A Combination of Molecular and Traditional Chemotherapy: Prospects of Synergies Against Cancer

A COMBINATION OF MOLECULAR AND TRADITIONAL CHEMOTHERAPY: PROSPECTS OF SYNERGIES AGAINST CANCER

Preetinder Pal Singh

A Thesis for the Degree of Doctor of Philosophy

Faculty of Medicine

University of New South Wales

Oncology Research Centre

Prince of Wales Clinical School

August, 2009

ORIGINALITY STATEMENT

I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis.

I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.’

Signed ………………………………………

Date:

ABSTRACT

In this study, we have explored the combination of a novel Purine Nucleoside

Phosphorylase mediated Gene Directed Enzyme Prodrug Therapy (PNP-GDEPT) with chemotherapeutics, Taxotere and/or Carboplatin to target prostate and ovarian cancer (PC

& OC). PNP converts the prodrug (Fludarabine-phosphate) to a toxic purine, 2- fluoroadenine (2FA) that inhibits RNA/DNA synthesis. Taxotere is active against late- stage PC whilst carboplatin is first line therapy for OC. Neither modality is adequately effective. We expect that a combination will target heterogeneity via cytotoxicity to diverse cancer cell populations leading to effective synergies, which may improve efficacy and quality of life. For PC, Synergy between Ad-PNP-GDEPT and Taxotere were assessed in vitro and in vivo. Cell killing effects of combination led to significant synergistic killing of human PC-3 & murine RM1 PC cells accompanied by enhanced apoptosis. A lower individual dose (by up to 8 fold) led to enhanced efficacy. In vivo, the combination regimen given at the suboptimal doses led to reduction in local tumour (PC-

3 & RM1) growth in nude and in C57BL/6 mice, respectively. A significant reduction in lung RM1 colony numbers indicated enhanced systemic efficacy. Combination treated mice also displayed significantly improved survival (25 days vs 15 days for control mice).

Importantly, the condition of combination treated mice (e.g. weight loss) was better than those given individual treatments. The possible involvement of the immune system in this enhanced effect is under investigation. For OC, three-way synergy between Ad-PNP-

GDEPT, Taxotere and carboplatin was effectively demonstrated in SKOV-3 and

OVCAR-3 cells. This was significantly greater than bimodal or individual treatments. A

10-50 fold dose reduction of individual treatments was effective when combined,

4 accompanied by enhanced apoptosis. Western-blotting analyses revealed a shift in the expression of anti-apoptotic and proapoptotic proteins upon treatment with various combinations. This is the first demonstration of synergy between these modalities.

ACKNOWLEDGEMENTS

A research project of this scope is only possible by the support and kindness of colleagues, mentors and friends and family. I dedicate this work to my parents, Surjeet Singh Grewal and Mrs. Balwant Kaur, whose prayers and hopes have been realized.

I have had the good fortune to be ably guided by my supervisor, Dr Aparajita Khatri. She has inspired me to venture into uncharted territory, to attempt the improbable and to discover reserves of endurance that I was hitherto unaware of. Thank you for your faith in my ability. I salute your enthusiasm and scientific expertise.

My co-supervisor, Prof Pamela J Russell, has been a steadfast supporter of my work. She arranged and ensured the maintenance of my scholarship from the Sydney Foundation for

Medical Research without which I would have had to abandon my work. You have been kind and understanding on innumerable occasions.

For providing me a home away from home, I am forever indebted to Jagmohan Kisana and Yadwinder Kaur. Thank you very much for your un-stinting support and encouragement during the course of this study. My friends Varinder Jeet and Hafeez

Khalid have been more than helping hands in and out of the lab. It has also been a pleasure to spend time with Brain Tse and to share the daily rituals of our lab work.

Brian, no doubt you are more than a friend, I’ll miss those Friday evening nibbles shared with you, Julie and Mila.

Swapna Joshi has generously helped with the in vivo/protein work and accommodated me with a warm and cheerful spirit. I must thank Mila too for her support with the animal studies.

For the immunohistochemistry related work, I would have been lost without the experience and kindness of Kim Ow.

I wish to express my cordial appreciation to Dr Sham Nair from Macquarie University for his valuable time and suggestions regarding proteomics analysis.

I would also like to acknowledge the tremendous support from Dr. Leif Lindholm and Dr.

Maria Magnusson (Gothenburg University, Sweden) for their help in the construction of

Her-2 neu targeted viruses.

I am greatly indebted to Dr. Viola from Royal Women’s hospital for providing me some very important clinical samples. Although the work couldn’t progress any further but ‘the kindness’ is greatly appreciated.

I have learned much from discussions with Dr. Carl Power. Thank you for sharing your experience and insights. Three wonderful ladies who have impressed me with their organizational skills are Sheri, Liz and Alex. Thank you so much for being there.

I would also like to acknowledge the other members of Oncology Research centre for providing me a very nice and warm environment away from my home land Punjab, India.

My sanity was greatly preserved by a vast social circle and active participation in Punjabi

Cultural Shows (both in Sydney and Melbourne). My friends Gurpreet, Ranjit Khera,

Charnamat Singh and Rajwant Singh have provided nourishment for my soul and enabled me to return to the lab with renewed vigour. You all have a share in my success.

Two special people that I must fondly mention here are my bother, Tejwinder and sister,

Teji whose affection reminds me that there is more to life than research.

Finally, and most importantly, I would like to thank the almighty God , for his provisions of joys, challenges, and grace for growth.

“Dream is not what you see in sleep, but is the thing which does not let you sleep” By Dr. A. P. J. Abdul Kalam, the eleventh President of India, Popularly known as the "People's President"

PUBLICATIONS

At present I am in process of submitting three research papers and two review papers.

Research papers

Conventional plus molecular chemotherapy for treating prostate cancer: the

promise of enzyme-prodrug therapy in combination with docetaxel

(to be submitted in Clinical Cancer Research)

Combining therapies for the treatment of ovarian cancer (to be submitted in

Molecular Therapy)

Developing trancriptionally and transductionally targeted adenoviruses for the

treatment of cancer (manuscript in preparation)

Review Paper

Molecular and traditional chemotherapy: a united front against prostate cancer

(Review: accepted for publication in Cancer Letters)

Combination of molecular and traditional chemotherapy for the treatment of

ovarian cancer

CONFERENCE PRESENTATIONS/PRIZES

2009 Australian Society for Gene Therapy (ASGT) Conference, Royal Prince Alfred Auditorium, Sydney-Australia (Oral) A combination of molecular chemotherapy and traditional chemotherapy: prospects of synergies against cancer http://www.agts.org.au/conference/AGTS_Programme_2009.pdf

2008 American Society of Gene Therapy (ASGT) Conference, Boston, Massachusettes, USA (Poster) Khatri A, Singh P, Husaini Y, Ow K, Chapman J, Russell PJ: Prospects of combination of gene directed enzyme prodrug therapy with other systemic therapies in treatment of prostate cancer; ASGT Meeting Abstracts 2008: 166 http://www.asgt.org/am08/program/final_program.pdf

2007 AACR Annual Meeting in Los Angeles, California, USA (Poster) Singh P, Russell PJ, Magnusson M, Lindholm L and Khatri A: Docetaxel and purine nucleoside phosphorylase-enzyme-prodrug therapy act synergistically against ovarian cancer cells; AACR Meeting Abstracts 2007: 3334. http://aacrmeetingabstracts.org/content/vol2007/1_Annual_Meeting/index.dtl

2007 International Cancer Conference, Lorne, Victoria, Australia (Poster) Singh P, Russell PJ and Khatri A: Conventional plus molecular chemotherapy for treating ovarian cancer: the promise of enzyme-prodrug therapy in combination with Docetaxel. http://www.lornecancer.org

2006 Merck Sharp and Dohme (Aus) Research Student Poster Award : UNSW Faculty of Medicine Research Day, Sydney, Australia (WINNER - 1st PRIZE) Singh P, Russell PJ and Khatri A: Combination of Conventional and Molecular Chemotherapy Using Adenoviral Delivery of Enzyme-Prodrug Therapy for the Treatment of Ovarian Cancer http://www.med.unsw.edu.au/

FINANCIAL SUPPORT

The PhD studentship was provided by Sydney Foundation for Medical Research,

Sydney Australia.

The project was supported primarily by the funding acquired from Prince of Wales

Hospital (SESAHS), Randwick-Sydney, Australia.

Additional support was received from an NHMRC Project Grant [ID-510238 (2008-

2010)] “Combined novel tumour-targeted molecular and traditional chemotherapy

for treating androgen refractory prostate cancer.”

TABLE OF CONTENTS

A COMBINATION OF MOLECULAR AND TRADITIONAL CHEMOTHERAPY: PROSPECTS OF SYNERGIES AGAINST CANCER...... 1 ORIGINALITY STATEMENT...... 2 ABSTRACT...... 3 ACKNOWLEDGEMENTS...... 5 PUBLICATIONS...... 8 CONFERENCE PRESENTATIONS/PRIZES...... 9 FINANCIAL SUPPORT ...... 10 TABLE OF CONTENTS...... 11 LIST OF FIGURES AND TABLES...... 12 ABBREVIATIONS ...... 22

LIST OF FIGURES AND TABLES

CHAPTER 1: INTRODUCTION

Figure 1.1: Processes involved in development of cancer

Figure 1.2: Historical timeline of OC chemotherapy and outcomes

Figure 1.3: Docetaxel: primary mode of action

Figure 1.4: Docetaxel (Taxotere) and cancer

Figure 1.5: Mechanism of carboplatin action

Figure 1.6: Vectors used in cancer gene therapy clinical trials

Figure 1.7: Cell-entry pathway of the adenoviral vector

Figure 1.8: PNP-GDEPT: mode of action

Figure 1.9: Gene therapy approaches for PC treatment

Table 1.1: Chemotherapeutic agents with activity against Ovarian Cancer

Table 1.2: Advantages and disadvantages of different gene delivery vectors

Table 1.3: Types of adenoviral vectors

Table 1.4: Clinical trials for ovarian cancer gene therapy

Table 1.5: GDEPT and cancer

Table 1.6: PNP-GDEPT and cancer

Table 1.7: List of promoters used in ovarian cancer gene therapy

Table 1.8: Combination of Ad mediated-gene therapy and chemotherapy and ovarian

cancer

Table 1.9: Docetaxel alone or in combination chemotherapy regimens for HRPC

Table 1.10: Other drugs/therapeutic agents used in combination with docetaxel for the

treatment of prostate cancer

Table 1.11: List of promoters/enhancers used in PC gene therapy

CHAPTER 2: MATERIALS AND METHODS

Figure 2.1: Flowchart showing construction and characterization of Recombinant

Adenoviral vector

Figure 2.2: A schematic overview of the production of recombinant Ad

Figure 2.3: Rescue of recombinant Ad with the elements of interest in HEK 293A

cells

Table 2.1: Buffers and solutions used in DNA based molecular techniques

Table 2.2: PCR conditions

Table 2.3: Reagents and their amounts used in a PCR cycle

Table 2.4: Bacterial strains

Table 2.5: Media and solutions for bacterial culture

Table 2.6: Reagents for protein analysis

Table 2.7: Reagents used in routine maintenance and culturing of mammalian cell

lines

Table 2.8: Mammalian cell lines and culture conditions

Table 2.9: List of reagents and cytotoxic drugs used

Table 2.10: Detailed information about cytotoxic drugs used in this study

Table 2.11: Recommended symbols for describing synergism, additivity or

antagonism in drug combination studies analyzed with the Combination

Index (CI) Method

Table 2.12: Materials and methods used in animal studies

CHAPTER 3: PROSPECTS OF COMBINING CONVENTIONAL AND MOLECULAR CHEMOTHERAPY FOR THE TREATMENT OF OVARIAN CANCER

Figure 3.1: Cell growth curves for different ovarian cancer cell lines

Figure 3.2: Docetaxel dose response curves of OC cell lines

Figure 3.3: Carboplatin dose response curves of OC cell lines

Figure 3.4: Transduction of OC cell lines with Ad/CMV/GFP

Figure 3.5: Evaluation of bystander effects associated with PNP-GDEPT in OC cells

Figure 3.6: Clonogenic assay for OVCAR-3 cells given different treatments

Figure 3.7: Evaluation of cell growth inhibitory effects of combination of Taxotere

and carboplatin

Figure 3.8: Analysis of combined drug effects of Taxotere and carboplatin

Figure 3.9: Evaluation of cell growth inhibitory effects of combination of PNP-

GDEPT and Taxotere

Figure 3.10: Analysis of combined drug effects of Taxotere and PNP-GDEPT

Figure 3.11: Evaluation of cell growth inhibitory effects of combination of carboplatin

and PNP-GDEPT

Figure 3.12: Analysis of combined drug effects of carboplatin and PNP-GDEPT

Figure 3.13: Evaluation of cell growth inhibition by combination of Taxotere,

carboplatin and PNP-GDEPT

Figure 3.14: Analysis of combined drug effects of Taxotere, carboplatin and PNP-

GDEPT

Table 3.1: Optimal Plating densities for different OC cell lines

Table 3.2: Taxotere (nM) needed to kill 50% of ovarian cancer cell populations (IC50

values)

Table 3.3: Carboplatin (M) required to kill 50% of OVCAR-3 and SKOV-3 cell

populations (IC50 values)

Table 3.5: IC50 values of PNP-GDEPT in different OC cell lines

Table 3.6: Design of a combination therapy experiments

Table 3.7: Combined effects of Taxotere and carboplatin in OC cells (drugs added as

constant ratio of 1:1)

Table 3.8: Combined effects of Taxotere and PNP-GDEPT in OC cells (drugs added

as constant ratio of 1:1)

Table 3.9: Combined effects of carboplatin and PNP-GDEPT in OC cells (drugs dded

as constant ratio of 1:1)

Table 3.10: Combined effects of Taxotere + carboplatin and PNP-GDEPT in OC cells

(drugs added as constant ratio of 1:1)

Table 3.11: A comparative account of four different drug combination effects in OC

cells (ratio: 1:1)

Table 3.12: Properties of OC cell lines used in this study

CHAPTER 4: MECHANISM STUDIES FOR OC COMBINATION THERAPY

Figure 4.1: Apoptotic pathways in cancer: a general view

Figure 4.2: Quantitative estimation of Apoptosis in OC cells given different

treatments (M30 CytoDEATH assay)

Figure 4.3: Cell cycle analysis in ovarian cancer cells given different treatments

Figure 4.4: Shotgun proteomics to evaluate PNP-GDEPT inducted effects in treated

OVCAR-3 cells

Figure 4.5: A normalised plot showing log2 transformations of PNP-GDEPT treated

vs. un-treated data points

Figure 4.6: Evaluation of treatment related effects on BCL-2 expression in OVCAR-3

cells

Figure 4.7: Evaluation of treatment related effects on survivin expression in OVCAR-

3 cells

Figure 4.8: Evaluation of treatment related effects on BAX expression in OVCAR-3

cells

Figure 4.9: Evaluation of treatment related effects on Bik expression in OVCAR-3

cells

Figure 4.10: Evaluation of treatment related effects on Bok expression in OVCAR-3

cells

Figure 4.11: Evaluation of treatment related effects on caspase-7 expression in

OVCAR-3 cells

Figure 4.12: Evaluation of treatment related effects on caspase-9 expression in

OVCAR-3 cells

Figure 4.13: Evaluation of treatment related effects on PARP expression in OVCAR-3

cells

Figure 4.14: A model outlining how desmosomes could contribute to tumorigenesis

Table 4.1: Quantitative estimation of apoptosis in SKOV-3 cells in response to

different treatments

Table 4.2: List of proteins that were significantly down regulated in PNP-GDEPT

treated samples and their role in cancer

Table 4.3: List of proteins that were significantly up regulated in PNP-GDEPT

treated samples and their role in cancer

Table 4.4: Summary of treatment related effects on different pro and anti-apoptotic

proteins (western blot analysis)

Table 4.5: List of selected genes/proteins used for western blot analysis based on

their role in OC progression and treatment

CHAPTER 5: PROSPECTS OF COMBINING CONVENTIONAL AND MOLECULAR CHEMOTHERAPY FOR TREATMENT OF PROSTATE CANCER

Figure 5.1: Cell growth curves for prostate cancer cell lines

Figure 5.2: Response of PC cells to Taxotere treatment

Figure 5.3: Evaluation of Ad-transduction in cancer cell lines

Figure 5.4: Response of PC cells to Fludara treatment

Figure 5.5: Evaluation of bystander effects associated with PNP-GDEPT in PC cells

Figure 5.6: Clonogenic assay for PC-3 cells given different treatments

Figure 5.7: Evaluation of cell growth inhibition by the combination of PNP-GDEPT

and Taxotere in PC cells

Figure 5.8: Analysis of combined drug effects of Taxotere and PNP-GDEPT in PC

cells

Figure 5.9: Quantitative estimation of apoptosis in response to different treatments

Figure 5.10: Evaluation of efficiency of Ad-transduction in PC-3M-luc-C6 cells

Figure 5.11: In vitro bioluminescence in PC-3M-luc-C6 cells

Figure 5.12: The experimental plan for evaluation of different therapies in PC-3M-luc-

C6 tumour bearing BALB/c nude mice

Figure 5.13: The effects of combination therapy on s.c. PC-3M-luc-C6 tumours in

BALB/c nude mice

Figure 5.14: Relative body weight changes in treated and un-treated PC-3M-Luc

tumour bearing BALB/c nude mice

Figure 5.15: Effects of different doses of PNP-GDEPT on RM1 tumours growing in the

prostate or in the lungs in C57BL/6 mice:

Figure 5.16: Effects of different doses of Taxotere on RM1 tumours growing in the

prostate or in the lungs in C57BL/6 mice

Figure 5.17: Experimental plan for Taxotere and PNP-GDEPT combination therapy in

C57BL/6 animal (RM1 model)

Figure 5.18: Effects of combination of PNP-GDEPT and Taxotere treatments on RM1

tumour growth in C57Bl/6 mice

Figure 5.19: Toxicity analysis in mice treated with Taxotere/PNP-GDEPT either alone

or in combination

Figure 5.20: The relative body weight changes in treated and un-treated RM1 tumour

bearing C57BL/6 mice

Figure 5.21: Survival of RM1 tumour bearing C57Bl/6 mice given different treatments

Figure 5.22: Effects of different treatments on tumour infiltration by immune cells and

apoptosis in intraprostatic RM1 tumours

Table 5.1: Optimal plating densities for different PC cell lines

Table 5.2: Taxotere (nM) needed to kill 50% of PC-3 and RM1 cell populations (IC50

values)

Table 5.3: IC50 values of PNP-GDEPT in two different PC cell lines

Table 5.4: A comparison between efficacies of drug combinations at different ratios

in PC cells

Table 5.5: Quantitative estimation of apoptosis in PC-3 cells in response to different

treatments.

