designing the next-generation oncolytic vaccinia virus · a decreased interferon response. we...

Designing the Next-Generation Oncolytic Vaccinia Virus

by

Tiffany Yun-Yee Ho

A thesis submitted in conformity with the requirements for the degree of Master of Science

Institute of Medical Science University of Toronto

© Copyright by Tiffany Yun-Yee Ho 2017

ii

Designing the Next-Generation Oncolytic Vaccinia Virus

Tiffany Yun-Yee Ho

Master of Science

Institute of Medical Science

University of Toronto

2017

Abstract

Many oncolytic viruses (OVs), such as double-deleted vaccina virus (vvDD), are engineered

with enhanced tumor-selectivity based on increased cell proliferation in cancer cells. We

proposed that OVs with improved tumor efficacy and equal tumor-selectivity could be generated

by exploiting the dysregulated immune response in tumors. Vaccinia virus (VV) proteins that

inhibit the interferon response are redundant for replication in tumors, which often already have

a decreased interferon response. We deleted VV immunomodulatory genes (N1L, K1L, K3L,

A46R, or A52R) from VV and compared these candidate VVs to vvDD. Candidate VVs

demonstrated equal or superior in vitro viral replication, spread, and tumor cytotoxicity in colon

cancer cells compared to vvDD and were potent against ovarian cancer cells. At doses 20-1000

times less than the vvDD treatment dose, the best in vitro candidate VVs (∆K1L, ∆A46R,

∆A52R VVs) demonstrated tumor-selectivity and equal or prolonged survival in mouse models

of peritoneal carcinomatosis.

iii

Acknowledgements

The work described in this dissertation would not have been possible without the support and

guidance of several people. First, I would like to thank my principal investigator and mentor, Dr.

Andrea McCart. Beyond the constant guidance and opportunities provided to me as a scientist,

your calm demeanor and patience were instrumental for me to continue on confidently despite

numerous hurdles throughout this project. When I would fret about the smallest setbacks, you

kept my eyes on the big picture until the end. I would also like to thank my committee members,

Dr. Eleanor Fish and Dr. Christine Allen, for their feedback and encouragement that pushed me

to think critically about my research.

To the members of the McCart lab, past and present, I would like to offer my deepest gratitude

for going above and beyond whenever I needed help. To Dr. Kathryn Ottolino-Perry, your

immense knowledge and enthusiasm whenever I asked for help, even when you had graduated,

were indispensible throughout my time here. To Dr. Sergio Acuna and Lili Li, I will be forever

grateful to you for going out of your way to teach and help me with my project, especially for

long and arduous experiments when you, too, were busy.

My time as a graduate student was made much more enjoyable thanks to the support from friends

and family. First and foremost, I would like to thank my family who supported my pursuit in

every way possible from planning events around my experiment schedule. A special thank you is

owed to my brother for letting me hog the most isolated corner in the house (his room) to work

and study, sometimes to the point of being exiled to Waterloo. To my friends working on the 4th

floor of the Canadian Blood Services building, knowing that I would see you downtown made

the commute much more bearable. Our discussions about everything from cute raccoons and the

newest food fad to hardcore science concepts certainly made incubation times more interesting.

Lame jokes and painfully nerdy analogies with you kept my sanity while learning and doing a

project that, at times, felt overwhelming. Thank you for being my hiding place when I needed

one, both literally and figuratively. We complemented each other much too well to be from

separate labs. Our trials throughout our graduate journey had an uncanny resemblance and it was

comforting to lean on someone who understood. To my many other friends who braved every

extreme weather condition to deliver bubble tea as consolation or celebrate my smallest victories

iv

over dinner, the foodie in me is forever grateful. Though the chronicles of my graduate journey

and my description of every confounding situation won‘t be published in a book, our online

conversations will be a testament of how you listened to my every rant and went out for food

with me at the smallest sign of a food craving.

It has been put into my heart to also acknowledge and thank God for being there throughout my

journey here before and during my graduate studies, and certainly, He will be there after it. He

had fashioned every trial, success, and circumstance has fallen into place to give me these friends

that I cherish and experiences that have fostered growth. He has been faithful and I await the

next adventure He has in store.

v

Statement of Contributions

Tiffany Y. Ho generated the ∆N1L-, ∆K1L-, ∆K3L-, and ∆A46R- deleted vaccinia viruses. She

also designed and carried out experiments, analyzed the data, and wrote the thesis. Nan Tang

generated the ∆A52R-deleted vaccinia virus and the vvDD-R2R-Luc virus described in this

dissertation. Lili Li generated viral stocks and assisted in carrying out the experiments. Dr. J.

Andrea McCart designed the shuttle plasmids for all vaccinia viruses generated in this project,

conceived and designed the experiments, and supervised the study.

vi

Table of Contents

Acknowledgements ...................................................................................................................... iii

Statement of Contributions .......................................................................................................... v

Table of Contents ......................................................................................................................... vi

List of Figures .............................................................................................................................. xii

List of Tables .............................................................................................................................. xiv

List of Abbreviations .................................................................................................................. xv

Chapter 1: Introduction ............................................................................................................... 1

1.1 Oncolytic Viruses............................................................................................................ 1

1.1.1 Overview ................................................................................................................... 1

1.1.2 History and Development ......................................................................................... 2

1.1.3 Mechanisms of Tumor-Specificity ........................................................................... 3

1.1.4 Mechanisms of Action .............................................................................................. 5

1.1.5 Vaccinia Virus .......................................................................................................... 8

1.1.5.1. Clinical Safety of VV as a Smallpox Vaccine ................................................... 8

1.1.5.2 Vaccinia Virus Biology ..................................................................................... 9

1.1.5.3 Advantages of Vaccinia Virus as an Oncolytic Virus ..................................... 12

1.1.5.4 Double-deleted vaccinia virus - vvDD ............................................................ 13

vii

1.1.6 Oncolytic Viruses in Clinical Trials ....................................................................... 14

1.1.6.1 Vaccinia Virus in Clinical Trials ..................................................................... 17

1.2 Host Immune Response Against Viruses ...................................................................... 19

1.2.1 Overview ................................................................................................................. 19

1.2.2 Pathogen Recognition ............................................................................................. 20

1.2.2.1 Toll-Like Receptors ......................................................................................... 20

1.2.2.1.1 MyD88-Dependent Pathway ....................................................................... 21

1.2.2.1.2 TRIF-Dependent Pathway (MyD88- Independent Pathway) ...................... 22

1.2.2.2 Cytosolic PRRs ................................................................................................ 22

1.2.2.3 PRR Recognition of WR VV ........................................................................... 23

1.2.3 NFкB ....................................................................................................................... 26

1.2.4 Interferons ............................................................................................................... 28

1.2.4.1 Overview ......................................................................................................... 28

1.2.4.2 IFN Signaling Pathway .................................................................................... 29

1.2.5 Protein Kinase R (PKR) .......................................................................................... 32

1.3 VV Evasion of Innate Immunity ................................................................................... 33

1.3.1 Overview ................................................................................................................. 33

1.3.2 VV TLR Inhibitors .................................................................................................. 33

1.3.3 VV NFкB Inhibitors ............................................................................................... 35

viii

1.3.4 VV PKR Inhibitor ................................................................................................... 36

1.4 Dysregulation of IFN Induction and Signaling Pathways in Cancer Cells ................... 37

1.4.1 Overview ................................................................................................................. 37

1.4.2 TLRs in Cancer ....................................................................................................... 37

1.4.3 NFкB in Cancer ...................................................................................................... 38

1.4.4 PKR in Cancer ........................................................................................................ 39

1.5 Peritoneal Carcinomatosis (PC) .................................................................................... 40

1.5.1 Overview ................................................................................................................. 40

1.5.2 PC Tumor Origin and Incidence ............................................................................. 40

1.5.3 Colorectal Cancer (CRC) ........................................................................................ 41

1.5.4 Ovarian Cancer ....................................................................................................... 41

1.5.5 Pathophysiology and Biology of PC ....................................................................... 42

1.5.6 Treatment of CRC PC and Ovarian PC .................................................................. 43

1.5.7 Clinical Need .......................................................................................................... 45

1.6 Aims and Hypothesis .................................................................................................... 47

1.6.1 Rationale ................................................................................................................. 47

1.6.2 Hypothesis............................................................................................................... 47

1.6.3 Specific Aims .......................................................................................................... 48

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Chapter 2: Materials and Methods ........................................................................................... 49

2.1 Cell Lines ...................................................................................................................... 49

2.2. Vaccinia Viruses ........................................................................................................... 49

2.3. Creation of the Candidate Vaccinia Virus Deletion Mutants ....................................... 50

2.4. Viral DNA Extraction and PCR .................................................................................... 51

2.5. Virus Stock Production ................................................................................................. 52

2.6. Virus Plaque Assay ....................................................................................................... 53

2.7. Viral Replication ........................................................................................................... 53

2.8. Viral Cytotoxicity ......................................................................................................... 54

2.9. Measuring Viral Spread by Red fluorescent protein (RFP) Expression ....................... 54

2.10. Tumor Spheroid Generation, Infection, and Analysis .................................................. 54

2.11. Mice .............................................................................................................................. 55

2.12. In vivo Toxicity Studies ................................................................................................ 55

2.13. Syngeneic Model .......................................................................................................... 56

2.14. Xenograft Model ........................................................................................................... 56

2.15. Biodistribution .............................................................................................................. 56

2.16. Statistical Analysis ........................................................................................................ 57

Chapter 3: Results....................................................................................................................... 58

3.1 Aim 1: Generate VV-deletion mutants via homologous recombination ...................... 58

x

3.2 Aim 2: Compare candidate VV deletion mutants to vvDD in terms of in vitro viral

replication, cytotoxicity, and spread in colon and ovarian cancer cell lines. ............................ 71

3.3 Aim 3: Characterization of the candidate VV deletion mutants to vvDD in terms of in

vivo tumor-selectivity, toxicity and efficacy in mouse models of PC. ..................................... 92

Chapter 4: Discussion ............................................................................................................... 103

4.1. General Discussion ..................................................................................................... 103

4.2. Project Summary ......................................................................................................... 113

4.3. Experimental Challenges and Limitations .................................................................. 113

4.3.1. Tumor Spheroids ................................................................................................... 113

4.3.2. In vitro to In vivo translation ................................................................................. 115

4.3.3. Mouse Models ....................................................................................................... 116

4.3.4. Intraperitoneal Tumor Implantation ...................................................................... 117

4.3.5 IFN Sensitivity in Tumors .................................................................................... 118

4.4. Future Directions ........................................................................................................ 119

4.4.1. Determining the Mechanisms of Action ............................................................... 119

4.4.2. Potential Treatment for Other Cancer Types ........................................................ 121

4.4.3. Improving VV Delivery ........................................................................................ 121

4.4.4. Combination Therapy ........................................................................................... 122

4.4.5. Deletion of Other VV Immunomodulatory Genes................................................ 123

4.5. Final Remarks ............................................................................................................. 124

xi

References .................................................................................................................................. 125

xii

List of Figures

Figure 1.1. Vaccinia virus (VV) enacts multiple mechanisms of action against tumors. ............... 7

Figure 1.2. Vaccinia virus life cycle. ............................................................................................ 12

Figure 1.3 Interactions between pathogen recognition receptors (PRR) and vaccinia virus (VV)

inhibitory proteins. ........................................................................................................................ 26

Figure 1.4. The interferon (IFN) signaling pathway and the vaccinia virus (VV) inhibitors. ...... 32

Figure 3.1. Schematic diagram of shuttle plasmid and final construct of candidate VV deletion

mutant using ∆N1L VV as an example. ....................................................................................... 59

Figure 3.2. Confirmation of pvX-R2R-LUC plasmid. .................................................................. 60

Figure 3.3. Left and right flanking DNA fragments of VV N1L gene as generated by PCR. ...... 61

Figure 3.4. Confirmation of pVX-R2R-Luc with left-flanking DNA insertion. .......................... 62

Figure 3.5. Confirmation of the final shuttle plasmid. .................................................................. 63

Figure 3.6. Sample images of CV-1 cells after transfection/infection and subsequent rounds of

re-infection with recombinant VV. ............................................................................................... 65

Figure 3.7. PCR confirmation of the absence of parental virus from recombinant VV plaques. . 68

Figure 3.8. PCR confirmation of candidate viral stocks. .............................................................. 70

Figure 3.9. Replication of candidate VVs and vvDD in monolayers of colon and ovarian cancer

cell lines. ....................................................................................................................................... 74

Figure 3.10. Viral spread of VV deletion mutants and vvDD in monolayers of colon and ovarian

cancer cell lines. ............................................................................................................................ 76

Figure 3.11. Quantification of viral spread in monolayers of colon and ovarian cancer cell lines.

....................................................................................................................................................... 77

xiii

Figure 3.12. Cytotoxicity of vvDD and candidate VVs towards colon and ovarian cancer cell

lines. .............................................................................................................................................. 81

Figure 3.13. Viral spread of candidate VVs and vvDD in MC38 tumor spheroids. ..................... 83

Figure 3.14. Viral spread of candidate VVs and vvDD in DLD-1 spheroids. .............................. 84

Figure 3.15. MC38 spheroid size after treatment with candidate VVs or vvDD. ......................... 86

Figure 3.16. Clonogenic assay of tumor spheroids treated with candidate VVs or vvDD. .......... 89

Figure 3.17. Determining the IP MTD of candidate VVs in nude and C57BL/6 mice. ............... 94

Figure 3.18. Biodistribution of candidate VVs and vvDD in tumor-bearing mice. ...................... 99

Figure 3.19. Efficacy of candidate VVs and vvDD in a syngeneic model of PC. ...................... 100

Figure 3.20. Efficacy of candidate VVs and vvDD in xenograft models of PC. ........................ 102

xiv

List of Tables

Table 2.1. Primers for producing inserts for the shuttle plasmid .................................................. 51

Table 3.1. Summary of the in vitro assays comparing candidate VVs to vvDD .......................... 91

xv

List of Abbreviations

AFP – alpha-fetoprotein

APC – adenomatous polyposis coli

ARID1A – AT-rich interaction domain 1A

ATCC – American Type Culture Collection

BCA – bicinchonic acid

Bcl-2 – B-cell lymphoma 2

bp – base pair

BRAF – v-raf murine sarcoma viral oncogene homolog B1

BSA – bovine serum albumin

CARD – caspase-recruitment domain

CD150 – cluster of differentiation 150







xvi

cDC – conventional dendritic cell

CEV – cell-associated enveloped virus

CEV – cellular-associated enveloped virion

Cox2 – cyclooxygenase 2

CRC – colorectal cancer

CrKL – v-crk sarcoma virus C10 oncogene homology (avian)-like

CRS – cytoreductive surgery

CTNNB1 – catenin beta 1

d – day(s)

DAI – DNA-dependent activator of interferon-regulatory factor

DAMP – damage-associated molecular pattern

DC – dendritic cells

DIC – differential interference contrast

DMEM – Dulbecco‘s Modified Eagle Medium

DMSO – dimethyl sulfoxide

DNA – deoxyribonucleic acid

dpi – days post-infection

ds – double-stranded

EEV – enveloped extracellular virion

xvii

EEV – extracellular enveloped virus

EGF – epidermal growth factor

EGFR – epidermal growth factor receptor

eIF2α – eukaryotic initiation factor 2 alpha

EMT – epithelial-mesenchymal transition

EPIC – early post-operative intraperitoneal therapy

ERK – extracellular signal-related kinase

FADD – Fas-associated protein with death domain

FBS – fetal bovine serum

GAF – interferon γ activation factor

GAG – glycosaminoglycan

GAS – gamma-activated sequence

GDP – guanine diphosphate

GM-CSF – granulocyte macrophage colony stimulating factor

GTP – guanine triphosphate

h – hour(s)

HBSS – Hank‘s buffered saline solution

HCC – hepatocellular carcinoma

HIPEC – hypothermic intraperitoneal chemotherapy

xviii

HMGB1 – high mobility group box 1

hpi – hours post-infection

HSP90 – heat shock protein 90

HSV – herpes simplex virus

IEV – intracellular enveloped virion

IFI16 - IFNγ-inducible protein 16

IFN - interferon

IFNAR1– interferon α receptor

IFNGR – interferon γ receptor

IFNLR – interferon λ receptor

IKK – IκB kinase

IL-1 – interleukin 1

IMV – intracellular mature virion

iNOS – nitric oxide synthase

IP – intraperitoneal

IPS-1- interferon β promoter stimulator 1

IRAK – interleukin 1 receptor kinase

IRF – interferon regulatory factor

ISG – interferon-stimulated genes

xix

ISGF3 – interferon-stimulated gene factor 3

ISRE – interferon-stimulated regulatory elements

IT – intratumoral

IV – intravenous

JAK – Janus kinase

KRAS – Kirsten rat sarcoma viral oncogene homolog

LD50 – lethal dose 50

LGP2 – laboratory of genetics and physiology -2 protein

MAL – MyD88 adaptor-like protein

MAPK – mitogen-activated protein kinases

MDA5 – melanoma differentiation-associated gene 5

Mda7 – melanoma-differentiation associated gene 7

MOI – multiplicity of infection

mRECIST – modified Response Evaluation Criteria in Solid Tumors

MTD – maximum tolerable dose

mTORC – mammalian target of rapamcycin complex

MTS – 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-

tetrazolium

MV – measles virus

MVA – modified vaccinia Ankara

xx

MyD88 – myeloid differentiation factor 88

NDV – Newcastle disease virus

NF-κB – nuclear factor kappa-light-chain-enhancer of activated B cells

NK – natural killer

NLR – nucleotide-binding oligomerization domain (NOD)-like receptor

NYVAC – New York vaccinia virus

OV – Oncolytic virus

PACT – PKR (protein kinase R)-associated factor

PAMP – pathogen-associated molecular pattern

PC – peritoneal carcinomatosis

pDC – plasmacytoid dendritic cells

pfu – plaque-forming units

PIK3CA – Phosphatidylinositol-4, 5-biphosphate 3-kinase catalytic subunit alpha

PKC – protein kinase C

PKR – protein kinase R

Poly HEMA – poly(2-hydroxyethylmethacrylate)

PRR – pathogen recognition receptors

RFP – red fluorescent protein

RHD – Rel-homology domain

xxi

RIG-1 – retinoic-acid inducible gene-1

RIP – receptor interacting protein

RLR – retinoic acid inducible gene 1 (RIG-1)-like receptor

RPMI 1640 – Roswell Park Medical Institute medium

RV – reovirus

SARM – Sterile-α and armadillo motif-containing protein

SD – standard deviation

SEM – standard error of the mean

ss – single-stranded

STAT – signal transducer and activator of transcription

TAB – TAK1 (TGFβ ( transforming growth factor β) – activated kinase 1)-binding proteins

TAK1 – TGFβ ( transforming growth factor β) – activated kinase 1

TBK1 – TRAF family member-associated NFκB activator-binding kinase 1

TGFβ – transforming growth factor β

TIC – tubal intraepithelial carcinoma

TICAM -1 – toll-like receptor adaptor protein 1

TIR – Toll/interleukin 1 receptor homology

TIRAP – TIR (Toll/interleukin 1 receptor homology)-domain containing adaptor protein

TK – thymidine kinase

xxii

TLR – Toll-like receptor

TNFα – tumor necrosis factor α

TRADD – tumor necrosis factor receptor type 1 – associated death domain

TRAF – tumor necrosis factor receptor-associated factor

TRAM – TRIF (toll receptor associated activator of interferon)-related adaptor molecule

TRBP – trans- activation response RNA-binding protein

T-reg – regulatory T-cells

TRIF – toll receptor-associated activator of interferon

T-Vec – talimogene laherparepvec

TYK2 – tyrosine kinase

VEGF – vascular endothelial growth factor

VGF – vaccinia growth factor

VIPER – viral inhibitor peptide of toll-like receptor 4

VSV – vesicular stomatitis virus

VV – Vaccinia virus

vvDD – double-deleted vaccinia virus

WR – Western Reserve

xgprt – xanthine-guanine phosphoribosyltransferase

ZBP1 – Z-DNA binding protein 1

1

Chapter 1

1 Introduction

1.1 Oncolytic Viruses

1.1.1 Overview

Chemotherapy and radiotherapy are often used as a non-surgical means to treat many

malignancies today; however, these treatments are considerably non-specific and have many

detrimental side effects. The aim of oncolytic virotherapy is to use replication-competent viruses

to kill tumor cells while leaving normal cells unscathed. Several viruses have been examined as

potential virotherapy agents such as Newcastle disease virus (NDV), reovirus (RV), measles

virus (MV), herpes simplex virus (HSV), vesicular stomatitis virus (VSV), and vaccinia virus

(VV). Some viruses usually replicate in non-human hosts but are found to be naturally

oncotropic (e.g. NDV, RV) while other oncolytic viral vectors have enhanced tumor-selectivity

based on engineered attributes (e.g. VV, VSV, MV) (Antonio Chiocca, 2002). Many factors

determine host susceptibility to virus infection including: receptor expression, proliferation rate,

response to cell death signals, and the host immune response against viruses. The hallmarks of

individual cancer cells often overlap with characteristics that a virus seeks to induce to benefit

the infection. Thus tumor cells can be an ideal environment for viral replication and lysis. Some

of these characteristics include: increased cell proliferation, nucleotide synthesis, and protein

synthesis and decreased apoptosis and interferon-mediated antiviral responses (Ilkow et al.,

2014). Many oncolytic viruses (OV) in the clinic are engineered to more selectively replicate in

tumors based on increased cell proliferation rates (McCart et al., 2001; Breitbach et al., 2015).

The oncolytic viruses generated through this project were designed to exploit the decreased

interferon-mediated antiviral responses to confer enhanced tumor-selectivity in VV.

2

1.1.2 History and Development

As early as the mid-1800s, there were several reports of tumor regression in cancer patients

naturally infected with viruses (Kelly and Russell, 2007). In one of the most widely cited cases,

Dock describes a temporary but dramatic 70-fold decrease in leukocyte count during an

influenza infection in a 42-year old woman with leukemia (Dock, 1904). Reports of cancer

remission was also noted to occur concurrently with measles, varicella, and hepatitis infections

(Kelly and Russell, 2007). Though highly unethical, the first attempts to exploit viruses for

therapeutic gain in cancer treatments started in the beginning of the 20th

century by injecting

cancer patients with infectious bodily fluids or tissues derived from patients with ongoing

infections (Kelly and Russell, 2007). These naturally-occurring viruses were coined first-

generation oncolytic viruses. In the 1950s and 60s, tissue culture techniques allowed for more

reliable production of viruses, adaptation of wildtype viruses to become more oncotropic by

multiple passages in tumor cells, and the investigation of the therapeutic efficacy of oncolytic

viruses in animal models. Yet, interest for oncolytic virotherapy dwindled in the 1970s and 80s

due to dose-limiting toxicities or the lack of therapeutic efficacy in first-generation OVs and no

alternative methods to improve them (Kelly and Russell, 2007; Cattaneo et al., 2008).

Beginning in the early 1990s, the advent of recombinant DNA techniques coupled with a deeper

understanding of virology and cancer biology led to the development of second-generation

oncolytic viruses which have genetic manipulations that enhance tumor-selectivity of a first-

generation oncolytic virus. One of the first genetically-engineered oncolytic viruses to be used in

humans was ONYX-015, which is derived from a hybrid of Ad2/Ad5 serotypes of adenovirus.

The deletion of p53-inhibitory protein, E1B-55kD, was proposed to limit the replication of the

adenovirus to p53-deficient cells such as tumors because the majority of human cancers have lost

p53 pathway function (Bischoff et al., 1996; Kirn, 2001). Although the exact mechanism of

selectivity has been debated (Dix et al., 2001; Kirn, 2001) and the clinical efficacy was minimal

(Kirn, 2001), clinical trials with ONYX-015 became the proof of principle that OVs can be

systemically delivered safely and infect and replicate in tumors within humans (Kirn, 2001).

3

In addition to genetic manipulations to enhance tumor-selectivity, third-generation oncolytic

viruses are armed with therapeutic genes to improve potency and efficacy. Several arming

strategies have been employed to 1) improve virus spread, 2) enhance the immunostimulatory

effect of the virus on the host against the tumor, 3) disrupt tumor vasculature, 4) or work in

combination with other cancer therapies by encoding a prodrug-converting enzyme (Kirn and

Thorne, 2009). One promising example of a third-generation OV is Pexa-vec (JX-594) which is a

Wyeth strain VV with a deletion in its thymidine kinase (TK) gene to enhance its tumor-

selectivity and armed with human granulocyte-macrophage colony stimulating factor (GM-CSF)

to drive the proliferation of white blood cells and stimulate the host immune response against the

cancer during virus infection (Kim et al., 2006b; Breitbach et al., 2015). Preclinical and clinical

testing of Pexa-vec has demonstrated safety, anti-cancer immunity stimulation, and improved

survival (9 months) of late-stage heptacellular carcinoma patients treated with a high dose

Pexa-vec compared to the low dose cohort (Heo et al., 2013).

1.1.3 Mechanisms of Tumor-Specificity

OVs are tumor-selective based on intrinsic and/or engineered attributes. Many attributes in

cancer cells are already congruent with the characteristics that create an optimal environment for

virus entry, replication, and cytotoxicity (Ilkow et al., 2014). For example, adenovirus type II

(Segerman et al., 2003) and measles virus binds to the cell surface receptor CD46 for entry,

which is commonly upregulated in cancer cells (Anderson, 2004).

In addition to the intrinsic characteristics that make certain viruses preferentially infect and kill a

tumor cell, researchers also engineer OVs to build upon its natural tumor tropism. Engineered

OV tumor-selectivity usually employs one or more of the following strategies: 1) deleting genes

that are redundant for replicating in tumor cells but remain essential for replication in normal

cells, 2) redirecting viral entry by altering the proteins involved to target ligands commonly

overexpressed or uniquely found in tumors, 3) and subjecting genes essential for viral replication

under the control of a cancer-specific promoter (Cattaneo et al., 2008).

