Cancers (Basel). 2021;13:4379, on behalf of EuroFlow
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Optimization and validation of the TRBC1-FCM approach for detecting clonal Tαβ-cells
(n=211 normal, reactive and pathological samples)
Muñoz-García N et al, Cancers (Basel). 2021;13:4379
Ranges for Polyclonal (Normal and Reactive) Tαβ-Cells and Major Tαβ-Cell Populations
Tαβ-cell
subset
% TRBC1+ cells* TRBC1+/TRBC1- ratio Probability (%) of Finding A Clonal
Tαβ Expansion When
TRBC1+/TRBC1− Ratio is Outside the
Range Mean ± 3 SD
(ρ-Value)
Mean ± 1 SD Range
(Mean ± 3 SD) Mean ± 1 SD
Range
(Mean ± 3 SD)
Tαβ cells 40 ± 6.7 20–60 0.66 ± 0.071 0.25–1.4
99.73%
(<0.001)
Tαβ CD4+ 43 ± 6.3 24–62 0.75 ± 0.067 0.31–1.6
Tαβ CD8+ 35 ± 8.8 8.3–61 0.53 ± 0.096 0.091–1.6
Tαβ DP 36 ± 12 1.6–71 0.57 ± 0.13 0.016–2.5
Tαβ DN 29 ± 10 0-61 0.41 ± 0.12 0–1.5
Bimodal distribution of TRBC1 for every TCRVβ subset of polyclonal Tαβ-cellsMore mature stages of Tαβ-cells were outside the normal
range of TRBC1+/TRBC1- ratio observed for total Tαβ-cells
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Optimization and validation of the TRBC1-FCM approach for detecting clonal Tαβ-cells
(n=211 normal, reactive and pathological samples)
Muñoz-García N et al, Cancers (Basel). 2021;13:4379
TRBC1-FCM Assay vs. TCRVβ-FCM and/or Molecular
Techniques for Assessment of Tαβ-Cell Clonality
Sensitivity of TRBC1-FCM assay for Detection
of Clonal Tαβ-Cells
Serial dilutional experiments
(of PB pathological Tαβ cells in normal blood cells)
Sensitivity level for detecting clonal Tαβ cells
(identified among cells displaying an aberrant/suspicious
phenotype) was of at least 10-4 in 7/8 T-CLPD cases tested
112/117 (96%) concordance
Clonality status by other
techniques
TRBC1 expression pattern
P-valuePolytypic
(n=23)
Monotypic
(n=94)
Poly/oligoclonal
(n=24)21/24 (87%) 3/24 (13%)
<0.0001Monoclonal
(n=93)2/93 (2%) 91/93 (98%)
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REMARKS AND CONCLUSIONS
• The optimal TRBC1 staining is achieved when CD3 antibody is added (not
before TRBC1)
• High specificity: 96% with TRBJ gene rearrangement / with other
conventional clonality techniques
• Sensitivity level of at least 10-4 can be reached in combination with
aberrant phenotype (which improves when combined with TCRVβ)
The TRBC1 approach in is a useful, simple and fast FCM assay for Tαβ-cell
clonality assessment in patients with suspicious T-CLPD
When used in combination with aberrant phenotypes, the approach has
high specificity and sensitivity
TRBC1-FCM approach for detecting clonal Tαβ-cells
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Next future
• Implementation of anti-TRBC1 in screening, diagnostic and MRD panels
for the study of T-CLPD
• To built appropiate reference databases for automated análisis (i.e. LST
including both B-cell and T-cell clonality markers)
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Immunophenotypic identification of Sézary cells in blood:
additional value of a T-cell clonality marker (TRBC1)
#OPO-2100462
CD4 CD7 CD26CD7
CD
3
CD
26
CD3
CD
279 (
PD
-1)
Sézary cells
Normal
(residual)
CD4+ T cells
CD8+ T cells
CD
2
CD
28
Sézary cells
Normal (residual)
CD4+ T cells
CD8+ T cells
TCR-Cb1TCR-Cb1 (TRBC1)
CD
279 (
PD
-1)
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Participants: Neus Villamor (UB, Barcelona, Spain), Paula Fernández (KSA, Aarau, Switzerland), Matthias Ritgen(University of Schleswig-Holstein, Kiel, Germany),
Anton W Langerak (Erasmus MC, RT, The Netherlands)
Classification and monitoring of T/NK-CLPD (WP L&L-10)WP Leaders: Julia Almeida (USAL, Spain) and Margarida Lima (CHP Porto, Portugal)
EuroFlow Leaders: Jacques van Dongen and Alberto Orfao