Table 5.6: Permissivity of PC-3M-luc-C6 cell for Ad infections

Table 5.7: Effects of treatments on growth of sc PC-3M-luc-C6 tumours in BALB/c

nude mice (Mean Tumour Bioluminescence (MTB)

Table 5.8: Effects of treatments on growth of s.c PC-3M-luc-C6 tumours in BALB/c

nude mice (Mean Tumour Volume (MTV)

Table 5.9: Serum analysis for biochemical markers of kidney and liver function in

treated vs. untreated mice

Table 5.10: Immunohistochemical analyses of RM1 prostate tumour sections showing

effects of different treatments on tumour infiltration by immune cells and

apoptosis

CHAPTER 6: TRANSCRIPTIONAL AND TRANSDUCTIONAL TARGETING OF ADENOVIRUS MEDIATED PNP-GDEPT

Figure 6.1: Key strategies to achieve targeted gene expression from Ad vectors

Figure 6.2: Multiple aspects of Her-2/neu in cancer: key features and therapeutic

approaches

Figure 6.3: The structural features of Her-2/neu targeted Ad.ZZ vector

Figure 6.4: Multiples roles of survivin

Figure 6.5: HER-2/neu expression in OC cell lines

Figure 6.6: Evaluation of Ad.ZZ.GFP transduction in different cell lines

Figure 6.7: Evaluation of Ad.ZZ.GFP transduction in cancer cell lines

Figure 6.8: Evaluation of effects of different doses of Ad.ZZ.GFP on Her-2 positive

and negative cell lines

Figure 6.9: Expression of Ad.ZZ.GFP is Her-2/neu specific in OC cells

Figure 6.10: A Schematic representation for the development of

pSc.BGH.MUC1.HER-2.Luc

Figure 6.11: Evaluation of Her-2/neu promoter activity in pGL3.BGH.Her-2.Luc

transfected Her-2 positive and negative cell lines

Figure 6.12: Evaluation of Her-2/neu transcriptional activity of Ad.BGH.MUC1.Her-

2.Luc in OC cells

Figure 6.13: A schematic representation for the development of pSc.BGH.survivin.Luc

Figure 6.14: Evaluation of tumour specificity of Ad.BGH.Survivin.Luc in different cell

lines

Table 6.1: Evaluation of Her- 2 neu promoter activities in pGL3.BGH.Her-2.Luc

transfected SKOV-3 and MCF-7 cells

Table 6.2: Fold changes in Her-2/neu promoter activity in pGL3.BGH.Her-2.Luc

transfected cells in comparison to control plasmid (pGL3) transfected cells

Table 6.3: Evaluation of Her- 2 neu promoter activity in Ad.BGH.MUC1.Her-2.Luc

infected SKOV-3 and MCF-7 cells

Table 6.4: Comparison of Ad.BGH.Survivin.Luc and Ad.CMV.Luc activities in OC

and PC cell lines

ABBREVIATIONS

g microgram l microliter M micromole per litre/micromolar Ad3 adenovirus serotype 3 Ad5 adenovirus serotype 5 ADP adenoviral death protein AFP -fetoprotein ALP alkaline phosphatise ALT alanine aminotransferase Amp ampicillin AR androgen receptor ATCC american type culture collection BCA bicinchoninic Acid Assay BGH bovine growth hormone bp base pair BPH benign prostate hyperplasia CAR coxsackie-adenovirus receptor Car carboplatin CD cytosine deaminase cDNA complementary DNA cGMP current good manufacturing practice CI combination index cm centimetre CMV cytomegalovirus (promoter) cox-2 cyclooxygenase-2

CO2 carbon-dioxide CR2 constant region 2 CRAd conditionally replicating adenovirus

CRPC castration-resistant prostate cancer CsCl cesium chloride CSIRO commonwealth scientific and industrial research organisation C-terminal carboxy-terminal CTL cytotoxic T-lymphocyte DAB diaminobenzidine DHT dihydrotestosterone DMEM dulbecco’s modified eagle medium DNA deoxyribonucleic Acid ECL enhanced chemiluminescence E.coli escherichia coli EDTA ethylenediamine tetra-acetic acid EGF epidermal growth factor EGFR epidermal growth factor receptor FACS fluorescence activated cell sorting F-ara-A 9--D-arabinosyl-2-fluoroadenine FC flourocytosine FCS foetal calf serum FDA food and drug administration FGF2 basic fibroblast growth factor FITC fluorescein isothiocyanate Fludara fludarabine phosphate FU flourouracil g gram GCV ganciclovir GDEPT gene directed enzyme pro-drug therapy GFP green fluorescent protein GPAT genetic pro-drug activation therapy GM growth medium

H2O water hCEA human carcinoembryogenic antigen Her-2 human epidermal growth factor-2

H&E hematoxylin-eosin h hour/s HRP horse radish per-oxidase HRPC human refractory prostate cancer HSG heparan sulfate glycosaminoglycan HSV-TK herpes simples virus type I thymidine kinase hTERT human telomerase reverse transcriptase IC25 inhibitory concentration killing 25% cells IC50 inhibitory concentration killing 50% cells IC75 inhibitory concentration killing 75% cells IFN interferon IHC immunohistochemistry Ig immunoglobulin i.p. intraperitoneal iprost intraprostatic i.v. intravenous Kan kanamycin kb kilobase kD kiloDalton LA luria agar LB luria broth L region late region LTR long tendem repeats luc firefly luciferase M mole/l mA milliampere MeP-dR 9-(2-deoxy--D-ribofuranosyl)-6-methylpurine mg milligram MHC I major histocompatibility complex I min minute mL millileter moi multiplicity of infection

25 mRNA messenger RNA MS mass spectrometry mTOR mammalian target of rapamycin n Number nM nanomolar nW nanowatt OC ovarian cancer Oligo oligonucleotides O/N overnight ORF open reading frame P (value) probability PAGE poly acrylamide gel electrophoresis PBS phosphate-buffered saline PC prostate cancer PCR polymerase chain reaction Pen-Strep pencillin-streptomycin PDGF platelet derived growth factor pfu plaque forming unit PKR protein kinase R PNP purine nucleoside phosphorylase Poly 80 polysorbate 80 PSA prostate specific antigen Rb retinoblastoma RGD(-4C) arginine-glycine-aspartic acid RLU relative light units RPMI roswell park memorial institute RSV rous sarcoma virus RT room temperature RT-PCR reverse transcriptase-polymearse chain reaction s.c subcutaneous SD standard deviation SDS sodium dodecyl sulphate

SLPI secretory leukoprotease inhibitor TAE tris acetate buffer Tax taxotere TB terrific broth TE tris-EDTA TEMED tetramethylethylenediamine TGA therapeutic goods administration TNF tumour necrosis factor TSP tumor/tissue specific promoter UTR untranslated region VEGF vascular endothelial growth factor Vp/ml viral particle/millilitre

Table of Contents 1

LITERATURE REVIEW ...... 8 1.1 Ovarian Cancer: treatment related issues...... 9 1.2 Combination regimens involving conventional treatment ...... 13 1.2.1 Surgery and chemotherapy...... 13 1.2.2 Radiation therapy, surgery and chemotherapy...... 14 1.3 Chemotherapy; the mainstay treatment for ovarian cancer...... 14 1.3.1 Docetaxel and OC ...... 22 1.3.1.1 Docetaxel: mode of action ...... 23 1.3.1.2 Docetaxel as monotherapy ...... 25 1.3.1.3 Docetaxel in combination with other modalities ...... 25 1.3.2 Carboplatin (CP) and OC...... 27 1.3.2.1 Carboplatin: mode of action...... 27 1.3.2.2 Carboplatin in combination with other modalities...... 29 1.3.2.2.1 Combining Carboplatin with taxanes...... 30 1.4 Gene therapy and ovarian cancer ...... 31 1.4.1 Gene transfer systems ...... 33 1.4.1.1 Viral vectors...... 33 1.4.1.1.1 Adenoviral vectors ...... 36 1.4.1.1.1.1 Potential advantages and disadvantages of Ad vectors...... 37 1.4.1.1.1.2 Tropism ...... 38 1.4.2 Gene therapy approaches ...... 42 1.4.2.1 Mutation compensation/Gene Substitutions ...... 46 1.4.2.1.1 Reactivation of Tumour Suppressor Gene (TSG)...... 46 1.4.2.1.2 Inactivation of oncogenes ...... 47 1.4.2.2 Molecular chemotherapy...... 48 1.4.2.2.1 GDEPT and ovarian cancer...... 49 1.4.2.2.2 PNP-GDEPT and OC...... 53 1.4.2.2.3 GDEPT and chemotherapy ...... 54 1.4.2.3 Conditionally replicating adenovirues ...... 62 1.4.2.3.1 Oncolytic adenoviruses armed with gene therapy ...... 63 1.4.2.4 Transductional targeting...... 68 1.4.2.5 Transcriptional targeting ...... 69 1.5 Prostate cancer (PC): treatment related issues ...... 73

Table of Contents 2

1.6 Role of chemotherapy in treating hormone refractory prostate cancer (HRPC)...... 74 1.6.1 Docetaxel: mode of action in PC ...... 75 1.6.2 Docetaxel as a monotherapy for HRPC ...... 76 1.6.3 Docetaxel in combination with other therapies...... 79 1.6.4 Docetaxel in combination regimens agsinst PC: Phase III trials ...... 82 1.7 Gene therapy and prostate cancer ...... 84 1.7.1 Tackling prostate cancer heterogeneity or ‘robustness’...... 84 1.7.2 Potential for prostate cancer gene therapy ...... 85 1.7.3 Gene therapy in combination regimens and PC...... 85 1.7.4 Sites of PC gene delivery ...... 86 1.7.4.1 Gene delivery systems ...... 87 1.7.5 PC as a molecular target...... 88 1.7.6 Gene therapy approaches for the treatment of prostate cancer ...... 88 1.7.6.1 Mutation compensation gene therapy ...... 90 1.7.6.2 Gene Directed Enzyme Pro-drug Therapy (GDEPT) and PC...... 91 1.7.6.2.1 Herpes Simplex Virus -thymidine kinase (HSV-tk) and prodrugs ...... 91 1.7.6.2.2 Cytosine deaminase (CD) and 5-fluorocytosine ...... 93 1.7.6.2.3 Purine nucleoside phosphorylase (PNP) and prodrugs ...... 93 1.7.6.2.4 Other GDEPT systems ...... 95 1.7.6.3 Virotherapy (oncolytic viral vectors)...... 95 1.7.6.3.1 Oncolytic Adenoviruses and radiation therapy...... 96 1.7.6.3.2 Oncolytic Adenoviruses and chemotherapy...... 97 1.7.6.4 Genetic immunotherapy...... 98 1.7.6.5 Anti-angiogenesis therapy...... 98 1.7.6.6 Transcriptional targeting ...... 100 Aims of the study ...... 105 Hypothesis...... 108 Specific Aims of Thesis: ...... 108 OC Studies ...... 108 PC Studies ...... 108 Transcriptional and transductional targeting of gene-therapy vectors...... 109

Table of Contents 3

MATERIALS AND METHODS...... 110 2.1 Molecular Biology Techniques...... 111 2.1.1 DNA based molecular methods ...... 111 2.1.1.1 Polymerase Chain Reaction (PCR) amplification of DNA sequences...... 114 2.1.1.2 Plasmid preparation (Mini-prep)...... 115 2.1.1.3 Maxi-prep plasmid preparation...... 115 2.1.1.4 Restriction digestion...... 116 2.1.1.5 Agarose gel electrophoresis ...... 117 2.1.1.6 Purification of DNA fragments...... 117 2.1.1.7 Spectrophotometry ...... 119 2.1.1.8 Molecular techniques involving use of bacteria...... 119 2.1.1.8.1 Bacterial strains and reagents...... 119 2.1.1.8 Ligation reactions...... 121 2.1.1.9 Preparation of competent cells...... 122 2.1.1.10 Transformation of competent cells...... 122 2.1.1.11 Preparation of glycerol stocks...... 123 2.1.2 Molecular techniques for protein based analyses...... 124 2.1.2.1 Whole cell protein extraction...... 124 2.1.2.2 Protein quantitation using BCA assay ...... 124 2.1.2.1 Whole cell protein extraction...... 127 2.1.2.2 Protein quantitation using BCA assay ...... 127 2.1.2.3 Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) ...... 128 2.1.2.4 Western blot analysis ...... 129 2.1.2.5 Coomassie staining ...... 130 2.1.2.6 Mass spectrometry ...... 130 2.1.2.7 Protein identification after mass spectrometry...... 132 2.2 Mammalian Cell Culture...... 132 2.2.1 Maintenance of mammalian cell lines...... 132 2.2.2 Cryopreservation of mammalian cell lines ...... 136 2.2.3 Determination of cell viability using trypan blue dye exclusion test...... 136 2.2.4 Mammalian Cell Based Assays...... 137 2.2.4.1 Transduction of cells with plasmids/Adenoviral vectors...... 137

Table of Contents 4

2.2.4.2 Cell viability assays ...... 138 2.2.4.2.1 WST-1 based cell viability assay ...... 141 2.2.4.2.2. Clonogenic assays to assess cell cytotoxicity ...... 141 2.2.4.3 Evaluation of synergy between drugs and PNP-GDEPT...... 142 2.2.4.4 Evaluation of therapeutic interactions...... 142 2.2.4.5 M30 CytoDEATHTM Apoptosis assay...... 146 2.2.4.6 Cell-cycle analysis ...... 146 2.3 Therapeutic Effects in vivo...... 147 2.3.1 Evaluation of synergy between Taxotere and PNP-GDEPT in BALB/c nude mice...... 148 2.3.2 Bioluminescencent imaging of PC-3M-luc-C6 cells or tumours in mice...... 149 2.3.3 Evaluation of synergy between Taxotere and GDEPT in C57BL/6 mice ...... 149 2.3.4 Toxicity analysis ...... 151 2.4 Immunohistochemical Analysis...... 152 2.4.1 Evaluation of expression of HER-2/neu in OC cell lines ...... 152 2.4.2 Immunohistochemical (IHC) analysis of orthotopic prostate tumours...... 153 2.5 Construction and Characterization of Recombinant Ad Vectors...... 154 2.5.1 Overview of AdEasy system...... 156 2.5.2 Vectors used for new recombinant Adenoviral vectors ...... 158 2.5.3 Biosafety ...... 159 2.5.4 Construction of pShuttle vector with gene of interest...... 159 2.5.5 Generation of recombinant Ad plasmid with gene of interest ...... 160 2.5.5.1 Electroporation in BJ5183 bacterial cells ...... 160 2.5.5.2 Miniprep and restriction digestion confirmation of Ad plasmids ...... 160 2.5.5.3 Large-scale production of recombinant Ad plasmid in DH10B cells...... 161 2.5.6 Rescue of recombinant Adenovirus ...... 161 2.5.7 Production and purification of high titer Ad viruses...... 164 2.5.7.1 CsCl density banding ...... 164 2.5.7.2 Nap 25-column chromatography...... 165 2.5.8 Characterisation and titration of recombinant Adenoviruses...... 165 2.5.8.1 Physical viral particle number (VP) method...... 166 2.5.8.2 Infectious viral titre using traditional plaque assay...... 166 2.6 Statistical Analysis...... 167

Table of Contents 5

PROSPECTS OF COMBINING CONVENTIONAL AND MOLECULAR CHEMOTHERAPY FOR THE TREATMENT OF OVARIAN CANCER ...... 168 3.1 Introduction...... 169 3.2 Results...... 173 3.2.1 Optimisation of cell plating densities for dose response studies...... 173 3.2.2 Effects of Taxotere treatment on OC cell lines...... 175 3.2.3 Effects of Carboplatin treatment on OC cell lines ...... 178 3.2.4 Efficiency of Ad-transduction in different OC cell lines...... 180 3.2.5 Bystander effects of PNP-GDEPT correlate with the efficiency of gene transduction...... 182 3.2.5 Bystander effects of PNP-GDEPT correlate with the efficiency of gene transduction...... 182 3.2.6 PNP-GDEPT, Taxotere and Carboplatin act synergistically in OC cells in vitro ...... 185 3.2.6.1 Clonogenic assay...... 186 3.2.6.2 Evaluation of cell growth inhibition in cells given combination treatment ...... 188 3.2.6.2.1 Combined effects of Taxotere and carboplatin ...... 191 3.2.6.2.2 Combined effects of PNP-GDEPT and Taxotere...... 195 3.2.6.2.3 Combined effects of PNP-GDEPT and carboplatin...... 199 3.2.6.2.4 Combined effects of PNP-GDEPT, carboplatin and Taxotere...... 202 3.3 Discussion ...... 208

PNP-GDEPT, TAXOTERE AND CARBOPLATIN IN COMBINATION AGAINST OVARIAN CANCER: ROLE OF APOPTOSIS ...... 217 4.1 Introduction...... 218 4.2 Results...... 222 4.2.1 Evaluation of early apoptosis in OC cells after different treatments ...... 223 4.2.2 Effects of different treatments on cell cycle in treated cells ...... 226 4.2.3 Proteomic studies using PNP-GDEPT treated OVCAR-3 cells ...... 228 4.2.5 Treatment related effects on pro- and anti-apoptotic proteins ...... 241 4.3 Discussion ...... 253

Table of Contents 6

PROSPECTS OF COMBINING CONVENTIONAL AND MOLECULAR CHEMOTHERAPY FOR THE TREATMENT OF PROSTATE CANCER ...... 267 5.1 Introduction...... 268 5.2 Results...... 272 5.2.1 Optimisation of cell plating densities for dose response studies...... 272 5.2.2 Effects of Taxotere treatment on PC cell lines...... 274 5.2.3 Efficiency of Ad-transduction in two different PC cell lines...... 276 5.2.5 Bystander effects of PNP-GDEPT correlate with the efficiency of gene transduction...... 280 5.2.6 PNP-GDEPT and Taxotere act synergistically in PC cells in vitro ...... 282 5.2.6.1 Clonogenic assay...... 282 5.2.7 Effects of different treatments on Apoptosis ...... 290 5.2.8 Effects of PNP-GDEPT and/or Taxotere treatments on growth of subcutaneous PC-3M-luc-C6 tumours in nude mice...... 293 5.2.8.1 Evaluation of permissivity of PC-3M-luc-C6 cells to Ad transduction....293 5.2.8.1.2 Evaluation of bioluminescence in PC-3M-luc-C6 (in vitro)...... 295 5.2.8.1.3 Evaluation of therapeutic effects of Taxotere and/or PNP-GDEPT on s.c PC-3M-luc-C6 tumour growth ...... 297 5.2.9 Effects of PNP-GDEPT on RM1 tumour growth in immunocompetent C57BL/6 mice...... 305 5.2.10. Effects of Taxotere alone on RM1 tumour growth in vivo ...... 308 5.2.11 Effects of combination therapy on RM1 tumour growth in vivo ...... 311 5.2.12 Analysis of treatment related toxicity in C57BL/6 mice (RM1 model) ...... 316 5.2.13 Impact of combination therapy on animal survival...... 321 5.2.14 Immunohistochemical analysis of apoptosis and immune infiltration of RM1 tumours...... 323 5.3 Discussion ...... 326

Table of Contents 7

TRANSCRIPTIONAL AND TRANSDUCTIONAL TARGETING OF ADENOVIRAL VECTORS ...... 335 Why Her-2/neu based targeting?...... 338 Why Survivin based Targeting?...... 343 6.2 Results...... 346 6.2.1 Her-2/neu expression in OC cell lines ...... 346 6.2.2 Evaluation of tumour-specificity of transductionally targeted Her-2/neu Adenovirus (Ad.ZZ)...... 348 6.2.3 Development and functional characterization of transcriptionally targeted Her- 2/neu Adenovirus ...... 354 6.2.3.1 Construction of Adenovirus containing BGH.MUC1.Her-2 promoter regulating the expression of Luciferase gene (Ad. BGH.MUC1.Her-2.Luc) ...... 355 6.2.3.2 Recombination of pSc.BGH.MUC1.Her-2.Luc with pAdeasy to generate pAd.BGH.MUC1.Her-2.Luc and rescue of Ad.BGH.MUC1.Her-2.Luc ...... 360 6.2.3.3 Evaluation of tumour specificity of Ad.BGH.MUC1.Her-2.Luc...... 360 6.2.4 Construction and functional characterization of transcriptionally targeted survivin promoter containing Adenovirus (Ad BGH.Survivin.Luc) ...... 362 6.2.4.1 Generation of a shuttle vector with BGH.Survivin.Luc expression cassette (pSc.BGH.Survivin.Luc)...... 363 6.2.4.2 Recombination of pSc.BGH.Survivin.Luc with pAdeasy to generate...... 365 pAd. BGH.Survivin.Luc and rescue of Ad. BGH.Survivin.Luc in 293A cells ....365 6.2.4.3 Evaluation of tumour specificity of Ad.BGH.Survivin.Luc ...... 365 6.2.5 Construction of transcriptionally targeted survivin promoter containing Adenovirus plasmid that expresses PNP (pAd BGH.Survivin.PNP)...... 368 6.3 Discussion/Concluding Remarks ...... 370 Work initiated but not completed in this study ...... 373 SUMMARY AND PERSPECTIVES ...... 375 REFERENCES...... 382 APPENDIX...... 458

Chapter 1: Literature Review 8

LITERATURE REVIEW

Chapter 1: Literature Review 9

Treatment of solid tumours, such as ovarian and prostate cancer is still inadequately effective and despite progress, the prognosis of late stage disease for both is dismal (1).