4

The first strategy could be employed in almost all OVs which are complex enough to express

genes that are redundant for successful propagation in tumors. One of the most popular strategies

is to exploit the pool of available nucleotides in actively dividing cells such as tumors cells, but

not quiescent normal tissues (Ilkow et al., 2014). Large viruses such as HSV and orthopoxviruses

express proteins to increase nucleotide synthesis to support its viral replication and virion

assembly, ensuring self-sufficient replication even in quiescent cells. Deletion of whole or

subunits of virally-encoded proteins that skew DNA synthesis, such as the ICP6 gene that

encodes the large subunit of ribonucleotide reductase from HSV-1 and HSV-2 (Chung et al.,

1999) or the thymidine kinase (TK) gene from VV (Puhlmann et al., 2000), restricts viral

replication to occur selectively in actively dividing cells such as tumor cells. However, deleting

genes in OVs that restrict its replication in actively dividing cells often compromises its potency

against quiescent tumour-initiating cells.

Another promising strategy involves exploiting the defective host immune response against

viruses in tumors. An estimated 65-70% of all cancers have some defects in interferon (IFN)

signaling, crippling the ability of the tumor cell to fight against a virus infection (Stojdl et al.,

2003). Viruses often express proteins to counter host antiviral mechanisms which may not be

necessary to infect a tumor cell. Engineered tumor-selectivity on the basis of this strategy could

be subtle, as in VV which expresses many immunomodulatory proteins (discussed in Section

1.3.), or dramatic, as in VSV which becomes vastly sensitive to interferon when its matrix M

protein is mutated (Stojdl et al., 2003).

The second strategy is to affect viral entry based on tumor cell-surface proteins (Cattaneo et al.,

2008; Verheije and Rottier, 2012). However, this approach is limited to viruses that require

specific known proteins for viral entry such as measles virus (Anderson, 2004) or adenovirus

(Zhang and Bergelson, 2005). For viruses that use unknown host-cell receptors for entry or have

complex viral entry mechanisms, such as HSV (Akhtar and Shukla, 2009) or poxviruses

(Schmidt et al., 2012), this method would not be suitable. Nevertheless, this strategy has been

shown to elicit tumor-selectivity when it is amenable. For example, single chain fragment

variable (scFv) antibodies have been incorporated into the measles virus receptor to retarget the

5

virus to other receptors commonly expressed on the surfaces of tumor cells instead of its natural

receptors, such as CD46 (Anderson, 2004) and CD150 (Tatsuo et al., 2000), CD20 (non-

Hodgkins lymphoma) (Bucheit et al., 2003) and CD38 (myeloma) (Peng et al., 2003).

The tumor-selectivity of oncolytic viruses can also be engineered at the transcriptional level by

putting essential viral genes for replication under the control of a cancer-specific promoter, thus

restricting viral propagation to specific cancers (Cattaneo et al., 2008; Antonio Chiocca, 2002).

This approach is widely used in large DNA viruses such as HSV-1 and adenovirus (Antonio

Chiocca, 2002). A prime example is the oncolytic adenovirus CN706 where the viral early gene,

E1A, is downstream of the prostate-specific antigen promoter, which causes the virus to

selectively replicate in prostate cancer cells (Rodriguez et al., 1997). Other adenoviruses have

been reprogrammed by subjecting E1A under the control of other tumor tissue-specific promoters

such as alpha-fetoprotein AFP (hepatocellular carcinoma) (Li et al., 2001) and uroplakin-II

(bladder cancer) (Zhang et al., 2002).

1.1.4 Mechanisms of Action

OVs are attractive anti-cancer agents due to the multiple mechanisms OVs employ that lead to

tumor cell death (Figure 1.1) (Kirn and Thorne, 2009). When the field of oncolytic virotherapy

was in its infancy, tumor debulking via direct viral killing of cancer cells was accepted as the

main mechanism of anti-cancer efficacy. Indeed, a variety of viruses, such as NDV (Wakamatsu

et al., 2006), encode distinct proteins that cause cell lysis. Interestingly, VV can induce apoptosis

in melanoma cell line Mel526 (Greiner et al., 2006), yet ovarian cancer cell lines (A2780,

SKOV3, TOV21G) undergo programmed necrosis (Whilding et al., 2013). Since VV encodes

many genes, it is possible that VV induces cell death via many mechanisms depending on cell

type and VV strain. Many OVs have also been engineered with cytotoxic proteins to aid in

tumor-killing.

6

Further investigations suggest that an interplay between the virus and the host immune system in

the tumor microenvironment also work together to kill tumors. In addition to infecting the tumor

itself, VV and VSV specifically infect tumor vasculature leading to neutrophil attraction and

eventual vascular occlusion that cuts off the tumor blood supply, causing tumor necrosis

(Breitbach et al., 2011b; Breitbach et al., 2013; Angarita et al., 2013).

The last mechanism involves overcoming the immunosuppressive tumor microenvironment and

changing it into an immunostimulatory setting that allows for the development of an anti-tumor

adaptive response and subsequent long-term immunological memory (Kirn and Thorne, 2009).

Viral infection of tumors and surrounding tissue activates the interferon signaling cascade

mediated by pathogen-associated molecular patterns (PAMPs) recognized by pattern recognition

receptors (PRR) such as Toll-like receptors (TLRs), RIG-like receptors (RLRs) and Nod-like

receptors (NLRs). The infection can induce immunologic cell death which triggers the release of

damage-associated molecular patterns (DAMPS) such as calreticulin, high mobility group box 1

(HMGB1), and heat shock protein 90 (HSP90) (Guo et al., 2014). In concert, these pathways

lead to the release of a plethora of inflammatory cytokines to counteract the immunosuppressive

tumor microenvironment, enabling plasmacytoid dendritic cells to prime naive T-cells with the

tumor antigens that were released along with the viral antigens during tumor cell lysis, initiating

the host adaptive immunity against the cancer cells and the eventual immunological memory that

leads to long-term immunity (Workenhe and Mossman, 2014; Guo et al., 2014; Melcher et al.,

2011; Bartlett et al., 2013).

7

Figure 1.1 Vaccinia virus (VV) enacts multiple mechanisms of action against tumors. VV has multiple anti-

tumor mechanisms. First, it can directly infect, replicate and lyse tumor cells. VV can also specifically infect tumor

endothelial cells which lead to vascular collapse either by the direct infection or the infiltration of neutrophils that

cause occlusion. Last, tumor cell infection and lysis leads to the release of proinflammatory cytokines, danger

signals, and tumor and VV antigens, which can change the immunosuppressive environment into a pro-

inflammatory environment that induces an anti-tumor innate and adaptive immune response. This environment can

also induce DC maturation and antigen presentation, priming long-term anti-tumor immunity. [Reprinted with

permission by McMillan Publishers [NATURE REVIEWS CANCER] (Kirn, D. and Thorne, S. Targeted and armed

oncolytic poxvirus: a novel multi-mechanistic therapeutic class for cancer), Copyright 2009. (Kirn and Thorne,

2009)

8

1.1.5 Vaccinia Virus

Vaccinia virus (VV) was most famously involved with the global eradication of smallpox;

however its origins still remain elusive. Originally, Edward Jenner isolated cowpox from

milkmaids to use as a vaccine against smallpox (Riedel, 2005). Vaccination is usually

administered via dermal scarification (Damon, 2013). After more than 130 years of passaging the

virus, it became clear that the live vaccine had become a distinct virus from cowpox and was

henceforth called vaccinia virus. There are many strains of vaccinia virus which vary in

virulence towards humans and other mammals including: Wyeth, Lister, Copenhagen, Western

Reserve, TianTian, modified vaccinia Ankara (MVA), and NYVAC (Kirn and Thorne, 2009).

Today, VV is also investigated for its potential as an oncolytic virus.

1.1.5.1. Clinical Safety of VV as a Smallpox Vaccine

As a result of its global use as a smallpox vaccine, the safety profile of vaccinia virus is well-

documented (Lane et al., 1970; Belongia and Naleway, 2003). Transmission usually occurs

through accidental inoculation to close contacts (Silva et al., 2010). Vaccinia pathophysiology

can be mild or serious and systemic. Mild, self-limited symptoms include satellite lesions, fever,

muscle aches, regional enlargement of lymph nodes, headache, nausea, rash, and soreness at the

vaccination site (Belongia and Naleway, 2003). A re-investigation of the smallpox vaccination in

the U.S. military has also associated mild myocarditis to vaccinia (5.5/10 000 vaccinations)

(Morgan et al., 2008). More serious adverse events such as death (1/million vaccinations),

progressive vaccinia (1.5/ million vaccinations), eczema vaccinatum (39/million vaccinations),

postvaccinial encephalitis (12/ million vaccinations), and generalized vaccinia (241/million

vaccinations) are infrequent (Belongia and Naleway, 2003; Lane et al., 1970). However, serious

adverse events are often limited to immune-immature and immunodeficient individuals such as

infants or older adults with defects in their cell-mediated immunity, respectively (Belongia and

Naleway, 2003).

9

1.1.5.2 Vaccinia Virus Biology

VV is part of the Poxviridae family and the Orthopoxvirus genera. The virus is characterized by

a double-stranded DNA genome within a brick-shaped particle of approximately 300 x 240 x 120

nm. Its 192 kb genome containing about 200 non-overlapping genes is arranged such that genes

crucial for viral replication are in a central conserved region while immunomodulatory and other

host interaction genes are at its end regions, flanked by two inverted terminal repeats that form a

hairpin loop at the ends. Within the virus, VV also encapsidates viral proteins such as DNA

polymerase, early transcription factors, DNA-dependent RNA polymerase, and capping proteins

to facilitate its replication in the cytoplasm and comprise its viral transcriptosome (Moss, 2013).

VV exists as two infectious forms: intracellular mature virus (IMV) and extracellular enveloped

virus (EEV). IMV is surrounded by a single lipoprotein membrane while EEV has an additional

host-cell derived membrane. The two forms of VV have different surface proteins and structural

differences determine the role and function of IMV and EEV forms within the VV life cycle

(Smith et al., 2002; Roberts and Smith, 2008). Most VVs are in its IMV form and are released

after cell lysis, but a small amount of EEVs can be released prior to lysis for long-range

dissemination (Roberts and Smith, 2008). The two forms are also antigenically different where

IMV has many targets for antibody neutralization but the A5 protein is the only known EEV

surface protein that induces neutralization (Putz et al., 2006). Laboratory stocks of VVs are in

IMV form as the isolation process damages the delicate outer lipoprotein layer in EEVs.

VV has a broad host range owing to its versatile cell attachment and entry mechanisms. An

unprecedented number of at least 16 proteins on the IMV membrane are involved in VV entry: 4

for cell binding, and 12 for membrane penetration (Laliberte et al., 2011); after initial cell contact

and before EEV entry, the non-fusogenic dissolution of the second outer membrane reveals the

IMV surface (Law et al., 2006). The cellular entry receptor for VV is still unknown but laminin

(Chiu et al., 2007) or ubiquitously-expressed cell-surface glycosaminoglycans (GAGs) such as

heparan sulfate (Chung et al., 1998) or chondroitin sulfate (Hsiao et al., 1999) have been shown

10

to be important but not always necessary to facilitate VV binding depending on cell type (Carter

et al., 2005; Chiu et al., 2007). IMV can enter cells by endocytosis (Townsley et al., 2006) or

fusion with the plasma membrane (Carter et al., 2005), however VV attachment and primary

mechanisms of entry are dependent on the host cell type and VV strain (Whitbeck et al., 2009;

Bengali et al., 2009).

Vaccinia virus has a complex morphogenic pathway (Figure 1.2) (McFadden, 2005; Roberts and

Smith, 2008). After cell entry, the virus core is released into the cytoplasm and transported by

microtubules to the perinuclear region (Carter et al., 2003) where the virus-associated

transcriptosome begins the early transcription process. Early genes express proteins that initiate

DNA replication, modify the host cell environment, and evade the host antiviral response. Then,

intermediate genes encode regulatory factors for late gene transcription which are involved in

producing proteins for new virus particles and a set of enzymes packaged into the new virion for

the next infection cycle (reviewed in (Broyles, 2003) ). Concomitantly, viral progeny are formed

in the cytoplasm away from cellular organelles, termed ―viral factories‖. The first visible

progeny are lipid- and protein-containing crescent-shaped immature virions that eventually grow

into oval or spherical shapes that encapsulate the virus core. The virion becomes the

characteristic brick-shaped IMV after proteolytic cleavage packages the VV DNA genome inside

the structure (Smith et al., 2002). The morphogenesis of most virions remain in the cytosol as

IMV until cell lysis, but a small percentage are transported by microtubules to become wrapped

in a membrane derived from either endosomes (Tooze et al., 1993) or the Golgi complex

(Schmelz et al., 1994) to become the EEV intermediate, intracellular enveloped virus (IEV), and

transfer to the cell periphery. At the periphery, actin tail formation pushes the cell-associated

enveloped virus (CEV) towards adjacent cells or releases the virion as free EEV (Smith et al.,

2002).

11

Vaccinia Virus Life Cycle

12

Figure 1.2. Vaccinia virus life cycle. The entire VV life cycle occurs in the cytoplasm by a complex pathway.

There are two forms of infectious VV particles: IMV and EEV, which is an IMV particle wrapped in an extra cell-

derived membrane. The cell-surface glycoproteins also differ between these two forms with IMV containing more

antigenic proteins. Entry of IMV by endocytosis or fusion is mediated by several VV proteins that interact with cell-

surface GAGs. EEV sheds its outer layer before entry. VV particles are transported to the perinuclear space by

microtubules to undergo early, intermediate, and late protein synthesis in ‗viral factories‘. After maturation, most

IMV stay in the cytosol until lysis. Some IMV are wrapped in a endosome- or Golgi-derived membrane to form IEV

which is pushed to the cell surface to form CEV which may be pushed further away by actin polyermization to

release free EEV particles. Abbreviations: VV – vaccinia virus, IMV – intracellular mature virus, EEV, extracellular

enveloped virus, GAG – glucosaminoglycan, IEV – intracellular enveloped virus, CEV – cell-associated enveloped

virus. [Reprinted with permission from McMillan Publishers: [NATURE REVIEWS MICROBIOLOGY]

(McFadden, G. Poxvirus tropism. 3(3): 201-213), Copyright 2005. (McFadden, 2005)

1.1.5.3 Advantages of Vaccinia Virus as an Oncolytic Virus

There are many attributes that make vaccinia virus a good candidate as an oncolytic virus:

The VV life cycle is spent entirely in the cytoplasm so the risk of integrating the viral

genome into the host chromosome is minimal (Moss, 2013)

VV has a broad host tropism allowing for its investigation as an anti-cancer agent in

numerous preclinical animal models and its application in humans (McFadden, 2005)

Vaccinia virus, unlike most OVs, remains stable in the blood after intratumoral (IT) and

intravenous (IV) injection. After initial tumor infection, some progeny is released in the

EEV form, which has an extra cell membrane layer with host complement control

proteins that protects the virus from immune recognition by complement or antibodies in

the blood (Vanderplasschen et al., 1998), allowing better delivery to tumors.

13

The VV genome can be easily engineered by standard DNA manipulation techniques. Up

to 25kb of DNA sequence can be inserted without deleting anything from its genome. VV

also has many non-essential genes that may also be deleted from its genome. Naturally

encoded or synthetically-developed promoters that drive high gene expression in VV are

also of merit (Damon, 2013; Guse et al., 2011).

VV has an excellent safety profile in humans which was demonstrated during its use in

the smallpox eradication program. Clinical information such as adverse events and

symptoms upon VV infection are extensively documented (Belongia and Naleway, 2003;

Lane et al., 1970).

1.1.5.4 Double-deleted vaccinia virus - vvDD

vvDD is a Western Reserve vaccinia virus with two non-essential gene deletions from its

genome: thymidine kinase (TK) and vaccinia growth factor (VGF) (McCart et al., 2001). Single

deletions of these genes from the VV genome have been shown to attenuate VV in normal cells

compared to wildtype WR VV (Buller et al., 1988a; Buller et al., 1985), but the double-deletion

works synergistically to further enhance VV tumor selectivity while maintaining wild-type

replication ability in tumors (McCart et al., 2001).

In humans, TK1 catalyzes the conversion of nucleoside thymine to thymidine monophosphate

(dTMP) in the salvage pathway in order to maintain of pool of nucleosides for dividing cells.

Human TK1 expression is mainly limited to the S-phase in normal cells (Sherley and Kelly,

1988) so VV expresses its own TK to ensure a supply of nucleotides to facilitate viral replication

at all stages of the cell cycle (Black and Hruby, 1991). Hence, the deletion of TK from VV

restricts viral replication to cells intrinsically expressing TK; an optimal host would be tumor

cells as many malignancies have been reported to constantly express TK at high levels (Topolcan

and Holubec, 2008). The deletion of VV TK- have been shown to reduce virulence (Buller et al.,

14

1985). Additionally, a TK-deleted vaccinia virus expressing luciferase was at least a 672-fold

higher in vivo luciferase expression in tumors compared to normal tissues (Puhlmann et al.,

2000).

Viral VGF is a secreted homologue of epidermal growth factor (EGF) that specifically binds to

the EGFR in uninfected adjacent cells to stimulate DNA replication and cellular proliferation

(Buller et al., 1988b; Stroobant et al., 1985), thereby preparing an optimal environment for

subsequent viral infection and replication. The deletion of VGF renders VV replication

dependent on inherently-initiated mitotic status. The LD50 of the VGF- VV for intracranial

injection in mice was 1000-fold higher than the wildtype WR VV (Buller et al., 1988a).

The potential of vvDD as an oncolytic agent has been tested both clinically and pre-clinically. In

one of its first pre-clinical evaluations, vvDD replication in normal tissues was similar or lower

than wildtype, TK-, and VGF-deleted VV replication in systemically-treated nude tumor-bearing

mice while maintaining a similarly high viral load within tumors (McCart et al., 2001). Its safety

was further supported in non-human primate studies where vvDD was significantly less toxic

than wildtype WR VV after intradermal injection, isolated limb perfusion, and IV treatment

(Naik et al., 2006). Its clinical efficacy is discussed in Section 1.1.6.1 below.

1.1.6 Oncolytic Viruses in Clinical Trials

No less than 96 clinical trials were initiated are ongoing for the investigation oncolytic viruses in

the clinic since January 2008 (Pol et al., 2015). Engineered vectors include but are not limited to

adenovirus, coxsackievirus, herpes simplex virus, measles virus, Newcastle disease virus,

reovirus, vaccinia virus, and vesicular stomatitis virus (Russell et al., 2012). Clinical trials offer

valuable information in terms of safety, adverse events, and therapeutic efficacy in humans.

15

The majority of clinical trials with OVs are in phase 1 and 2 with a primary endpoint to

determine the safety of the virus, dosing routes and schedules and the maximum tolerable dose

(MTD); though, efficacy was evaluated as a secondary endpoint. Current oncolytic viruses were

shown to be clinically safe and MTDs are often restricted by manufacturing limitations rather

than dose limiting toxicities (Russell et al., 2012; Miest and Cattaneo, 2014). Predominantly, the

side effects of local and systematic oncolytic virotherapy treatment have been transient and

tolerable with scant reports of serious adverse events. The most common treatment-related

adverse events were grade 1/2 flu-like symptoms such as fever, malaise, headache, and chills

(Lichty et al., 2014; Miest and Cattaneo, 2014). More severe toxicities are dependent on the virus

construct in addition to dosing routes (e.g. intravenous, intratumoral, intraarterial, or

intraperitoneal (IP)). For example, low-grade intravascular coagulation and transient

transaminitis was related to IV adenovirus (ONYX-015) treatment (Small et al., 2006;

Nemunaitis et al., 2001) while IV VV (JX-594) was associated with transient transaminitis and

cutaneous pustules (Heo et al., 2013). To date, there were no reports of treatment-related death

with oncolytic virotherapy (Russell et al., 2012; Liu et al., 2007). Overall, the safety profile and

adverse events of oncolytic virotherapy compare favourably in contrast to other phase I oncology

trials (Horstmann et al., 2005).

Environmental shedding is a concern that is unique to oncolytic virotherapy as a cancer

treatment: there is a possibility the virus may be released into the environment from the treated

patient, then mutate and regain wildtype pathogenicity; however current clinical data do not

support this concern (Liu et al., 2007; Buijs et al., 2015). Out of the clinical trials that evaluate

the presence of virus in urine, feces, or saliva, very few detect infectious particles (Liu et al.,

2007). Among the trials that report evidence of viral shedding in the urine, as an example, virus

levels were low and shedding was transient (Laurie et al., 2006; Deweese et al., 2001; Kimball et

al., 2010; Comins et al., 2010). For example, less than 50 infectious particles/ml of oncolytic

adenovirus CV706 were found in the urine for up to 29 days (Deweese et al., 2001). To date,

there are no reports of viral transmission to untreated contacts.

16

The host immune response is a major determinant of effective oncolytic virotherapy in patients.

In addition to direct tumor lysis, viral infections in the tumor can cause acute local inflammation

that redirects the host immune response towards long-term anti-tumor immunity. Alternatively,

the host response may prematurely eradicate the virus before a sufficient anti-cancer vaccination

effect can be mounted (Chiocca and Rabkin, 2014). Pre-existing neutralizing antibodies and

premature sequestration of the virus by the liver or spleen are recognized as significant barriers

to oncolytic virus delivery and efficacy (Russell et al., 2012). However, clinical data do not

always support this idea. For example, the presence of pre-existing antibodies against VV did not

affect JX-594 replication, safety, or anti-tumor effect of either IT (Heo et al., 2013) nor IV

treatment (Breitbach et al., 2011a). Immunological evaluation has also been highly suggestive of

treatment-stimulated anti-tumor immunity. Studies report a proportional increase in immune-

reactive lymphocyte subsets (such as cytotoxic CD8+ Tcells and natural killer) cells, neutralizing

antibodies, and/or infiltrating lymphocytes concurrent with tumor response with treatments with

reovirus (White et al., 2008), Newcastle Disease virus (Laurie et al., 2006), VV (Kim et al.,

2013), HSV (Kaufman et al., 2010), and adenovirus (Hemminki et al., 2015).

A few oncolytic viruses have been tested in more advanced phases of clinical trials which have

begun to discern therapeutic efficacy and survival advantage. Frontrunners include H101 (E1B-

deleted replication-selective adenovirus) (Xia et al., 2004), CG0070 (adenovirus armed with

granulocyte-macrophage colony stimulating factor (GM-CSF)) (Burke et al., 2012), T-Vec

(ICP47 and ICP34.5-deleted HSV expressing GM-CSF) (Andtbacka et al., 2015), and JX-594

(TK-deleted VV expressing GM-CSF) (Heo et al., 2013; Breitbach et al., 2011a). Recently,

talimogene laherparepvec (T-Vec) became the first oncolytic virus to be approved by the Food

and Drug Administration (FDA) for cancer treatment. T-Vec is an engineered HSV armed with

the immunomodulatory protein, GM-CSF, which will be used as an IT immunotherapy for

melanoma patients with unresectable lesions (Greig, 2016). In its phase III IT trial with patients

with advanced melanoma, the T-Vec treatment was compared to GM-CSF injections and was

reported to improve the durable response rate (16.3% v.s. 2.1%, p<0.01), overall response rate

17

(26.4% v.s.5.7%), and median overall survival (23.3 months v.s. 18.9 months; hazard ratio 0.79,

p=0.051) (Andtbacka et al., 2015).

1.1.6.1 Vaccinia Virus in Clinical Trials

To date, three oncolytic vaccinia viruses are being tested in clinical trials: JX-594 (a.k.a.

Pexavec, a TK-deleted Wyeth strain VV expressing GM-CSF and β-galactosidase marker gene)

(Heo et al., 2013; Breitbach et al., 2011a), vvDD (TK and VGF-deleted Western Reserve VV)

(Zeh et al., 2015; Downs-Canner et al., 2016) and GL-ONC1 (a.k.a. GLV-h168, a F14.5, TK,

and A56R-deleted Lister strain VV expressing GFP marker gene) (Pol et al., 2015).

Clinical investigations of IT and intravenous JX-594 treatment in solid tumors (e.g. melanoma

(Hwang et al., 2011), hepatocellular carcinoma (HCC) (Heo et al., 2013), colorectal carcinoma

(Park et al., 2015)) have demonstrated safety and promise as an anti-cancer treatment. The most

common adverse event among patients treated with IT and IV JX-594 were grade1/2 flu-like

symptoms with a minority of patients also presenting treatment-related pustule formation which

resolved within 2-3 weeks with no sequelae. Two patients with late-stage hepatocellular

carcinoma who were administered the highest IT dose (3x109 pfu) experienced grade III

hyperbilirubinaemia and so 1x109 pfu was deemed the MTD (Park et al., 2008). A maximum

feasible dose was determined for other injection routes or malignancies as there were no dose-

limiting toxicities in patients treated at the highest doses for multiple IT injections for melanoma

(up to 108 pfu/treatment up to 8 cycles) (Mastrangelo et al., 1999; Hwang et al., 2011), biweekly

IV infusion for colorectal cancer (up to 3x107pfu/kg) (Park et al., 2015), single IV treatment for

HCC (up to 3x107 pfu/kg) (Breitbach et al., 2011a), or single IT injections in children with solid

tumors (up to 107 pfu/kg) (Cripe et al., 2014). Viral genomes in the blood, infectious viral

particles in the tumor, transgene expression of GM-CSF, antibody induction to the β-

galactosidase marker gene, and tumor response were correlated to viral dose.