Hanahan and Weinberg have proposed that malignant transformation of normal cells is dependent upon changes in six different phenotypes (2) (Figure 1.1); to support unlimited growth, cancer cells often display self-sufficiency in growth signals, insensitivity to anti-growth signals, limitless replication potential, evasion of apoptosis, and propensity for tissue invasion metastases and upregulation of angiogenic factors to promote neovasculature to support tumour growth. Most of the anticancer therapies designed to date are designed to target one or more of these phenotypes (i.e. through targeting pathways/genes involved) as shown in Figure 1.1. In this chapter a critical review of treatment options for ovarian and prostate cancer is given.

1.1 Ovarian Cancer: treatment related issues

Ovarian cancer (OC) claims more lives than any other tumour of the female reproductive system. It is projected by the Australian Institute of Health and Welfare

(AIHW) that OC will result in 1500 new cases and will contribute to the death of 960

Australian women in 2009 (http://www.aihw.gov.au). Due to a lack of effective prevention or screening methods, at the time of diagnosis, the majority (75%) of patients have metastatic advanced disease (FIGO stages III and IV). Surgery is the first intervention to treat OC but when advanced, complete removal of tumours (microscopic or macroscopic implants) is not feasible (3). For advanced stage OC, standard treatment involves use of cyto-reductive surgery/radiation followed by 6 cycles of platinum/taxane-based chemotherapy (1,4). Although, current therapy regimens achieve complete clinical remission in 70-80% of the patients, the majority relapse within 18

Chapter 1: Literature Review 10 months of initial diagnosis. With better clinical management, however, the five-year survival rate has significantly improved from 30% in 1960 to almost 50% now, but overall survival still remains minimal (4,5).

Like other cancers, the genesis and progression of OC cannot be attributed to a single gene, mechanism or pathway. Specific gene changes contributing to the continued growth, survival or metastasis of ovarian cancer has yet to be identified. This aetiological heterogeneity is the major reason why single agent therapies have not met expectations. Clinical experience has shown that tumour resistance related to one form of therapy results in potential recurrence of the disease (6). Even aggressive therapy has not shown any improved survival and most drugs fail on the score of therapeutic index

(7). Clinical trends from the last 10 years have shown that treatment achievements for advanced stage disease have now reached a plateau. Clearly, there is a need to develop better strategies for the medical management of OC patients, aimed to increase efficacy with minimal side effects.

More specifically, current investigational approaches have focused on the development and testing of new cytotoxic and non-cytotoxic (biological) OC-targeted therapies; these include, immunotherapy (monoclonal antibodies), targeted gene therapy (transcriptional and transductional targeted vectors); evaluation of the timing and scope of cytoreductive surgery; intraperitoneal therapy; dose and sequential administration of chemotherapy plus radiation and finally, the combination of available therapies. The current practices, recent advances, controversies and the future prospects of these approaches have been extensively reviewed (8-13). A recent shift to targeted therapies or so called ‘molecular therapeutics’ has led to numerous studies leading to fascinating

Chapter 1: Literature Review 11 data about the potential ‘drugable’ therapeutic targets, however, the success of these would be limited to a sub-set of ovarian cancer patients (e.g. Her-2/neu targeted therapies are likely to effective in 15-30% of OC patients). While the effectiveness of these therapies is encouraging the challenge still remains to broaden the scope and efficacy of new therapies in a broader population. In the absence a single “magic bullet” solution, a combination of regimens targeting different cell populations with synergistic cytotoxity appears to be the best approach, both to enhance efficacy and to ensure better patient management and quality of life.

12 Chapter 1: Literature Review 12

Figure 1.1 Processes involved in development of cancer: Key changes that underpin the progression to cancerous phenotype can be divided into six categories; the pathways and molecules involved also serve as potential targets of various anticancer therapies.

Self-sufficiency in Insensitivity Growth Signals to Anti-growth Signals

Evading Limitless Apoptosis Replicative Cancer Potential

Sustained Tissue Angiogenesis Invasion and Metastasis

Figure adapted from Hanahan, D. and Weinberg, R.A. 2000. Cell. 100: 57 (originally from) Margaret E. Tome and Margaret M. Briehl, Presentation/Lecture “Apoptosis, Oxidative Stress and Cancer”

Chapter 1: Literature Review 13

1.2 Combination regimens involving conventional treatment

To increase the efficacy of OC treatment approaches bringing together the conventional treatments e.g. surgery, chemotherapy and radiation in various combinations are discussed below.

1.2.1 Surgery and chemotherapy

Surgery plays a major role in the treatment of OC; to minimize the tumour burden before curative therapy is called ‘cytoreducton’ or ‘primary de-bulking surgery’ (PDS).

Several groups have demonstrated a relationship between residual tumour mass and prognosis with optimal cytoreduction defined as a residual tumour of size <1-2cm

(14,15). Subsequent treatment with chemotherapy in general has led to better survival; a number of non-randomized studies have established the survival benefits of surgery in combination with induction or post-operative adjuvant chemotherapy (16-18). Indeed, the ‘gold standard’ for treatment of advanced OC is cytoreduction (surgery) in combination with platinum/paclitaxel-based chemotherapy. However, the extent and timing of surgery and its therapeutic sequence with regard to chemotherapy is still in debate (19). It is assumed that optimal surgical reduction can only be achieved in 50% of advanced stage OC patients, while in others it remains unresectable. In these patients, neo-adjuvant therapy, defined as chemotherapy prior to surgical ablation (20) has shown significant improvements in median survival rates. Such an intervention results in favourable surgical conditions by reducing the tumour size, which occurs when cytoreductive surgery is optimal (21,22). While the clinical benefit of this type of therapy has been shown in numerous studies, the data remain controversial due to the additional possibility of selection of drug-resistant clones and hence, high local relapse

Chapter 1: Literature Review 14 of more aggressive form of OC (17,23-25). Especially, in patients with advanced stage

IIIc and IV, neoadjuvant chemotherapy followed by interval debulking surgery (IDS) does not seem to confer any advantage, with the prognosis of patients treated with either sequence remaining similar (26); however, more clinical studies are needed to confirm this advantage.

1.2.2 Radiation therapy, surgery and chemotherapy

Combined radiation and chemotherapy (chemoradiation) has a very long curative history for treating resected (post-operative) OCs especially in patients with microscopic or minimal residual disease (27,28). Although, several promising studies have shown survival benefits of post-operative external beam radiation therapy, its use in the clinic has continuously declined in the last decade, partly due to advances in the field of chemotherapy. More recently, a group of studies has established the role of abdomino-pelvic radiation (APR) in consolidation therapy (29-31). Unfortunately, this is currently limited to newly diagnosed OC (not spread beyond the stomach) and despite the initial response, it does not have any long term survival advantage (32). In addition, the issue of low radiation tolerance of the upper abdominal organs (small bowel, kidneys, and liver) also needs to be addressed and clinical strategies need to be improved for treating OC patients with residual disease in the upper abdomen.

1.3 Chemotherapy; the mainstay treatment for ovarian cancer

Historically, chemotherapy has proven to be the most effective for the treatment of patients with OC (Figure 1.2) (2). Chemotherapy began as a single agent therapy using different alkylating agents, which dominated the scene till the mid 1970s. Different

Chapter 1: Literature Review 15 types of chemotherapeutic agents available to date are extensively reviewed (1,33-36).

Those with activity against OC, along with their toxicity profiles are listed in Table 1.1.

Cisplatin was the first platinum compound to show efficacy in OC patients, followed by another platinum compound, Carboplatin, which was FDA approved in 1989. The combination of Cisplatin and Cyclophosphamide was accepted as standard therapy in surgically resected patients during the mid 80s. Finally, the early 90s saw the beginning of the ‘taxane era’ that leads to the discovery and development of the two novel taxanes, paclitaxel and docetaxel. During 2000-2005, clinical trials established that Carboplatin had better efficacy and tolerability compared to Cisplatin (37-39).

Chapter 1: Literature Review 16

Timeline History of OC chemotherapy & outcomes Advantage of Doxorubicin Introduction and development of addition shown first platinum compound: Cisplatin Topotectan Gemcitabine approved by FDA approved by FDA Cisplatin plus an Carboplatin shows Single Alkylating alkylating agent becomes better tolerability agent therapy a standard therapy than Cisplatin

1970 1975 1980 1985 1990 1995 2000 2005

Carboplatin Paclitaxel replaces Five-year survival showed efficacy Cyclophosphamide in Five-year survival less than 20% as a single agent combination with Cisplatin improves to 50%

Paclitaxel activity Therapeutic equivalence demonstrated of paclitaxel and docetaxel shown

SCOTROC (Scottish Randomised

Trial in Ovarian Cancer) 16

Figure 1.2: Historical timeline of OC chemotherapy and outcomes Adapted from WP McGuire and M Markman (2003 BJCancer) (1) 17 Chapter 1: Literature Review 17

Table 1.1 Chemotherapeutic agents with activity against ovarian cancer DRUG CLASS MODE OF ACTION TOXICITY/SIDE-EFFECTS REF. Carboplatin Alkylating agent Binds to DNA; forms cross- Myelosuppression, especially (40-49) links and intrastrand adducts; thrombocytopenia inhibition in DNA synthesis Diarrhea Nausea and vomiting Nephrotoxicity Less cytotoxic than cisplatin Cisplatin Alkylating agent -Same as above- Severe nausea and vomiting (43,45,46,49- Nephotoxicity 52) Ototoxicity Myelotoxicity Peripheral neuropathy Hypomagnesaemia Mouth blistering Oxaliplatin Alkylating agent -Same as above- Neuropathy (53-60) Neutropenia Nausea and vomiting Fatigue

18 Chapter 1: Literature Review 18

Less nephotoxicity and ototoxicity than cisplatin or carboplatin

Cyclophosphamide Mustard alkylating Inter or intrastrand DNA cross Bone marrow suppression (45,61-63) agent linkages Nausea, vomiting and diarrhea Alopecia Hemorrhagic Cystitis Docetaxel Taxane Promotes microtubule Bone marrow suppression esp. (64-76) (Taxotere) polymerization; neutropenia and anaemia G2/M phase cell cycle arrest Fluid retention (weight gain) Nausea, vomiting and diarrhea Peripheral neuropathy Fatigue and weakness Paclitaxel Taxane Promotes microtubule -Same as docetaxel- (41,45- (Taxol) polymerization; 47,65,66,69,7 G2/M phase cell cycle arrest 1,72,76,77) Irinotecan Topoisomerase-I Blocks the activity of Extreme suppression of the immune (78-81) (CPT-11) inhibitor Topoisomerase I, thus, system especially neutropenia inhibiting DNA replication and Severe diarrhea transcription

Chapter 1: Literature Review 19 19

Topotecan Topoisomerase-I -Same as above- -Same as above- (82-86) inhibitor Etoposide Topoisomerase-II -Same as above- -Same as above- (87-91) inhibitors Celecoxib Non-steroidal anti Cox-2 inhibitor Gastrointestinal adverse drug (92-95) (Celebrex) inflammatory drug reactions (NSAID) Allergy Risk of heart attack and stroke Gemcitabine Nucleoside analogue S-phase-specific antimetabolite Myelosupression (58,96-101) (Gemzar) Neutropenia Leukopenia Nausea and fatigue Doxorubicin Anthracyclin Inhibits DNA and RNA Neutropenia (102-109) synthesis, cause break of DNA Nausea and vomiting strains by producing free Alopecia radicals Severe cardiac problems including congestive heart failure and dilated cardiomyopathy

Chapter 1: Literature Review 20

Vinorelbine Vinca alkaloid Spindle poison that arrests Peripheral neuropathy (110-116) (Nevelbine) mitosis through alteration of Anaemia microtubular proteins Diarrhea Nausea Asthenia Phlebitis Hexamethylmelamine Alkylating agent Precise mechanism unknown, Peripheral neuropathy Nausea and (117-120) (HMM) (Altretamine) but N-demethylation of vomiting Leukopenia Altretamine may produce Mild anemia reactive intermediates which covalently bind to DNA, resulting in DNA damage

Chapter 1: Literature Review 21

To date, different forms of chemotherapy have been explored for the medical management of OC: postoperative chemotherapy, neoadjuvant therapy, maintenance therapy and intraperitoneal chemotherapy.

Post-operative chemotherapy has replaced radiation with better survival and improved quality of life. This is now regarded as a ‘standard therapy’, which has outperformed all other drug regimens in most clinical studies. In a recent clinical trial, Neoadjuvant therapy in patients with a large ascites volume (>500ml) resulted in significantly higher tumour resection rates with prolonged survival (22). Further to that, a combination of different chemotherapies holds the most promise for curing OC patients with paclitaxel

and cisplatin being used as a ‘gold Principles of Combination Chemotherapy standard’ in post-operative patients. Using agents with proven clinical activity In a nonrandomized phase II study against specific cancer type conducted on International Using agents to restrict cancer cell resistance Federation of Gynecology and Using agents with non-overlapping toxicities Obstetrics (FIGO) defined stage IIIc Using agents exhibiting therapeutic patients, clinical benefits were

synergies in pre-clinical/clinical evaluations, obtained with the use of 3 cycles of

such that individual therapeutic dosing and platinum/taxane-based combination

resulting side effects are reduced chemotherapy followed by

significantly cytoreductive surgery and 3 additional cycles of platinum/taxane-based combination chemotherapy (22). Since most patients in complete remission following chemotherapy will ultimately relapse and experience disease progression, maintenance and consolidation chemotherapy is given to prevent recurrence of disease. As part of this schedule, a number of different forms

Chapter 1: Literature Review 22 of chemotherapeutic drugs have been tried with acceptable toxicity profiles but none had shown significant survival advantage (91,121-123). Intraperitoneal chemotherapy is another approach, which has been used successfully in patients with small-volume

OC. Given that early stage OC is confined to the peritoneal cavity, theoretically this form of disease ought to be an attractive target for IP therapy, which can potentially achieve a higher concentration of localised drug as a first line option (124-127). Anti- neoplastic agents with low vesicant activity and slow clearance from the IP space are preferred for this form of therapy, with paclitaxel and cisplatin being currently ‘the drugs of choice’ (128-130). A number of clinical studies have shown a potential therapeutic role for paclitaxel plus cisplatin in initial chemotherapy (131), consolidation or salvage therapy (132) and as first line chemotherapy (133), yet, use of this regimen as a standard therapy is still debatable due to excessive associated toxicities (17,134).

1.3.1 Docetaxel and OC

As already discussed, the taxanes, paclitaxel and docetaxel, are potent chemotherapeutic agents with significant activity against clinical OC. These are semisynthetic taxoids, prepared from precursors extracted from the renewable needle biomass/inner bark of

Pacific yew (Taxus brevifolia). Paclitaxel, first isolated in the National Cancer Institute

(NCI) screen of antineoplastics, was shown to act by stimulating microtubule polymerisation (135). By 1995, paclitaxel was engineered semi-synthetically using a precurser, baccatin III (from yew needles and leaves), further leading to the development of the second-generation taxane, docetaxel. Like paclitaxel, docetaxel acts as a spindle poison leading to the inhibition of microtubule dynamics and cell cycle arrest (64), albeit with greater antitumour effects and a better therapeutic index (65,67).

Chapter 1: Literature Review 23

Its potency is now proven against many cancers (including OC) especially, ones that are refractory to chemotherapy in in vitro and in vivo studies (52,136). It is the only drug, which is clinically approved for use in five different types of cancers (75,76,137-140).

In addition to better efficacy, docetaxel displays considerable tolerability advantages and promise over paclitaxel in the management of ovarian cancer

1.3.1.1 Docetaxel: mode of action

As mentioned earlier, docetaxel is a microtubule inhibitor; this affects cells in the G2-M phase, ultimately arresting neoplastic cell proliferation (Figure 1.3). Earlier studies suggested that it was a potent inducer of mitotic arrest rather than apoptosis (141).

However, more recently, apoptotic cell death has been shown to be a key mechanism involved in the activity of this drug, involving various apoptotic proteins such as caspases, proapoptotic members of Bcl-2 family (e.g. Bax) and by the inactivation of antiapoptotic proteins e.g. by Bcl-2 phosphorylation (142). In recent reports, docetaxel cell killing effects have also been shown to be augmented by targeting the fibronectin/PI-3K/Akt2 pathway (143), down-regulating either the X-linked inhibitor of apoptosis protein (XIAP) (144) or focal adhesion kinase (FAK) (145). Ovarian cancer cells having an abrogated or mutant p53 status are more sensitive to taxane treatment, which shows that cell cytotoxic effects of docetaxel may be p53 independent (77,146-

148).

Distinct from its role on microtubule stabilization or apoptosis, docetaxel also affects the immune response by stimulating anticancer and pro-inflammatory genes and proteins, thus suggesting its potential for a broader therapeutic application beyond cancer chemotherapy (reviewed in (71,149,150).

Chapter 1: Literature Review 24 24

Figure 1.3 Docetaxel: primary mode of action

Depolymerization Microtubules

G2 Microtubule Dynamics Docetaxel

S Mitosis

Cell Death G1 Polymerization

Docetaxel is a microtubule inhibitor, which arrests cells in G2/M phase of cell cycle *Figure source: Novartis Oncology

Chapter 1: Literature Review 25

1.3.1.2 Docetaxel as monotherapy

The clinical efficacy of docetaxel monotherapy was established in variety of solid tumours including OC in earlier phase I clinical trials (66,151-153). Subsequently, in phase II trials in OC patients refractory to both paclitaxel and cisplatin, use of docetaxel as a single agent demonstrated good response rates and acceptable toxicity profiles

(52,68,154). It offers both symptomatic and survival benefits to those who respond to the treatment. Unfortunately, significant toxicity leading to grade 3/4 neutropenia, severe fluid retention, diarrhea and acute hypersensitivity also results. However, the neurotoxicity profile is favourable compared to paclitaxel or cisplatin, which forms a foundation for its combination with different platinum compounds (155-157).

1.3.1.3 Docetaxel in combination with other modalities

Docetaxel, as a single agent, does not cure advanced OC and is associated with unwanted side effects at therapeutic doses. Hence, novel combinations of docetaxel with other therapies are being explored in multimodality approaches to cure high risk localized OC with minimal toxicity. Examples of docetaxel in combination with traditional and new therapies has been reported; these include combination with platinum therapy (44,46,52,70,158), irinotecan (CPT-11) (73), COX-2 inhibitor; celecoxib (94), gemcitabine (159,160), doxorubicin (161,162) and vinorelbine (116) and the angiogenesis inhibitor, bevacizumab (163). Impressive synergies between docetaxel and gene therapy have also been reported, especially the ones involving oncolytic viruses in preclinical studies (164,165). 26

Chapter 1: Literature Review 26

Docetaxel in Cancer Treatment

History/Landmark phase trials/ Successive FDA approvals for Docetaxel in Ovarian and Prostate Toxicity issues docetaxel use in cancer treatment cancer treatment

History May 2004: In combination with prednisone for Ovarian cancer 1980: Taxane activity related to microtubule treatment of metastatic, androgen-independent dynamics prostate cancer patients -Clinical efficacy established (several phase I/II 1995: Semisynthetic docetaxel production trials) (yew tree biomass) Aug. 2004: In combination with doxorubicin and -Major toxicities: grade 3/4 neutropenia, severe 1995-2000: Therapeutic equivalence of cyclophosphamide for treatment of node-positive fluid retention, diarrhea and acute paclitaxel and docetaxel shown breast cancer patients hypersensitivity Landmark phase trials -better tolerated than Paclitaxel and Cisplatin -Prostate Cancer: TAX 327/SWOG 9916 Mar. 2006: In combination with cisplatin and -Combination with other therapies (carboplatin, -Breast Cancer/TAX316 fluorouracil for treatment of advanced gastric irinotecan, gemcitabine, vinorelbine etc.) is -Stomach cancer/TAX325 adenocarcinoma highly active and well tolerated in advanced -Squamous cell carcinoma of the head and epithelial OC neck (SCCHN)/TAX323 Oct. 2006: In combination with cisplatin and -Non-small cell lung cancer/TAX 320 fluorouracil as induction treatment of inoperable, Prostate cancer Major Toxic Effects locally advanced (SCCHN) -Myelosuppression: neutropenia and anaemia -Established as single agent therapy (Phase -Fluid retention (weight gain) Nov. 2006: In combination with cisplatin for I/II/III trials) -Nausea, vomiting and diarrhea treatingunresectable, locally advanced or -Only drug with marginal survival benefit against -Peripheral neuropathy metastatic non-small cell lung cancer (NSCLC Castration resistant prostate cancer (CRPC) -Fatigue and weakness without prior chemotherapy -Combination with chemotherapeutic e.g. estramustine, prednisone displayed enhanced efficacy

Figure 1.4 Docetaxel (Taxotere) and Cancer: A flow schematic showing development of docetaxel for cancer therapy with specific details for ovarian and prostate cancer

Chapter 1: Literature Review 27

1.3.2 Carboplatin (CP) and OC

Platinum based compounds represent some of the most active cytotoxic agents for the clinical management of OC in that, carboplatin and cisplatin have been the mainstay of combination and single drug regimens since the 1970s. The earliest evidence came from two large meta-analyses of randomized clinical trials, which showed that platinum- based therapy was associated with survival benefit of two and five years compared to non-platinum based regimens (166,167). As a result, cisplatin based drug regimens are accepted as standard therapy for the treating OC (50,51); however, the higher toxicity profile of Cisplatin led to the discovery and evaluation of a new platinum analogue,

Carboplatin (CBDCA or JM8) (40-42,48). Three different randomized studies have shown that carboplatin has similar antitumour activities but with a lower toxicity profile compared to cisplatin (43,48,49).

1.3.2.1 Carboplatin: mode of action

A number of studies have investigated possible cell killing mechanisms of cisplatin or carboplatin; at the molecular level, these bind to DNA forming cross-links and intrastrand adducts resulting in cell death (168) (Figure 1.5). Both cisplatin and carboplatin have a unique potential to trigger a number of proapoptotic and antiapoptotic responses to harness apoptosis, generally leading to activation of different caspases, up or downregulation of BCL-2 or p53 related genes (168,169). Some of the earlier studies have shown that cisplatin results in DNA-damage induced apoptosis through mitogen- activated protein kinase (MAPK)/extracellular recognition kinase (ERK) pathway, which may be both p53 dependent and independent (170,171).

Chapter 1: Literature Review 28

Carboplatin: primary mode of action

Figure 1.5 Mechanism of carboplatin action: Carboplatin is an alkylating agent, which covalently binds to DNA; possible formation of cross-links and intra-strand adducts resulting in loss of DNA function and resulting in cell death

Recent investigations of carboplatin induced apoptosis confirmed that p53 may act as an upstream regulator of ERK activation in carboplatin-treated cervical cancer cells (172).

In a breast cancer study, it was demonstrated that carboplatin activity was dependent on cyclin-dependent kinase 5 (Cdk5)/ERK, which further modulates p53 transactivation to

Chapter 1: Literature Review 29 induce apoptosis (173). Other apoptosis related genes have also been implicated in carboplatin activity. In carboplatin-treated HL-60 leukemic cells, overexpression of

FAS, B cell lymphoma/leukemia-2 (BCL-2) and caspase-3 genes was observed during early stages of apoptosis (174). In an clinical study of OC, caspase-3 dependent apoptosis was shown in 5/7 chemo-sensitive patients (175). In addition, up-regulation of p53 and p21, and a lowering in BCL-2 expression is related with apoptosis following cisplatin and carboplatin treatment in retinoblastoma Y79 cells (176). The effects of carboplatin in a squamous carcinoma cell line were associated with activation of

Caspases-3 and –8, and further modulation of BCL-2 family proteins, Bax-alpha and

Bcl-x(L) (177). In conclusion, the last two decades of research have shown that carboplatin has a unique potential to kill cancer cells via multiple cell killing mechanisms. Further elucidation of these mechanisms will be instrumental in designing carboplatin based combination drug regimens.

1.3.2.2 Carboplatin in combination with other modalities

Use of carboplatin as a single chemotherapeutic agent or as part of combination drug regimens has been extensively reported. When used as monotherapy in ICON3 clinical trials, it has produced significant clinical response rates with a better toxicity profile for carboplatin compared with cisplatin (45). Some dose intensification studies (either by increasing the dose per cycle (dose escalation) or by decreasing the time between treatments (dose density) of carboplatin have also been reported but success was limited with unwanted side effects (178,179).

Chapter 1: Literature Review 30

The potential role of carboplatin in combination regimens has also been explored (180).

At the pre-clinical level, synergistic effects of carboplatin with different compounds including phenoxidol (181), BCL-2/Bcl-XL family inhibitor ABT-737 (182), heat shock protein 90 inhibitor (183), PI3K inhibitor, LY294002 (184), endogenous estradiol metabolite 2-methoxyestradiol (2ME) (185) have been shown. Overall, an increase in the cancer cell sensitivity to programmed cell death was postulated as the cause of enhanced efficacy. Favorable interactions were also shown when carboplatin was used in combination with interference RNA anti-sense oligonucleotides of FAP-1 and

Nuclear factor erythroid-2-related factor 2 (Nrf2) (186,187).

1.3.2.2.1 Combining Carboplatin with taxanes

Laboratory evidence has led to the clinical evaluation of carboplatin-based combinations with docetaxel and paclitaxel. Combining carboplatin (CP) and paclitaxel is the most widely used option to treat different stages of OC and is currently the front line standard therapy (188). Usually these two drugs are given simultaneously without considering their schedule dependence to get a maximal response. However, in an investigational study it was shown that the optimal schedule for this combination drug regimen is sequential exposure using paclitaxel followed by carboplatin (69). Although, the drug combination of CP/paclitaxel has outperformed other drug regimens, efforts are continuing to improve patient survival and their quality of life. As a result, docetaxel has been explored, replacing paclitaxel in combination regimens. Synergistic interactions between CP and docetaxel have been shown in vitro in OC cell lines (69).

Some non-randomized, dose finding clinical studies have established that a combination of carboplatin and docetaxel is highly active and well tolerated in advanced epithelial

OC (44,162). An international, multicenter, randomized trial (the SCOTROC trial)

Chapter 1: Literature Review 31 compared combination of carboplatin with the paclitaxel to that with docetaxel as first- line chemotherapy for stage Ic-IV epithelial ovarian or primary peritoneal cancer. In this study, randomly assigned 1077 women received docetaxel at 75 mg/m2 of body surface area or paclitaxel at 175 mg/m2. The treatments were followed by carboplatin to an area under the plasma concentration–time curve of 5. Both treatments led to similar impacts on progression free survival and response but displayed different spectra of toxicity: docetaxel-carboplatin was associated with substantially less overall (grade 2 or higher) neurotoxicity than paclitaxel-carboplatin but more grade 3-4 neutropenia and neutropenic complications (47).

1.4 Gene therapy and ovarian cancer

It is obvious that single agent chemotherapeutic options are not effective enough for the treatment of OC and the high dosing requirements often lead to unwanted side effects resulting in low quality of life for patients. Different drug combinations have shown

better outcomes but

Considerations for a clinical gene therapy protocol with limited success.

Successful delivery of the therapeutic gene Therefore, alternative

Sufficient expression of the transgene therapies that maximise

Stability of transgene expression specificity and

Mechanistic effects of the therapeutic gene product minimize the

Sustainable therapeutic efficacy therapeutic doses of the

Acceptable toxicity profile (vector or gene product) individual treatments are needed. This has

Chapter 1: Literature Review 32 directed our focus to combinations of conventional with non-conventional novel therapeutic modalities.

It has been established that cancer is a genetic disease involving multiple mutations ultimately leading to un-controlled division of cancer cells. So gene-therapy, defined as transferring new genetic material and manipulating the existing genetic material, is considered a favourable approach to control cancer cell growth and reverse tumorigenecity. Indeed, with advances in gene technology and a better understanding of

OC biology, it is fast emerging as a promising and viable therapy, especially to enhance cancer-specificity. It has been postulated that combining chemotherapy with gene therapy is a more realistic approach to target variety of cancers (189). OC, in particular, is an ideal model for gene therapy because of the possibility of local (intraperitoneal, ip) application of the treatment, thus (i) preventing the problems that can occur with systemic gene delivery and (ii) enhancing the efficiency of in situ gene delivery due to the possibility of gene compartmentalised delivery.

In a recent summary of 1309 published clinical trials in gene therapy, most (66.5%) were aimed at the treatment of cancer (190). Through these studies some important considerations for successful gene therapy have been identified. Different genes have been used for targeted gene therapy approaches to target cancer (see Table 1.4). In the last two decades enormous efforts have been directed at improving these gene therapy approaches. Most were found to be safe, but only few resulted in favourable and effective clinical responses. Thus far these clinical studies have identified that, regardless of the strategy, a bigger challenge is to improve gene therapy vectors with better potency and safety profiles.

Chapter 1: Literature Review 33

1.4.1 Gene transfer systems

In the recent thrust towards developing gene-delivery systems to improve in situ gene delivery and expression, viral and non-viral vectors have been developed for gene transfer to loco-regional and disseminated cancer cells and have shown certain advantages and disadvantages (Table 1.2) (191,192). Viral vectors are the most explored delivery vehicles for cancer gene therapy and are discussed below.

1.4.1.1 Viral vectors

The fact that viruses have a natural tropism to infect and deliver their genetic materials to cells has been exploited in cancer gene therapy from the early 1950s. Both DNA and

RNA viruses have been evaluated in numerous gene therapy clinical trials. Adenoviral vectors (24.7%) are leading followed by retroviruses (22.8%) (Figure 1.6). Some other viruses such as vaccinia virus (6.8% of trials), poxvirus (6.4%), adeno-associated virus

(3.5%), and herpes simplex virus (3.2%) have also shown promise, however, their clinical use is still limited (190). Adenoviral vectors form the focus of this review. 34 Chapter 1: Literature Review 34

Table 1.2 Advantages and disadvantages of different gene delivery vectors

TYPES ADVANTAGES DISADVANTAGES

VIRAL VECTORS Retroviruses High transfection efficiency; stable integration leading to Very unstable; low titer; integrate into the host cell (RNA virus) long-term gene expression; infect hematopoietic and genome so only infect dividing cells; risk of malignant epithelial cells; absence of immunogenic viral proteins transformation in affected cells due to integration into host genome; relatively small amount of genetic information (~ 9-12 kb)

Adenovirus Well studied; high titer; stable and resistant to physical Immunogenic; potentially hepatotoxic; short term gene (DNA virus) stress (e.g. freezing); non integrating, transient expression, expression as it does not integrate in host genome; virus side effects are less severe; infect epithelial cells at high neutralization with pre-existing antibodies frequency; higher packaging capacity; easy to engineer; infect dividing and non-dividing cells effectively, cellular proliferation not required Adeno- Stable; integrates into non-dividing cells at low frequency Small capacity for DNA; low titre; requires a helper associated virus virus Herpes virus Infects a wide range of cell types; can achieve high titer; has No integration into genome of infected cells; cytotoxic; relatively prolonged expression immunogenic; difficult to engineer/handle due to complexity; complex packaging system

Reovirus Infection limited to cells with activated ras pathway Not well characterized

35 Chapter 1: Literature Review 35

TYPES ADVANTAGES DISADVANTAGES

NON VIRAL VECTORS

DNA cassettes Non-viral; easy to use and develop, can be used for sense and Low efficiency of transfection in vivo; temporary antisense expression expression, stability Liposomes Non-viral, easy to develop Low frequency of modification, especially in vivo; cytotoxic to some cell Oligonucleotides Non viral, small in size, potential use in RNA interference Low efficiency of transfection in vivo; temporary expression, stability

Chapter 1: Literature Review 36

Figure 1.6 Vectors used in cancer gene therapy clinical trials

20.90% 18%

7.90%

6.90%

24.00% 5.80% 4.30% 3% 4.50% 1.40% 3.20%

Adenovirus Retrovirus Naked/Plasmid DNA Vaccinia virus Lipofection Pox Virus Adeno-associated virus Herpes RNA transfer Other categories Unknown

1.4.1.1.1 Adenoviral vectors

Adenoviruses are non-enveloped, linear, double stranded DNA viruses with DNA of approximately 30-35kb in length (193). These viruses primarily attack mucoepithelial cells of the conjunctiva, respiratory tract, and gastrointestinal and genitourinary tracts and are generally associated with relatively mild and self-limiting diseases in humans

(194). Since the discovery of Adenovirus (Ad) in human adenoid tissue in 1953 (195) at least 51 human serotypes have been identified and grouped from A-F based on their degree of genome relatedness. Ads from group C serotypes (Ad2 and Ad5) are the best characterized and vectors based on these have been extensively used in cancer gene therapy.

Chapter 1: Literature Review 37

1.4.1.1.1.1 Potential advantages and disadvantages of Ad vectors

Ad vectors have a number of advantages, which make them a favourite choice among other vector systems to transfer and express therapeutic genes (Table 1.2). These vectors can infect most human cells including proliferating and quiescent cells. This is important given that most cancers contain cycling and non-cycling tumour cells. Ad vectors are safe as Ad genomes do not integrate into the host cell chromosome and mediate transient transgene expression, which also makes them ideal for cancer therapy requiring only short-term expression of cytotoxic genes. Further, Ad vectors are more stable and resistant to physical stress (e.g. freezing) and they can be easily concentrated to high titres and stored at low temperatures. A major limitation of this vector is the induction of a host immune response, which could eventually result in some fatal inflammatory reactions. In fact, adenoviral vectors caused the first reported death in a clinical gene therapy study sponsored by University of Pennsylvania (196). In addition to the generated cell-mediated humoral response, an innate immune response is also triggered against the injected Ad virus. This leads to a diminished transgene activity when upon re-administration of Ad vectors. To circumvent this, virus co-administration with some immunosuppressive drugs or cytokines has been succesfully used (197).

Further, given that most humans have pre-existing Ad-neutralising antibodies, the efficacy of Ad vectors may be further compromised due to clearance from the host. The resulting short-term gene expression necessitates repeated administration of the viral vector. One approach to deal with this problem is to use different Ad serotypes at different times of administration (198). Another hurdle for their possible use in gene therapy trials is the their potential to ‘switch’ from replication defective state to replication incompetent state, especially during their mass production in propagating cell line/s (HEK293) which contain the missing viral elements in trans.

Chapter 1: Literature Review 38

1.4.1.1.1.2 Tropism

Adenoviral vector entry into cells is a multi-stage process, requiring virus interactions with Coxsackie’s and Adenovirus Receptor (CAR) and v3 integrins (199,200) (Figure

1.7). CAR is a membrane-based protein, which is expressed in a variety of cancerous

(201-206) and non-cancerous cell types including heart, muscle, brain, lung and liver cells (207-209). Most cancer cells down-regulate this protein to become refractory to

Ad infections (204,208,210,211). Expression of CAR in normal cells is also a critical determinant of Ad related non-specific toxicity. It is believed that hepatotoxicity, a common side effect of Ad infections is due to the abundant level of CAR expression in liver Kupffer cells (200). However, some preclinical studies have reported hepatotoxicity even when CAR ablated Ads were systemically administered (212,213).