18

Tumor responses to JX-594 treatment were evaluated as a secondary endpoint to the clinical

trials. In its landmark trial with metastatic HCC patients, the authors report the first randomized

trial with an oncolytic virus treatment associated with a significant prolonged overall survival of

14.1 months compared to 6.7 months for the high dose group (1x109 pfu) and low dose group

(1x108pfu), respectively (Heo et al., 2013). The overall intrahepatic disease control rate at week

8 was 46% as evaluated by the modified Response Evaluation Criteria in Solid Tumors

(mRECIST) (Heo et al., 2013; Lencioni and Llovet, 2010) Induction of anti-cancer immunity

was also demonstrated in this trial when 11 out of 16 patients evaluated had antibody-mediated

complement-dependent cytotoxicity against 4 HCC cell lines (Heo et al., 2013). This is further

supported by the decrease in tumor size in injected tumors, as well as non-injected tumors in

some patients, in IT clinical trials (Mastrangelo et al., 1999; Hwang et al., 2011; Heo et al.,

2013). Concurrent serial dynamic MRI scans and subsequent histological analysis with patient

samples from this and other HCC clinical trials were conducted and affirmed selective tumor

vasculature disruption as another mechanism of action as alluded by pre-clinical studies

(Breitbach et al., 2007; Breitbach et al., 2013). Currently, clinical trials for IV JX-594 treatment

of renal cell carcinoma and colon carcinoma in combination with irinotecan are ongoing

(Breitbach et al., 2015; Pol et al., 2015).

The double-deleted vaccinia virus, vvDD, has recently been evaluated in phase 1 trials for IT

(Zeh et al., 2015) and IV (Downs-Canner et al., 2016) delivery to treatment-refractory solid

tumors (including colon cancer, pancreatic cancer, hepatocellular carcinoma, melanoma, and

breast cancer). For both, a maximum feasible dose was set at 3x109 pfu as there were no dose-

limiting toxicities and exquisite tumor-selectivity was demonstrated. Notably, a 1mm strip of

normal skin between two large melanoma lesions was spared despite IT injection and evidence

of viral replication in both tumor masses (Zeh et al., 2015). Evidence of immune cell activation

and virus infection in tumors was also reported for both treatments. Virus infection and tumor

response was present in injected and non-injected lesions for some patients treated IT (Zeh et al.,

2015). There were no objective clinical responses in the IV trial, however, some patients had

mixed responses where some lesions regressed or were stable before re-growing (Downs-Canner

19

et al., 2016). Nevertheless, clinical investigation of the true efficacy of vvDD as an oncolytic

virus will require larger patient populations.

Several preclinical examinations suggest GL-ONC1 as a promising oncolytic virus to test in

humans, including a study with human HCC cell lines in mice reported tumor response and the

induction of anti-tumor inflammation (Gentschev et al., 2011). A few clinical trials have since

been completed with GL-ONC1, but results have yet to be published such as: Phase 1 trial of

intrapleural GL-ONC1 in patients with malignant pleural effusion, phase I/II trial with IP GL-

ONC1 in patients with advanced peritoneal carinomatosis, and a phase 1 trial of intravenous GL-

ONC1 with head and neck cancer patients concurrent with cisplatin treatment (Pol et al., 2015).

1.2 Host Immune Response Against Viruses

1.2.1 Overview

The host immune response against viral infections is a complex process comprised of the innate

and adaptive immune responses. Interferons (IFNs) are critical for shaping the host response

against invading viruses. When viral components are recognized by the host cell, a cascade of

signaling events result in the production of many inflammatory cytokines, such as tumor necrosis

factor alpha (TNFα) and interleukin 1 (IL-1), chemokines, and type I IFNs, to culminate in pro-

inflammatory and antiviral processes (Kumar et al., 2011). Type I IFNs are important for

regulation of >300 interferon-stimulated genes (ISGs) to create an antiviral environment which

includes: the maturation of dendritic cells for antigen presentation, recruitment of monocytes,

and shaping the appropriate adaptive immune response (Schneider et al., 2014). In terms of the

adaptive immune response, CD8+ T-cells are important for VV clearance (Belyakov et al., 2003),

but the dependency of CD8+ T cells on CD4

+ T-cell help is dictated by infection route (Hu et al.,

2014). Nevertheless, CD4+ T-cells are important for long-term memory against VV (Medeiros-

Silva et al., 2013). Here, the antiviral response against VV is described with a focus on virus

recognition and the type I IFN signaling pathway, especially on the proteins related to this

project: Toll-like receptors (TLR), nuclear factor kappa-light-chain enhancer of activated B cells

(NFκB), and protein kinase R (PKR).

20

1.2.2 Pathogen Recognition

The first step in the host immune response against pathogens is recognition. Currently, 4 main

classes of pathogen recognition receptors (PRRs) were shown to detect VVs: toll-like receptors

(TLRs), retinoic acid inducible gene 1 (RIG-1)-like receptors (RLRs), and nucleotide-binding

oligomerization domain (NOD)-like receptors (NLRs), and cytoplasmic DNA sensors

(Perdiguero and Esteban, 2009; Kumar et al., 2011). TLRs are found either at the cell surface or

endosomal compartments of immune cells and some epithelial cells while RLRs, NLRs, and

DNA sensors are found in the cytoplasm of almost all cells. PRRs recognize pathogen-associated

molecular patterns (PAMPs) that are usually conserved on a pathogen. Signaling cascades via

TLRs, RLRs, and cytosolic DNA sensors result in inflammatory cytokine and type I IFN

expression, while the maturation of IL-1 is dependent on NLR activity against VV (Kumar et al.,

2011). Together, PRR signaling works co-operatively to scale and direct the appropriate

immune response (Tan et al., 2014). It is also important to note that PRRs also recognize danger-

associated molecular patterns (DAMPs) in response to host damage that may arise from viral

replication and lysis (Jounai et al., 2013). Figure 1.3 illustrates the induction pathway used by

PRRs (Perdiguero and Esteban, 2009).

1.2.2.1 Toll-Like Receptors

TLRs are mainly expressed in immunomodulatory cells, such as dendritic cells (DCs),

macrophages, and B cells, though TLRs are also found in some intestinal, respiratory, and

urogenital epithelial cells. To date, 13 TLR receptors have been identified in humans and mice;

10 are found in humans (TLR 1-10) and 12 in mice (TLR 1-9, 11-13). Viral PAMPs are

recognized by TLR2, TLR3, TLR4, and TLR9 in both humans and mice. TLR7 and TLR8

recognize viral single-stranded RNA (ssRNA) in mice and humans, respectively (Kawai and

Akira, 2006; Perdiguero and Esteban, 2009). The TLRs are compartmentalized on the cell

surface or within endosomes, on the basis of where its ligand is expected to appear upon

infection. Hence, TLRs that recognize viral lipoproteins, TLR2 and TLR4, are found on the cell

surface and TLRs that recognize viral nucleic acids, TLR3 (double-stranded RNA, dsRNA),

21

TLR 7/8 (ssRNA), and TLR9 (CpG-containing dsDNA), are compartmentalized in the

endosomes. All TLRs are trans-membrane proteins and have a horseshoe-shaped motif with

leucine-rich repeats for ligand recognition and a cytoplasmic Toll/IL-1 receptor (IL-1R)

homology (TIR) domain for downstream signaling. Upon ligand binding, TLRs dimerize and the

TIR-domains change conformation to recruit TIR-domain-containing adaptor proteins. There are

4 adaptors that promote inflammatory and antiviral responses: myeloid differentiation factor 88

(MyD88), MyD88 adaptor-like protein (MAL; also known as TIR-domain containing adaptor

protein, TIRAP), Toll receptor-associated activator of IFN (TRIF, also known as toll-like

receptor adaptor protein 1, TICAM-1), and TRIF-related adaptor molecule (TRAM)(Xagorari

and Chlichlia, 2008; Koyama et al., 2008). Sterile-α and armadillo motif-containing protein

(SARM) is a TIR-domain-containing adaptor protein that specifically inhibits TRIF-dependent

signaling (Carty et al., 2006). All TLRs are involved in either the MyD88-dependent signaling or

the TRIF-dependent signaling or both. Further, TLR4 is unique as the only TLR that can signal

with all 4 adaptor proteins; After induction of the MyD88-dependent pathway with

MyD88/MAL, TLR4 is endocytosed and interacts with TRIF/TRAM to initiate the TRIF-

dependent pathway (Kagan et al., 2008).

1.2.2.1.1 MyD88-Dependent Pathway

With the exception of TLR3, all TLRs can signal through the MyD88-dependent pathway. Upon

PAMP recognition, TLRs recruit MyD88 and the proteins interact via their TIR domains. While

other TLRs only recruit MyD88 directly upon PAMP recognition, TLR1, TLR2, TLR4, and

TLR6 also recruit MAL (Kumar et al., 2011). Upon MyD88 interaction, death domains of

MyD88 and IL-1 receptor kinase-4 (IRAK4) interact to recruit IRAK1 or IRAK2. Subsequently,

the IRAK complex interacts with the ubiquitin E3 ligase, tumor necrosis factor (TNF) receptor-

associated factor 6 (TRAF6), which activates TGF-β-activated kinase (TAK1). TAK1 can then

activate the members of the mitogen-activated protein kinases (MAPKs) Jnk, p38 and

extracellular signal-related kinases (ERKs) to activate ATF2/cJun. TAK1 can also form a

complex with TAK1-binding proteins TAB1, TAB2, and TAB3 to activate the IκB kinase (IKK)

complex (consisting of IKK-α, IKK-β, and IKK-γ (also known as NFκB essential modulator

22

(NEMO)) to phosphorylate IκB family, marking it for ubiquitination, which ultimately allows

NFκB to translocate into the nucleus. To also translocate into the nucleus, interferon regulatory

factor 5 (IRF5) forms a complex with MyD88 and TRAF6 to translocate to the nucleus while

IRF7 complexes with MyD88, IRAK1, and TRAF6. Together, ATF2/cJun, NFκB, and the IRFs

regulate the transcription of inflammatory cytokines and type I IFNs (Kumar et al., 2011).

1.2.2.1.2 TRIF-Dependent Pathway (MyD88- Independent Pathway)

TLR3 and TLR4 utilize the TRIF-dependent pathway which will ultimately lead to the activation

of pro-inflammatory cytokines and type I IFNs via IRF3, NFκB, and MAP kinases (Koyama et

al., 2008; Perdiguero and Esteban, 2009). While TLR3 interacts only with TRIF at the first step,

TLR4 also recruits TRAM as a bridging adaptor (Fitzgerald et al., 2001). TRIF can complex with

two proteins, the TRAF family member-associated NFκB activator (TANK)-binding kinase 1

(TBK1) and inducible IκB kinase (IKK-i, also known as IKKε), to phosphorylate IRF3 which

will translocate to the nucleus, form a homodimer and initiate IFNβ expression. TRIF can also

activate NFκB by interacting with the receptor interacting protein (RIP) family (RIPI, TRADD,

FADD) with its C-terminus or recruiting TRAF6. These pathways may converge to activate the

highest amount of NFκB. Interaction with TRAF6, as in the MyD88 pathway can also activate

the MAPK pathway (Koyama et al., 2008; Perdiguero and Esteban, 2009).

1.2.2.2 Cytosolic PRRs

In contrast to TLRs which are found mainly in immunomodulatory cells, cytosolic PRRs are

found in almost all cell types. Three groups of cytosolic PRRs recognize viruses: RLRs, NLRs,

and cytoplasmic DNA sensors. RLRs are a class of PRRs made up of 3 RNA helicases that

recognize viral RNA: retinoic-acid inducible gene-1 (RIG-1), melanoma differentiation-

associated gene 5 (MDA5), and laboratory of genetics and physiology-2 (LGP2). RLRs are

found in several types of cells including fibroblasts and conventional DCs (cDCs), but not

plasmacytoid DCs (pDCs). All members have a DexD/H box helicase domain and a C-terminal

23

repressor domain, but only RIG-1 and MDA5 have 2 caspase-recruitment domains (CARD)

while LGP2 has none. RIG-1 recognizes short dsRNA and longer ssRNA with a 5‘-triphosphate

while MDA5 binds to long dsRNA (Wu and Chen, 2014). The role of LGP2 is unclear, but has

been suggested to be a negative regulator of RLR signaling (Rothenfusser et al., 2005). Upon

viral RNA recognition, RLR signaling also initiates the expression of type I IFNs through the

IFNβ promoter stimulator 1 (IPS-1), TRAF3 and IRF3. The activation of NFκB enacted by

RLRs can be induced via the phosphorylation of the IKK complex via either TRAF3 or share

other components of the tumor necrosis factor (TNF) signaling pathway, Fas-associated protein

with a death domain (FADD) and TNFR type I-associated death domain protein (TRADD) (Wu

and Chen, 2014). Different kinds of cytosolic DNA sensors exist depending on cell type, but

these PRRs are also capable of inducing antiviral mechanisms. For example, a protein called

DNA-dependent activator of IFN-regulatory factors (DAI; also known as Z-DNA binding

protein 1 (ZBP1)) has been shown to associate with IRF3 to enable type I IFN expression

(Takaoka et al., 2007). NLRs comprise a family of proteins that recognize a wide range of

PAMPs which ultimately results in the expression of pro-inflammatory cytokines, the formation

of an ―inflammasome‖ that cleaves cytokines such as IL-1β into its mature form via caspase 1, or

the initiation of cell death (Kumar et al., 2011).

1.2.2.3 PRR Recognition of WR VV

The immune response elicited against the parental virus described in this project, WR VV, is not

fully understood, but several groups have reported TLR-dependent and TLR-independent

mechanisms. For example, in response to WR VV, the TLR2/Myd88 pathway was important for

expression of pro-inflammatory cytokines, DC maturation, and CD8 T cell secretion, but the

production of IFN-β was TLR-independent (Zhu et al., 2007). However, not all innate immune

sensing of WR VV has protective effects. TLR4 activation has a protective effect against

pulmonary WR VV infection (Hutchens et al., 2008a), but TLR3 signaling against WR VV

increased virulence and viral replication, partly by inducing an excessive inflammatory response

(Hutchens et al., 2008b). In terms of cytosolic PRRs, WR VV DNA has been shown to induce

the production of IFN-β via the RLR, MDA5, (Delaloye et al., 2009) and activate the NLR AIM2

24

inflammasome cleavage of pro-IL-1β into mature IL-1β (Rathinam et al., 2010). IFN-γ-inducible

protein (IFI16) (Unterholzner et al., 2010) and DAI (Takaoka et al., 2007) are cytosolic DNA

sensors that sense VV DNA.

26

Figure 1.3 Interactions between pathogen recognition receptors (PRR) and vaccinia virus (VV) inhibitory

proteins. Toll-like receptors (TLR), RIG-1-like receptors (RLR) and Nod-like receptors (NLRs) sense viral

components and leads to the activation of transcription factors (IRFs, NF-κB, and ATF2/c-Jun) to induce the

expression of type I IFNs and pro-inflammatory cytokines. A46 binds to adaptor molecules MyD88, TRIF, MAL,

and TRAM to inhibit TLR signaling. Downstream IRAK-2 and TRAF6 proteins are inhibited by the VV A52

protein. K7 prevents IRF nuclear translocation. NFκB activation is inhibited by and N1, B14, K1, and M2.

[Reprinted with permission by Mary Ann Liebert Inc. [JOURNAL OF INTERFERON AND CYTOKINE

RESEARCH] (Perdiguero, B. and Estaban, M. The Interferon System and Vaccinia Virus Evasion Mechanisms.

29(9):581-598) Copyright 2009. (Perdiguero and Esteban, 2009)

1.2.3 NFкB

NFκB is a family of transcription factors that are important for regulating the immune response

against es, but it is also a critical regulator of cell cycle and survival in response to a plethora of

stimuli. In mammals, the NFκB family consists of transcriptional activators characterized by a

Rel homology domain (RHD) in its N-terminus: RelA (p65), RelB, c-Rel, NFκB1 (p50), or

NFκB-2 (p52). RelA, RelB, and c-Rel are expressed in their mature form and contain a

transcriptional activator domain at their C-terminus. NFκB-1 and NFκB-2 do not have a

transcriptional activator domain and exist in the cytoplasm as precursor proteins, p105 and p100,

respectively (Gilmore, 2006). The NFκB family forms homodimers and heterodimers via the

RHD to differentially regulate gene expression. The most abundant form is the RelA/p50

heterodimer (Chen et al., 1999). NFκB is usually inactive in the cytoplasm and bound to an IκB

protein (RelA, RelB, c-Rel) or exists in its uncleaved proform (NFκB-1, NFκB-2 ) (Hoesel and

Schmid, 2013).

A variety of stimuli and signal transduction pathways ultimately culminate in NFκB activation.

Inducers range from conditions, such as DNA damage and hypoxia, pro-inflammatory cytokines,

such as IL-1 and TNF-α, or PRR recognition of PAMPs as described above. In the canonical

pathway of NFκB activation, the IKK complex phosphorylates the bound IκB protein (IκBα,

IκBβ, IκBγ or IκBε), marking it for subsequent degradation and releasing the NFκB into the

27

nucleus. In the alternative non-canonical pathway, NFκB is released following proteolytic

cleavage of its precursors into its mature form (NFκB-1, NFκB-2 ) (Hoesel and Schmid, 2013).

Many genes are activated by NFκB, including genes that express proteins that exert antiviral

mechanisms; pro-inflammatory cytokines, chemokines and adherins to facilitate NK cell

recruitment, and proteins related to cell cycle and survival. However, the target genes and the

magnitude at which they are expressed are context-dependent, determined by factors such as cell

type and stimulus. Co-activators, covalent modifications of NFκB, and the structure of the

binding site are also important factors (Smale, 2011; Chen and Greene, 2004; Oeckinghaus et al.,

2011). The expression of some proteins that regulate NFκB activation and repression are also

under the control of a NFκB promoter (Smale, 2011).

With respect to the antiviral mechanisms enacted by NFκB activation, NFκB regulates a

multitude of genes to orchestrate an appropriate immune response. First, it activates the

expression of pro-inflammatory cytokines such as IL-1, IL-6, IL-8, and TNFα (Hoesel and

Schmid, 2013; Santoro et al., 2003), chemokines and adhesion molecules for neutrophil

extravasion, and proteins for antigen presentation such as the major histocompatibility complex

(MHC) (Santoro et al., 2003). Second, enzymes that catalyze the production of molecules that

cause inflammation, such as cyclooxygenase 2 (Cox2) and nitric oxide synthase (iNOS), are also

upregulated by NFκB (Santoro et al., 2003). Third, NFκB is implicated in the survival and

development of innate immune cells, such as DCs. The survival of T- and B-cells during

development was also attributed to anti-apoptotic proteins from NFκB activation (Siebenlist et

al., 2005).

28

1.2.4 Interferons

1.2.4.1 Overview

IFNs are secreted cytokines that initiate and regulate potent antiviral properties (Samuel, 2001;

Teijaro, 2016; Grandvaux et al., 2002), but have also been implicated to have antineoplastic

functions (Fuertes et al., 2013; Zitvogel et al., 2015). There are 3 classes of IFNs, type I-III, that

are differentiated by their signaling receptors. The signaling enacted by the three types of IFNs

culminate in varying types of responses with respect to the regulated gene profile, induction and

scale of antiviral, anti-proliferative, and immunomodulatory processes (Schneider et al., 2014).

Some antiviral effects associated with IFN signaling include increasing the sensitivity of PRRs to

PAMP detection, co-stimulation of CD8+ T-cells resulting in enhanced cytotoxicity and

proliferation, promoting NK cell cytotoxic capacity and DC maturation, and expressing

molecules that inhibit viral entry, replication, translation, and egress (Teijaro, 2016; Schneider et

al., 2014; Crouse et al., 2015). Protein kinase R (PKR) is also one of the proteins involved in

inhibiting viral translation as a result of type I and II IFN signaling (García et al., 2007).

Type I IFNs comprise the largest class of IFNs and signal through a heterodimeric complex of

IFNα receptor 1 (IFNAR1) and IFNAR2, including: IFN-β, IFN-ε, IFN-κ, and 13 subtypes of

IFN-α. PAMP recognition is mostly responsible for the expression of type I IFNs, leading to very

potent antiviral responses. Almost all cells can express IFN-α and IFN-β, but pDCs express the

majority of IFN-α in response to a viral infection (Teijaro, 2016).

IFN-γ is the sole type II IFN. It exists as a homodimer and complexes with two IFN-γ receptor 1

(IFNGR1) subunits and two IFNGR2 subunits to initiate receptor activation. IL-12 and IL-18

induce the expression IFN-γ in immune cells such as CD8+ T-cells, CD4

+ T-cells, NK cells, B-

cells, and professional antigen-presenting cells express IFN-γ, but all cells can respond to IFN-γ.

The antiviral actions of IFN-γ are indirect; its mode of action is primarily regulating immune

cells in both the innate and adaptive immune response. One important function of IFN-γ in

29

response to virus involves skewing the immune response to the cell-mediated (Th1) immune

response (Schroder et al., 2004).

The most recently discovered class, type III IFNs, consists of IFN-λ1, IFN-λ2, and IFN-λ3 (also

known as IL-29, IL-28A, and IL-28B, respectively) and the recently discovered IFN-λ4. These

cytokines signal through a type III IFN-specific receptor, IFN-λ-receptor 1 (IFNLR1), and share

a ubiquitously expressed receptor with cytokines IL-10, IL-22 and IL-26, the IL-10 receptor 2

(IL10-R2) (Wack et al., 2015). Both type I and type III IFNs signal for a strong antiviral

response and activate similar subset of genes targeted against viruses (Schneider et al., 2014),

however all cells respond to type I IFNs while only a subset of cells, such as mucosal epithelial

cells, respond to type III IFNs (Wack et al., 2015).

1.2.4.2 IFN Signaling Pathway

All IFNs signal through the Janus kinase/ signal transducer and activator of transcription

(JAK/STAT) pathway as illustrated in Figure 1.4 (Perdiguero and Esteban, 2009). There are 3

known Janus kinases that are ubiquitously expressed and involved in the IFN signaling pathway:

JAK1, JAK2, and tyrosine kinase 2 (TYK2). In mammals, there are 7 known STAT proteins:

STAT1, STAT2, STAT3, STAT4, STAT5a, STAT5b, and STAT6. Inactive forms of JAK

proteins are pre-associated to the cytosolic domain of IFN receptors. When IFNs bind to their

respective receptors, the two IFN receptors are brought close together and the two JAK proteins

are juxtaposed to each other. Additionally, binding with IFN changes the conformation of the

cytosolic domain of the IFN receptors, thereby activating JAK-mediated phosphorylation of the

tyrosine residues on the receptor. The phosphorylation recruits STAT proteins where JAK

proteins also phosphorylate the tyrosine residues on the STAT protein which homodimerize or

heterodimerize to translocate into the nucleus to activate the expression of ISGs. Generally, type

I and III IFNs signal through JAK1 and TYK2 leading to heterodimers of STAT1-STAT2 which

bind to IRF9 to form a complex called IFN-stimulated gene factor 3 (ISGF3). ISGF3 translocates

into the nucleus to bind to IFN-stimulated regulatory elements (ISREs) to activate the expression

30

of type I and III ISGs. On the other hand, type II IFN signals through JAK1 and JAK2 to activate

STAT1 proteins to form a homodimer, called the IFN-γ activation factor (GAF), that translocates

to the nucleus to bind to the gamma-activated sequence (GAS) to initiate the expression of type

II ISGs (Schneider et al., 2014; Perdiguero and Esteban, 2009). Type I IFNs can also activate

homo- and heterodimers of other STAT proteins, as well as a heterodimer between STAT5 and

v-crk sarcoma virus CT10 oncogene homolog (avian)-like (CrKL) (Fish et al., 1999). Further, the

induction profile of ISGs by IFNs are shaped by pathways that either modify the JAK/STAT

pathway or are complementary non JAK/STAT signaling cascades that are simultaneously

induced with IFNs (e.g. PKC (protein kinase C) and MAPK signaling pathways and mTORC1

(mammalian target of rapamycin complex) and mTORC2 pathways) (Fish and Platanias, 2014).

Though type I IFNs signal through the same receptors, different subtypes result in widely

different functional effects. Variations in IFN subtype structure affect receptor-ligand

interactions and conformational changes in the receptor that ultimately determine downstream

signaling cascades (Thomas et al., 2011). Taken together, the induction of physiological effects

by IFN in response to different pathogens is a complex process shaped by simultaneously

activated pathways and differences in IFN subtype binding.

32

Figure 1.4. The interferon (IFN) signaling pathway and the vaccinia virus (VV) inhibitors. Antiviral,

antiproliferative and immunoregulatory responses are activated by IFN signaling through the JAK/STAT pathway.

VV encodes B8 and B19 to block IFN binding to the corresponding receptors. K3L and E3L gene products block

PKR activity. VV VH1 phosphatase, a virion component, inhibits STAT1 dephosphorylation. [Reprinted with

permission by Mary Ann Liebert Inc. [JOURNAL OF INTERFERON AND CYTOKINE RESEARCH]

(Perdiguero, B. and Estaban, M. The Interferon System and Vaccinia Virus Evasion Mechanisms. 29(9):581-598)

Copyright 2009. (Perdiguero and Esteban, 2009)

1.2.5 Protein Kinase R (PKR)

PKR is an IFN-induced dsRNA dependent protein kinase involved in many facets of an immune

response. Principally, dsRNA, potentially from the virus replication cycle, activates PKR

leading to autophosphorylation and subsequent phosphorylation of eukaryotic initation factor 2

alpha (eIF2α). The eIF2α phosphorylation interferes with eIF2β exchange of guanine

triphosphate (GTP) to guanine diphosphate (GDP), leading to the inhibition of eIF2 activity and,

ultimately, protein translation. The cessation of protein translation will also shut down viral

protein translation and, therefore, viral propagation. In addition to dsRNA, PKR is regulated by

many activators (PKR-associated factor (PACT), melanoma-differentiation-associated gene 7

(Mda7)) and inhibitors (heat shock protein 70 (Hsp70), trans-activation response RNA binding

protein (TRBP) (García et al., 2007). PKR is also implicated in many inflammation pathways.

First, PKR activates NFκB via the IKK complex (Zamanian-Daryoush et al., 2000), though it

remains controversial whether this activation is mediated by direct contact or kinase activity

(Gil et al., 2001; Bonnet et al., 2000). Most recently PKR may be associated with the NLRP3

inflammasome activation, though its effect is still debated (Yim et al., 2016; He et al., 2013;

Hett et al., 2013; Lu et al., 2012). In addition, PKR can phosphorylate the serine 392 residue of

the tumor suppressor protein, p53 (Cuddihy et al., 1999) and has been suggested to be

important for its tumor-suppressive function (Yoon et al., 2009).