In mice, systemically given Ad accumulates in liver, lungs, kidney, heart and spleen

(214,215). Virus related toxicity in these organs has been demonstrated, irrespective of their CAR expression levels (216). This would suggest possible involvement of some other interactions between virus and the host cell surface. Other surface receptors such as heparan sulfate glycosaminoglycans (HSG) (217,218) and major histocompatibility complex I (MHC I) (219) have been implicated in viral entry into cells. Thus, emphasis is now on improving the safety profile of these vectors through making them tumour specific. For this, a number of genetic modifications have been incorporated at both transcriptional and transductional levels with demonstrated improvement in tumour specificity of these vectors (See Sections 1.4.2.4 and 1.4.2.5).

Chapter 1: Literature Review 39

Figure 1.7 Cell-entry pathway of the adenoviral vector: Adenovirus attachment to the cells is mediated by coxsackie adenovirus receptor (CAR). First, the fibre knob in the viral capsid binds to the CAR receptor and then penton protein present at the base of fibre interacts with integrins on the cell surface leading to receptor- mediated endocytosis of the virus. Once internalised, the acidic conditions in endosomes release the double-stranded viral DNA which eventually gets translocated into the nucleus (220).

Chapter 1: Literature Review 40

1.4.1.1.1.3 Development of Adenoviral vectors

Both replication competent and replication incompetent ad vectors have been developed for cancer gene therapy applications. As shown in Table 1.3 there are four different categories of Ad vectors: First generation, second generation, third generation or “helper dependent” or “gutless vector” and more recently, conditionally replicating adenoviral vectors. Most studies performed to date have used the first generation type 5

Ad vectors, which have been rendered replication defective through deletions of the E1 and E3 viral genes. The second-generation vectors have additional E2 and/or E4 deletions, which provide them with a larger capacity for foreign DNA (221-225). These vectors are shown to be less immunogenic and show improved transgene persistence compared to first generation vectors (221-225). However, these results remain controversial, as more clinical data are required for their successful application.

‘Gutless” or “helper dependent” Ad vectors have been generated in an effort to improve both gene carrying capacity and to reduce their immunogenicity. In these vectors, all viral genes have been deleted with excepting ITR repeats and a packaging signal; this provides them with the capacity to carry up to 37kb of foreign DNA (226,227). While these vectors are attractive tools for gene therapy applications, again technical issues associated with their mass productions remain to be resolved. More recently, over the last decade, conditionally replicative adenoviruses (CRAds) have entered the arena and have already shown promise in clinical trials. These vectors have been developed and engineered to achieve the ultimate goal of selective cancer cell killing whilst sparing the normal cell populations. Their current role in cancer gene therapy is discussed in

Section 1.4.2.3. 41 Chapter 1: Literature Review 41

Table 1.3 Types of adenoviral vectors TYPE GENETIC FEATURES PROPERTIES First generation E1 and or E3 regions are deleted Replication incompetent; capacity for transgene insertion ~ 8.1Kb; impaired replication; immunogenic; production in E1 complementary cell line e.g. HEK293 cells; chances of production of replication competent viruses during homologous recombination with E1 sequences; some reports of replication at very high multiplicity of infections Second generation E1, E2 and E3 and/ or E4 regions are Replication incompetent; higher capacity for transgene deleted insertion compared to first generation vectors; improved transgene persistence; less immunogenic; lower viral yield; production in E2 or E4 complementary cell lines Third generation/high capacity All essential gene are deleted except Contains only ITR repeats and a packaging signal; can or gutless vectors ITR and packaging signal sequences accommodate up to 37kb foreign DNA; least immunogenic with prolonged transgene expression Conditionally Replicative Modulated based on cancer cell Replication competent only in cancer cells; gene expression properties (e.g. p53) to allow cancer- depends upon promoter activity; selective in expression selective replication or important viral genes placed under the control of cancer specific promoters

Chapter 1: Literature Review 42

1.4.2 Gene therapy approaches

The ultimate goal of most cancer gene therapy strategies is to kill the target cancer cell rather than correct it genetically. This can be achieved either directly by the production of cell killing toxins or indirectly through cancer targeted stimulation of immune system to clear cancer cells. Cancer gene therapy strategies can be divided into six therapeutic types based on gene or the vector system used.

1. Mutation compensation/Gene substitutions

2. Molecular chemotherapy

3. Virotherapy/Oncolytic gene therapy

4. Genetic Immunopotentiation/immunotherapy

5. Anti-angiogenesis therapy

6. Combination gene therapy

In this review, the first three have been described in detail, as they have found more widespread applications in OC targeted gene therapy studies.

Chapter 1: Literature Review 43 43 Table 1.4 Clinical trials for ovarian cancer gene therapy TYPE STRATEGY/ VECTOR STATUS TITLE/PROTOCOL REF. TRANSGENE

Mutation compensation/Gene substitution Replacement of p53 Adenovirus Phase I A phase I study of Adp53 (INGN 201; ADVEXIN) for patients (228) TSG1 with platinum- and paclitaxel-resistant epithelial ovarian cancer Adenovirus Phase I/II A phase I/II trial of rAd/p53 (SCH 58500) gene replacement in (229) recurrent ovarian cancer BRCA12 Retrovirus Phase I A phase I trial of retroviral BRCA1sv gene therapy in ovarian (230) cancer Retrovirus Phase I/II Ovarian cancer BRCA1 gene therapy: Phase I and II trial (231) differences in immune response and vector stability

Gene addition MDR-13 Retrovirus Phase I Use of safety-modified retroviruses to introduce chemotherapy (232) resistance sequences into normal hematopoietic cells for chemoprotection during the therapy of ovarian cancer: a pilot trial

Retrovirus Phase I Results of MDR-1 vector modification trial indicate that (156) granulocyte/ macrophage colony-forming unit cells do not contribute to posttransplant hematopoietic recovery following intensive systemic therapy Retrovirus Phase I Phase I trial of retroviral-mediated transfer of the human MDR1 (233) gene as marrow chemoprotection in patients undergoing high- dose chemotherapy and autologous stem-cell transplantation

Chapter 1: Literature Review 44 44

TYPE STRATEGY/ VECTOR STATUS TITLE/PROTOCOL REF. TRANSGENE Gene Inactivation Her-24/neu or Adenovirus Phase I A cancer gene therapy approach utilizing an anti-erbB-2 single- (234) ERBB-25 chain antibody-encoding adenovirus (AD21): a phase I trial Liposome/ Phase I Cationic liposome-mediated E1A gene transfer to human breast Ad E1A and ovarian cancer cells and its biologic effects: a phase I (235) clinical trial Liposome Phase I A multicenter Phase I gene therapy clinical trial involving intraperitoneal administration of E1A-lipid complex in patients (236) with recurrent epithelial ovarian cancer overexpressing HER- 2/neu oncogene

Molecular HSV-tk/GCV6 Retrovirus Phase I The treatment of ovarian cancer with a gene modified cancer chemotherapy (Vaccine) vaccine: a phase I study (‘suicide’ gene Retroviral Phase I A phase I trial of in vivo gene therapy with the herpes simplex (237ka therapy) producer cells thymidine kinase/ganciclovir system for the treatment of ma,23 (LTKOSN.1) refractory or recurrent ovarian cancer 8) Retrovirus Phase I Vaccine therapy for ovarian cancer using herpes simplex virus- (Vaccine) thymidine kinase (HSV-TK) suicide gene transfer technique: a phase I study (239) Adenovirus Phase I A phase I study of recombinant adenovirus vector-mediated intraperitoneal delivery of herpes simplex virus thymidine kinase (HSV-TK) gene and intravenous ganciclovir for previously (237) treated ovarian and extraovarian cancer patients

45 Chapter 1: Literature Review 45

TYPE STRATEGY/ VECTOR STATUS TITLE/PROTOCOL REF. TRANSGENE Genetic immuno- Interferon Beta Adenovirus Phase I Interferon beta adenoviral gene therapy in a patient with ovarian (240) potentiation cancer (Passive and Interleukin- rIL-27 and Phase I Phase I trial of intraperitoneal recombinant interleukin- (241) active immuno- 2/LAK8 LAK 2/lymphokine-activated killer cells in patients with ovarian therapy) cancer (242) T cells in with T cells/IL-2 Phase I A phase I study on adoptive immunotherapy using gene- high-dose IL-2 modified T cells for ovarian cancer. (243) Interlukin-2 rIL-2 Phase I A phase I trial of intraperitoneal recombinant interleukin 2 in patients with ovarian carcinoma. Virotherapy Ad.delE1B Adenovirus Phase I Phase I trial of intraperitoneal injection of the E1B-55-kd-gene- (244) ONYX-015 deleted adenovirus ONYX-015 (dl1520) given on days 1 through 5 every 3 weeks in patients with recurrent/refractory epithelial ovarian cancer.

1TSG1, Tumour suppressor genes; 2BRCA-1, breast cancer associated gene; 3MDR-1, multiple drug resistance-1 gene; 4Her-2, human epidermal growth factor recptor-2; 5ERBB-2, erythroblastic leukemia viral oncogene homolog 2; 6HSV-tk/GCV, Herpes simplex virus-thymidine kinase/Gancyclovir, 7rIL-2, recombinant interlukin-2; 8LAK, lymphokine-activated killer cells.

Chapter 1: Literature Review 46

1.4.2.1 Mutation compensation/gene Substitutions

The development of malignant tumours is a multi-step process generally associated with genetic alterations in oncogenes or tumour suppressor genes (TSG), which generally play an important role in key cellular pathways involved in growth and development.

Oncogenes refer to those genes whose activation from proto-oncogenes result in cancer activation while tumour suppressor genes when lost or inactivated contribute to the malignant phenotype. The potential role of various oncogenes and TSG has been characterized in a number of human cancers, but relatively few have been associated with disease progression in ovarian cancer. Several gene therapy strategies based on oncogenes and tumour suppressor genes have been designed and tested; although these prove the safety but only a few have shown any clinical benefit (discussed below).

1.4.2.1.1 Reactivation of Tumour Suppressor Gene (TSG)

Reintroduction of a functional TSG is one of the earliest approaches of cancer gene therapy. Of these, p53 is the most extensively studied and almost 50-75% of the advanced stage ovarian adenocarcinoma harbour p53 mutations, making it an ultimate target of gene therapy. Most of the pre-clinical studies have shown that the restoration or augmentation of p53 function in cancer cells can result in tumour regression, which may be associated with the induction of cell cycle arrest and/or apoptosis (245-248).

The bystander effects were also noted with P53 therapy although effective preclinically, a clinical output was not that significant (228-229). Based on promising pre-clinical data, clinical trials of recombinant adenoviral vectors delivering wild-type p53 were conducted to treat patients with recurrent OC. An acceptable toxicity profile and a successful transfer of wild-type p53 have confirmed the feasibility of this approach

Chapter 1: Literature Review 47

(228,229,249). However, results from this approach did not show any therapeutic efficacy in patients with OC; a number of reasons were suggested. These include: inadequacy of single gene therapy approach, inefficient delivery, inability of Ads to infect cancer cells due to CAR downregulation or Ad clearance by neutralising antibodies (250).

Breast cancer 1 (BRCA1) is a typical TSG and women with mutations in this gene have a 40-60% risk of developing OC by age 85. Tait et al have shown significant tumour regression and improved survival with a retroviral based BRCA-1 gene therapy in a nude mouse model (251). Subsequently, clinical studies have shown that delivery of

BRCA1sv with retrovirus was safe and well tolerated (230) and in this phase I trial, 3 out of 12 patients demonstrated partial responses. However, the phase II trial did not show any such responses or disease stabilisation (231). In addition to p53 and BRCA 1, other important TSGs altered in OC involve the genes PTEN, p16, p21, BAX and N5.

Gene therapy strategies with these TSGs have shown some early promise but more preclinical evaluations are required for their successful translation to the clinic.

1.4.2.1.2 Inactivation of oncogenes

The concept is to inactivate or downregulate the oncogenes to suppress tumour cell growth. Although, amplification or overexpression of a number of oncogenes is implicated in OC development, only a few have been explored for targeted OC therapy.

The important ones among these are ERBB-2 (Her-2/neu), K-ras, BCL-2, c-myc and survivin genes. Antisense therapy is the most widely used approach to minimise the gene function of oncogenes (252-257). Of these, Her-2/neu is the most explored; this

Chapter 1: Literature Review 48 gene is overexpressed in 15-30% of ovarian cancers patients and has been associated with poor prognosis (258). In a phase I trial using an adenoviral vector encoding a single chain anti-erbB2 antibody (Ad21: anti-erbB2-scFv) to downregulate ERBB-2 expression in 15 cancer patients, no dose limiting toxicities were associated with the vector and five out of 13 patients had stable disease whilst the remaining eight showed progression (234). In another clinical trial, the potential role of Adenoviral E1A gene to downregulate Her-2/neu expression was explored in patients with recurrent ovarian or breast carcinoma and found to be safe. Liposomal E1A gene delivered weekly for three weeks via an intraperitoneal catheter was shown to be safe with no dose-limiting toxicity. The results from the study were considered promising as E1A gene expression was observed in all patients with two of them showing downregulation in Her-2/neu gene (235).

1.4.2.2 Molecular chemotherapy

Molecular chemotherapy engendered by gene directed enzyme pro-drug therapy

(GDEPT)/Virus directed enzyme pro-drug therapy (VDEPT) offer a particularly attractive solution to the current limitations of effective gene delivery in situ. After the first successful report in 1991 (259), a number of GDEPT systems have been explored in pre-clinical/clinical studies to treat different types of cancers and have been extensively reviewed (260-268). By 2007, GDEPT has been evaluated in 109 clinical trials out of which three have reached phase III stage (190,261). There are two components of any GDEPT system: a ‘non-toxic pro-drug’ and pro-drug converting enzyme. The biggest advantage of GDEPT approach over other gene therapy strategies is that it leads to in situ amplification of cytotoxic effects through engendering a

Chapter 1: Literature Review 49

‘bystander effect’. This effect was first described by Moolten (269) as extension of cell killing effects to surrounding (local bystander effect) or distant (distant bystander effect) un-modified cancer cells (270-274). Several mechanisms have been postulated to be involved; these include transfer of apoptotic vesicles (62,275,276), transduction of endothelial cells in tumour vessels (277), via gap junctions (278,279), diffusion of soluble toxic metabolites (280-282) and induction of an anti-tumour immune response

(cytokines, NK and T cells) (283-286). The potency of GDEPT is dependent upon the selection of a suitable enzyme and the substrate drug (pro-drug). Most enzymes used to date are of bacterial or viral origin and the main criteria underpinning their selection is that humans shouldn’t produce the substrates for these. These criteria are extensively reviewed in (287-290). Prodrugs are chemicals that are inert and relatively non-toxic even at quite high doses, but can be converted to toxic species at the target site/cell, enzymatically or non-enzymatically, to exert a therapeutic effect. A number of reviews have focused on the selection and development of prodrugs with the emphasis on their suitability for suicide gene therapy (262,291-293).

1.4.2.2.1 GDEPT and ovarian cancer

Different GDEPTs have been explored for the treatment of ovarian cancer with some in clinical trials (Table 1.4). Of these, Herpes Simplex Virus-Thymidine Kinase (HSV- tk)/Ganciclovir based GDEPT is the most widely explored and in fact, the first ever- clinical trial to use a GDEPT approach was based on this strategy in patients with OC

(294). Several clinical trials using retroviral or adenoviral delivery of HSV-tk with

GCV have been completed in OC patients (237-239). Results from these studies reveal that this form of therapy is a feasible approach with accepted toxicity profiles.

Chapter 1: Literature Review 50

Although promising, the biggest limiting factor for HSV-tk GDEPT was that this was only effective on fast dividing cells. Another problem relates to the fact that the bystander killing effects rely upon cell-to-cell contact via gap junctions or apoptosis vesicles. Hence, while HSV-tk/GCV is an attractive approach to target OC, these important issues need to be addressed for future clinical applications.

While a number of other GDEPT systems have been explored and have shown promise for OC treatment (Table 1.5) for the purposes of this review, we will focus especially on applications involving the use of relatively novel, PNP-GDEPT.

Chapter 1: Literature Review 51

Table 1.5 GDEPT and cancer

APROACH PRODRUG TOXIC TYPE ADVANTAGES/DISADVANTAGES REF. METABOLITE HSV-TK Ganciclovir Ganciclovir Antimetabolites In clinical trials (278,279, triphosphate Associated with significant local and 295-299) distant ‘bystander effects’ Acyclovir Acyclovir Activated drug is an S-phase specific triphosphate cytotoxin and hence, effective on fast dividing cells only Dependence on cell to cell based gap Valacyclovir Valacyclovir junctions or apoptosis vesicles for triphosphate bystander effects E.coli 5-Fluorocytosine 5-Fluorouracil Antimetabolite Pre-clinical studies (300-305) CDUPRT Kills dividing and non-dividing cells Prodrug activation dependent on further metabolism of enzymes Development of 5FU resistance in some cancer cells Higher toxicity of activated end product (long half life) HSV-TK and Ganciclovir Ganciclovir Antimetabolites Double suicide gene therapy leads to (306,307) E. coli triphosphate enhanced cancer cell killing without CDUPRT enhancing toxicity to non-target (Double suicide 5-Fluorocytosine 5-Fluorouracil organs 51 gene therapy)

Chapter 1: Literature Review 52

APROACH PRODRUG TOXIC TYPE ADVANTAGES/DISADVANTAGES REF. METABOLITE E.coli PNP 6-Methylpurine-2’- 6-Methylpurine Antimetabolites Currently in a phase I clinical trial (308) deoxyriboside (6-MEP) (Australia: personal communication) (MeP-dR) Associated with strong ‘bystander Fludarabine 2-Flouroadenine effect’ and results in killing of dividing Phosphate (Fludara) as well non-dividing cancer cells E.coli CB1954 (5-aziridin- Hydroxylamines Alkylator Preclinical (309-320) Nitroreductase 1-yl)-2,4- Forms DNA crosslinks in both cycling dinitrobenzamide and non-cycling cells 2-Nitrobenzyl Local and distant bystander effects carbamates Distant bystander effect may also involve induction of stress proteins, HSP25 and HSP70 Pseudomonas 4-[(2-chloroethyl)(2- Active mustard Alkylator Preclinical (317,321, putida mesyloxyethyl) species with the Strong local bystander effect 322) Carboxypeptidases amino] benzoyl-L- removal of Cell killing mechanisms not well CPG2 glutamic acid glutamic acid studied (CMDA) 52

Chapter 1: Literature Review 53

1.4.2.2.2 PNP-GDEPT and OC

GDEPT based on the E. coli enzyme, purine nucleoside phosphorylase (PNP) has shown potentcy against various types of cancers including OC (Table 1.6). This approach is based on the structural and functional differences between E.Coli PNP and its mammalian counterpart (reviewed by Zhang (323)). Although, earlier studies have explored the use of a prodrug called 6-methyl-purine-2'-deoxyribonucleoside (6-

MPDR), more recently this drug has been replaced with Fludarabine phosphate

(arabinofuranosyl-2-fluoroadenine monophosphate), which is also a clinically approved drug (324-326). E. coli PNP converts systemically administered prodrug, fludarabine phosphate, to a toxic purine metabolite, 2-fluoroadenine (2FA). Through its incorporation into RNA as well as DNA, 2FA kills non-dividing as well as dividing cells surrounding the transgene expressing cells & leading to ‘a local bystander effect’

(327,328), which has been shown to be more efficient than other GDEPTs such as

HSV-TK (328). This is attributed to the abilty of toxic metabolites from PNP-GDEPT to diffuse freely across the cell membranes to kil surrounding non-transduced cells

(Figure 1.8) (328,329). Indeed, the superiority of this system was shown by the significant amount of cell killing achieved in vivo when as few as 1 in 1000 cells expressed PNP (308). Preclinical studies have also shown that GDEPT-mediated regression of non-transduced parental cells at distant sites, leading to a so-called

‘distant bystander effect’ in immunocompetent mouse models. Finally, the potential of

PNP-GDEPT for treating different types of cancers has been unequivocally shown

(Table 1.6). These studies have laid the foundation for the first phase I clinical trials in prostate cancer patients (Australia). Thus, PNP-GDEPT is a novel system that has a potential to induce potent ‘local & distant ‘bystander effects’ via stimulating systemic

Chapter 1: Literature Review 54 anticancer responses and therefore has potential to simultaneously treat local & metastatic disease.

1.4.2.2.3 GDEPT and chemotherapy

Despite the promise against OC, GDEPT based molecular therapy has displayed inadequate efficacy as a single agent in the clinic. Hence, a combination of GDEPT based molecular therapy with available chemotherapeutic options has led to encouraging outcomes. In an early study, it was shown that HSV-tk/GCV based therapy can sensitise OC cells to a variety of chemotherapeutic agents (330). Further, a moderate favourable preclinical response was obtained when suicide gene therapy was combined with either topotecan or paclitaxel (303). In a similar study, Hasenburg et al

(297,298) conducted a phase I trial to treat patients with recurrent OC with the recombinant Ad containing the HSV-tk gene administered intraperitoneally (i.p.) followed by an administration of Acyclovir (prodrug) and Topotecan. The results showed that i.p. delivery of adenoviral vector with concomitant topotecan chemotherapy was a feasible approach with improved efficacy and acceptable toxicity profile.

Systemic added non toxic Pro-drug (Fludarabine Phosphate)

Cancer cells

Ad. PNP PNP Surrounding cancer Adenovirus expressiong PNP cells are killed 1 ‘Local Bystander’ Effect 2 Toxic drug

Cancer cells spread to other organs are killed Immune response 3

‘Distant Bystander’ Effect 1. The expressed PNP gene converts pro-drug Fludarabine Phosphate to its toxic metabolites, which kills cells expressing this gene 2. The toxic drug diffuses passively to adjacent cells resulting in a local ‘bystander effect’ 3. Cancer cells spreading to other organs are killed via a “distant bystander effect” potentially involving sttimulation of the host immune system 55 Figure 1.8: PNP-GDEPT: Mode of Action

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Table 1.6 PNP-GDEPT and cancer

CANCER VECTOR PRO-DRUG TITLE/PROTOCOL OUTCOME/RESULTS REF. TYPE Colon Plasmid 6-MPDR Tumour cell bystander killing in Expression of E. coli PNP in < 1% of a (328) cancer colonic carcinoma utilizing the human colonic carcinoma cell line lead Escherichia coli DeoD gene to to complete cell killing generate toxic purines (in vitro) Measles virus 6-MPDR An immunocompetent murine model With the use of a targeted measles virus (331) for oncolysis with an armed and MV-PNP-anti CEA, 100% survival was targeted measles virus (in vivo) achieved with 9 out of 10 C57BL6 animals showing complete remission Melanoma Plasmid 6-MPDR Bystander killing of melanoma cells Mixed cultures containing 1-2% of PNP (329) using the human tyrosinase promoter expressing cells resulted in 100% growth to express the Escherichia coli purine inhibition in melanoma cancer cell lines nucleoside phosphorylase gene (in vitro) Plasmids/ 6-MPDR Prodrug converting enzyme gene L. monocytogenes-mediated bactofection (332) Bacteria L. Fludarabine delivery by L. monocytogenes (in was proved as an efficient method for the monocytogenes Phosphate vitro) tumour specific activation of prodrugs in live animals Lymphoma Measles virus Fludarabine Lymphoma chemovirotherapy: Synergistic effects of oncolytic measles (333) Phosphate CD20-targeted and convertase-armed virus and PNP-GDEPT in CD20-positive measles virus can synergize with non-Hodgkin's lymphoma (NHL) cell fludarabine (in vitro and in vivo) lines and xenografts were shown.

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Prostate Adenovirus 9-(beta-D-2- Relative efficiency of tumour cell The PNP- GDEPT was found superior (334) cancer deoxy- killing in vitro by two enzyme- compared to HSV-TK/ganciclovir erythropentofuran prodrug systems delivered by system in prostate cancer cell lines osyl) 6- identical adenovirus vectors (in vitro) methylpurine Adenovirus 6-MPDR In vivo gene therapy for prostate Improvement in survival of BALB/c (335) cancer: preclinical evaluation of two nude mice with s.c PC-3 tumours when different enzyme-directed prodrug treated with PSA promoter driven PNP – therapy systems delivered by GDEPT. identical adenovirus vectors (in vivo) Adenovirus 6-MPDR Transcription-targeted gene therapy Androgen-independent, prostate- (336) for androgen-independent prostate targeting Ad5 expressing PNP driven by cancer (in vivo) rat probasin promoter resulted in reduction of PC-3 tumours in nude mice Adenovirus Fludarabine Gene therapy for prostate cancer Use of ovine Ad vector containing PNP (337) (Ovine) Phosphate delivered by ovine adenovirus and was effective against androgen mediated by purine nucleoside independent, aggressive murine RM1 phosphorylase and fludarabine in and human PC-3 tumours grown s.c or mouse models (in vivo) orthotically (intraprost) Adenovirus Fludarabine Gene-directed enzyme prodrug The ovine Ad vector expressing (338) (Ovine) Phosphate therapy for prostate cancer in a mouse PNP/fludarabine resulted in survival model that imitates the development advantage in immune-competent of human disease (in vivo) TRAMP mice 57

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Adenovirus Fludarabine Purine nucleoside phosphorylase and Suppression of local prostate cancer (339) Phosphate fludarabine phosphate gene-directed growth and reduced lung colony enzyme prodrug therapy suppresses (pseudo-metastases) formation in the primary tumour growth and pseudo- RM1 tumour model. Immunostaining metastases in a mouse model of showed an increased Thy-1.2(+) cell prostate cancer (in vivo) infiltration into the prostate tumour site; a possible role of immune mediated distant bystander effect Adenovirus Fludarabine Preclinical evaluation of a prostate- Ovine atadenovirus vector (OAdV623) (340) Phosphate targeted gene-directed enzyme expressing PNP under the control of prodrug therapy delivered by ovine androgen independent prostate targeted atadenovirus promoter resulted in tumour growth inhibition in LNCaP-LN3 and PC-3 lines and their xerografts Breast Adenovirus 9-(beta-D-2- Relative efficiency of tumour cell The PNP based GDEPT was found (334) cancer deoxy- killing in vitro by two enzyme- superior compared to HSV-TK erythropentofuran prodrug systems delivered by /ganciclovir system in breast cancer cell osyl) 6- identical adenovirus vectors lines methylpurine Glioma D54MG glioma 6-MPDR In vivo gene therapy of cancer with Preliminary studies showing the promise (341) cells expressing Fludarabine E. coli purine nucleoside PNP-GDPT in treating nude mice E. coli PNP phosphate phosphorylase (in vivo) bearing human malignant D54MG glioma tumours expressing PNP D54MG glioma 6-MPDR Antitumour activity of 2-fluoro-2'- This study showed that 2-fluoro-2'- (342) cells expressing 2-fluoro-2'- deoxyadenosine against tumours that deoxyadenosine (F-dAdo) can also be a E. coli PNP deoxyadenosine express Escherichia coli purine promising pro-drug for PNP (F-dAdo) nucleoside phosphorylase (in vivo)

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Adenovirus Fludarabine Excellent in vivo bystander activity The study showed that a higher tumour (343) Lentivirus Phosphate of fludarabine phosphate against response can be achieved when ~ 95% of human glioma xenografts that express the tumour mass is composed of the escherichia coli purine nucleoside untransduced bystander cells phosphorylase gene (in vivo) Lentivirus 6-MPDR Antibiotic-mediated chemoprotection The study compared PNP gene delivery (344) enhances adaptation of E. coli PNP based on lentiviral, MuLv, and HSV for herpes simplex virus-based based vectors and showed that additional glioma therapy (in vivo) antibiotic therapy can augment cell killing by eliminating the enteric flora encoding PNP enzymes Foamy virus/ Fludarabine Experimental therapy of allogeneic The study showed oncolytic effects of (345) retrovirus Phosphate solid tumours induced in athymic foamy virus in addition to PNP- GDEPT mice with suicide gene-transducing in a human glioblastoma tumour /nude replication-competent foamy virus mice model vectors (in vivo) Liver Vaccinia virus 6-MPDR Thymidine kinase-deleted vaccinia The study showed potential of vaccinia (346) cancer virus expressing purine nucleoside virus to deliver PNP based GDEPT in phosphorylase as a vector for tumour- nude mice with hepatic metastases directed gene therapy (in vivo) Adenovirus Fludarabine Gene therapy of hepatocellular This study showed superiority of PNP- (347) Phosphate carcinoma in vitro and in vivo in GDEPT over HSV-TK /GCV system in nude mice by adenoviral transfer of the treatment of hepatocellular the Escherichia coli purine nucleoside carcinoma (HCC) cell lines and tumour phosphorylase gene (in vitro and in xenografts vivo) 59

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Adenovirus Fludarabine Mechanisms of cell death induced by A mechanism study, which proved that (348) Phosphate suicide genes encoding purine PNP-GDEPT may be compared to HSV- nucleoside phosphorylase and TK- GDEPT based on its independence thymidine kinase in human from p53 and the Fas/FasL based cell hepatocellular carcinoma cells in killings in HepG2 and Hep3B cell lines vitro (in vitro) Liposome / Fludarabine Experimental studies on PNP suicide Liposomal delivery of PNP in human (349) Plasmid Phosphate gene therapy of hepatoma (in vitro hepatoma HepG2 cells is an effective and in vivo) way to express PNP and subsequent cell killing after pro-drug administration Plasmid 6-MPDR [Killing effect of PNP/MeP-dR PNP/MeP-dR system driven by AF0.3 (350) suicide gene system driven by an promoter results in tumour specific cell AFP promoter AF0.3 on AFP- killings in AFP-positive hepatoma positive hepatoma cells] (in vitro) HepG2 cells in both hypoxic and normoxic conditions Plasmid 6-MPDR Targeting gene therapy for This study demonstrated the successful (351) hepatocarcinoma cells with the E. coli use of chimeric human alpha-fetoprotein purine nucleoside phosphorylase (AFP) promoter, [HRE] AF for tumour suicide gene system (in vitro) specific killings in HCC cell lines Ovarian Plasmid 6-MPDR In vivo sensitization of ovarian In this ovarian cancer study, a high (308) cancer tumours to chemotherapy by efficacy of PNP-GDEPT was expression of E. coli purine demonstrated; significant tumour nucleoside phosphorylase in a small reduction was achieved even when 1 out fraction of cells (in vitro and in vivo) of 1000 cells expressed PNP. Compared to control animals a 30% increase in survival and 50% reduction in tumour size was achieved in mice implanted

with SKOV-3 tumours

Thyroid Plasmid / 6-MPDR Calcitonin-specific transcription and This study demonstrated that Adenoviral (352) cancer Adenovirus splicing targets gene-directed enzyme delivery of PNP gene under the 60

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prodrug therapy to medullary thyroid transcriptional control of a T2 promoter carcinoma cells (in vitro) (Ad.T2-PNP) is an effective way to kill medullary thyroid carcinoma (MTC) cells in a cancer- specific manner Neuoblasto Plasmid Fludarabine Neuroblastoma-specific cytotoxicity The study proved that a vector, in which (353) ma Phosphate mediated by the Mash1-promoter and PNP gene expression is driven by Mash1 E. coli purine nucleoside promoter can result a cell-specific phosphorylase (in vitro) toxicity in neuroblastoma cell lines

Bladder Retrovirus / Fludarabine Delivery of replication-competent The study demonstrated that replication- (354) cancer leukemia virus Phosphate retrovirus expressing Escherichia coli competent retroviral (RCR) vectors purine nucleoside phosphorylase based on murine leukemia virus in increases the metabolism of the combination with Fludara can prodrug, fludarabine phosphate and significantly inhibit the growth of pre- suppresses the growth of bladder established KU-19-19 bladder tumours in tumour xenografts (in vivo) nude mice Pancreatic Plasmid 6-MPDR Transcriptional tumour-selective In this pancreatic cancer study, (355) cancer promoter targeting of E. coli purine effectiveness of transcriptional targeting nucleoside phosphorylase for was demonstrated. The promoter pancreatic cancer suicide gene sequences of CEA or MUC1 were therapy (in vitro and in vivo) successfully used to derive PNP gene both in vitro and in vivo Plasmid 6-MPDR hTERT-targeted E. coli purine The hTERT promoter based PNP- (356) nucleoside phosphorylase gene/6- GDEPT demonstrated a siginificant cell methylpurine deoxyribose therapy for killing in a human pancreatic cancer cell pancreatic cancer (in vitro) lines, SW1990 61

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1.4.2.3 Conditionally replicating adenovirues

Cancer gene therapy clinical trials, especially those involving modulation of cancerous genes, have demonstrated limited therapeutic efficacy; this has been primarily attributed to inefficient gene delivery in situ (e.g. in p53 gene therapy clinical trial) (250).

Although, in situ amplification of the cytotoxic effects engendered by the bystander effects associated with GDEPT based therapies address this issue, pre-clinical/clinical data show effective delivery to remain as a primary limitation to efficacy. Hence, to increase the efficiency, researchers have explored the use of targeted replication- competent oncolytic viral vectors (e.g. conditionally replicating adenoviruses (CRAds) to carry these genes. These vectors lead to specific cancer cell killing via cancer specific oncolytic effects: this is generally achieved by preferential replication of virus in tumour cells either through modification of viral biology such that it only replicates in cancer cells through genetic modifications in the Ad genome to abrogate their replication in normal cells; or, through modifications to the viral tropism (transductional targeting) and lastly, through placing the viral replication genes (E1/E3/E4 genes) under tissue or tumour specific genes to regulate viral replication (transcriptional targeting).

Further, the cell killing can be enhanced by engineering a cytotoxic gene (e.g. GDEPT) or through introduction of anti-cancer host immune system stimulating gene (cytokines) into these vectors (357). Following the positive outcomes in preclinical studies, the safety and feasibility of CRAds have been established in numerous early clinical trials involving patients of head and neck, bladder, colorectal, pancreatic including ovarian cancer (358,359).

OC is especilly suited for such investigations; it represents a solid tumour contained within the ip cavity along with expression of targetable receptors and transducible cells.

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Indeed, CRAds have been evaluated in several preclinical and clinical OC studies. In a phase I clinical trial, the Onyx-015 Ad vector with E1B deletions to preferentially replicate in and kill p53 deficient cells, was administered i.p. to 16 patients with recurrent/refractory epithelial OC (244). The results showed an acceptable toxicity profile but unfortunately without clinically significant responses. In another study, successful use of another oncolytic adenovirus that selectively targets cancer cells defective in the retinoblastoma (Rb)/p16 pathway (through deletion of specific sequences from early E1A regions that bind to Rb gene), has been reported (360-363).

Although, successful systemic applications of CRAds in mouse models of different cancers have lead to some early optimism, but their transition to systemic use in the clinic is still limited by inadequate safety of these vectors. As a result, the current focus is to improve the therapeutic index of CRAds that can be achieved by two different approaches; either by the use of cancer/tissue specific promoters (transcriptional targeting) or/and modification of the viral tropism such that it infects only tumour cells and not the normal cells (e.g. CAR independent targeting (transductional targeting).

1.4.2.3.1 Oncolytic adenoviruses armed with gene therapy

Properties of an ideal oncolytic vector Tumour specificity (ability to infect cancer cells and not the normal cells) (through transductional and transcriptional targeting) Effective in situ amplification within the tumour cell and subsequently, within the tumour mass, through lateral dispersion to neighbouring tumour cells Potential to stimulate the host-immune system favouring cancer reduction Adequate capacity to carry various cytotoxic/immunostimulatory transgenes to induce cell killing Easy to engineer (to add to the therapeutic arms e.g. additional suicide genes) Easy to produce in high titres Potential to synergise with other forms of therapy Ability to evade immune response against the vector itself Acceptable toxicity profile

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Although significant inroads have been made in the development of CRAds, but their clinical use as a single agent has not yielded optimal efficacy. The common strategy used to circumvent this situation is to improve the ‘therapeutic arms’ of CRAds, mostly by employing the use of ‘suicide’ genes (e.g. HSV-tk, CD) or a pro-apoptotic gene (e.g.

BAX, p53, TRAIL, Caspases). In particular, CRADs armed with GDEPT systems like

CD (301,305,364) or HSV-tk (305,365-368) alone or combined (369) have been reported to have enhanced activity against cancers of prostate, colon and ovary.

Specifically, when used against OC (Ovcar-5), replication-competent bicistronic adenoviral vector in which CD and E1A gene expression were regulated by a TSP, L-

Plastin (L-Plastin-CRAd/CD) + pro-drug (5-fluorocytosine (5-FC), led to additive cytotoxic effects in vitro and improved survival of treated nude mice bearing subcutaneous OC tumours Vs. individual modalities (301).

1.4.2.3.2 Oncolytic adenoviruses and chemotherapy

The use of oncolytic adenovirus in combination with different forms of chemotherapy has been translated from preclinical studies to clinical trials for treating various cancers including OC (see Table 1.4) (370-372). Generally, when used together, the activity of the one or the other agent was augmented and greater anti-tumour effects were achieved involving known and/or unknown mechanisms (373). For these evaluations, chemotherapy has been delivered along with Ad vectors encoding mutation compensation genes, suicide genes (especially, GDEPT) and cancer specific oncolytic

Adenovectors (unarmed or armed with GDEPT) (Table 1.8). More recently, promising results from a Phase II trial of an oncolytic adenovirus ONYX-015 in combination with

5-flurouracil and cisplatin was reported in patients with recurrent head and neck squamous cell carcinoma (370,371). With regards to OC, a replication selective Ad

Chapter 1: Literature Review 65 virus (Ad5/3-delta24) in combination with either gemcitabine or epirubicin (common second-line treatment options for platinum-resistant OC) has shown greater therapeutic effects compared with the individual modalities (362,363). Impressive synergies have also been observed between oncolytic adenoviruses and taxanes (paclitaxel and docetaxel) against different cancer types in vitro and in vivo (164,374,375). CRAds with human uroplakin II promoter in conjunction with docetaxel led to synergistic antitumour efficacy in the OC cell line PA-1 and a mouse xenogeneic model of bladder cancer (165). Investigation of the mechanism involved in Ad transduction and taxanes have shown these beneficial synergies to be mediated via the ability of the taxanes to enhance Ad transduction coupled with vice versa enhancement of chemosensitivity of

Ad-transduced cells (164). Thus, combining oncolytic adenovirus and chemotherapy has the potential to improve therapeutic efficacy whilst maintaining an acceptable toxicity profile. However, a better insight into the cell killing mechanisms leading to these synergistic or additive effects would help decide the sequence of administration, thus allowing better management of the disease and a better clinical output.