33

1.3 VV Evasion of Innate Immunity

1.3.1 Overview

VV expresses many immunomodulatory proteins to counteract the host immune system to

facilitate successful VV replication (Figure 1.3 and 1.4) (Perdiguero and Esteban, 2009). Several

aspects of the innate antiviral immune response can be inhibited by products of VV

immunomodulatory genes including the complement system, IFN induction, IFN signaling,

NFκB activation, cytokines, chemokines, PKR activation, apoptosis, and NK cell cytotoxicity

(Perdiguero and Esteban, 2009; Smith et al., 2013). Here, we describe the VV genes pertinent

to the project described in this dissertation: TLR inhibitors (A46R, A52R), NFκB inhibitors

(N1L, K1L), and a PKR inhibitor (K3L).

1.3.2 VV TLR Inhibitors

The first step towards an immune response against VV infection is recognition. VV expresses

many early viral genes to counter immediate downstream processes induced by recognition by

PRRs. The VV genes relevant to this project are A46R and A52R which express non-redundant

early VV proteins A46 and A52, respectively, which inhibit a broad range of TLRs.

The full-length A46 is a 240-amino-acid protein that inhibits host TLR and IL-1 signaling

(Bowie et al., 2000; Stack et al., 2005). Specifically, A46 interacts with the TIR-domain

containing proteins such as MAL, TRAM, MyD88, and TRAF, ultimately inhibiting the

activation of NFκB, MAPK, and IRF3 (Bowie et al., 2000). Additionally, A46 does not interact

with SARM, a negative inhibitor of TRIF-dependent TLR signaling (Carty et al., 2006). The

structure of A46 is thought to contain a Bcl-2-like α-helix fold based on bioinformatic

prediction (González and Esteban, 2010) and biophysical examination (Oda et al., 2011;

Fedosyuk et al., 2014). Though Bcl-2 motifs are related to proteins associated in the regulation

of cell death, A46 function is not related to apoptosis (Postigo and Way, 2012). Its structure

34

hides the BH3 groove so that it cannot interact with apoptotic effector proteins (Fedosyuk et al.,

2014). Further, it has also been proposed that A46 may have a binding site for TRAM and a

different binding site for MAL or MyD88 since an 11-amino-acid oligonucleotide derived from

the A46 protein sequence, termed viral inhibitor peptide of TLR-4 (VIPER), could

competitively inhibit A46 interaction with the TIR domain on TRAM but not for MAL or

MyD88 (Lysakova-Devine et al., 2010; Kim et al., 2014). Functionally, the deletion of the

A46R gene from WR VV decreases its virulence after intranasal injection into Balb/c mice

(Stack et al., 2005). When investigated for its role in immunogenicity, the deletion of A46R

from the NYVAC strain of VV increased TNF, IL-6 and IL-8 secretion by human macrophages

in vitro and improved antigen-specific T-cell and B-cell responses in Balb/c mice (Perdiguero et

al., 2013) but its deletion from the MVA strain of VV failed to improve immunogenicity

(Cottingham et al., 2008).

A52 is a 23kDa intracellular protein that also inhibits IL-1 and TLR signaling (Bowie et al.,

2000), but interacts with comparatively more downstream proteins, IRAK2 and TRAF6 (Harte

et al., 2003). A52 also activates the p38 MAP kinase to drive TLR-4 mediated expression of the

immunosuppressive cytokine, IL-10 (Maloney et al., 2005). Recently, A52 was implicated in

influencing the MAPK/AP-1 (c-Jun) pathway as a single protein without infection (Albarnaz et

al., 2016). Structurally, the A52 protein is entirely α-helical with a Bcl-2-like fold. However,

like A46, its structure occludes the BH3 interaction motif so the protein does not interact with

BH3-domain-containing pro-apoptotic proteins, Bid and Bax (Graham et al., 2008; Postigo and

Way, 2012). Similar to A46, when the A52R gene was deleted from WR VV, weight loss and

signs of sickness was significantly reduced following intranasal treatment in Balb/c mice

(Maloney et al., 2005). Though A52 and A46 have very similar structures and overlapping

effects as a result of inhibiting IL-1 and TLR signaling, such as inhibiting MyD88-dependent

NFκB activation, each protein is functionally distinct. A52 is a potent inhibitor of NFκB but not

the TLR3-dependent IRF3. In contrast, A46 is a potent inhibitor of TLR3- and TRIF-dependent

IRF3 activation, but a weak inhibitor of TLR3-mediated NFκB activation (Stack et al., 2005).

35

1.3.3 VV NFкB Inhibitors

NFκB is an important protein in the IFN signaling and induction pathway against viruses

(Perdiguero and Esteban, 2009). As such, VV also counteracts the gene modulation by NFκB

with its own proteins. The VV genes investigated in this study under this category are N1L and

K1L.

The VV N1L gene protein product, N1, exists as a 14kDa intracellular homodimer that inhibits

apoptosis, NFκB and IRF3 activation. The anti-inflammatory effect against NFκB and IRF3

activation was thought to be related to the interaction with the IKK complex and TBK1,

respectively (DiPerna et al., 2004), but whether the N1 protein co-precipitates with the IKK

complex after infection is debated (Chen et al., 2008). The structure of N1 also contains α-

helixes to form Bcl-2-like fold that functionally inhibits pro-apoptotic proteins at its BH3 motif

(Aoyagi et al., 2007). Further, N1 contains separate binding sites for its anti-inflammatory and

anti-apoptotic activity (Maluquer de Motes et al., 2011). The deletion of VV N1L from WR VV

reduced virulence following intranasal and intradermal injection into Balb/c mice (Bartlett et al.,

2002), but virulence is driven by its anti-inflammatory activity more than its anti-apoptotic

properties (Maluquer de Motes et al., 2011). Immunologically, N1 was implicated in reducing

the infiltration of NK cells and increasing the proportion of lymphocytes bearing the early

activation marker, CD69 (Jacobs et al., 2008) .The presence of the N1 was also shown to inhibit

secretion of IFNα, IFNβ, TNFα, and IL-1β in primary human monocytes in vitro (Zhang,

Zhouning et al., 2005).

The K1L gene encodes a protein (K1) that acts as both an NFκB inhibitor and a host range

protein, and its role as both are enacted by the same protein motif (Meng et al., 2009). K1

prevents the degradation of IκBα, which would have allowed NFκB to enter the nucleus and

activate pro-inflammatory and antiviral genes (Shisler and Jin, 2004). Its deletion rendered VV

susceptible to type I interferon signaling (Meng et al., 2009). Further, K1 can inhibit the

36

phosphorylation of PKR in RK13 and HeLa cells (Willis et al., 2009). The structure of K1

consists entirely of ankyrin repeats (7 complete, 2 incomplete) that form a convex shape for

protein: protein interaction (Li et al., 2010). When K1L was deleted from the TianTian strain of

VV, its virulence was significantly reduced compared to VV following intranasal and

intracranial injection (Liu et al., 2013). Host range genes are important for successful viral

replication in different types of cells. Pertaining to VV, either C7L or K1L is usually required

for replication in many human cell lines (Perkus et al., 1990; Gillard et al., 1986). Alternatively

C7L does not affect viral propagation in rabbit kidney RK13 cells, while either K1L or the

cowpox virus gene CP77 are required for successful replication (Ramsey-Ewing and Moss,

1996; Perkus et al., 1990). It is unclear how K1L enables host range, but deletions of different

sets of ankyrin repeats in K1 in a C7L-deleted WR VV mutant were shown to reduce replication

in rabbit RK13 and human HeLa cells (Meng and Xiang, 2006).

1.3.4 VV PKR Inhibitor

One of the proteins activated as a result of IFN signaling is PKR, which is responsible for the

shutdown of protein translation, thereby preventing viral protein production. In this study, the

VV K3L gene which encodes for K3, an inhibitor of PKR, was deleted.

K3 is a 10.5 kDA protein that binds to PKR and prevents eIF2α phosphorylation, thereby

stopping the inhibition of protein translation and potentiating VV propagation (Langland and

Jacobs, 2002). X-ray crystallography reveals two distinct regions that are implicated in PKR

inhibition: a β-barrel with a helix insert region similar to the S1 domain in the K3 protein

structure. Strong sequence homology between the K3 and one third of the eIF2α protein from its

N-terminal, suggests K3 can competitively bind to the eIF2α binding site on PKR. The ability of

K3 to non-competitively inhibit PKR phosphorylation is proposed to be affiliated with the helix

insert region although the mechanism is unknown (Dar and Sicheri, 2002). Deletion of K3L

37

from the Copenhagen strain of VV maintained wildtype replication in HeLa cells but not BHK

cells (Langland and Jacobs, 2002).

1.4 Dysregulation of IFN Induction and Signaling Pathways in Cancer Cells

1.4.1 Overview

Cancer is a result of accumulated mutations that lead to uncontrolled proliferation. Before the

aberrant cells become clinical malignancies, the cancer cells must overcome the host immune

system. Hence, in exchange for immune escape from recognition despite uncontrolled

proliferation, many types of cancer cells have mutations that dysregulate one or many effectors

involved in the IFN induction and signaling pathways (Critchley-Thorne et al., 2009). In a

normal cell, the IFN response and the proteins involved are tightly regulated. Tumors that

escape immune detection often have aberrant expression of function of these key players. Thus,

the VV immunomodulatory genes (described in Section 1.3.) may be redundant for the evasion

of the antiviral immune response. Here, we describe mutations relating to IFN induction and

signaling with a focus on TLRs, NFκB, and PKR.

1.4.2 TLRs in Cancer

TLRs are usually expressed in immune cells and some epithelial cells that line surfaces prone to

pathogen infection. Specifically, alveolar and bronchial epithelial cells, normal keratinocytes

found on skin, and epithelial cells found in the digestive system, and the female reproductive

tract normally express TLRs. Elevated TLR expression is also found or upregulated in a wide

variety of tumors: ovarian (Zhou et al., 2009), colon (Furrie et al., 2005), and melanoma (Goto

et al., 2008). MyD88 mutation in haematological malignancies (Wang et al., 2014) and variants

of TLR in prostate cancer (Sun et al., 2005). In general, the role of TLRs in tumor survival are

thought to be related to downstream effects of enhanced TLR activation leading to pro-tumor

NFκB functions, where activation may be from continuous stimulation of DAMPs associated

38

with dying tumor cells, and TLR-4 mediated IL-10 expression in response to

lipopolysaccharides (Huang et al., 2008; Killeen et al., 2006).

1.4.3 NFкB in Cancer

The tightly-regulated functions of NFκB play important roles in inflammation, immune

response, and cell survival; however, aberrant NFκB expression can drive tumorigenesis, tumor

survival and migration. Persistent activation of NFκB has been observed in a variety of

lymphomas and solid tumors including: B-cell lymphoma (Staudt, 2010), colorectal cancer

(Lind et al., 2001), breast cancer (Sovak et al., 1997), pancreatic cancer (Fujioka et al., 2003),

lung cancer (Chen et al., 2011), and melanoma (Ueda and Richmond, 2006).

Though constant activation by PRRs could cause persistent NFκB activation, the constitutive

induction of NFκB activity could also be caused by direct mutations in the genes encoding

NFκB subunits or the proteins within its signaling pathway, though this phenomenon is more

prevalent in lymphomas. For example, chromosomal rearrangements and deletions have been

observed in the NFκB-2 gene in several lymphomas, including B-cell lymphoma and multiple

myeloma, result in a truncation of the C-terminal ankyrin repeats essential for repressing NFκB-

2 nuclear translocation. The protein processing of the truncated p100 is also associated with a

gain of transcriptional function in distinct target genes (Qing et al., 2007). Though rare, direct

gene mutations of proteins involved in NFκB signaling in solid tumors have also been reported.

For example, mutations in genes encoding NFκB-2, IκBα, IκBε, and IKK-β have been found in

breast cancer (Jiao et al., 2012). Constitutive expression of NFκB can also be induced by

persistent interaction of NFκB activators and oncoproteins as illustrated by the indirect

activation of IKK/ NFκB by the mutated Ras protein through AKT and Raf proteins (Basseres et

al., 2010).

The persistent activation of NFκB has been suggested to have many tumor-promoting roles.

First, NFκB can activate the expression of cytokines (IL-1, IL-6, IL-8, TNF-α), enzymes that

39

catalyze inflammatory products (COX2, iNOS), and chemokines and adherins to attract

neutrophils that secrete reactive oxygen species. Together, a constitutive inflammatory state is

induced which may lead to DNA damage and oncogenic mutations (Hoesel and Schmid, 2013;

Ben-Neriah and Karin, 2011; Kim et al., 2006a). Though NFκB activation may be pro-apoptotic

or anti-apoptotic depending on context (Radhakrishnan and Kamalakaran, 2006), it is also

implicated in prolonging tumor survival by its anti-apoptotic and cell proliferation properties.

Expression of growth factors (Cyclin D1, c-myc, KU70, KU80) and promotion of angiogenesis

(vascular endothelial growth factor (VEGF)) is also related to NFκB activation (Guttridge et al.,

1999; La Rosa et al., 1994)(Hoesel and Schmid, 2013). Further, NFκB can activate the

expression of matrix metalloproteinases (MMPs), thus it is implicated in contributing to

epithelial-mesenchymal transition (EMT) and metastasis (Huber et al., 2004). Last, NFκB in

epithelial cancer cells was postulated to be involved in a crosstalk with tumor-associated

macrophages resulting in the maintenance of anti-inflammatory M2-phenotype after prolonged

tumor growth instead of the inflammatory, anti-tumor M1-phenotype, thereby facilitating tumor

survival and immune escape (Hagemann et al., 2008; Hoesel and Schmid, 2013).

1.4.4 PKR in Cancer

IFN-induced PKR activity is also complex in normal cells; hence its role in cancer remains at

least equally complex. PKR expression in head and neck cancer and some melanoma, colon and

lung cancers was down-regulated and induction of PKR expression improved prognosis

(Marchal et al., 2014). Functional PKR was also an important target for treatment of colon and

breast cancer cell lines with 5-FU to cause tumor cell apoptosis (García et al., 2011). However,

its overexpression in thyroid carcinoma, broncheoalveolar carcinoma, breast cancer, liver

cancer, and some melanoma, colon, and lung cancers suggested PKR did not always have an

anti-tumor role (Marchal et al., 2014). It was postulated that the elevated PKR may be to initiate

NFκB pro-tumor activation as described above (Delgado André and De Lucca, 2007).

40

1.5 Peritoneal Carcinomatosis (PC)

1.5.1 Overview

Peritoneal carcinomatosis (PC) is classified as a type of late-stage peritoneal surface malignancy

wherein cancer cells deposit in the visceral or parietal peritoneal surfaces and constitutes a

tumor burden in the peritoneal cavity. Primary peritoneal surface malignancy is the de novo

occurrence of the metastatic disease and includes peritoneal mesothelioma and primary PC.

Though rare, primary PC can arise from de novo formation and is considered a variant of

ovarian cancer, accounting for 7-14% of ovarian malignancies. More often, secondary PC arises

from primary tumors, colon, ovarian, gastric, and appendiceal origin being most common

(Nissan et al., 2009). For this study, the oncolytic VV candidates generated in this project were

tested in animal models of PC originating from colon and ovarian cancer cell lines.

1.5.2 PC Tumor Origin and Incidence

Secondary PC can arise from a variety of primary tumors. In clinical studies of non-

gynecological PC, 54.6% of PC patients had synchronous PC wherein the most common

symptoms were ascites (34.9%) and bowel obstruction (24.3%) (Chu et al., 1989; Sadeghi et al.,

2000). In a more recent study with 370 patients, EVOCAPE, the distribution of PC tumor

origins were as follows: 33.8% gastric, 31.9% CRC, 15.7% pancreatic, 1.1 % small bowel, 0.8%

liver, 3.2% appendiceal, 1.9% mesothelioma, and 11.6 % of unknown origin (Sadeghi et al.,

2000).

The incidence of PC is usually described in relation to its primary tumor. Approximately 10% of

all CRC cases develop PC during the course of the disease (Kerscher et al., 2013). On the other

hand, PC is found in 5-30% of patients during surgery for gastric cancer (Gill et al., 2011). In

Canada, 65.8% of ovarian cancer patients have late stage spread at the time of diagnosis

(Maringe et al., 2012).

41

1.5.3 Colorectal Cancer (CRC)

Colorectal cancer (CRC) is the third most lethal cancer in Canada. An estimated 9300

Canadians died of colon cancer in 2015. Despite recent advances in early detection, there was

only a modest decrease in mortality (Canadian Cancer Society, 2015). There are many risk

factors associated with sporadic CRC. Many lifestyle choices affect the risk of CRC including

diet and exercise. The incidence of CRC is also higher in migrants and inhabitants of the urban

areas of developed countries with Western culture. Further, non-modifiable risk factors of CRC

include age, family history of CRC, and a history of inflammatory bowel disease (Haggar and

Boushey, 2009).

1.5.4 Ovarian Cancer

Ovarian cancer is the leading cause of death among gynecological malignancies. An estimated

1750 Canadian women died of ovarian cancer in 2015 (Canadian Cancer Society, 2015). Early

detection is difficult as there are no specific symptoms attributed to the early stages of disease

(McLemore et al., 2009). Additionally, Canadian women with late stage (stage IV) epithelial

ovarian cancer have a 5-year relative survival of 18% (Canadian Cancer Society, 2015) . The

etiology of ovarian cancer is not clearly defined, but a number of causes have been proposed.

Risk factors for ovarian cancer include age, family history, chronic inflammation, diet, infertility

drug use, obesity, smoking and asbestos exposure (McLemore et al., 2009).

Most ovarian cancers are of epithelial origin, where rarer types develop into sex-cord stromal,

germ cell-, or mixed cell- type tumors (Kalir et al., 2013). Epithelial ovarian carcinomas can be

broadly categorized into two categories: type I and type II. Type I ovarian carcinomas are

usually low grade tumors. Type II ovarian carcinomas are more frequent and are aggressive,

malignant, high-grade serous tumors that are often found in late stage ovarian carcinoma

(Nezhat et al., 2015)

42

1.5.5 Pathophysiology and Biology of PC

The development of PC can be described by 3 mechanisms: dissemination from the primary

tumor, de novo formation of tumor in the peritoneum, or polyclonal multifocal origin

(Kusamura et al., 2010). Peritoneal seeding is the most common pathway of PC of ovarian

(Masoumi Moghaddam et al., 2012) and gastrointestinal origin (Terzi et al., 2014).

Dissemination can occur via 2 routes: the transmesothelial or translymphatic route (Kusamura et

al., 2010). In the transmesothelial route, the dissemination of PC from primary tumor that has

invaded the serosa can be from the natural sloughing or spontaneous release of viable tumor

cells within the peritoneum. The spontaneous dissemination could be aided by the down-

regulation of adhesion molecules such as E-cadherin. The down-regulation of E-cadherin has

been reported in PC of colon, gastric, and ovarian origin. Alternatively, viable tumor cells may

be accidentally released during surgery from tumor perforation or spillage of resected

lymphatics and blood vessels (Kusamura et al., 2010). Free cancer cells spread through the

lymphatic stomata found in ―milky spots‖ where peritoneal macrophages traverse into the

peritoneal cavity. ―Milky spots‖ are small structures devoid of a capsule, supported by the blood

and lymphatic system, are in contact with the peritoneal membrane, and contain macrophages

and lymphocytes (Sacchi et al., 2007). Cancer dissemination usually occurs in the

abdominopelvic regions where milky spots are found such as the Douglas pouch, greater

omentum, inferior diaphragm, and pelvis (Carmignani et al., 2003).

Adhesion to the mesothelium is facilitated by the elevated expression of adhesion molecules

such as CD44, lymphocyte homing molecules, and members of the integrin superfamily (Jayne,

2003). Subsequent invasion into the mesothelial layer is mediated by cytokine production

leading to the contraction of mesothelial cells and exposure of the submesothelial membrane

(Kusamura et al., 2010). Invasion into the submesothelial membrane is then facilitated by matrix

mellaproteinases to degrade the peritoneal blood barrier (Jayne, 2003). Proliferation of the

newly-attached tumor cells is triggered by paracrine and autocrine loops of growth factors, such

as epidermal growth factor (EGF), and the production of new vasculature via vascular

endothelial growth factor (VEGF) (Masoumi Moghaddam et al., 2012).

43

Primary PC is a more rare form of PC where examples include diffuse malignant mesothelioma.

The mechanism of spontaneous formation of PC is unclear and may be caused by DNA damage

from a variety of effects from environmental stresses, as in the case of asbestos-associated

diffuse malignant mesothelioma (Musti et al., 2006; Toyokuni, 2009; Shukla et al., 2003). In the

last form of PC wherein tumors originate from different multiple gene mutations, as in PC with

ovarian tumors with low malignant potential, the mosaic of mutational differences is possibly

attributed to the spectrum of X-chromosome inactivation patterns between cells (Gu et al.,

2001).

1.5.6 Treatment of CRC PC and Ovarian PC

Until a few decades ago, PC was viewed as a terminal disease and was treated with palliative

surgery. In 1995, Sugarbaker treated PC as a loco-regional disease and proposed peritonectomy,

or cytoreductive surgery (CRS), as a possible treatment. This novel and aggressive surgical

technique involved peritoneum stripping, omentectomy, and resection of all visible tumor even

if it entailed partial or complete organ resection (Sugarbaker, 1995). After surgical resection, the

extent of tumor resection is recorded with the completeness of cytoreduction (CCR) score

(Jacquet and Sugarbaker, 1996). The completeness of resection is an important factor in

treatment outcomes (Verwaal, 2003).

After CRS, chemotherapy drugs heated to 41-43°C could be delivered intraperitoneally

immediately following resection in the operating room (hyperthermic intraperitoneal

chemotherapy (HIPEC)). The heat can increase the cell membrane permeability and drug uptake

in malignant cells (Sticca and Dach, 2003). The chemotherapy agents for intraperitoneal

delivery vary between institutions, but mitomycin C and oxaliplatin is most commonly used for

CRC PC. Different combinations of paclitaxel, cisplatin, doxorubicin, and cyclophosphamide

have been used for intraperitoneal delivery to ovarian PC (Rubino et al., 2012). With

44

intraperitoneal delivery, chemotherapy can be administered at higher doses compared to

systemic therapy (Katz and Barone, 2003). The chemotherapy can also be delivered 1-5 days

post-operatively (early post-operative intraperitoneal chemotherapy (EPIC)) (Rubino et al.,

2012).

The prognosis of patients with CRC PC was grim until recently; a retrospective analysis

determined that the median survival of patients in this category treated with palliative surgery is

7 months (Jayne et al., 2002). Today, the standard treatment of advanced CRC is CRS with

systemic chemotherapy. Modern modalities of chemotherapy include combinations with the

older agents, 5-fluoracil (5-FU) and leucovorin, and the newer chemotherapy agents irinotecan

and oxaliplatin (Nissan et al., 2009). Additionally, CRS with HIPEC and systemic

chemotherapy have been promising in clinical trials compared to CRC PC with the best

supportive chemotherapy (Klaver et al., 2012). In the only randomized phase III trial, patients

treated with the standard care had a median survival of 12.3 months compared to 22.3 months

for patients in the CRS with HIPEC arm (Verwaal, 2003). In the 8-year follow-up report of this

trial, the median disease-specific survival was 12.6 months compared to 22.2 months in the

HIPEC arm. Further stratifications of the HIPEC arm revealed that the 5-year survival was 45%

among patients with no macroscopic disease after CRS (Verwaal et al., 2008). However, it

should be noted that the post-operative mortality in this arm was also 8% and treatment-related

grade 4 morbidity was 45%. (Verwaal, 2003).

Front-line treatment of advanced ovarian cancer, or ovarian PC, is CRS with systemic platinum

(e.g. carboplatin, cisplatin) and taxane combination (e.g. paclitaxel, cycophosphamide) of

chemotherapy. The cancer is generally responsive to this front-line treatment, but 20%-30% of

ovarian cancers are platinum-resistant. Despite treatment of advanced ovarian cancer with CRS

and systemic chemotherapy, the incidence of recurrence still occurs in 60-70% of ovarian cancer

patients (Helm, 2009). Hence, CRS with intraperitoneal chemotherapy is an attractive treatment

for ovarian PC to eradicate microscopic tumor nodules. Three randomized phase III clinical

trials demonstrated superior survival compared to front-line treatment in stage 3 ovarian PC

45

(Alberts et al., 1996; Markman et al., 2001; Armstrong et al., 2006). In the most recent trial, 429

patients were stratified between CRS with systemic chemotherapy or CRS with post-operative

intraperitoneal chemotherapy and systemic chemotherapy. The overall survival was improved

from 49.7 months to 65.6 months. However, there were more severe adverse events in the

experimental treatment group including myelosuppression, neurotoxicity and vomiting

(Armstrong et al., 2006). A number of observational studies have also been published about the

treatment of advanced stage or recurrent ovarian PC with CRS with HIPEC. In general, the

survival benefits associated with the combined CRS and HIPEC treatment were improved or

similar to standard CRS with systemic chemotherapy. Larger randomized trials are ongoing or

proposed to elucidate its true efficacy in ovarian PC (Coccolini et al., 2013).