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Table 1.8 Combination of Ad mediated-gene therapy and chemotherapy and ovarian cancer CHEMOTHERAPY STRATEGY/ STATUS AIM/PROTOCOL REF. PLUS TRANSGENE Molecular HSV/GCV plus Phase I Thymidine kinase gene therapy with concomitant topotecan (297,298) chemotherapy Topotecan chemotherapy for recurrent ovarian cancer. HSV/GCV plus In vivo Intraperitoneal adenovirus-mediated suicide gene therapy in (303) topotecan and or combination with either topotecan or paclitaxel in nude mice paclitaxel with human ovarian cancer. HSV/GCV plus In vitro Adenovirus mediated thymidine kinase gene therapy may (330) topotecan enhance sensitivity of ovarian cancer cells to chemotherapeutic agents Mutation Ad.p53 plus In vivo Combination therapy with SCH58500 (p53 adenovirus) and (376) compensation Cyclophosphamide cyclophosphamide in preclinical cancer models Ad.p53 plus In vitro Cooperative effect of adenoviral p53 gene therapy and standard (377) standard chemo chemotherapy in ovarian cancer cells independent of the (Taxol/Carboplatin) endogenous p53 status. Ad.p53 plus In vitro Effect of p53 gene transfer and cisplatin in a peritonitis (378) Cisplatin In vivo carcinomatosa model with p53-deficient ovarian cancer cells. Ad.p53 plus In vitro Adenovirus-mediated p53 gene therapy has greater efficacy when (379) cisplatin, and In vivo combined with chemotherapy against human head and neck, paclitaxel ovarian, prostate, and breast cancer. Ad.p53 plus In vitro/ Adenovirus-mediated p53 gene therapy and paclitaxel have (380) paclitaxel In vivo synergistic efficacy in models of human head and neck, ovarian, prostate, and breast cancer Ad.Bax plus In vitro Combination effect of adenovirus-mediated pro-apoptotic bax (381) Cisplatin/Taxol gene transfer with cisplatin or paclitaxel treatment in ovarian cancer cell lines Ad.Bax plus In vitro Pro-apoptotic treatment with an adenovirus encoding Bax (382) 66

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Chemotherapy enhances the effect of chemotherapy in ovarian cancer Ad.Bcl-Xs plus In vitro Synergistic efficacy of adenovirus-mediated Bcl-Xs gene therapy (383) cisplatin and cisplatin in ovarian cancer cell Oncolytic Oncolytic Ad5/3- In vivo Oncolytic adenovirus Ad5/3-delta24 and chemotherapy for (363) delta24 plus treatment of orthotopic ovarian cancer epirubicin and gemcitabine Ad5/3-Delta24 plus In vitro Combination of gemcitabine and Ad5/3-Delta24, a tropism (362) Gemcitabine In vivo modified conditionally replicating adenovirus, for the treatment of ovarian cancer Ad5/E1A plus In vitro E1A-mediated paclitaxel sensitization in HER-2/neu- (384) paclitaxel In vivo overexpressing ovarian cancer SKOV3.ip1 through apoptosis involving the caspase-3 pathway

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1.4.2.4 Transductional targeting

As discussed in previous section (see adenoviral tropism, section 1.4.1.1.1.2), Ad5 entry into the target cell is dependent upon CAR and integrin expression on the cell surface. These receptors, while downregulated in cancer cells, are abundantly expressed on liver cells. Hence, Ad based vectors display low infectivity in cancer cells while having significant tropism for liver, thus leading to hepatotoxicity. Consequently, Ad5 is considered a poor candidate for systemic gene therapy clinical trials. Several strategies have been designed to change the tropism of virus from native to alternate receptors having a preferential expression on cancer cells (385-387). A novel CRAd carrying RGD-4C (arginine-glycine-aspartic acid) in an HI loop (a region in the knob domain that connects the strands H and I) showed enhanced gene transductions in

OC cell lines (199,388-390). In addition, this vector showed CAR independent binding with relatively lower levels of neutralising antibodies compared to wild type, which may be associated with its higher therapeutic efficacy (391). Significant improvements were obtained when these vectors were further modified by inserting a polylysine (pk7) motif in the capsid region, exhibiting a higher efficacy in a subcutaneous tumour model

(392). In another study, a chimeric adenoviral vector (Ad5/3), which has a substitution of the Ad serotype 5 knob with type 3 knob was reported to enhance infection and subsequent oncolytic replication in OC (393,394). More recently, to avoid the Ad5 neutralising antibodies in humans, genetic modifications leading to ‘xenotype’ knob switching to non-human adenovirus (canine knob) have also been successfully evaluated (395).

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1.4.2.5 Transcriptional targeting

Cancer cell specific regulation of transgene expression is based on the realisation of basic transcriptional differences between a normal and deregulated cancer cell. Most gene therapy strategies used to date have employed some generic promoters such as

cytomegalovirus (CMV) Transgenes used with OC specific promoters and SV40 promoters. Reporter genes (GFP, Luc and LacZ) Although, these are Suicide gene (HSV-TK, CD, NTR, PNP) associated with a higher Pro-apoptotic (Bax, Caspases, GranzymeB) level of transgene Oncolytic (E1A and E1B) expression, their ubiquitous activity leads to gene expression in non-target normal tissues. CMV promoter has also been reported to be inactivated in vivo through promoter methylation

(396) and is prone to frequent downregulation in vivo (397). These issues pose major hurdles to their use in the clinic. Hence, to achieve specific killing of tumour cells, tumour-specific promoters that are overactive in cancer cells and not normal cells, have been developed to regulate therapeutic genes (398,399). There have been a growing number of potential genes whose overexpression or amplification is implicated in ovarian tumorigenesis but few of them have been defined for their promoter activity

(400). A number of OC specific promoters have been evaluated; e.g. those regulating L-

Plastin, SLPI, COX-2, Midkine, human telomerase reverse transcriptase (hTERT), ceruloplasmin, MucI /DF3 and Mesothelin genes. A list of candidate promoters, respective vector backbone and the subsequent cancer gene therapy studies is tabulated in Table 1.7. These have been used to regulate expression of reporter genes, suicide genes, genes facilitating apoptosis and genes responsible for Ad-mediated oncolysis

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(400). Specifically, Type II CRAds (Table 1.7) use TSPs to restrict viral replication to the cancer cells. Like any other approach, transcriptional activity of Type II CRAds is also dependent upon the promoter activity, which must be specific, strong and maintained in situ under different conditions within the tumour microenvironment e.g. hypoxia. Infact, CRAd activity on the basis of replication regulation by cancer-specific

L-Plastin (301), SLPI (401) and COX-2 (402,403) hasled to promising results in vitro and in vivo which were used to drive the expression of E1A, either alone or in combination to a suicide gene (301). Results from these studies have revealed that these promoters are able to restrict transgene expression to OC cells while sparing normal cells, thus improving their therapeutic index. Thus far, the preliminary preclinical findings have clearly proven that use of TSPs is a realistic approach and eventually may lead to development for treatment of clinical OC.

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Table 1.7 List of promoters used in ovarian cancer gene therapy

PROMOTER VECTOR TRANSGENE STATUS REF. L-plastin Ad Lac Z1 In vitro (404) LacZ/CD In vitro/in vivo (405) E1 gene In vitro (301) CD/E1 gene In vitro/in vivo Uroplakin Ad Oncolytic In vitro (165) Ceruloplasmin Ad Luc2 In vitro/in vivo (406) IAI.3B Ad Oncolytic In vitro/in vivo (407) GSTP13 Ad CD::upp4 In vitro/in vivo (300) Clusterin Ad Luc In vitro (406) Human Ad Luc In vitro (406) Glutathione Peroxidase MUC15 Ad LacZ/Bax In vitro/in vivo (408) COX-26 Ad TK In vitro/in vivo (398) Fiber modification In vitro/in vivo (403) RGD-4C7 Triple targeted In vitro/in vivo (402) E1/Delta24 /Sero3 Fiber modifications Midkine Ad TK In vitro/in vivo (398,400) HER-2/neu HER-2/neu In vitro (409) Telomersae Plasmid Luc In vitro (410-412) (hTERT8) Plasmid TK (suicide gene) In vitro (413) Plasmid CD and TK In vitro (307) Plasmid CD / TK + Pro-Cas-3 In vitro (414)

Ad NTR (suicide gene) In vitro/in vivo (313) Ad TK (suicide gene) In vitro (30) Ad Sodium iodide In vivo (415)

symporter PET9 reporter gene Ad Caspase-3 In vitro (416) OSP-110 Plasmid Luc In vitro (411,412,4 Retrovirus TK In vitro 17) hESE111 Plasmid Luc In vitro (418) KDR12/flk-1 - CD In vitro/in vivo (419) SLPI13 Ad Luc/ TK In vitro/in vivo (420) Ad Luc/ TK In vitro/in vivo (421) Ad E1A (5/3 chimeric) In vitro/in vivo (401) hE414 Plasmid Luc In vitro (411)

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CXCR-415 Ad Luc In vitro/in vivo (422) Survivin Plasmid Granzyme B In vitro/in vivo (423) MDR1 Ad CD::UPP In vitro/in vivo (304) Metallothionein Plasmid TK In vitro (424) Mesothelin Ad Luc In vitro (425) Luc/Chimeric 5/3 In vitro/in vivo (426)

1Lac Z, beta-galactosidase; 2Luc, Luciferase; 3GSTP1, glutathione S-transferase pi gene; 4CD:upp, cytosine deaminase gene and uracil phosphoribosyltransferase gene; 5Muc-1, mucinous gene-1; 6COX-2, cyclooxygenase-2; 7RGD-4C, arginine-glycine-aspartic acid motif-4; 8hTERT, human telomerase reverse transcriptase; 9PET, Positron emission tomography; 10OSP1, ovarian specific promoter 1; 11hESE1, human epithelium-specific ets transcription factor; 12KDR, kinase domain-containing receptor; 13SLPI, secretory leukoprotease inhibitor; 14hE4, human epididymis protein 4; 15CXCR-4, alpha chemokine CXC motif receptor-1

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1.5 Prostate cancer (PC): treatment related issues

Prostate cancer (PC) is the second leading cause of death in Australian men. It is estimated that in 2009, approximately 18,784 new cases and 3,283 prostate cancer- related deaths will occur in Australia (Based on Australian Institute of Health and

Welfare; AIHW projections). It is prevalent in men aged more than 65 years and is generally considered as the ‘disease of old people’. As the ageing population is increasing in Australia, PC will need considerable attention in coming years. At present, approximately 28% of men are over the age of 50 and 12% over the age of

65 years. It is projected that by 2036, 6.3 million Australians will be aged 65 years or over, representing a quarter of the nation’s population (427,428) (www.aihw.gov.au).

Although initial screening has been revolutionized with the introduction of prostate specific antigen test (PSA), the accuracy of PSA based diagnosis is still controversial.

The localized form of PC can be cured at a high rate using radical prostatectomy or radiation. At the time of diagnosis, many patients still present with the aggressive form of the disease that is generally associated with metastasis. Studies to assess the molecular basis of PC progression have led to identification of some genetic factors that determine whether a cancer will remain indolent or turn aggressive eventually, but these data need further studies for their confirmation (429,430). A fraction of patients initially treated with primary curative therapy will develop metastases, a stage which is often treated with androgen ablation therapy (431-433). Historically, in a noble prize winning discovery, Huggins et al were the first to report that androgen ablation therapy could cause regression of primary and metastatic androgen-dependent prostate cancer (434).

But later studies have shown that the role of this therapy is palliative rather than curative and most patients undergoing hormone depletion eventually develop aggressive

Chapter 1: Literature Review 74 cancers that are hormone refractory (433-435). Depending on the clinical presentation, the aggressive form of disease has a median survival of one year with chemotherapy

(436,437).

1.6 Role of chemotherapy in treating hormone refractory prostate cancer (HRPC)

(more recently, castrate resistant prostate cancer CRPC)

Until early 1980s, it was believed that chemotherapy had no role in treating patients with HRPC largely due to chemoresistant nature. There was also concern that aged patients would not tolerate the toxicities associated with chemotherapy. In an earlier study, Eisenberger et al (438) indicated that there is a very poor overall response rate of

4.5% from 17 randomised chemotherapy clinical trials involving 1,464 patients.

Petrylak et al (439) also reviewed 26 chemotherapy clinical trials performed between

1987-1991 but this time with a marginal improvement in response rate of 8.7%. These results were disappointing, however, after 26 years, Logothetis et al (440) reported one of the earliest papers of the role of chemotherapy in advanced HRPC. Since then a significant change in trends has commenced, primarily due to introduction of new chemotherapeutic agents and novel combination drug regimens (137,436,441,442).

Following a landmark clinical trial in advanced stage HRPC patients (443), the combination of Mitoxantrone plus prednisone was approved by the US Food and Drug

Administration (FDA) as a palliative standard for care. Although, these compounds were not associated with any survival advantage, their use established that chemotherapy could improve the clinical outcome in advanced stage HRPC. In addition,

Chapter 1: Literature Review 75 recent results from two independent taxane-based chemotherapy studies TAX327 and

SWOG9916 (Southwest Oncology Group) have revealed a marginal survival benefit in patients with HRPC (444,445) over mitoxantrone plus steroids. After the successful results of these trials, US FDA approved docetaxel and prednisone as a first line treatment for patients with HRPC. The use of docetaxel based drug regimens is considered as a milestone in systemic chemotherapy but still the median survival of these patients has not gone past 18 months exhibiting a clear need for improved treatment regimens.

1.6.1 Docetaxel: mode of action in PC

As described in Section 1.3.1, docetaxel has displayed remarkable activity against different cancer types including prostate cancer, in vitro as well as in vivo. A number of mechanisms have been postulated to explain the cell killing properties of docetaxel but inhibition of tubulin depolymerisation is considered to be the primary mode of action (135,446-449). Docetaxel associated disruption in microtubule organization activates both intrinsic and extrinsic cell death pathways. These pathways are mainly triggered by the release of various mitochondrial components including anti- and pro- apoptotic members of the BCL-2 family (446,447). BCL-2 is an oncogenic protein that works as an apoptosis inhibitor in diffrent cancer types (450,451) and has a much broader role in the pathogenesis and progression of prostate cancer (452,453). Several preclinical studies have recorded increased expression of BCL-2 after hormone ablation therapy (454-456). This has suggested that BCL-2 may play an important role in the transition from androgen dependence to androgen independence and hence, its expression is used as a prognostic marker for HRPC patients (457,458). Docetaxel

Chapter 1: Literature Review 76 inactivates BCL-2 by phosphorylation resulting in increased apoptosis, which may be partially due to loss of BCL-2 anti-apoptotic function or due to decreased BCL-2 binding to BAX protein (459-461). Based on these preliminary studies, the predictive value of BCL-2 in docetaxel treated patients has also been assessed (457,462).

Following these studies, a number of combination therapy approaches have been reported where docetaxel was combined with BCL-2 antagonists to improve the therapeutic outcome (For details see docetaxel combination therapy, Section 1.6.3)

(463). Although, loss of BCL-2 function with docetaxel treatment is considered to be an important cell killing mechanism, in a recent study it was shown that docetaxel anticancer activity in DU145 prostate tumour xenografts was independent of BCL-2 activity (464) suggesting involvement of other mechanisms. Considering this, an understanding of other cell killing mechanisms potentially involved in docetaxel activity is important; this combined with what is already known may direct the design and rationale of new combination therapy approaches.

1.6.2 Docetaxel as a monotherapy for HRPC

Docetaxel is one of the most promising taxanes used to treat HRPC (465). Its role as a single agent therapy has been established in several clinical trials (466,467) (Table 1.9).

In one of the earliest clinical trials, Picus et al (468) treated 35 HRPC patients with docetaxel alone at 75 mg/m2 every 3weeks. Significant results were obtained as 28% of patients had an objective response, 46 % had a decline in PSA greater than 50% and the median survival was found to be 27 months. In a parallel study, using the same dose schedule, comparable levels of objective responses and a decrease in PSA levels were recorded (457). Further, Berry et al assessed the efficacy and tolerability of docetaxel monotherapy in sixty patients with progressive metastatic prostate cancer in another

Chapter 1: Literature Review 77 phase II trial (469). Compared to previous studies, a lower dose of docetaxel (36 mg/m2q) was administered and all patients received dexamethasone prior to docetaxel infusion. This study concluded that lower doses of docetaxel could also achieve considerable response rates and more importantly with a decreased toxicity profile. A similar study conducted by Beer et al (470) further confirmed that docetaxel monotherapy was effective with an acceptable tolerability in HRPC patients. More recently, Gravis et al (471) treated 30 symptomatic patients with HRPC with 35mg/m2q of docetaxel weekly for 6 consecutive weeks up to a maximum of 24 weeks. From the data, it was concluded that weekly docetaxel demonstrated significant improvements in clinical benefit response and a better quality of life, half of the patients achieved a 50%- or greater PSA decline and 46% of patients achieved a positive pain response.

Moreover, the therapy was well tolerated with mild neutropenia being the only noticeable adverse effect. The role of docetaxel monotherapy as an adjuvant or neo adjuvant therapy has also been tested in some clinical trials. In these studies, docetaxel was used in HRPC patients as neo-adjuvant therapy (472), before or after radical prostatectomy (473,474) and after hormonal therapy (475). In all these categories of patients, considerable efficacy with respect to symptom palliation, tumour response, time to progression and survival was observed with an acceptable toxicity profile.