The treatment-related morbidity and mortality has been a concern for CRS with HIPEC

treatment. To address this, a multi-institutional retrospective review was conducted for this

treatment of non-gynecological PC involving 1290 patients. The overall median survival was 34

months and the 5-year survival was 37%. The mortality and morbidity rates were 4.1% and

33.6%, respectively, and the authors conclude that these rates are similar to major surgical

treatments such as esogophagectomy and pancreaticoduodectomy (Glehen et al., 2010)

1.5.7 Clinical Need

Late stage metastatic disease, such as PC, remains very difficult to treat. Though CRS coupled

with HIPEC or EPIC is a possible treatment for PC patients, the procedure entails significant

post-operative mortality and morbidity rates (Glehen et al., 2010). Additionally, criteria such as

the completeness of resection are important prognostic factors for PC (Verwaal, 2003; Helm,

2009), hence the patient must meet certain eligibility criteria to undergo this aggressive

treatment. The current health of the patient, the tumor burden, tumor grade, and tumor location

are all factors to be considered, though criteria differ between institutions. Only a small

proportion of patients are eligible for CRS with HIPEC treatment. A retrospective study

46

estimates that only 20% of the CRC PC patients would have been eligible (Jayne et al., 2002).

Thus, there is a need for a safe and targeted novel anti-cancer therapy that is effective at every

stage of dissemination. Oncolytic virotherapy (discussed in Section 1.1) may be able to meet

this need.

47

1.6 Aims and Hypothesis

1.6.1 Rationale

Late stage cancers, such as CRC PC and ovarian PC, are often difficult to treat. Though CRS

with HIPEC treatment is promising, the tumor burden is often too high in many PC patients to

derive benefit from this treatment. OVs, such as vvDD, have demonstrated safety and tumor-

selectivity in both pre-clinical and clinical investigations, but increasing OV potency can

improve therapeutic efficacy. Most OVs in the clinic are tumor-selective based on cell

proliferation rates, which may not replicate in and kill slow-growing cancer cells efficiently.

Engineering strategies should exploit a different mechanism of tumor-selectivity.

Many proteins associated with the antiviral IFN response are often dysregulated in

malignancies; therefore VV immunomodulatory genes are redundant for successful replication

in tumors. The VV immunomodulatory genes described in this project (N1L, K1L, K3L, A46R,

and A52R) inhibit major proteins in the IFN induction and signaling pathways that are also

found to be dysregulated in many cancers. Further, these VV genes have previously been shown

to be virulence factors. Therefore, we propose to generate a panel of oncolytic VVs with greater

tumor potency and similar tumor-selectivity compared to vvDD, by deleting one of the

aforementioned genes from WR VV.

1.6.2 Hypothesis

The deletion of VV immunomodulatory genes (N1L, K1L, K3L, A46R, or A52R) will yield an

oncolytic VV with improved potency towards colon and ovarian cancer while maintaining equal

or better attenuation in normal tissue compared to vvDD.

48

1.6.3 Specific Aims

Aim 1: Generate VV deletion mutants via homologous recombination

Aim 2: Compare the candidate VV deletion mutants to vvDD in terms of in vitro viral

replication, cytotoxicity, and viral spread in colon and ovarian carcinoma cell lines

Aim 3: Compare the candidate VV deletion mutants to vvDD in terms of in vivo tumor-

selectivty, toxicity, and efficacy in mouse models of PC.

49

Chapter 2

2 Materials and Methods

2.1 Cell Lines

Human colorectal adenocarcinoma cell line DLD-1, human ovarian cancer cell line A2780, and

normal monkey kidney fibroblast cell line CV-1 were obtained from the American Type Culture

Collection (ATCC; Manassas, Virginia, USA). MC38 murine colorectal adenocarcinoma cell

line cells and C57BL/6 murine sarcoma cell line 24JK were obtained from the National Institute

of Health (NIH; Bethseda, Maryland, USA). Cells were cultured at 37°C and 5% CO2 in media

supplemented with 10% fetal bovine serum (FBS; PAA Laboratories, Etobicoke, ON, Canada)

and 1% penicillin-streptomycin (Invitrogen, GIBCO, Grand Island, New York, USA). All cell

lines were maintained in Dulbecco‘s Modified Eagle Medium (DMEM; Sigma-Aldrich,

St.Louis, Montana, USA) except A2780 cells which were maintained in Roswell Park Memorial

Institute medium (RPMI 1640; in-house Toronto Medical Discovery Tower media, University

Health Network, Toronto, ON, Canada).

2.2. Vaccinia Viruses

Western Reserve (WR) vaccinia virus F13L+ (wildtype virus with lacZ insertions (Roper and

Moss, 1999)) was used as the backbone virus in the creation of our candidate viruses. All

candidate viruses were compared to the previously described virus, vvDD (McCart et al., 2001),

a WR vaccinia virus with a deletion in its thymidine kinase (TK) and vaccinia growth factor

(VGF) genes. Specifically, vvDD-R2R-Luc is used. The viral TK gene is interrupted with a

sequence for red fluorescent protein (RFP) insertion conjoined with Renilla luciferase via a foot-

and-mouth disease virus 2A motif to allow for bicistronic marker expression and the VGF genes

found within the VV inverted terminal repeats are interrupted by a lacZ gene at both ends of the

virus genome (Lun et al., 2009).

50

2.3. Creation of the Candidate Vaccinia Virus Deletion Mutants

Wildtype WR vaccinia virus, F13L+, was used as a backbone virus for the creation of the

vaccinia virus deletion mutants via homologous recombination by using a vaccinia virus shuttle

plasmid. The final candidate viruses were wildtype WR vaccinia viruses with a deletion in one

of the following genes: N1L, K1L, K3L, A46R, or A52R. The shuttle plasmid, pVX-R2R-Luc,

has a RFP gene fused to Renilla luciferase via a foot-and-mouth disease virus 2A motif to

facilitate bicistronic marker expression under the control of a synthetic late promoter pSyn/late

and a xanthine-guanine phosphoribosyltransferase (xgprt) gene under regulation of the early/late

p7.5 promoter. Five hundred base pair gene segments flanking the right and left regions of the

wildtype candidate genes for deletion were generated by polymerase chain reaction (PCR) with

the VJS6 virus DNA (VGF- WR vaccinia virus with lacZ gene insertions). The left flanking

gene segments were digested with MfeI and SpeI and ligated between the MfeI and NheI (which

has compatible ends with an SpeI digestion) on the plasmid. The right flanking gene segments

were digested and ligated between the BssHII and PvuII sites on the plasmid. The final shuttle

plasmids had the RFP/Renilla luciferase fusion and xgprt genes and the promoters mentioned

above flanked with wildtype gene segments from the candidate genes to allow for homologous

recombination. Monolayers of CV-1 cells at 80-90% confluence in a 6-well plate were infected

with 1.25x104 F13L+ (Western Reserve strain vaccinia virus with a lacZ insertion) in 500µl of

low-serum media (2.5% FBS) at 37°C for 2 hours with intermittent shaking every 15 minutes.

The supernatant was removed and a liposomal transfection (Lipofectamine 2000; Invitrogen,

GIBCO) was conducted with OptiMEM media (Invitrogen, GIBCO) containing 2.5 µg shuttle

plasmid DNA and 10 µl liposomes/well at 37°C for 4 hours. The transfection media was

removed and replaced with drugged media (10% FBS) (10 mg/ml xanthine, 149.25 mg/ml

hypoxanthine, 2.5 mg/ml mycophenolic acid; Sigma Aldrich) for selection. After 3 days of

incubation at 37°C, cells were collected in drugged low-serum media (2.5% FBS), subjected to

3 freeze-thaw cycles, sonicated, and serially diluted (1/4, 1/5, and 1/10). Each dilution was re-

infected in duplicate in 500 µl drugged low serum media (2.5% FBS) at 37°C into a monolayer

of confluent CV-1 cells that were incubated with drugged media (10% FBS) in a 6-well plate for

at least 24 hours. After 2 hours, the supernatant was replaced with 2ml agarose/drugged media

51

(10% FBS) overlay and incubated at 37°C. Three days later, the monolayers were observed for

RFP expression and viral plaque formation. Six RFP-positive plaques were isolated and

resuspended in drugged low-serum media (2.5% FBS) for re-infection into another monolayer

of drugged CV-1 cells. After 5-6 rounds of selection, all plaques were positive for RFP for all

candidate viruses.

Table 2.1. Primers for producing inserts for the shuttle plasmid

Virus Left Flanking Insert Right Flanking Insert

N1L Fwd gatccaattg cctaactctt tcgaatactt gatcgcgcgcgtacatacatcgccgtcatc

Rev gatcgctagc ggaagagtca ttcaccatac gatccagctgttatggaggatatgtgaacgc

K1L Fwd gatccaattgtgacgtacatgagtctgagt gatcgcgcgctttgcatgttaccactatca

Rev gatcgctagccgtggatatgatgattctct gatccagctgcagacatggatctgtcacga

K3L Fwd gatccaattgtaccggatctacgttctact gatcgcgcgcataatccttctcgtatac

Rev gatcgctagcggatatatagatgtcaatta gatccagctgtgctgatcctcccattccgt

A46R Fwd gatccaattgcacgataatatcagaggagt gatcgcgcgctgacttacttgtataataag

Rev gatcgctagccttcattacgtatgactaat gatccagctgcagaacatgtagacgaatca

A52R Fwd gatccaattgcgggagacgaggatatagct gatccccgggacgcgtgacaatgatgcggaagaaca

Rev gatccccgggaggcctatagacctctgtacataaaa gatcgacttgagcgtcatctggtagatagaccatcg

Abbreviations: Fwd, forward; Rev, reverse.

2.4. Viral DNA Extraction and PCR

Confluent CV-1 monolayers were infected with half of the suspension of each isolated plaque

from the 5th

or 6th

round of selection (described in Section 2.3) or a small amount from the CV-1

propagation during virus production until complete cytopathic effect was seen. Cells were

washed and collected in 1 ml homemade PCR buffer (50 mM KCl (Sigma Aldrich), 10 mM Tris

52

HCl, pH 8 (Fisher Scientific, Fair Lawn, New Jersey, USA), 2.5 MgCl2, 0.1 mg/ml gelatin,

0.45% Tween 80, and 0.45% NP40 (BioShop, Burlington, Ontario, Canada)). Viral DNA was

released from cells by Proteinase K treatment (ThermoScientific, Lithuana) at 55°C for an hour,

then at 95°C for 10 minutes to deactivate the enzyme prior to PCR. A standard PCR with the

crude viral DNA extract was conducted with the primers originally used to produce inserts for

the shuttle plasmid. Specifically, the forward primer from the left flanking insert and the reverse

primer from the right flanking insert were used (Table 1). PCR validation was conducted after

the 5th

-6th

cycle of selection, after propagation in CV-1 cells during virus stock production and

at the end of the virus stock production (See Section 2.5).

2.5. Virus Stock Production

Half of the suspension of the RFP-positive plaque from the 5th

-6th

cycle of virus selection

(described in Section 2.3) was reinfected into a monolayer of CV-1 cells grown in a 6-well

plate. When complete cytopathic effect was seen, the cells were harvested with a CellScraper

(Sarstedt, Sarstedt AG & Co, Germany) and re-infected into confluent CV-1 monolayers in two

175 cm2 flasks for 2 days and collected. After PCR re-validation with a small amount of cell

suspension (see above), the candidate virus was propagated by reinfecting into thirty 144 cm2

plates of confluent 24JK cells. After 3 days, infected 24JK cells were harvested and centrifuged

at 1500 rpm (342 g) for 10 minutes (SLA-1500 rotor, Sorvall; ThermoScientific). The cell pellet

was resuspended in 20 ml Tris-Cl (pH 9.0), subjected to 3 freeze/thaw cycles and mechanically

homogenized with a sterile Dounce Grinder (Sigma-Aldrich). Ultracentrifugation of the cell

lysate was performed at 25,000 rpm (113,000 g) for 80 minutes (XL-70 Ultracentrifuge, SW 28

rotor; Beckman Coulter, Brea, California, USA) at 4°C over a 36% sucrose cushion. Finally, the

virus pellet was resuspended in Tris-Cl (pH 9.0), aliquoted, and stored at -80 °C.

53

2.6. Virus Plaque Assay

CV-1 cells were seeded in 6-well plates with 3x105 cells/well and incubated at 37°C for 2 days.

Infected samples were subjected 3 freeze/thaw cycles and sonicated to release the virus from the

cells. Viral lysates were serially diluted in low serum media (2.5% FBS) and used to infect the

CV-1 monolayers with 400µl per well at 37°C with intermittent shaking every 10 minutes. Two

hours later, 1.5 ml of media (10% FBS) was added and incubated at 37°C. Two days later, the

cell monolayers were stained with crystal violet and plaques were counted.

2.7. Viral Replication

Tumor cells (DLD-1, A2780) were seeded in 6-well plates until confluent, at which point the

number of cells were determined. MC38 cells were seeded in 6-well plates with 5x105 cells/well

and incubated overnight to achieve 80-90% confluency. Cells were infected at an MOI of 0.1 of

either vvDD or one of the candidate viruses in 0.5ml low serum media (2.5% FBS) at 37°C for 2

hours with intermittent shaking every 10-15 minutes. Cells were supplemented with media (10%

FBS) and incubated at 37°C. Cells and supernatants were harvested in triplicates at each time

point (2, 24, 48, and 72 hours post-infection (hpi) using a Cell Scraper (Sarstedt, Sarstedt AG &

Co, Germany) and stored at -80°C until use. Virus was quantified by viral plaque assays on CV-

1 cells where CV-1 cells were seeded at 3x105

cells/ well in 6 well plates and incubated for 2

days at 37°C until confluency. The virus treated samples were subjected to 3 freeze/thaw cycles

and sonicated on ice before serial dilution in DMEM-2.5% FBS. Subsequently, 0.4ml of the

dilutions were added into a confluent well of CV-1 cells and incubated at 37°C for 2 hours with

intermittent shaking and then supplemented with DMEM-10% FBS and incubated at 37°C. Two

days later, the monolayers were stained with crystal violet and plaques were counted.

54

2.8. Viral Cytotoxicity

MC38 cells were seeded in a 96-well plate with 5x103 cells/well and incubated overnight at

37°C before infection. A2780 and DLD-1 cells were seeded in 96-well plates with 1x104

cells/well and incubated overnight at 37°C before infection. Cells were infected at an MOI of

0.1, 1, or 5 in triplicate with either vvDD or one of the candidate viruses in 25µl of media (2.5%

FBS) for 2 hours at 37°C, then supplemented with 75µl media (10% FBS). Cytotoxicity was

evaluated at 2, 24, 48, and 72 hpi with 3-(4,5-dimethyl-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-

sulfophenyl)-2H-tetrazolium (MTS) cell viability assay (CellTiter96® Aqueous One Solution,

Promega, Madison, Wisconsin, USA) according to the manufacturer‘s protocol. The background

absorbance from medium blanks was subtracted from absorbance values of wells with infected

and mock-infected cells. Relative cell viability was then calculated by dividing the absorbance

of infected wells with the absorbance of the mock-infected wells.

2.9. Measuring Viral Spread by Red fluorescent protein (RFP) Expression

Experiments were conducted as described in the viral replication protocol. Before harvesting the

cell monolayers, fluorescence microscopy was conducted to acquire brightfield and RFP images

(acquired under the Cy3 lens) at 10x magnification using the Zeiss AxioObserver microscope

(Carl Zeiss, Oberkochen, Germany) equipped with a Series 120Q Fluorescence Illumination unit

(EXFO, Quebec City, Quebec, Canada). Images were taken with a Zyla 5.5 sCMOS camera

(Andor Technologies, Belfast, United Kingdom). Percent area infected was measured with the

Fiji ImageJ software with a uniform threshold based on RFP presence within the image.

2.10. Tumor Spheroid Generation, Infection, and Analysis

Spheroids were cultured using tumor cell lines MC38 and DLD-1. Cells were dissociated with

Accutase and seeded at 1,000 cells/well in 96-well round-bottomed plates coated with 1%

polyHEMA (Sigma Aldrich). Plates were subsequently spun at 1,500 rpm for 10 minutes and

55

incubated at 37°C for 72 hours prior to infection. vvDD, one of the candidate VVs (MOI=2) or

media alone DMEM-2.5% FBS was used to infect the spheroids in triplicate for 2 hours at 37°C

and supplemented with media DMEM-10% FBS. Infection was confirmed by RFP expression

visualized with a LSM 700 Confocal Microscope (Carl Zeiss). Tumor spheroid size was

measured with the Fiji ImageJ software. Briefly, brightfield images of the spheroids were

converted to 8-bit greyscale images where spheroids were converted into a binary mask and the

major and minor axis of a fit elliptical were measured. Tumor volume was calculated based on

the following equation assuming spheroid shape: V= 4/3*π ([major axis]/2)([minor axis]/2)2.

Clonogenic assays were also conducted 96 hpi. Approximately 30-50 spheroids were collected,

centrifuged, and disaggregated with trypsin. Live cells were plated in 6-well plates at 25-100

cells/well in duplicate and incubated for 10 days before crystal violet staining. Surviving

fraction was calculated by the number of colonies (>50 cells) divided by the number of cells

originally seeded.

2.11. Mice

Female C57BL/6 mice and NU/NU athymic nude mice (Jackson Laboratory, Bar Harbor,

Maine, USA) were used as syngeneic and xenograft models, respectively. All mice were housed

under standard conditions and given food and water ad lib. Experimental protocols were

approved by the Animal Care Centre, University Health Network, Toronto. Mice were

euthanized by CO2 asphyxiation when signs of morbidity were present including: viral toxicity,

a subcutaneous tumor at the injection site >1.5 cm, difficulty breathing, moribund, cachectic or

inability to obtain food or water.

2.12. In vivo Toxicity Studies

Female C57BL/6 mice or NU/NU athmymic nude mice (n=3) were injected with the indicated

doses of virus in HBSS+0.1%BSA or HBSS+0.1% BSA alone and observed for survival. Body

weight was measured every 2-3 days.

56

2.13. Syngeneic Model

Female C57BL/6 mice were injected intraperitoneally (IP) with 105 MC38 cells in serum-free

media. Twelve days post-tumor injection, mice were injected with the indicated doses of virus in

1 ml Hanks- Buffered Saline Solution (HBSS; Invitrogen, GIBCO) + 0.1% bovine serum

albumin (BSA) or HBSS+0.1% BSA alone. Mice were followed for survival (n=8) or sacrificed

6 days post-infection for biodistribution studies (n=3).

2.14. Xenograft Model

Female NU/NU athymic nude mice were injected IP with either 5x106 DLD-1 cells or 10

7

A2780 cells in serum-free media. Twelve days post-tumor injection, mice were injected with the

indicated doses of virus in HBSS+0.1% BSA or HBSS+0.1% BSA alone. Mice were followed

for survival (n=8) or sacrificed 6 days post-infection for viral biodistribution studies (n=3).

2.15. Biodistribution

Mice from the syngeneic or xenograft model had tumors and virus injected as described above

and then euthanized 6 days post-infection and the tumors, ovaries, kidneys, bowel, liver, spleen,

lung, heart, brain and bone marrow were harvested and stored at -80C° in HBSS. Tissues were

homogenized with the TissueLyzer II (Qiagen, Hilden, Germany), subject to 3 freeze-thaw

cycles, and sonicated prior to the viral plaque assay with CV-1 cells. Titers were normalized to

total protein per sample (mg) measured with the PierceTM

bicichoninic acid (BCA) protein assay

kit (Thermo Fisher Scientific, Waltham, Maryland, USA). Relative titers in normal tissues were

calculated by dividing the normalized tissue titer by the average normalized titer in tumors

infected with the corresponding virus.

57

2.16. Statistical Analysis

Data were analysed by a two-tailed independent samples t-test between candidate VV and vvDD

where applicable. Survival curves were evaluated with the log-rank test. Graphs were generated

with the Prism 5 Software (GraphPad Software Inc., La Jolla, California, USA). Data are

presented as Mean ± SEM.

58

Chapter 3

3 3

3 Results

3.1 Aim 1: Generate VV-deletion mutants via homologous recombination

The first aim of our project was to generate Western Reserve (WR) vaccinia viruses (VVs) with

a single gene deletion of one of our candidate immunomodulatory VV genes (N1L, K1L, K3L,

A46R, and A52R. The shuttle plasmids for vaccinia virus (VV) gene deletions were derived

from a pre-existing plasmid pVX-R2R-LUC. This vector was the same shuttle plasmid used to

generate the vvDD-R2R-Luc as first described by Lun et al. Briefly, relevant features of the

plasmid include 1) a VV synthetic early-late promoter upstream of a gene with RFP conjoined

to Renilla luciferase via the foot-and-mouth disease virus 2A motif to facilitate bicistronic

expression and 2) a xanthine-guanine phosphoribosyltransferase (xgprt) gene for viral selection

under the VV p7.5 promoter, and 3) an ampicillin gene to enable bacterial selection (Lun et al.,

2009). Sequences originally flanking the gene of interest (e.g. N1L) would be cloned into the

plasmid to flank the first 2 elements to create the shuttle plasmid (Figure 3.1 A) that will be used

to generate the desired VV deletion mutant with the DNA construct exemplified in Figure 3.1 B.

59

Figure 3.1. Schematic diagram of shuttle plasmid and final construct of candidate VV deletion mutant using

∆N1L VV as an example. A) Diagram of the shuttle plasmid created to facilitate homologous recombination with

VV to generate deletion mutant interrupted with RFP/Rluc and xgprt genes as illustrated in B. RFP and Rluc are

conjoined by a foot-and-mouth disease virus 2A motif. Abbreviations: RFP: red fluorescent protein, Rluc: Renilla

luciferase, Pse/l: synthetic VV early/late promoter, p7.5: p7.5 VV early/late promoter, xgprt: xanthine-guanine

phosphoribosyltransferase, AmpR: ampicillin resistance.

A)

B)

60

Before manipulating the plasmid, the plasmid preparation was confirmed to be pVX-R2R-Luc

by restriction enzyme digestion with SpeI and MfeI, yielding the expected band sizes of 6kb and

600bp. A second double digestion with BssHII and DrdI yielded the expected sizes of two 2.8

kb and one 1kb bands (Figure 3.2).

Figure 3.2. Confirmation of pvX-R2R-LUC plasmid. Existing DNA plasmid preparations were confirmed to be

pVX-R2R-LUC by 1) a double digest with SpeI and MfeI, which yielded the expected band sizes of 6kb and 800bp

and 2) a double digest with BssHII and DrdI, which yielded the expected band size of two 3.2 kb and one 1kb

bands.

Our strategy was to delete VV genes via homologous recombination by flanking the

aforementioned marker genes in pVX-R2R-LUC with 300-500 bp sequences from either side of

the candidate gene as determined by the Western Reserve (WR) VV genome sequence found in

GenBank (Accession number: NC_006998.1). Shuttle plasmids were made to facilitate the

deletion of the N1L, K1L, K3L, and A46R VV gene. The ∆A52R VV had been made by a

previous lab member, Nan Tang. All subsequent figures pertaining to the creation of shuttle

6 kb-

pVX-R2R-Luc

uncut

500bp-

1 kb-

Cu

t w

ith

Sp

eI +

Mfe

I

Cu

t w

ith

Bss

HII

+ D

rdI

3 kb-

61

plasmids (Figure 3.3 – 3.5) will use the production of ∆N1L VV shuttle plasmid, pVX-N1L-

R2R-Luc, as a representation of the cloning process.

Primers to amplify DNA sequences on the left and right side of the candidate genes were

derived from the VV genome sequence (Table 2.1) to facilitate PCR cloning. The PCR reaction

was performed using the VJS6 (WR VV with a TK gene deletion) viral DNA as template

(McCart et al., 2001). The sizes of the PCR products for the left and right flanking sequences

were confirmed by agarose gel electrophoresis (Figure 3.3). The DNA fragments were named

based on the corresponding candidate gene followed by L or R depending on whether the

sequence flanked the left or right side of the candidate gene, respectively. For example, the PCR

product from amplifying the DNA sequence on the left side of the N1L gene was named ―N1L-

L‖.

Figure 3.3. Left and right flanking DNA fragments of VV N1L gene as generated by PCR. Primers to amplify

the DNA sequences flanking the candidate VV gene, N1L, were designed from the WR VV genome sequence. PCR

products amplified from the VJS6 viral DNA were confirmed by agarose gel. A) Left-flanking DNA, N1L-L

(expected size: 549 bp) and B) Right-flanking DNA (expected size: 519 bp), N1L-R. Neg = negative control (H2O).

The corresponding left DNA fragments were inserted into pVX-R2R-Luc. First, the plasmid was

digested with MfeI and SpeI and the PCR fragments were digested with MfeI and NheI (which

makes compatible ends to SpeI overhangs). After ligation, bacterial transformation and

N1L-L

500 bp-

Neg N1L-R A) B)

1 k

b l

add

er

1 k

b l

add

er

500 bp-

Neg

62

ampicillin selection, at least 3 colonies were tested for the presence of the correct insert via

colony PCR (Figure 3.4 A). The PCR primers used for the colony PCR were the same primers

used to create the insert. Positive clones were grown up for subsequent plasmid DNA isolation

and further confirmed to contain the desired insert by restriction enzyme digestions (Figure 3.4

B). The resulting plasmids from bacterial transformation were named according to the format:

―pVX--<gene name>-L-R2R-Luc‖. For example, the pVX-R2R-LUC plasmid with an N1L-L

insert was called ―pVX-N1L-L-R2R-Luc‖.

Figure 3.4. Confirmation of pVX-R2R-Luc with left-flanking DNA insertion. A) Half a colony of ampicillin-

selected transformants were directly confirmed to contain the left-flanking DNA insert (N1L-L) by colony PCR.

(expected size: 549 bp) Positive control: VJS6 DNA and negative control (Neg): H2O. At least 3 clones were tested

for the presence of the desired partial shuttle plasmid B) Plasmid DNA preparations were confirmed to contain the

desired left side flanking DNA fragment (N1L-L) by a restriction enzyme digest based on a unique or rare cut sites

within the insert and in the pVX-R2R-Luc. Specifically, potential pVX-N1L-L-R2R-Luc plasmid DNA was

digested with HindIII (expected sizes: ~3kb and ~4.5kb)

1 k

b l

add

er

VJS

6

Neg

A) B)

500 bp-

Clone #

1 2 3 4 5

1 k

b l

add

er

4 kb-

pVX-N1L-L-R2R-Luc

Clone #

uncut 1 2 3

pVX-N1L-L-R2R-Luc

63

The plasmid preparation of one clone for each shuttle plasmid was used for subsequent cloning

steps. The right side insert and the vectors with the corresponding left inserts were then double

digested with PvuII and BssHII, ligated together, transformed into bacteria, and the final

transformants were also confirmed by colony PCR first (Figure 3.5 A) and then by restriction

enzyme digestion (Figure 3.5 B). All plasmid preparations were confirmed to be the desired

clones by restriction enzyme digestion of unique or rare sites found in the insert and plasmid.

The final shuttle plasmids to delete the N1L, K1L, K3L, and A46R gene were named pVX-

N1L-R2R-Luc, pVX-K1L-R2R-Luc, pVX-K3L-R2R-Luc, and pVX-A46R-R2R-Luc

respectively.

Figure 3.5. Confirmation of the final shuttle plasmid. A) Half a colony of each transformant was directly used

for colony PCR confirmation for the presence of the right-flanking DNA fragment, N1L-R (expected size: 519 bp).

Negative control (Neg): H2O. B) Plasmid DNA preparations from positive clones in A) were confirmed to contain

the desired right side flanking DNA fragment by a restriction enzyme digest based on a unique or rare cut sites

within the insert and in the pVX-R2R-Luc. pVX-N1L-R2R-Luc DNA from 2 clones digested with HindIII

(expected sizes: ~800bp and ~5.3kb)

500 bp- 500 bp-

pVX-N1L-R2R-Luc

Clone #

1 2 3 4 Neg

500 bp-

1 k

b l

add

er

A) B)

750 bp- 1 kb-

5 kb-

pVX-N1L-R2R-Luc

Clone #

uncut 1 2

64

After confirmation by PCR and restriction enzyme digestion, the shuttle plasmids were

amplified and transfected into F13L+ (wildtype WR VV)-infected CV-1 cells. The cells were

harvested, serially diluted, and re-infected into a new monolayer of CV-1 cells growing in media

supplemented with mycophenolic acid, hypoxanthine, and xanthine. Mycophenolic acid inhibits

the salvage pathway for purine synthesis, specifically, the formation of guanine. If the F13L+

viruses undergo homologous recombination with the shuttle plasmid, in addition to the deletion

of the candidate gene, the recombinant virus will express the RFP/Renilla luciferase marker

gene and the Escherichia coli xgprt gene. The xgprt gene will allow the recombinant virus to

circumvent the inhibition of mycophenolic acid and produce guanine to facilitate its replication,

while the wildtype virus will be able to infect cells, but not replicate (Mulligan and Berg, 1981).

RFP expression was observed in single cells 72h after the transfection/infection. After the initial

re-infection of transfected cell suspension, RFP-expressing plaques were picked 72 hours post-

infection (hpi) (Round 0) and re-infected into new monolayers of mycophenolic acid-treated

CV-1 cells. Subsequent RFP-expressing plaques were picked for at least 5 rounds to dilute out

the parental virus until the whole population was the desired recombinant virus as confirmed by

PCR. Evidence of RFP expression after transfection and a sample RFP-expressing plaque at

round 0 and 5 of selection are presented in Figure 3.6.

65

Figure 3.6. Sample images of CV-1 cells after transfection/infection and subsequent rounds of re-infection

with recombinant VV. CV-1 cells were transfected with the shuttle plasmid, infected with wildtype WR VV

(F13L+) then incubated in media containing mycophenolic acid, hypoxanthine, and xanthine (drugged DMEM).

The transfected/infected monolayer was harvested 72hpi and re-infected into another CV-1 monolayer grown in

drugged DMEM (Round 0). Subsequent RFP plaques were harvested and re-infected into new monolayers for at

least 5 more rounds. Brightfield and fluorescent images (Cy3 filter) were taken with a 10x objective lens at 72hpi

after each round

66

Confirmation that the selected RFP-expressing plaques were free from parental virus was

determined by a PCR reaction, visualized via agarose gel electrophoresis and presented in

Figure 3.7. The same primers used to produce the flanking PCR products for insertion into

pVX-R2R-Luc shuttle plasmid were also used for these confirmation PCR reactions.

Specifically, the forward primer that amplified the left insert and the reverse primer of the right

insert were used. For example, to confirm that the ∆N1L VV was parental free, the PCR

reaction was undertaken with the N1L-L forward and N1L-R reverse primers. In this way, if the

virus is recombinant with the desired interruption of the open reading frame (ORF) of the

candidate VV gene, the expected band as a result of the inserted marker genes would be

approximately 4kb. If parental virus F13L+ was still present in the recombinant virus sample,

the PCR product will be the combined length of both PCR inserts used for cloning and the

wildtype candidate gene sequence left in between (approximately 1kb). Although it is possible

that the PCR reaction can yield the recombinant DNA product, a length of 4kb is very difficult

to achieve in a PCR reaction with standard Taq polymerase, especially with a crude preparation

of viral DNA template. Clones were considered fit for further use based primarily on the

absence of the ~1kb PCR product from the candidate gene in a wildtype WR VV. As expected,

some PCR reactions yielded neither the 4kb nor the 1kb band, such as the ∆K1L VV clone # 4

(Figure 3.7 B). The plaque from this clone was still amplified into viral stocks because the viral

RFP expression and growth in the presence of mycophenolic acid indicated the presence of the

desired virus. For the other viruses, the following clones were used to amplify the desired

recombinant viruses: clone #4 of ∆N1L VV (Figure 3.7 A), clone #6 of ∆K3L VV (Figure 3.

7C), and clone #2 of ∆A46R VV (Figure 3.7 D).

67

-4 kb

-1 kb

∆K1L VV

Clone #

1 2 3 4 5 6 F1

3L

+

pV

X-K

1L

-R2

R-L

UC

Neg

1 k

b l

add

er

A) B)

-4 kb

-1 kb

∆N1L VV

Clone #

1 2 3 4 5 6 F1

3L

+

pV

X-N

1L

-R2

R-L

UC

Neg

1 k

b l

add

er

C) D)

F1

3L

+

pV

X-K

3L

-R2

R-L

UC

-4 kb

-1 kb

∆K3L VV

Clone #

1 2 3 4 5 6 Neg

1 k

b l

add

er

pV

X-A

46

R-R

2R

-LU

C

-4 kb

-1 kb

∆A46R VV

Clone #

1 2 3 4 5 6 Neg

F1

3L

+

1 k

b l

add

er

68

Figure 3.7. PCR confirmation of the absence of parental virus from recombinant VV plaques. CV-1 cells

were infected with one of 6 plaques after round 5 of mycophenolic acid selection. When complete cytopathic effect

(CPE) was observed, cells were harvested and digested with Proteinase K. The samples were tested by PCR for the

absence of parental virus (F13L+). The forward primer from the left flanking DNA fragment and the reverse primer

of the right flanking DNA fragment were used as primers for the PCR reactions. Positive control for parental virus

was viral DNA from F13L+ infected CV-1 cells, and the corresponding shuttle plasmid DNA was used as template

for the positive control for the recombinant band, negative (Neg) control from mock-infected cells. Only viruses for

which a shuttle plasmid was made during this project are tested here: A) ∆N1L VV, B) ∆K1L VV, C) ∆K3L VV,

D) ∆A46R VV.

During and after the process of amplifying the candidate VVs into viral stocks, the same PCR

reaction described in Figure 3.8 was conducted to further confirm that absence of parental WR

VV virus before further use for experimental assays. If there were any parental virus left in the

selected plaques tested above that did not produce a 1kb band, due to some reason such as too

low amounts of parental virus DNA template compounded by inhibitory factors within the crude

DNA preparation, the amplification process will have also amplified the parental virus and

produced a 1kb band in the PCR reaction by the end of the viral stock production. The stock of

∆A52R virus was also tested here. It was confirmed that all stocks of candidate VVs were free

from parental WR VV (Figure 3.8). There is a ~1.5kb DNA fragment produced from the ∆A52R

VV stock, however, since the PCR reaction with the parental virus (F13L+) yielded a product of

~750 bp, the ∆A52R stock is still considered free from parental virus.

70

Figure 3.8. PCR confirmation of candidate viral stocks. CV-1 cells were infected with virus stocks amplified

from plaques of candidate VVs. Infected cells were harvested and PCR with the forward primer of the left flanking

insert and the reverse primer of the right flanking insert was conducted to amplify the corresponding wildtype

candidate VV gene (~1kb), or a PCR product reflective of the marker genes interrupting the candidate genes

(~4kb). Negative control (Neg) was mock-infected cells, F13L+ (wildtype WR VV)- infected cells were positive

control for the wildtype product, and the corresponding shuttle plasmids, if available, were the positive controls for

the PCR product expected from the candidate deletion viruses: A) ∆N1L VV, B) ∆K1L VV, C) ∆K3L VV, D)

∆A46R VV, and E) ∆A52R VV.

After confirmation that the virus stocks were free from parental virus, the candidate VVs were

tested in vitro as described below in Aim 2.

71

3.2 Aim 2: Compare candidate VV deletion mutants to vvDD in terms of in vitro viral replication, cytotoxicity, and spread in colon and ovarian cancer cell lines.

The first step in evaluating the potential of our candidate deletion mutants as oncolytic agents

was testing the capability of these novel constructs for viral replication, tumor-killing, and viral

spread, compared to a clinical oncolytic virus such as vvDD. Throughout the study, the viruses

were studied in three cell lines: MC38 murine colon carcinoma, DLD-1 human colon

carcinoma, and A2780 ovarian colon carcinoma. These cell lines were chosen to correspond

with the cell lines used in our mouse models of peritoneal carcinomatosis used in Aim 3.

Candidate VV deletion mutants exhibit replication similar to or more efficient than vvDD

in monolayers of colon and ovarian cancer cell lines.

The replication of candidate VV deletion mutants and vvDD in cancer cell lines was assessed by

infecting monolayers of MC38, DLD-1 or A2780 at a low multiplicity of infection (MOI) of 0.1

(Figure 3.9). Infected monolayers were harvested and stored for subsequent virus quantification

by plaque assay at baseline (or 2h after the pre-infection process), 24 hours, 48 hours, and 72

hours post-infection (hpi) (Figure 3.9).

The replication of vvDD and VV deletion mutants in all cell lines resulted in a 2-3 log-fold

increase in total viral particles by 72hpi. In general, all candidate VVs exhibited similar or better

viral replication compared to vvDD in both MC38 and DLD-1 cells at peak viral titers. The

same can be concluded for most candidate VVs within A2780 cells, with the exception of

∆A46R VV. However, the replication efficiency of all tested VVs in A2780 cells was generally

higher compared to the other two colon carcinoma cells (range of mean viral fold change

compared to baseline at 72hpi: 712.2 – 2177.5 [MC38], 109.4 – 1520.4 [ DLD-1], and 792.0 –

72

4405.2 [A2780]). The ∆K1L VV demonstrated the most efficient replication ability across all

cell lines, with the average fold change in replication being 2.8, 13.9, and 2.3 times higher than

the average fold change of vvDD in MC38, DLD-1, and A2780 cells, respectively (p<0.05).

73

DL

D-1

DLD-1

A27

80

A) B)

MC

38

C) D)

E) F)

74

Figure 3.9. Replication of candidate VVs and vvDD in colon and ovarian cancer cell lines. Monolayers of

MC38 (A, B), DLD-1 (C, D), and A2780 (E, F) cells were infected with vvDD or candidate VVs at an MOI of 0.1.

Viral quantitation was determined by plaque assays at 2, 24, 48, and 72hpi. Data are presented as total plaque –

forming units (pfu) over time (A, C, E) or as fold change relative to baseline pfu at 2hpi (B, D, F). Values are

means of three replicates ± SEM corresponding to one out of three independent experiments (n=3). *p<0.05

compared to vvDD.

75

Candidate deletion mutant VV spread is similar to or better than vvDD in colon and

ovarian cancer cell lines.

The viral spread of the candidate VV deletion mutants was compared to vvDD in monolayers of

colon and ovarian cell lines, infected at an MOI of 0.1, as measured by fluorescence

microscopy. Differential interference contrast (DIC) images and fluorescent images with the

Cy3 lens were taken at 2 (baseline), 24, 48, and 72 hpi. Images at peak viral spread based on

RFP expression are presented: 72hpi of MC38 and DLD-1 cells and 48 hpi of A2780 cells

(Figure 3.10) Viral spread quantification was based on the area of RFP expression relative to the

total area of the image. (Figure 3.11).

The viral spread of all candidate VVs was similar or better than vvDD in all cell lines tested, as

confirmed by both visual assessment and quantitative analysis. Though statistical significance

was only achieved in MC38 cells for these viruses, visual assessment of viral spread confirms

the quantified trend of superior spread of ∆K1L VV, ∆N1L VV, and ∆A52R VV in all cell lines.

The best performer, ∆A52R VV, demonstrated consistently significant superior viral spread in

all cell lines, infecting approximately half of all cell lines at its peak (% infected area: 55.6% ±

6.1% [MC38], 39.7% ± 8.5% [DLD-1], 65.5% ±4.1 % [A2780]). As such, mean ∆A52R VV

spread was 11.8% - 33.7% better relative to vvDD at peak time points in all tested cell lines.

76

Figure 3.10. Viral spread of VV deletion mutants and vvDD in colon and ovarian cancer cell lines. Cell lines MC38, DLD-1 and A2780 were infected with either

the indicated VV deletion mutants or vvDD at an MOI of 0.1 and visualized under fluorescent microscopy with a Cy3 filter at 10x magnification.

vvDD ∆N1L ∆K1L ∆K3L ∆A46R ∆A52R Mock Mock (Brightfield)

MC

38 (

72 h

pi)

DL

D-1

(7

2 h

pi)

A2

78

0 (

48 h

pi)

77

Figure 3.11. Quantification of viral spread in colon and ovarian cancer cell lines. Monolayers of MC38, DLD-1, and A2780 cells were infected with candidate VV

deletion mutants and vvDD at an MOI of 0.1. Fluorescent images were taken with a Cy3 lens at 10x magnification and infected areas were measured by determining the

area with RFP marker expression over total image area, as calculated with ImageJ software, set at a uniform threshold at each time point. Data are a combination of two

independent experiments, each with three replicates, and values are mean ± SEM (n=6). *p<0.05 compared to vvDD (blue circle).

MC38 DLD-1 A2780

78

Candidate VV deletion mutants exhibit equivalent or enhanced cytotoxicity in colon and

ovarian cancer cell lines compared with vvDD.

The cytotoxicity of our candidate VVs were compared to vvDD at multiple infecting doses

(MOI 0.1, 1, and 5) and multiple time points (2, 24, 48, and 72 hpi) in monolayers of colon and

ovarian cancer cell lines. Cell viability was measured via the colorimetric MTS ([3-(4,5-

dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium inner

salt) assay. The results are shown in Figure 3.12.

Similar to the results of the viral replication experiments, the cytotoxicity of each of our

candidate VVs is either equal to or higher in the colon cancer cell lines, MC38 and DLD-1,

compared to vvDD. The difference in cytotoxicity of all candidate VVs compared to vvDD was

the most dramatic in MC38 cells, where candidate VV treatment at 72hpi at an MOI of 1

dramatically reduced the mean cell viability relative to mock controls by at least 1.92 times

compared to vvDD (range of % viability: 40.1% - 51.4% compared to 95.8% , p<0.05). All the

VVs were very effective at killing A2780 cells, however, cytotoxicity of all candidate VVs and

vvDD in A2780 cells was significant at a low MOI of 0.1 by 72 hpi (mean % viability: 24.6% -

63.0%). The cytotoxicity in all tumor cell lines of all candidate VVs was similar by 72hpi.

Among them, the ∆A46R VV was the most cytotoxic (mean % viability at MOI 1: 40.1%±0.3%

[MC38], 40.3%±2.0% [DLD-1], and 4.8%±1.1% [A2780]).

79

MC38 DLD-1 A2780

MOI = 0.1 A)

80

MC38 DLD-1 A2780

MOI = 1 B)

81

Figure 3.12. Cytotoxicity of vvDD and candidate VVs in colon and ovarian cancer cell lines. Monolayers of MC38, DLD-1 and A2780 were infected at an MOI of

A) 0.1, B) 1, C) and 5 and cell viability was measured at 2, 24, 48, and 72 hpi. Values are means of three replicates ± SEM corresponding to one of two independent

experiments (n=3). *p<0.05 compared to vvDD (blue circle).

C)

MC38 DLD-1 A2780

MOI = 5

82

Candidate VVs exhibit equal or better viral spread in tumor spheroids compared to vvDD.

Tumor spheroids mimic the 3D structure and microenvironment of a tumor and allow for more

relevant and realistic in vitro investigation (Casagrande et al., 2014) of the candidate VVs. In

this study, MC38 and DLD-1 spheroids were generated, infected at an MOI of 2, and viral

spread was observed through the Cy3 lens of a confocal microscope to track virally-induced

RFP expression throughout the spheroid over time. The spheroid diameter was approximately

250-300 µm at the time of infection. The images presented are representative fluorescent images

approximately halfway into the spheroid (~130 µm) (Figure 3.13 and 3.14). A snapshot of the

spheroid with the brightfield lens was also taken to calculate spheroid volume using an equation

that assumed a spherical/elliptical shape. Tumor volume was only calculated for MC38

spheroids, since DLD-1 spheroids tended to become very irregular as a result of infection.

A2780 cells were not used to make spheroids in this study, because tumor spheroid generation

with PolyHEMA plates did not yield the desired uniform, compact, cell aggregates which could

survive the aspiration step during infection. Instead, A2780 cells formed loose cell aggregates,

consistent with what has been reported in the literature (Casagrande et al., 2014).

Viral spread into tumor spheroids was evaluated qualitatively using visual examination of viral

RFP marker expression. The viruses varied in their ability to penetrate into the centre of the 3D

structures. Small amounts of RFP expression associated with vvDD infection could be seen at

130 µm depth into MC38 spheroids at 72hpi. In contrast, the ∆N1L, ∆K1L, ∆A46R, and ∆A52R

VVs infected most of the rim and exhibited some penetration into the MC38 spheroids. The

DLD-1 spheroids were more resistant to infection by vvDD and most candidate VVs, resulting

in small, dispersed foci of RFP by 72hpi. However, ∆A52R VV was able to infect a larger

portion of the DLD-1 spheroids. Out of all viruses tested, ∆A52R VV spread the furthest into

both MC38 and DLD-1 spheroids.

83

Figure 3.13. Viral spread of candidate VVs and vvDD in MC38 tumor spheroids. MC38 spheroids were infected at an MOI of 2 and visualized by confocal

microscopy with brightfield and Cy3 lens at 10x objective lens (n=4). Scale bar = 100 um A) Brightfield images of spheroids before infection B) Brightfield images of

MC38 spheroids 72 hpi, C) Virally-induced RFP expression of a cross-section of spheroids at 150 um (approximately halfway), visualized with a Cy3 filter.

vvDD ∆N1L ∆K1L ∆K3L ∆A46R ∆A52R Mock

A

B

C

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Figure 3.14. Viral spread of candidate VVs and vvDD in DLD-1 spheroids. DLD-1 spheroids were infected at an MOI of 2 and visualized by confocal microscopy

with brightfield and Cy3 filter at 10x objective lens 72 hpi (n=4). Scale bar = 100 um A) Brightfield images of spheroids before infection B) Brightfield images of DLD-

1 spheroids 72 hpi, C) Virally-induced RFP expression of a cross-section of spheroids at 150 um (approximately halfway) visualized with a Cy3 filter.

vvDD ∆N1L ∆K1L ∆K3L ∆A46

R

∆A52

R

Mock

A

B

C

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Candidate VVs and vvDD are cytotoxic in tumor spheroids.

The effect of VV infection on tumor spheroid volume, i.e. cytotoxicity, was evaluated in MC38

spheroids (Figure 3.14). Tumor spheroid volume was determined by measuring the longest

diameter (major axis) and the diameter of the spheroid at the axis perpendicular to the major

axis (minor axis) using brightfield images of each spheroid. These values were then used to

calculate spheroid volume, using an equation that assumed a spherical shape (V=4/3*pi*(minor

axis)2(major axis)). Since infected DLD-1 spheroids were often irregular, tumor volume was not

calculated for these spheroids. In general, vvDD- and candidate VV-infected MC38 spheroids

had significantly lower mean spheroid volume compared to mock-treated controls by 72hpi

(Figure 3.14 A). Additionally, candidate VVs were associated with similar or lower mean tumor

spheroid volume compared to vvDD (Figure 3.14 B). Moreover, the decrease in tumor spheroid

volume in infected spheroids started to plateau at 96 hpi. Hence, to confirm the cytopathic effect

of vvDD and candidate VVs in this model, a clonogenic assay was conducted with MC38 and

DLD-1 spheroids at 96hpi.

86

Figure 3.15. MC38 spheroid size after treatment with candidate VVs or vvDD. MC38 spheroids were infected

at an MOI of 2 and brightfield images were taken at 24 hour intervals post-infection with a 10x objective lens. The

grey box represents the expanded region from A) shown in B). Tumor volume was calculated based on the radii at

the major and minor axis of the spheroid measured with the images. V=4/3*pi*(minor axis)2(major axis). Values

are mean of four replicates ± SEM corresponding to one experiment (n=4).

A)

B)

87

The percent surviving fraction of virus-treated MC38 spheroids was low or undetectable (range

of mean surviving fraction 0-3.3%). MC38 spheroids treated with ∆A46R or ∆N1L VV did not

yield a detectable surviving fraction (Figure 3.16 A and B). Similarly, surviving fraction of

DLD-1 spheroids treated with all viruses was very low to undetectable (range of mean surviving

fraction: 0 – 1.3%). DLD-1 spheroids treated with ∆K1L, ∆N1L, and ∆A52R VV did not result

in a detectable surviving fraction (Figure 3.16 C and D). In contrast, many cells survived in

mock-treated spheroids (mean surviving fraction MC38: 60.2% ±12.0%, DLD-1: 87.7% ±

20.2%).

88

MC38 Spheroids

A)

B)

89

Figure 3.16. Clonogenic assay of tumor spheroids treated with candidate VVs or vvDD. MC38 (A, B) and

DLD-1 (C,D) spheroids infected at MOI 2 were dissociated at 96hpi and reseeded into 6-well plates at 25-100

cells/well, grown for 10 days, and stained with crystal violet. Surviving fraction was calculated based on the

number of colonies (>50 cells) relative to the number of cells originally seeded. The grey box represents the

expanded region from A) and C) shown in B) and D), respectively. Values are means of three replicates ± SEM

corresponding to one of two independent experiments (n=3).

C)

D)

DLD-1 Spheroids

90

In vitro assays suggest ∆K1L VV, ∆A46R VV, and ∆A52R VV are promising oncolytic

viruses.

The 3 best-performing candidate VVs in vitro were chosen for subsequent in vivo investigation.

Categorization of candidate VVs in Table 3.1 as more, equally, or less potent than vvDD were

based on statistical analysis via two-tailed t-test (p<0.05) in all assays, with the exception of

viral spread in tumor spheroids (last 2 columns) which was not quantified. Viruses were ranked

based on the quantitative mean where applicable or qualitative analysis (as in the case of viral

spread in tumor spheroids). One candidate VV for each category was the best performer across

all cell lines tested. Namely, ∆K1L VV exhibited the fastest VV replication, ∆A46R was the

most cytotoxic, and ∆A52R demonstrated the most viral spread in tumors. Hence, these 3

viruses were tested in in vivo models of cancer in Aim 3

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Table 3.1. Summary of the in vitro assays comparing candidate VVs to vvDD. Candidate VVs were assessed against vvDD for viral replication, spread and tumor

cytotoxicity in MC38, DLD-1, and A2780 cells and results are summarized, ranking the performance of each virus starting with the best performer first.

Replication

(Monolayer)

Cytotoxicity

(Monolayer)

Cytotoxicity

(Spheroids)

Spread

(Monolayer)

Spread

(Spheroids)

MC38 DLD-1 A2780 MC38 DLD-1 A2780 MC38 DLD-1 MC38 DLD-1 A2780 MC38 DLD-1

∆K1L ∆K1L ∆K1L ∆A46R ∆A46R ∆A46R ∆A46R

∆A52R

∆A52R ∆A52R ∆A52R ∆A52R ∆A52R

∆A52R ∆A52R ∆K3L ∆K1L ∆N1L ∆N1L ∆N1L ∆K1L ∆K1L ∆K1L ∆N1L ∆N1L ∆K1L

∆A46R ∆K3L ∆N1L ∆A52R ∆A52R vvDD ∆K3L ∆N1L ∆N1L ∆K3L ∆K1L ∆K1L ∆N1L

∆K3L ∆N1L ∆A52R ∆N1L ∆K1L ∆K3L vvDD ∆A46R vvDD ∆N1L vvDD ∆A46R ∆K3L

∆N1L ∆A46R vvDD ∆K3L ∆K3L ∆A52R ∆K1L ∆K3L ∆K3L ∆A46R ∆K3L ∆K3L ∆A46R

vvDD vvDD ∆A46R vvDD vvDD ∆K1L ∆A52R vvDD ∆A46R vvDD ∆A46R vvDD vvDD

More potent than vvDD

Equally potent compared to vvDD

Less potent than vvDD

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3.3 Aim 3: Characterization of the candidate VV deletion mutants to vvDD in terms of in vivo tumor-selectivity, toxicity and efficacy in mouse models of PC.

To further investigate the potential of our novel candidate VVs as oncolytic viruses, the best

performers from our in vitro assays were tested in nude (NU/NU) and immunocompetent mice

(C57BL/6). A maximum tolerable dose (MTD) was determined for each candidate VV and used

for subsequent investigation. For both the biodistribution and tumor survival studies, tumor

generation was induced by IP injection of either DLD-1 human colon carcinoma cells or A2780

human ovarian carcinoma cells into NU/NU mice, or MC38 murine colon carcinoma cells into

immunocompetent C57BL/6 mice. These mouse models are established models of peritoneal

carcinomatosis (PC) in our lab.

The MTD of candidate VVs is lower than the established vvDD treatment dose.

Before assessing the anti-tumor efficacy of each candidate VV treatment, MTDs were

determined for IP treatment (Figure 3.17). Non-tumor-bearing mice were injected IP at different

doses and followed for toxicity. Common adverse events of virus treatment in nude mice

included pox formation, usually on paws or tail, and weight loss. However, in C57BL/6 mice,

only weight loss, if at all, was observed after virus treatment.

In the first study in which C57BL/6 mice were injected at the same dose as the established

vvDD IP dose of 109 pfu, the mice treated with candidate VVs reached endpoint within one

week. Subsequent studies tested doses one at a time and mice were observed for at least 30 days

or until the first death, before the initiation of another study with an adjusted dose. Endpoint

criteria for these studies included: >20% weight loss, moribund, or otherwise unable to eat and

drink. Doses were increased or decreased by 0.5 log-fold in the next study, accordingly. For

most of the dose titration experiments, no mock group was used. Instead, vvDD was injected at

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the same dose as the candidate VVs for each study. According to the literature, vvDD is not

toxic to mice even at an IP dose of 109, though transient weight loss after injection is observed

at this dose (McCart et al., 2001; Ottolino-Perry et al., 2014). Thus, no deaths were expected

from the vvDD-treated group, especially at lower doses. Hence, the vvDD group served as 1) a

negative control similar to mock and 2) a treatment group to compare to candidate VV treatment

groups for in vivo toxicity.

For immunocompetent C57BL/6 mice, the IP MTD for the ∆K1L VV was 5x107

pfu, while the

MTD of ∆A46R VV and ∆A52R VV was 1x107

pfu (Figure 3.17 A, B). No mice reached

endpoint at the corresponding treatment doses within 30 days. However, mice in the ∆K1L VV-

treated group suffered transient weight loss approaching endpoint weight loss, before recovery

(~1 week) at a dose of 5x107 pfu.

The IP treatment dose for the tumor survival studies of all candidate VVs in nude mice was 106

pfu (Figure 3.17 C). Though one mouse from each of the ∆K1L and ∆A46R treatment groups

reached endpoint at 28 days, the MTD was still deemed to be 106 for these viruses.

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Figure 3.17. Determining the IP MTD of candidate VVs in nude and C57BL/6 mice. Non-tumor-bearing mice were injected IP with the indicated doses of

candidate VV or vvDD (n=3). A) 5x107 pfu into C57BL/6 mice B) 1x10

7 pfu into C57BL/6 mice, and C) 1x10

6 pfu into NU/NU mice.

A) B)

C)

5 x 107 pfu in C57BL/6 1 x 107 pfu in C57BL/6

1 x 106 pfu in NU/NU

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Candidate VVs and vvDD replication preferentially target tumors and ovaries.

The tumor-selectivity of IP-delivered candidate VV and vvDD replication was evaluated in

tumor-bearing models of PC (Figure 3.18). Specifically, a syngeneic model of PC with C57BL/6

mice bearing IP MC38 tumors and xenograft models of nude (NU/NU) mice bearing IP A2780

or DLD-1 tumors, were used. All mice were treated with IP virus or mock infection 12 days-

post tumor inoculation. In C57BL/6 mice, the doses were: 109 pfu of vvDD, 5x10

7 pfu of ∆K1L

VV, 1x107 pfu of ∆A46R VV or ∆A52R VV. Nude mice were treated at 5x10

6 pfu for all

viruses. Viral titers were normalized to total protein, to account for the differing protein contents

in each tissue type (Figure 3.18 A, C, E). Since the viral doses also differed among treatment

groups in C57BL/6, normalized viral loads of non-tumor tissues were also presented relative to

the normalized viral load in tumors, for studies in both C57BL/6 and NU/NU mice (Figure 3.18

B, D, F). Specifically, the normalized viral titers from non-tumor tissue were divided by the

viral load found in tumors from the same mouse. If the viral load of the non-tumor tissue was 0,

it is not presented on the graph. These data are presented in log-scale, thus bars below the x-axis

signify that the viral titers for the corresponding non-tumor tissues are lower than the viral load

in the tumors found in the same mouse.

Candidate VV and vvDD replication preferentially targeted the tumor and the ovaries in all

cancer mouse models tested. In C57BL/6 mice bearing MC38 tumors, 2-4 log-fold less

candidate VV was generally detected in the tumor compared to vvDD, possibly partially due to

the different doses. With the exception of the ovaries, all viruses had little to no infectious

particles in other non-tumor tissues compared to tumor. Most impressively, ∆A52R VV was

undetectable in the bowel, spleen, liver, heart, and brain. In NU/NU mice bearing DLD-1

tumors, the viral load of candidate VVs and vvDD found in tumors was more similar ( range:

1.3 x 105 pfu/mg – 1.5 x 10

6 pfu/mg compared to 4.1x10

5 pfu/mg) . In general, the concentration

of infectious particles of all candidate VVs and vvDD was lower in non-tumor tissues, except

the ovary, compared to tumor. In NU/NU mice bearing A2780 tumors, up to 10 times more than

the amount of virus injected into each mouse was found per milligram of tumor for all viruses.

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In addition, the viral load in all non-tumor tissues was at least 10 times lower than the viral load

found in corresponding tumors.

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vvDD K1L A46R A52R

MC38 in C57BL/6 A)

B)

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MC38 in C57BL/6


vvDD K1L A46R A52R

DLD-1 in NU/NU C)

D)

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Figure 3.18. Biodistribution of candidate VVs and vvDD in tumor-bearing mice. Nude mice were injected IP

with tumors and 12 days later, treated IP with vvDD or candidate VVs at MTDs of virus in MC38-bearing C57BL6

mice (A, B) or 5x106 pfu for DLD-1 (C,D) or A2780- bearing (E,F) nude mice. Non-tumor and tumor tissues were

harvested and viral load was quantified and presented as total pfu/mg (A, C, E) and total pfu/mg relative to tumor

titer (B, D, F). Values are means of three replicates ± SEM.

A2780 in NU/NU E)

F)

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Candidate VVs improve survival in orthotopic PC models compared to mock- and vvDD-

treated groups.

The survival advantage of candidate VVs and vvDD was assessed in syngeneic and xenograft

orthotopic models of PC. Mice were treated at the MTD 12 days post-tumor inoculation and

followed for survival. The endpoint criteria for these experiments included: >20% weight loss, a

subcutaneous tumor at the injection site of >1.5cm, difficulty breathing, moribund, or otherwise

unable to obtain food or water.

Candidate VVs improved survival equivalent to or better than vvDD with respect to mock-

treated controls in the MC38 tumor-bearing C57BL/6 syngeneic model (Figure 3.19). Both

vvDD- and ∆A46R- treated mice had a similar survival time compared to mock-treated mice. A

significant improvement in median survival time compared to vehicle-treated mice was

observed in ∆K1L-treated mice (35 days v.s. 28.5 days, p=0.0058), but ∆A52R VV-associated

median survival was also longer than vvDD (32.5 days).

Figure 3.19. Efficacy of candidate VVs and vvDD in a syngeneic model of PC. Kaplan-Meier survival curve of

MC38 tumor-bearing mice injected IP with candidate VV, vvDD, or mock-treatment (HBSS) 12 days post-tumor

injection (n=8).

MC38 in C57BL/6

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The efficacy of the candidate VVs was also similar or better than vvDD in xenograft models of

PC. In DLD-1 tumor-bearing mice (Figure 3.20 A), long-term survival until the end of the

experiment at 160 dpi was observed in 12.5%, 25%, and 37.5% of vvDD, ∆A46R VV and

∆A52R VV treated mice, respectively. In A2780 tumor-bearing mice (Figure 3.20 B), ∆K1L

VV treatment significantly improved median survival time compared to mock- treated mice

(53.5 days v.s. 40 days, p=0.0021). A 12.5% long-term survival rate was also associated with

vvDD, ∆K1L, and ∆A52R treatment.

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Figure 3.20. Efficacy of candidate VVs and vvDD in xenograft models of PC. Kaplan-Meier survival curve of

A) DLD-1 tumor-bearing NU/NU mice and B) A2780 tumor-bearing NU/NU mice injected IP with candidate VV,

vvDD, or mock-treatment (HBSS), 12 days post-tumor injection (n=8). The mock-treated group in A) had 7 mice

due to dramatic weight loss in one mouse before the experiment began. Death of one mouse in the vvDD group

presented in B) was censored due to a death related to neither virus treatment nor tumor burden.

DLD-1 in NU/NU

A2780 in NU/NU

p=0.0021

A)

B)

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Chapter 4

4 Discussion

4.1. General Discussion

The first aim of this project was to generate a panel of VV deletion mutants with a deletion in

one of the VV immunomodulatory genes (N1L, K1L, K3L, A46R, and A52R) from one of the

more virulent strains of VV, Western Reserve (WR). The WR strain was chosen as the

backbone of our viruses for its inherent tumor-selectivity compared to other strains of VV, as

measured by viral replication in tumors relative to non-tumor cells (Thorne et al., 2007).

Further, WR VV was used as the parental virus in the creation of vvDD (McCart et al., 2001).

We intended to exploit the defects in antiviral immunity commonly found in cancer by deleting

redundant immunomodulatory genes from VV. This mechanism of tumor-specificity is

exploited by other research groups and there are some promising OVs created using this

rationale. For example, the deletion of the VV inhibitor of IFNβ, B18R, resulted in a tumor-

selective OV (Kirn et al., 2007). There were several reasons for choosing the aforementioned

VV genes for deletion. The chosen candidate genes inhibited major proteins related to the IFN

induction or signaling pathways that are already dysregulated in several malignancies. Hence,

the expression of these VV immunomodulatory genes would be redundant for successful

replication in tumor cells. Further, independent research groups have reported decreased

virulence in normal cells, or animal models, following deletion of the candidate genes from WR

VV or other strains of VV (Stack et al., 2005; Harte et al., 2003; Bartlett et al., 2002; Langland

and Jacobs, 2002; Liu et al., 2013). Hence, we believed that the deletion of our candidate genes

would yield a promising tumor-selective oncolytic VV. Of note, the degree of mutations and

IFN resistance varies among cancers and cell lines, so the susceptibility of different tumors to

our candidate VVs would also vary.

104

The candidate deletion mutants were generated via homologous recombination with a shuttle

plasmid. Though some groups have already made deletion mutants of our candidate genes from

WR VV, it was important to make our own virus, to ensure consistency and comparability to

vvDD-R2R-Luc. The marker gene was a fusion protein of RFP and Renilla luciferase. RFP was

used to measure in vitro viral spread, however the Renilla luciferase was not used in this project

and cloned in for future studies. Overall, the first aim of this project was successfully achieved.

The shuttle plasmid had been confirmed with both colony PCR and restriction enzyme

digestions of unique sites (Figure 3.5). Further, expression of RFP in infected monolayers

confirmed the presence of the desired recombinant VV (Figure 3.6) and subsequent PCR

demonstrated the successful selection from parental virus via the absence of a ~1 kb PCR

product that would have been amplified in the presence of parental WR VV (Figure 3.7-3.8).

The recombinant VVs would have also been able to produce a 4kb band from the same PCR

reaction. Although it was not a requirement to determine the absence of the parental WR VV,

there was a 4kb band for all viruses except ∆K1L VV, which served as a double confirmation of

the presence of the desired deletion mutant. The crude DNA preparation and the length of the

PCR product may have hindered the production of the 4kb band during the PCR reaction for

∆K1L VV. Alternatively, a separate PCR reaction amplifying a smaller product, by replacing

one of the original primers with a DNA sequence derived from the inserted marker genes, could

confirm the presence of the desired ∆K1L VV with the expected insert.

For the second aim of our project, we tested our panel of candidate VV deletion mutants against

vvDD in terms of in vitro viral replication, viral spread and cytotoxicity in colon and ovarian

cancer cell lines. The cell lines MC38 murine colon adenocarcinoma, DLD-1 human colon

adenocarcinoma, and A2780 human ovarian carcinoma, were chosen to correspond to the cell

lines used for orthotopic models of PC in Aim 3. All candidate VVs performed similarly or

better than vvDD in monolayers of colon cancer cells, MC38 and DLD-1. Select candidate

viruses had significantly lower viral spread or cytotoxicity in monolayer ovarian carcinoma cells

relative to vvDD, but all VVs were also more efficient at replicating, spreading and killing

A2780 cells (Figure 3.9 – 3.12). It should be noted that since the MTS assay used to measure

105

cell viability is based on the metabolic activity of the cells, the assay quantifies both the

cytotoxic and cytostatic effects of the candidate VVs and vvDD on the tumor cell lines.

The improved viral replication and spread may be attributed to the different gene deletions

between vvDD and our candidate VVs. Specifically, vvDD has deletions in its TK and VGF

genes, which restrict its supply of nucleotides for replication to the dNTPs made by the cell

(McCart et al., 2001). In contrast, our candidate VVs retain the ability to express TK to add to

and use the pool of nucleotides already in the infected cell, in addition to expressing the

mitogen, VGF, to prime adjacent cells to activate its MEK/ERK pathway. Though cancer cells

usually constitutively activate the MEK/ERK pathway that produces cellular dNTPs, viral TK

and VGF will confer a larger advantage in slower growing cancers. On the other hand, IFN

limits the replication and spread of VV (Luker et al., 2005). Since in each case, a VV

immunomodulatory gene that counteracts major proteins in the induction and signaling pathway

of IFN is deleted, the replication of our candidate VVs may be differentially inhibited depending

on the degree of IFN responsiveness in the cancer cell. In contrast, vvDD still expresses the

whole armamentarium of WR VV immunomodulatory genes to counteract antiviral processes.

Together, the interplay of these factors contributes to the VV replication efficacy of vvDD and

our candidate VVs.

In addition to cell lysis from the cytoplasmic accumulation of VV progeny, cell death associated

with VV is enacted by various mechanisms depending on the cell type. For example, WR VV

infection induces apoptosis in Hela G cervical carcinoma cells, but causes necrosis in BSC-40

African green monkey kidney cells (Liskova et al., 2011). This suggests that the increased

cytotoxicity of the candidate VVs seen in our experiments may be a result of both VV-mediated

death and the cellular response to infection. In particular, cells could undergo cell death to

suppress VV replication and spread. An example would be the infection of VV in keratinocytes,

where rapid necrosis is induced by a STAT3-dependent pathway, resulting in lower VV titers

and the secretion of type I IFNs and pro-inflammatory cytokines (He et al., 2014). Alternatively,

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the infection of DCs results in apoptosis prior to the formation of viral factories (Chahroudi et

al., 2006). Similarly, some of the cell death observed in our experiments from infection with

candidate VVs could have been part of cell-intrinsic antiviral mechanisms. TLR, NFκB, and

PKR signaling can also result in cell death (Radhakrishnan and Kamalakaran, 2006; García et

al., 2007; Salaun et al., 2007). Since candidate viruses have a deletion in an immunomodulatory

protein that could inhibit a process related to the induction of pro-inflammatory cytokines and

IFN-stimulated proteins, more cells would have died by antiviral processes compared to vvDD,

which still expresses all the VV immunomodulatory proteins. The amount of death by cell-

intrinsic mechanisms, however, would be dependent on the type of mutation and the effect on

the antiviral mechanisms in the cancer cells themselves. Further, the observed increase in

replication of candidate VVs relative to vvDD suggests an increase in the amount of viral

nucleic acids that would be recognized by cytosolic PRRs such as RIG-1 and MDA-5 to activate

an antiviral response. Of note, premature cell lysis will contribute to a decreased amount of VV

virions. Hence, VV replication is also affected by these antiviral responses.

Viral spread is affected by the degree of replication and lysis, as well as the permissivity of cells

to infection. The amount of virions produced inside the cell and the subsequent release of IMV

forms of VV would contribute the most towards the amount of VV spread, as the EEV form

constitutes the minority of virions produced (Roberts and Smith, 2008).

VV replication, spread, and cytotoxicity among the cell lines used also differed. A2780 cells

were the most susceptible to candidate VVs and vvDD, followed by MC38 and DLD-1. General

characteristics of cancer cells coincide with the optimal environment for virus infection and

growth. Recognized attributes include increased cell proliferation, nucleotide and protein

synthesis and decreased antiviral responses and apoptosis (Ilkow et al., 2014). A combination of

these attributes may partially explain VV susceptibility. For example, MC38 cells were the most

aggressive and rapidly dividing cell line of the three, and that may have contributed to the

increased VV replication and cytotoxicity compared to DLD-1; however it is does not fully

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explain A2780 cell permissivity observed herein. It is unclear what specific gene expression

pattern or combination of characteristics lends itself to resistance or susceptibility to VV

infection. Other groups have attempted to determine the factors that contribute to widespread or

limited VV infection in cancer cells. For example, an oncolytic VV, GLV-1h68, was tested in a

panel of 76 cancer cell lines, and some correlations between in vitro susceptibility and gene

expression patterns were drawn. Generally, highly permissive cells had a downregulation of

genes related to IRF3/7 signaling. Further, ovarian cancer cell lines expressing genes indicative

of the epithelial cell phenotype were more resistant to VV infection, though this trend was not

observed in other cancer types (Ascierto et al., 2011). This might partially explain the

susceptibility to VV replication, spread, and cytotoxicity of vvDD and our candidate VVs in

A2780, which is a loosely adherent cell line that demonstrates a mix of epithelial-like and

mesenchymal-like properties (Huang et al., 2013). It is important to emphasize that the

susceptibility to VV infection is a complex and multi-factorial phenomenon and the permissivity

of a cell line towards VV infection is facilitated by a combination of many attributes.

Interestingly, the ∆K1L, ∆A46R, and ∆A52R VVs consistently demonstrated superior viral

replication, cytotoxicity and viral spread, respectively, across all cancer cell lines examined,

though superiority was usually not statistically significant compared to other candidate VVs.

This suggests, for example, that the K1L gene confers the least advantage towards VV

replication within the context of MC38, DLD-1 and A2780 monolayers. Yet, the K1L gene is

more important for other aspects of VV potency, such as viral spread and tumor cytotoxicity

than A52R and A46R, respectively. When these results are interpreted with the knowledge that

cancers are not completely resistant to antiviral IFN and pro-inflammatory responses, nor

absolutely anti-apoptotic, but rather these features are enhanced compared to normal cell lines

(Haralambieva et al., 2007), the reason for these results may be various. It is likely that the

constitutive activation of NFκB in these cell lines renders the NFκB-inhibiting activity of K1L

and N1L redundant for viral replication. However, since N1L also has anti-apoptotic properties

which can prolong the time VV has to replicate (Abrahams et al., 2005), its gene deletion

negatively affects VV replication more than the deletion of K1L. On the other hand, the anti-

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apoptotic activity of N1L reduces the amount of cell lysis and, therefore, tumor cytotoxicity and

viral spread. Likewise, the A46R and A52R genes are the most redundant VV genes in terms of

tumor cytotoxicity and viral spread, respectively, while remaining relatively more important

than K1L for VV replication. Both genes express proteins that inhibit TLR signaling, but

perhaps the abrogation of the A46R inhibition of TLR3- mediated IRF3 (Bowie et al., 2000)

results in more cell lysis despite N1L apoptotic activity, thus also leading to less viral replication

and spread than ∆K1L and ∆A52R VVs, respectively. Lastly, the activity of A52R may be

complemented by other VV immunomodulatory genes in the context our cancer cell lines,

leading to superior viral spread. Yet, its role in promoting TLR4-mediated expression of IL-10

or inhibiting NFκB through TLR signaling (Maloney et al., 2005) may have made the A52R

gene more important for VV replication and tumor cytotoxicity than K1L and A46R,

respectively.

The viral spread and cytotoxicity of our candidate VVs were also compared to vvDD in MC38

and DLD-1 tumor spheroids (Figure 3.13 – 3.16). The 3D architecture of multicellular spheroids

offers several characteristics of an in vivo tumor as a result of a shape that mimics the

physiological cell-cell contact. In contrast to monolayer cultures, only the cells on the surface of

the tumor spheroid are directly exposed to the nutrients in the growth media. Nutrients must

diffuse into the spheroid to reach cells in the inner portion of the spheroid, resulting in a gradient

of nutrient distribution, differential growth kinetics and waste metabolism in the same spheroid.

Spheroids have also been shown to be more resistant to anticancer drugs compared to monolayer

cultures, as a result of the physiological cell-cell contact that allows tight junctions and

communication. It should be noted that tumor spheroids obviously lack some aspects of an in

vivo tumor, such as vasculature and immune cell infiltration (Mehta et al., 2012)

As expected, viral spread for all candidate VVs and vvDD at the center of the spheroids was

inhibited compared to the spread observed in monolayer cultures. However, there was

widespread infection on the surface of all VV-treated spheroids. This is consistent with VV

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spread observed within ovarian cancer spheroids (Tong et al., 2015), where the quiescence of

the cells at the center of the spheroids was attributed to the reduced spread. Similar to the results

seen in monolayer cultures, the spread of the candidate VVs to the middle of MC38 and DLD-1

spheroids was also similar, or better, compared to vvDD. The factors that governed the

differences in viral spread between candidate VVs and vvDD in monolayer cultures could also

play a part in these spheroids. ∆A52R VV had the best spread in both MC38 (Figure 3.13) and

DLD-1 (Figure 3.14) spheroids, suggesting that the A52R gene is also the most redundant gene

of our candidate genes for viral spread within spheroids. The quiescent state of the cells at the

center of the spheroids had the greatest effect on vvDD spread, which relies solely on the cell-

intrinsic pool of dNTPs for successful viral replication. Nevertheless, all viruses effectively

killed most, or all, the cells within both types of spheroids by 96 hpi, as measured by clonogenic

assays (Figure 3.16) and the change in MC38 spheroid size of VV-treated spheroids compared

to mock (Figure 3.15 A). Though the cells in the spheroids were mostly killed, the spheroid size

was larger than initial spheroid volume before infection. Further, the spheroid volume seemed to

be still decreasing past 96 hpi, suggesting more tumor killing. The larger size at 96hpi may be a

result of tumor growth that superseded viral killing during the initial stages of infection resulting

in a net growth, resulting in a larger spheroid. The eventual decrease in tumor volume at later

time points is an indicator of more virus-mediated cell killing than tumor cell proliferation. The

continued decrease in spheroid volume after 96 hpi, albeit slower, despite almost no viability

measured by the clonogenic assay, can be explained by the nature of the assay. It is possible that

there were still many infected, but viable, tumor cells in the spheroid at 96 hpi that eventually

died and led to the decreased spheroid volume at later time points. The infected cells would

have not survived to generate colonies in the clonogenic assay; the clonogenic assay only serves

to measure the clonogenic potential of tumor cells after candidate VV and vvDD infection.

The best performers from the in vitro assays, ∆K1L, ∆A46R and ∆A52R VV were used in the in

vivo investigation in Aim 3. Here, we sought to determine the tumor-selectivity and therapeutic

efficacy of these candidate VVs compared to vvDD at MTDs in syngeneic and xenograft models

of PC. In order to determine the doses for tumor survival studies, non-tumor bearing C57BL/6

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and nude mice were injected IP with increasing doses of candidate VVs and followed for

toxicity and survival. In C57BL/6 mice, the MTD for ∆K1L VV was 5x107 pfu while the MTD

for ∆A46R VV and ∆A52R VV was 1x107 pfu (Figure 3.17 A, B). In nude mice, the MTD of all

candidate VVs was 1x106 pfu (Figure 3.17 C). Although one mouse from the ∆K1L and ∆A46R

group treated at this dose had died at 28 days (instead of after the 30 day predetermined

experimental endpoint), we continued our experiments using this dose because we speculated

the tumors in the mouse will act as a sink for viral replication and reduce the initial symptoms of

these candidate VV treatments. This was supported by the reduced weight loss in tumor-bearing

C57BL/6 mice during the first week after treatment with 5 x 107 pfu of ∆K1L VV compared to

non-tumor-bearing mice. The MTD for vvDD, as determined from the literature, for these

strains of mice is 1x109 pfu (McCart et al., 2001; Ottolino-Perry et al., 2014). The significantly

lower MTDs of our candidate VVs were not unexpected. It may be attributed to the heightened

immune response against our candidate VVs compared to vvDD. The abrogation of an

immunomodulatory gene in these viruses renders them more susceptible to the activation of pro-

inflammatory cytokines and IFNs compared to vvDD. A cytokine storm may have resulted in an

immune response that contributed more to the tissue damage and subsequent deaths than

candidate VV infection and cytotoxicity alone. However, further work to measure the pro-

inflammatory cytokines and IFN induction after infection with our candidate VVs and vvDD

must be done to confirm this speculation.

Our data confirm the biodistribution of vvDD reported in the literature (McCart et al., 2001;

Ottolino-Perry et al., 2014), wherein vvDD preferentially targeted tumor and ovaries for all 3

mouse models of PC. Similarly, the replication of candidate VVs was also the highest in the

tumors and ovaries (Figure 3.18). The VV replication in the bowel, kidney, spleen, liver, heart,

lung, brain and bone marrow was limited by comparison, especially for candidate VVs within

MC38-tumor bearing C57BL/6 immunocompetent mice. The mechanism of selective viral

replication could be partially attributed to the gene deletions. In vvDD, the TK and VGF gene

deletions will restrict replication to rapidly dividing tissues, yet vvDD expresses all VV

immunomodulatory genes to counteract antiviral mechanisms. In the candidate genes, the VV

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immunomodulatory gene deletions abrogate the ability of VV to inhibit NFκB and TLR

activation in the host cell, allowing non-tumor cells to more effectively inhibit candidate VV

replication via innate antiviral mechanisms. The intrinsic tumor-selectivity of the parental WR

(Thorne et al., 2007; McCart et al., 2001) may also play a role in the biodistribution of these

viruses. Though its mechanism is unknown, its large size has been suggested to restrict its

extravasation to tissues with leaky vasculature, such as the ovarian follicles and tumor tissues

(Shen and Nemunaitis, 2005). It is possible that the estrous cycle, in which there are periods of

increased cell proliferation and angiogenesis in mouse ovaries (Baranda-Avila et al., 2009),

contributed to the high VV titers found in our models. Of note, comparably lower amounts of

WR VV (3646 pfu/mg) were found in the ovaries of non-human primates 6 days after systemic

administration (Naik et al., 2006), suggesting a species-specific phenomenon. Similarly, no

vvDD was found in the ovaries of these primates 6 days and 6 weeks post-treatment (Naik et al.,

2006).

Our in vivo studies evaluating therapeutic efficacy were conducted in both immunocompetent

(C57BL/6) and immunocompromised mice (NU/NU), at previously determined MTDs (Figure

3.19 – 3.20). Excitingly, treatment with candidate VVs was associated with similar or improved

survival, despite being administered at a dose 20 – 1000 times lower than the vvDD dose. In the

syngeneic model with C57BL/6 mice bearing MC38 tumors, only the ∆K1L VV treatment

offered a statistically significant improvement in median survival compared to mock (35 days

v.s. 28.5 days; p=0.0058). This is interesting because the ∆K1L VV-treated mice in the

C57BL/6 biodistribution experiment also had the least amount of virus in tumors, despite

displaying the best viral replication in vitro and replicating to comparably higher titers in tumors

implanted in nude mice. Thus, direct viral infection and oncolysis may not be the primary mode

of tumor killing for ∆K1L VV in this model. It is well recognized that OVs can trigger multiple

mechanisms against cancer (Kirn and Thorne, 2009) Likely, the ∆K1L VV may initially have

replicated well in tumors and caused immunogenic cell death to a sufficient level in tumors and

tumor stroma to prime a robust tumor- and VV- specific adaptive response against infected and

uninfected tumors. An OV-induced immune response would have explained the concurrent

lower viral load and improved therapeutic efficacy. However, more studies are required to

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confirm this mechanism of action and explore how the deletion of ∆K1L contributed to the

mechanism of action compared to vvDD and other candidate gene deletions.

Different viruses improved survival in ovarian and colon cancer in nude mice. In short, no

viruses improved the median survival of DLD-1 tumor-bearing mice, but ∆A52R VV treatment

was associated with the highest number of mice experiencing a complete response and long term

survival (37.5%), followed by ∆A46R VV (25%) and vvDD and ∆K1L VV (12.5%). On the

other hand, ∆K1L VV treatment was the sole treatment that extended the median survival of

A2780 tumor-bearing mice compared to mock, though one mouse (12.5%) from ∆K1L, ∆A52R,

and vvDD-treated groups experienced complete responses. Intriguingly, these tumor responses

are associated with the candidate VVs at a dose 1000 times lower than the vvDD dose. It should

also be noted that some nude mice experienced treatment-related deaths or bowel obstruction

with moderate tumor load, but the endpoint for the majority of mice was related to high tumor

burden. In general, the reason for superior efficacy could be that the A52R gene and the K1L

gene are the most redundant genes in WR VV for infecting and lysing DLD-1 and A2780

tumors, respectively, in nude mice. The in vivo tumors had a 3D architecture similar to tumor

spheroids, but were much larger and some also had tumor vasculature. Most cells in areas with

low perfusion would be quiescent, thereby impeding vvDD penetration compared to candidate

VVs. In addition to the reasons proposed for efficacy against monolayer colon and ovarian

cancer cell lines, anti-tumor effects can also arise from the intact innate immunity in nude mice.

For example, neutrophils could be attracted to and obstruct tumor vasculature. Further, the cell

death induced by the candidate viruses could change the tumor microenvironment to repolarize

M2 macrophages or enhance M1 macrophages against the cancer. Since A2780 and DLD-1 are

different cell lines from different cancers, it is not surprising that different candidate VVs

exhibited different anti-tumor efficacy. As before, the potential mechanisms need to be

confirmed with further experiments.

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4.2. Project Summary

In summary, the project described herein explored the possibility of generating safe and potent

OVs based on the defective innate immunity in cancer, specifically focusing on genes associated

with an IFN response. In Aim 1, we generated 5 recombinant VVs with deletions in VV

immunomodulatory proteins from one of the most potent and tumor-selective strains, WR VV.

In Aim 2, we tested these candidate VVs in terms of in vitro viral replication, spread and tumor

cytotoxicity in colon and ovarian cancer cell lines, comparing them to a clinical OV, vvDD.

Here, we demonstrated that the gene deletions in the VV immunomodulatory genes did not

hamper the viral potency towards tumor cells compared to vvDD. Instead, the candidate VVs

were at least comparably effective against both cell lines and tumor spheroids of colon cancer

cells. All viruses and vvDD were potent against monolayer ovarian cancer cells. We propose

that the superior efficacy of the candidate VVs was due to the redundancy of the deleted genes

in our candidate VVs in the context of colon and ovarian cancer cells, compared to the TK- and

VGF- deletions in vvDD. The best performers, ∆K1L, ∆A46R, and ∆A52R VV, were further

evaluated in Aim 3, wherein in vivo tumor-selectivity and therapeutic efficacy were assessed.

Overall, the replication of the candidate VVs was tumor-selective. Most excitingly, there was

improved therapeutic efficacy associated with the candidate VVs examined at a dose 20 times

lower in immunocompetent mice and 1000 times lower in nude mice, relative to the treatment

dose of vvDD. Herein we present promising oncolytic VVs and confirm the hypothesis that the

deletion of VV immunomodulatory genes can lead to an OV with improved therapeutic efficacy.

Future studies are needed to characterize and develop next generation viruses for clinical use.

4.3. Experimental Challenges and Limitations

4.3.1. Tumor Spheroids

As described above, tumor spheroids offer a 3D architecture to better mimic the

microenvironment found in in vivo tumors. Our objective with the confocal imaging was to

compare the ability of the candidate VVs and vvDD to spread into the spheroid. The most

difficult region to spread into, and therefore the most representative of the ability of the VVs to

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penetrate spheroids, would be the middle of the spheroid. Hence, the images acquired from the

middle of each spheroid at a peak time point of RFP expression (72h) were used to compare the

viral spread, using RFP expression. Instead of uniformly penetrating the cells at the surface of

the spheroid, the virus infections occurred at random foci at early time points before spreading

across the surface and penetrating into the spheroid at approximately 48-72hpi. Hence, it would

have been ideal to measure viral spread throughout the whole spheroid, especially early in the

infection, albeit technically difficult. The spheroids were ~250-300 µm in diameter when they

were infected, but the upper limit for acquiring z-stacks via confocal imaging was 200µm, so

only a portion of the spheroid could be reliably imaged in thin sections. Two-photon microscopy

would have been able to visualize thicker specimens, but the low working distance of the

microscope means the spheroid formation via hanging drop method would be better suited for

this type of imaging. The hanging drop method is the spontaneous formation of spheroids

encouraged by the gravity and surface tension inside a small droplet hanging from the inside of

the lid of a tissue culture plate. However, the maintenance of these spheroids and the addition of

virus are delicate and labour-intensive protocols. Some research groups have assessed the

interior of larger spheroids by sectioning, staining and digitally reconstructing the spheroid

(Achilli et al., 2012). Since the spread of candidate VVs could still be compared at later time

points during spheroid infection using one section, we did not pursue these labour-intensive

alternatives.

Tumor response to treatment is also usually measured by monitoring tumor size over time. This

is usually achieved by measuring the diameter of the spheroid from brightfield images and

calculating tumor volume with an equation that assumes a spherical shape (Achilli et al., 2012).

Though this method worked well with MC38 spheroids, which retained a relatively spherical

shape throughout the experiment, this was not true for DLD-1 spheroids. DLD-1 spheroids were

spherical prior to infection, but upon infection by VV, the cells lose adherence and form a

loosely-held aggregate that eventually falls away from the main spheroid, leaving a crater where

the infected cells used to be attached. The resulting irregularly-shaped DLD-1 spheroids were

not amenable for calculating tumor volume using the above method. Accordingly, we used the

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clonogenic assay to evaluate the cyototoxicity of the VVs for the spheroids and confirmed that

the cells were killed.

4.3.2. In vitro to In vivo translation

In vitro assays were used to predict possible candidate VVs that would perform the best in the in

vivo experiments in Aim 3. The best 3 candidate VVs were then tested in mouse models of

peritoneal carcinomatosis. In vitro testing is a simple, reproducible and cost-effective method to

assess the tumor potency of our candidate VVs, however these assays do not test important

elements such as the role of the immune system in the viral infection. For example, the cell

mediated-immune responses from macrophages or T-cells are absent in our in vitro assays,

highlighting the importance of assessing the candidate VVs in mouse models. Nonetheless, our

in vitro assays were critical for screening our candidate VVs as potential oncolytic viruses.

The potency of candidate VVs was extensively compared to vvDD in tumor cell monolayer

studies. We recognize that there are many factors, in addition to immune infiltrates, existing in

vivo that may positively or negatively affected candidate VV replication, spread and tumor

cytotoxicity, that are absent in monolayers. Though experiments with monolayer cultures can

evaluate virus behavior in tumor cells in a simple, reproducible environment, they do not mimic

the differential signaling and the resulting response to OVs that likely exist in the 3D

architecture of tumors. Hence, the candidate viruses were also tested in the context of tumor

spheroids. Though the spheroid model more closely mimics in vivo tumors, it was difficult to

quantify viral spread in this model. Nevertheless, it was evident that ∆A52R VV had the greatest

spread in these studies. There remains a possibility that the potential of ∆N1L or ∆K3L VV as

OVs was overlooked. These viruses could have been less affected by the tumor cell-extrinsic

obstacles to viral delivery and may have superior efficacy in vivo, but were not tested herein.

However, since ∆K1L VV, ∆A46R VV and ∆A52R VV were consistently superior in all cell

lines examined, during our best efforts to predict in vivo efficacy with in vitro assays, these were

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the candidate VVs chosen for in vivo testing. Tumor-selectivity of our viruses was not tested in

cell cultures.

4.3.3. Mouse Models

The mouse models we used in our study were important for evaluating our VVs in an in vivo

context. Both immunocompetent (C57BL/6) and immunocompromised (NU/NU) mice provided

unique environments for extracting important information about in vivo toxicity, tumor-

selectivity and therapeutic efficacy. Immunocompetent mice have intact innate and adaptive

immune responses. Therefore the C57BL/6 mouse model provided an environment that

facilitated the multimechanistic anti-cancer effect of OVs which involves direct oncolysis,

disruption of tumor vasculature and the induction of anticancer immunity. This environment

also mirrored challenges that arise with an intact immune system, affecting viral delivery and

clearance (Kirn and Thorne, 2009). Thus, the syngeneic model may be a more clinically relevant

model. However, human cancer cell lines do not grow in immunocompetent mice, so xenograft

models are used to demonstrate the tumor response of human cancers to OV treatment. Though

nude mice lack a robust T-cell response and so viral clearance is not as effective in this model,

the vasculature and stroma provide a better model to measure the therapeutic efficacy of vvDD

and our candidate VVs against human cancers than in vitro models. Thus, both mouse models

have limitations, but can be used to foreshadow the possibility of using our candidate VVs in the

clinic. There are still differences between our mouse models and the human system; the true

feasibility of our candidate VVs as OVs requires extensive human clinical trials.

Both types of mice were important for assessing the safety of our candidate VVs. In this project,

we reported the toxicity of IP treatment with our candidate VVs in non-tumor bearing mice and

the biodistribution of VV replication in tumor-bearing immunocompetent and

immunocompromised mice. Since C57BL/6 mice have intact immune responses, these mice

were the most informative on whether the candidate VVs were toxic and the effect of the

immune response on the biodistribution of candidate VVs. Nude mice could model the toxicity

and biodistribution of the candidate VVs in the absence of an intact T-cell response.

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Encouragingly, MTDs could be determined and candidate VVs were tumor-selective in nude

mice. However, conclusions about safety derived from mouse models should be made with

caution; there are differences in murine and human immune systems. For example, 10 TLRs

(TLR 1-10) are present in humans, while 12 are identified in mice (TLR 1-9, 11-13) (Perdiguero

and Esteban, 2009). Hence, the true safety of the candidate VVs must be assessed in clinical

trials.

4.3.4. Intraperitoneal Tumor Implantation

Our objective in the in vivo studies was to evaluate the efficacy and tumor-selectivity of our

candidate VVs compared to vvDD in PC. The tumor microenvironment is instrumental in

determining the progression and development of the tumor and its response to treatment. In one

study, renal, colon and prostate cell lines implanted at orthotopic locations were more resistant

to treatment with immunotherapy with three agonist antibodies compared to subcutaneous

implantation (Devaud et al., 2014). Further, the sensitivity of tumors to type I IFNs is influenced

by tumor location (Brunda et al., 1987). Thus, we chose to inject tumor cells IP into mice to

mimic the tumor microenvironment of PC. Though the tumor locations had some variability for

tumor types and among individual mice, tumor nodules were usually found in the peritoneum,

urogenital area, diaphragm, bowel, mesentery, omentum and the serous membrane covering the

liver, similar to human disease (Klaver et al., 2012). Further, ascites development, which is a

common symptom in human PC and one of the factors influencing tumor dissemination (Terzi

et al., 2014; Carmignani et al., 2003), was also present in our model.

Our model of PC also presents a technical challenge for measuring tumor response over time.

Whereas subcutaneous tumor size can be easily tracked with calipers, IP tumors are not visible

on the surface. Many non-invasive imaging methods have been developed to track IP tumor

burden (e.g. bioluminescence imaging, positron emission tomography, computed tomography),

but the sensitivity of these techniques are hampered by the location and size of the tumor and

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the number of tumors disseminated in the peritoneal cavity (Rampurwala et al., 2009; Stollfuss

et al., 2015). For example, imaging by positron emission tomography can only detect 58% of

tumors between 1mm - 2mm and 88% of nodules between 2mm-4mm (Stollfuss et al., 2015),

which is approximately the size of many tumors at necropsy in our model, in addition to a few

larger 1-2 cm tumors. In bioluminescence imaging, nodules behind dense structures, like the

liver, are frequently undetected (Stollfuss et al., 2015). For these reasons, we did not feel

longitudinal monitoring of tumor burden would add useful information to our investigations and

so tumor-bearing mice were only followed for survival.

4.3.5 IFN Sensitivity in Tumors

The candidate VVs described in this project were created by gene deletions in VV proteins

associated with antagonizing the IFN induction and IFN-mediated responses. Hence, a

discussion of the immunogenicity in the tumor cells used in this project is warranted. MC38 is

poorly immunogenic. When MC38 cells were cultured in vitro with IFNα, MHC I expression

was enhanced but the immunosuppressive protein, programmed cell death 1 ligand, was also

upregulated. When MC38 cells were injected subcutaneously into C57BL/6 mice and treated

with IFN α, a strong programmed cell death 1 expression was induced in tumor-infiltrating T-

cells and the number of CD8+ T cells decreased (Terawaki et al., 2011). Further, tumor-

infiltrating macrophages of in vivo MC38 tumors drive tumor growth (Ries et al., 2014). In

contrast, DLD-1 cells are moderately responsive to IFN. Treatment of DLD-1 cells with 40

U/ml of IFNα was sufficient to confer 50% cell viability against a VSV infection challenge

compared to >5000 U/ml for completely IFN-resistant LNCap cells (Christian et al., 2012). In

vitro treatment of A2780 cells with IFNα was not able to induce antiviral mechanisms against

WR VV infection with or without a deletion in its viral IFNβ antagonist. Though A2780 was

able to produce IFNβ, it was not able to respond to it (Kirn et al., 2007). Thus, the cancer cells

that were used in this project were moderately to highly resistant to IFN induction and signaling,

providing an advantageous environment for candidate VV replication, spread, and cell-killing.

However, tumors are often made up of cells with varying degrees of sensitivity to IFN,

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including cells that are very sensitive to IFN that could be resistant to candidate VVs. However,

as discussed in Section 1.1.4, OVs have multiple mechanisms of action aside from direct tumor

infection and lysis including vascular disruption and the induction of the adaptive immune

response. The candidate VVs may still be effective against heterogeneous tumors. Our in vivo

PC models, wherein tumor cell lines are implanted, do not fully reflect the heterogeneity of

clinical tumors. Patient-derived tumors may be more reflective of the diversity in human disease

though this model is costly and requires availability of patient samples. As the initial study

characterizing the tumor efficacy of the candidate VVs, our model was the more practical, cost-

effective, and reproducible approach. However, future work may benefit from models with

patient-derived xenografts.

4.4. Future Directions

4.4.1. Determining the Mechanisms of Action

We have demonstrated anti-tumor efficacy in our mouse models, but did not specifically

determine the mechanism(s) of action against tumors by our candidate viruses. Understanding

how infection with the candidate VVs leads to tumor-killing is crucial for designing strategies to

improve the virus in the future. Multiple mechanisms of action have been identified in oncolytic

virotherapy (Kirn and Thorne, 2009). It would be of particular interest to investigate how ∆K1L

VV effected improved median survival in the MC38 tumor-bearing C57BL/6 mice, yet had the

lowest tumor titer in the biodistribution study within the same tumor model. Thus, it is

important to determine if and how the candidate VVs disrupt tumor vasculature and induce an

anti-tumor host response, in addition to implementing direct tumor lysis. In this project, we have

already demonstrated viral replication of the candidate VVs within in vivo tumors. The extent

and dispersion of infection throughout the tumor can be further assessed histologically with VV-

specific antibodies.

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Tumor vasculature shutdown, directly or indirectly, induced by OV infection, could have also

been a mechanism by which the candidate VVs induced tumor regression. Many studies have

been conducted to evaluate the role of the vasculature in anti-tumor efficacy of other OVs, but

whether our candidate VVs would employ this mechanism, remains to be determined. Similar

experiments can be conducted for our candidate viruses. Endothelial cells stained for CD31

would indicate whether VV staining co-localizes with the tumor vasculature (Ottolino-Perry et

al., 2014). Tumor perfusion studies should be performed by IV injection of fluorescent

microspheres into tumor-bearing mice before euthanization (Breitbach et al., 2011b). To assess

the role of neutrophil occlusion and clot formation in candidate VV efficacy, neutrophil

depletion, or the inhibition of clot formation with heparin, could be conducted to determine

whether efficacy is affected (Breitbach et al., 2007).

As mentioned, induction of an immune response is also a possible mechanism of action for

candidate VVs. Many OVs have been shown to induce immunogenic cell death that leads to a

host anti-cancer immune response (Guo et al., 2014). Studies have evaluated the induction of an

anti-tumor response in various ways such as re-challenge experiments in immunocompetent

mice that had complete responses (Kirn et al., 2007). Alternatively, Lemay et al. conducted an

adoptive cell transfer into naive mice from donor CT26-tumor bearing mice that had complete

responses from a VSV-infected cell vaccine treatment. CT26 and 4TI tumors were injected into

different flanks of the recipient naive mice and monitored for tumor growth, thereby measuring

tumor-specific responses from the treatment (Lemay et al., 2012). Similar experiments with the

candidate VVs would also determine whether a host immune response against cancer was

induced from VV treatment. Then, it would be interesting to investigate how the different

candidate VVs induced the host response. Immunohistochemistry of tumors from virus-treated

mice might reveal the types of immune cell infiltrates in the tumor, as a result of infection. In a

different experiment, conditioned media from infected monolayers of tumor cells could be used

to investigate how different lymphocytes would have been affected by the mixture of cytokines

secreted into the medium by the infected tumor cells. There might be a difference in effects on

the immune response associated with different candidate VVs, which could be useful

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information for selecting patients or designing therapy regimens. Overall, understanding the

mechanisms of action of our candidate VVs will be vital for designing the optimal treatment for

cancer patients and how to improve the candidate VVs.

4.4.2. Potential Treatment for Other Cancer Types

Though our project tested our candidate VVs in the context of colon and ovarian PC, many

other cancers have also accumulated defects in the innate antiviral immune response to

potentiate high viral replication, spread and cytotoxicity, relative to normal cells. Thus, the

rationale used to generate our panel of VVs is also applicable to other types of cancers. Within

the NCI-60 panel of cancer cell lines, several cancers were unresponsive to IFNα or IFNβ.

These malignancies included leukemia, non-small cell lung carcinoma, colon cancer, central

nervous system malignancy, melanoma, ovarian cancer, renal carcinoma, prostate cancer and

breast cancer (Stojdl et al., 2003). Further, VV has a broad tumor tropism (McFadden, 2005),

potentiating OV treatment with VV in several cancers. Thus, the therapeutic efficacy of

oncolytic VVs, such as vvDD, has been tested in several tumor types pre-clinically, some of

which include gliomas (Lun et al., 2009), renal cancer (Guse et al., 2010), peritoneal

mesothelioma (Acuna et al., 2014), breast cancer and melanoma (MacTavish et al., 2010).

Similarly, our candidate VVs can also be retested in the context of several malignancies.

4.4.3. Improving VV Delivery

It is possible to deliver OVs intratumorally, but intravenous delivery is more ideal for metastatic

cancers, in order to reach tumor nodules that cannot be directly injected, due to location, or to

eliminate undetected tumors. One of the major barriers to successful OV therapy is delivery to

the tumor. Widespread and dispersed infection of tumors is critical for complete responses (Le

Bœuf et al., 2013; Wein et al., 2003). When delivered systemically, OVs can be neutralized by

serum factors, or sequestered by the liver or spleen, before reaching and infecting the tumors.

This, too, will be a major issue for the candidate VVs which will usually be in IMV form, with

122

many antigenic proteins on its surface. The varying characteristics of the dispersed tumors found

in metastastic cancer (e.g. size, vascularization, immune infiltrates) also lead to differing

degrees of infection in each tumor mass (Ottolino-Perry et al., 2014).

Currently, different studies employ different strategies to shield the viruses, using cell-carriers

or coating the viruses with a polymer to improve delivery. Carrier cells are usually chosen for

their tumor-homing properties. Immune cells (cytokine-induced killer cells (Thorne, 2006), T-

cells (Ong et al., 2007), macrophages (Muthana et al., 2013), myeloid-derived suppressor cells

(Eisenstein et al., 2013) and mesenchymal stem cells (Komarova, 2006)) and cancer cells

(Power et al., 2007), are among the cell types being explored as possible cell carriers.

Biocompatible polymers, polyethylene glycol and N-[2-hydroxypropyl] methylacrylamide, have

been conjugated to adenoviruses to evade neutralization. Adenovirus coated with these polymers

was cleared 3.5 to 4 times slower than uncoated viral particles (Alemany et al., 2000; Green et

al., 2004). Overall, these shielding strategies have led to a longer lifespan in the bloodstream

and improved viral delivery to tumors. Therefore, it may be beneficial to combine our candidate

VVs with these masking strategies.

4.4.4. Combination Therapy

There is potential in testing our candidate VVs in combination with chemotherapy, radiotherapy,

immunotherapy, or surgery. Using the example of PC, there are many patients who are not

eligible for CRS with HIPEC due to tumor burden. The candidate VVs could be used for tumor

debulking that would then render these patients eligible for surgery. Alternatively, these VVs

could be administered IP along with chemotherapy, for a synergistic effect. However, these

possibilities require further investigation. The possibility of combining virotherapy with other

anti-cancer modalities has been investigated in several pre-clinical and clinical settings. Our

group demonstrated that vvDD can synergize with the chemotherapy drug, irinotecan (Ottolino-

Perry et al., 2015), and be used for peptide-receptor radiation therapy to improve survival from

CRC PC (unpublished data). There is also the possibility of arming the viruses with

immunomodulatory proteins such as GM-CSF. The herpes virus, T-Vec, and Wyeth strain VV,

123

JX-594, which express GM-CSF, have been shown to improve survival in many pre-clinical and

clinical investigations (discussed in Section 1.1.6). As our understanding of the mechanisms of

action of the candidate VVs begin to be delineated, it will be interesting to combine various

types of cancer treatment with these candidate VVs.

4.4.5. Deletion of Other VV Immunomodulatory Genes

In this project, we have evaluated the effect of deleting five VV immunomodulatory genes and

demonstrated that this strategy is a viable option for generating OVs. This strategy can be

pursued further. VV expresses several other proteins that can potentially be deleted to generate

other novel oncolytic VVs. There are many VV proteins that directly affect IFN induction and

IFN signaling pathways that have not been exploited. For example, K7L, F1L, H1L are

examples of VV immunomodulatory genes (Perdiguero and Esteban, 2009) that have yet to be

tested in the context of oncolytic virotherapy. Target genes do not necessarily have to be

involved in directly inhibiting proteins involved in the IFN system. The deletion of the D10R

VV gene is also a promising strategy. The D10 protein is expressed after DNA replication and

removes the 5‘ cap in VV mRNAs, expediting the degradation of these viral nucleotides and

reducing chances of viral RNA recognition by PRRs. Its deletion was associated with decreased

replication in normal tissues after IP injection into Balb/c mice (Liu et al., 2014). On the other

hand, it would also be interesting to evaluate VVs with a combination of gene deletions. The

deletions may work synergistically to generate an even safer virus, while retaining potency,

similar to how the combination of a TK and VGF deletion resulted in a more tumor-selective

virus, vvDD, relative to the TK- and VGF- viruses (McCart et al., 2001).

124

4.5. Final Remarks

Oncolytic virotherapy is a promising and rapidly developing anti-cancer treatment. Its multi-

mechanistic attack against cancer and broad tumor tropism make oncolytic VVs an appealing

option. As our understanding of cancer, the immune system and virology advance, new

strategies will arise to develop and fine tune oncolytic viruses to treat several malignancies. In

this project, we have combined the current knowledge of cancer immunology with the

understanding of VV immunomodulatory proteins, to design a panel of promising oncolytic

VVs. Concurrently, we have shown, as other research groups have, that exploiting the cancer

defects in antiviral immunity is a viable strategy for engineering a mechanism of tumor-

specificity for VV. More importantly, we have shown that this strategy can yield OVs with

similar or improved therapeutic efficacy than the current oncolytic VV, vvDD. As a result, we

have generated promising oncolytic VVs that have potential to be used in the clinic.

125

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