Chapter 1: Literature Review 78

Table 1.9 Docetaxel alone or in combination chemotherapy regimens for HRPC TYPE DOCETAXEL DOSE OTHER AGENT DOSE STAGE/ PATIENTS PSA Overall MEDIAN YEAR STATUS RESPONSE1 Response SURVIVAL REF. (%) Rate (%) (MONTHS) Single Agent (75 mg/m2q)2 every 3 wks3 NA4 Phase II 35 46 24 27 1999 (468) 75 mg/m2q every 3 wks NA Phase II 21 38 29 67% at 15 1999 months (457) 36 mg/ m2q wks for 6 of 8 wks NA Phase II 60 41 33 9.4 2001 (469) 36 mg/ m2q wks for 6 of 8 wks NA Phase II 25 46 40 9.7 2001 (470) 35 mg/ m2q wks for 6 of 8 wks NA Phase II 30 48 28(cSD5) 20 2003 Combination (471) Therapy 70 mg/ m2q every 3 wks Estramustine 280 mg TTD6 Phase II - 68 55 77% at 1 year 2000 days 1–5 ASCO7 (476)

70 mg/ m2q every 3 wks Estramustine 280 mg TTD Phase II 47 68 50 20 2001 days (477) 1–5 + hydrocortisone 40 mg/day 70 mg/ m2q every 3 wks Estramustine 280 mg every Phase II 42 45 20 13.5 2002 6 h×5 doses (478) and Coumadin 2mg daily TAX 327 75 mg/ m2q every 3 wks Prednisone 10 mg/day Phase III 1006 45 12 18.9 2004 30 mg/ m2q wks for 5 of 6 wks Prednisone 10 mg/day 48 8 17.3 (444) SWOG8 60 mg/ m2q every 3 wks Estramustine 280 mg TTD Phase III 770 50 17 18 2004 days 1–5 (444) 1PSA response: decline in Prostate Specific Antigen 50%; 2mg/m2q, milligram per meter square; 3wks, weeks; 4NA, not available; 5cSD: stable disease; 6TTD: three times a day; 7ASCO, American Society for Clinical Oncology; 8SWOG, South West Oncology Group (Adapted from Mancuso et al 2007 (479) 78

Chapter 1: Literature Review 79

1.6.3 Docetaxel in combination with other therapies

Although, docetaxel is the only drug with notable activity in HRPC patients, its use as a single agent has not improved median survival significantly. To achieve better clinical results, a number of approved and novel investigational agents have been explored in combination with docetaxel (Table 1.9 and 1.10) Clinical applications of combination drug regimens are aimed at improving the therapeutic outcome of the disease and the quality of life of the patient. At the preclinical level, agents are selected on the basis of their cell killing mechanisms, which generally differ from those of docetaxel in order to achieve a synergistic or additive effect. A variety of therapeutic agents has been evaluated in combination with docetaxel for the treatment of different forms of prostate cancer, e.g. traditional chemotherapeutic drugs, molecular targeted agents including inhibitors of angiogenesis and EGFR family, vaccines and anti-sense BCL-2 oligodeoxynucleotides (Table 1.10). Most of the selected agents have already been translated to clinical studies with significant outcomes. The most promising combinations are those with traditional chemotherapy agents, primarily estramustine, prednisone and mitoxantrone. Following its FDA approval in 1981 for use in prostate cancer, estramustine has shown moderate activity in HRPC patients. The rationale behind docetaxel and estramustine combinations is to achieve higher tumour cell killing via inhibition of microtubule function. Petrylak et al performed a phase I/II (480,481) trial of this combination to achieve a significant objective response, and a decrease in serum PSA levels but the drug regimens were associated with cumulative toxicities mainly grade ¾ neutropenia and hyperglycemia. The studies established that combined drug regimen of docetaxel and estramustine is active and well tolerated in patients with

HRPC. Docetaxel dose of 70 mg/m2 in minimally pretreated (MPT) patients and 60

Chapter 1: Literature Review 80 mg/m2 in extensively pretreated EPT patients was recommended for future studies.

Following these studies, a number of phase II trials have been conducted to evaluate the potential role of docetaxel-estramustine combination in treating prostate cancer with positive outcome (478,482-486). In these trials drug regimens at different doses and schedules were implemented to select those with the maximum clinical benefit.

Impressive results from some earlier studies have also lead to the foundation of Phase

III trials evaluating the efficacy of docetaxel with either estramustine or prednisone to treat HRPC patients (see Section 1.6.4). More recently, successful use of this combination as a second line therapy to treat HRPC patients resistant to docetaxel was reported (487). Docetaxel and estramustine are both microtubule inhibitors with an almost similar mode of action; thus, combinations with a third modaliy have been explored to assess if synergistic or at least an additive interaction would result. These include hydrocortisone (477,488,489), prednisone (490,491), carboplatin (492-494), calcitriol (495), vinorelbine (496), celecoxib (497), thalidamide (498), exisulind (499), enoxaparine (500), zoledronic acid (501). Most of these combinations result in an enhancement in cancer cell killing, but importantly some of these compounds just relieve pain and reduce bone fractures (zoledronic acid) rather than improving tumour cell killing.

Chapter 1: Literature Review 81

Table 1.10 Other drugs/therapeutic agents used in combination with docetaxel for the treatment of prostate cancer

DRUG/INHIBITOR TYPE REF.

TRADITIONAL CHEMOTHERAPY

Estramustine Estrogen derivative (483,492,502) Prednisone Synthetic corticosteroid hormone (444,445,503) Hydrocortisone Corticosteroid hormone (477,488,504) Mitoxantrone Type II Topoisomerase inhibitor (444,505,506) Calcitriol Biologically active form of vitamin D (507-509) Carboplatin Platinum compound (492,494,510) ANTI-ANGIOGENESIS THERAPY Thalidomide Angiogenesis inhibitors; block the (498,511-513) TNP-470 growth of new blood vessels supplying (514) Flavopiridol tumours with vital oxygen and nutrients (515,516) Sunitinib malate (517) Bevacizumab Monoclonal antibody; targets vascular (518,519) endothelial growth factor (VEGF) receptor ANTI-EPIDERMAL GROWTH FACTOR RECEPTOR DRUGS Erlotinib Selective inhibitors of epidermal growth (520-522) Gefitinib factor receptor (EGFR) tyrosine kinase (523-526) Cetuximab domain (517) Pertuzumab (527)

OTHER NOVEL MOLECULAR TARGETED DRUGS Imatinib Platelet-derived growth factor (PDGF) (528-532) receptor inhibitor Exisulind Apoptosis inducer;acts by inhibiting the (499,533- enzyme cyclic guanosine monophosphate 535) phosphodiesterase Capecitabine A prodrug, enzymatically converted to 5- (536-539) fluorouracil in the tumour tissue, where it inhibits DNA synthesis Bortezomib Proteasome inhibitor (540-543) Celecoxib Non-steroidal anti-inflammatory drug (497,544) (NSAID) drug; selectively inhibits Cyclooxygenase-2 (COX-2) Atrasentan Endothelin A receptor (545) RAD001 (Everolimus) Mammalian target of rapamycin (mTOR) (546) inhibitor PD98059 ERK inhibitor (463)

Chapter 1: Literature Review 82

VACCINE THERAPY GnRH-DT vaccine Gonadotropin releasing hormone vaccine (547) PSA (Prostate Specific Prostate-specific antigen gene based (548) Antigen) vaccine vaccine Recombinant vaccine Antigen-specific vaccination (549) BCL-2 TARGETED THERAPY Antisense BCL-2 Antisense oligodeoxynucleotides therapy; (550) oligodeoxynucleotides targets anti-apoptotic gene BCL-2 G-3139 (oblimersen) (551-554)

1.6.4 Docetaxel in combination regimens agsinst PC: Phase III trials

The efficacy and safety of docetaxel based combination regimens have been assessed in a number of phase III trials for treating prostate cancer patients (444,445,555-557). Of these, the results published by Tannock et al (TAX 327) (444) and Petrylak et al

(SWOG 9916) (445) have received considerable attention since these are the first to show any survival advantage in HRPC patients.

TAX327 was an international, multicentre randomized phase III study, which compared docetaxel/prednisone with mitoxantrone/prednisone in metastatic hormone-refractory prostate cancer patients. A total of 1006 patients were randomized to receive mitoxantrone (12 mg/ m2q every 3 weeks), and docetaxel, three weekly (75 mg/ m2q every 3 weeks) or weekly (30 mg/ m2q for 5 out of 6 weeks). In addition to these drug regimens, all patients received 5 mg of prednisone twice a day. The patients in the three-weekly docetaxel/prednisone treatment arm showed a median survival of 18.9 months compared with 16.5 months for those treated with mitoxantrone/prednisone,

Chapter 1: Literature Review 83 with a 24% reduction in the hazard of death (P = 0.009). The differences in the median survival in the other treatment arms were not statistically significant (p=0.36). There were also significant improvements in patient’s pain response (35% versus 22%;

P=0.01) and their quality of life, (22% versus 13%; P=0.09) when 3-weekly docetaxel/prednisone treatment arm was compared with the mitoxantrone/prednisone treatment arm (444).

In a parallel phase III study (SWOG 9916), the combination of docetaxel and estramustine demonstrated a survival advantage over the traditional combination of mitoxantrone and prednisone (445). In this study 770 HRPC patients were randomly assigned to one of the combination treatments; either 3-weekly docetaxel plus estramustine (docetaxel 60 mg/ m2q incresed to 70 mg/ m2q on day 2 and estramustine

280 mg three times a day on day 1-5) or mitoxantrone plus prednisone (mitoxantrone 12 mg/ m2q increased 14 mg/ m2q and prednisone 5mg orally twice a day). The results from this phase trial demonstrated an improvement of 2 months in the median survival in docetaxel-containing arm (median 18 months vs. 16 months) with a significant 20% reduction in the mortality risk (P=0.01).

The conclusion derived from these studies is that docetaxel-based combination regimens can improve median survival and pain response in HRPC patients. A combination of 3-weekly docetaxel plus prednisone regimen has finally been accepted as standard treatment for patients with androgen-independent disease (13).

Chapter 1: Literature Review 84

1.7 Gene therapy and prostate cancer

1.7.1 Tackling prostate cancer heterogeneity or ‘robustness’

The clinical failure of cancer therapy is often related to the heterogeneous and ‘robust’ nature of the disease (558,559). Understanding the molecular pathogenesis of cancer is crucial for developing rational based gene therapy approaches. ‘Robustness’ is an acquired feature of prostate cancer, which is related to its ability to survive even under different forms of stress or pressure that may be either intrinsic (internal genetic instability) (560) or extrinsic (some form of therapy e.g. chemotherapy). A simplistic approach to control this robustness would be to target prostate cancer heterogeneity, which is a marked feature of prostate cancer disease progression (561,562). Due to the genetic and phenotypic heterogeneity, advanced stage or metastatic prostate cancer is often considered as a group of diseases even within the same individual (563).

Chapter 1: Literature Review 85

1.7.2 Potential for prostate cancer gene therapy

Based on the biology and the nature of the disease, PC is considered ideal to test gene therapy based treatments. Targeted gene therapy either alone or in combination to other modalities is an attractive option for PC therapy. To support this, recently, a significant increase in clinical trials related to PC gene therapy has occurred (564,565).

Prostate cancer is an ideal model for gene therapy

Prostate is a non-essential organ after reproductive years; treatment related effects on

prostate will not have a significant impact on patient’s life

Easy access for in situ delivery using transrectal, transperitoneal, or transuretheral

approaches

Tumours grow slowly, which allows enough time for therapeutic evaluation or

sequential administration of therapeutic modalities used in combination gene therapy

Availability of biomarkers (e.g. PSA) to evaluate the clinical or therapeutic benefit

Availability of tumour specific promoters (e.g. PSMA/Pb based) for cancer targeting

Overexpression of cancer specific genes specifically the membrane receptor

expression that is favorable for transductional targeting e.g. Her-2/neu

1.7.3 Gene therapy in combination regimens and PC

Most combination therapy approaches available to date have attempted to address the issue of cancer heterogeneity; for example, the choice of individual modalities in chemotherapeutic combination designs are based on Goldie-Coldman’s hypothesis of combining non-cross-resistant regimens (566,567). A careful analysis of the proposed

Chapter 1: Literature Review 86 mathematical models clearly dictates the need for the development of novel combination approaches with better drugs or targeted therapies to address the issue of drug resistance (568,569). As discussed above, different chemotherapeutic agents have been used in combination to treat HRPC patients, while some are effective, but only for a limited time. One of the major drawbacks of combination chemotherapy is the combined overlapping toxicity, which severely affects the quality of life. Moreover, given that PC is more prevalent in older aged men; they are relatively ill equipped to undergo toxic and intolerable chemotherapy drug regimens (570,571). Clearly, carefully designed combination regimens with a higher therapeutic index are needed to extend the duration of therapeutic response and to improve overall survival in patients with advanced PC. Gene-therapy can be targeted specifically to cancer with lowered side effects and can potentially generate a long-term response (e.g. immunostimulatory genes). Furthermore, use of cytoreductive gene therapy such as the use of cancer specific oncolytic adenoviruses, has the potential to eradicate tumour mass using more than one mechanism of killing of cancer cells (358,359). This can significantly reduce the chances of acquired resistance.

1.7.4 Sites of PC gene delivery

The clinical and pre-clinical studies reported to date have used both in situ and systemic approaches for delivery of therapeutic genes. For clinically localized PC, gene therapy approaches that directly deliver the therapeutic genes into the prostate tumours have been preferred (572-575). However, while in situ delivery of gene therapy leads to tumour cell death; it can also lead to toxic side effects on the non-target prostate tissue.

However, this is not expected to impair the life of elderly patients significantly as the

Chapter 1: Literature Review 87 prostate is a non-essential organ, after reproductive years. Advanced stage or metastatic

PC has limited treatment options leading to a high mortality rate. A variety of novel agents like calcitriol, celecoxib, thalidamide, exisulind, enoxaparine have been explored

(576), but targeting cancer at multiple locations is still a big challenge. Consequently, a selective cancer gene therapy, which can systemically deliver its therapeutic effects at distant metastatic sites, may be expected to improve the clinical outcomes of this disease. A number of studies have explored the use of systemic cancer gene therapy

(564,565,577,578) but the efficacay to date is limited largely due to inefficiency and non-specificity of gene delivery by currently available vectors (579,580).

1.7.4.1 Gene delivery systems

Both viral and non-viral vectors have been successfully used to deliver therapeutic or reporter genes in cancer cells. The advantages and disadvantages of some of the important gene delivery systems have been discussed in Table 1.2. For PC therapy, at a clinical and pre-clinical level, viral vectors have displayed greater efficiency, compared to their non- viral counterparts (577). These include adenovirus, retroviruses, adeno- associated viruses, poxviruses, herpes viruses and reoviruses (577,581). Given that PC contains a mixture of dividing and non-dividing cell populations (582), effective gene delivery can only be ensured by using a vector that targets both of these cell types. Not surprisingly, Adenoviral vectors that effectively infect dividing and non-dividing cells have been those most explored for prostate cancer gene therapy (583) and their successful application as a gene delivery system (non-replicative) or as a cytolytic agent

(CRAds/Oncolytic) has been reported in several PC targeted clinical and pre-clinical studies (565,577,584) However, their use against clinical disease is still limited (585) primarily due to inherent immunogenecity of these vectors. Although, a number of non-

Chapter 1: Literature Review 88 viral vectors such as naked DNA, liposomes, cationic amphiphiles and more recently nanoparticles have been reported to address these issues, only few of them have shown promise and some are still in the early stages of development (586,587).

1.7.5 PC as a molecular target

At a molecular level prostate cancer pathogenesis and tumorigenesis is related to a number of genetic changes, which mainly lead to the functional loss of tumour suppressor genes, overexpression or amplification of a number of oncogenes and activation of various antiapoptotic pathways (306,588-591). An increasing ratio of antiapoptotic genes to pro-apoptotic genes often results in a favorable tumour environment (592,593). PC tumours frequently switch to hypoxic condition as a protective measure from different forms of therapies (594,595). Genes involved in these molecular events, which lead to the initiation, development, progression and maintenance of PC may serve as a potential target and hence, underpin the strategy design for prostate cancer molecular gene therapy.

1.7.6 Gene therapy approaches for the treatment of prostate cancer

Depending upon the type of the therapeutic gene or vector used, a wide variety of gene therapy approaches has been designed for use either alone or in combination with other modalities. There are five major types of strategies to target prostate cancer (Figure

1.9). The basic rationale behind these approaches has already been discussed (see

Section 1.4.2); only approaches relating specifically to prostate cancer gene therapy are discussed in this section.

Chapter 1: Literature Review 89

Gene Therapy Approaches for the Treatment of Prostate Cancer

Mutation Molecular Oncolytic/ or Genetic Anti- Compensation Chemotherapy Virotherapy Immunotherapy Angiogenesis

Reactivation of TSG; p53, Combination of ‘non-toxic Trancriptionally and/or Tumour vaccination; e.g. Targeting tumour p16, p21, PTEN, BRCA-1. pro-drug’ and pro-drug transductionally targeted Sipuleucel-T vasculature Induction of cytokine Delivery of angiogenesis converting enzyme gene; replication competent Inactivation of anti- expressing genes; inhibitors apoptotic genes and HSV-tk/GCV PNP/Fludara oncolytic viral vectors; interleukins, GM-CSF, e.g. Angiostatin, TNF, IFN alpha and CD/5FC or 5FU ONYX-015 Vasostatin, oncogenes; BCL-2, K-ras, gamma c-myc, Her-2/neu. CDUPRT/5FC or 5FU CV706 Induction of immune Endostatin, NTR/CB1954 Ad5/3-delta24 stimulatory genes; MHC-1, Interferons Induction of apoptotic CTLA4 genes; caspases, BAX

Chemotherapy Radiation Surgery Other modalities

Gene Therapy as a multi-modality approach

89 Figure 1.9: Gene therapy approaches for PC treatment

Chapter 1: Literature Review 90

1.7.6.1 Mutation compensation gene therapy

Replacement of tumour suppressor genes, inactivation of oncogenes and induction of pro-apoptotic genes are some major gene therapy approaches used to treat localized and advanced stage PC. Given that functional loss of a variety of TSGs has been implicated in the development and progression of prostate malignancy such as p53, p21, PTEN,

(596-598), replacement of these genes with normal genes is expected to have a potential therapeutic role. To date, a number of clinical and pre-clinical gene therapy strategies have demonstrated that the upregulation of TSG expression including p53 (599-603), p21(601,604), PTEN (600,605-607), DLC1 (608) and C-CAM1(609) may have a curative role in prostate cancer.

Additionally, amplification or overexpression of a variety of oncogenes is frequently associated with prostate cancer progression (590,591); inactivation of these oncogenes using primarily antisense approaches has been exploited for therapy. More recently, phase I/II trials have demonstrated safety and efficacy of specific BCL-2 antisense oxynucleotides used either alone or in combination with chemotherapy for the treatment of HRPC patients (551-553). In addition, strategies downregulating oncogenes, such as c-myc (554,610-612), C-raf (613), c-met (614), Her-2/neu (615,616) have shown significant pro-apoptotic activity which further led to tumour regression in preclinical models.

Prostate cancer cell death can be achieved in a controlled, regulated fashion through a number of cellular apoptotic pathways. Gene therapy approaches that can favourably activate various intrinsic or extrinsic apoptotic pathways have demonstrated expression of different caspases can force prostate cancer cells to undergo apoptosis (617-619).

Alternatively, overexpression of proapoptotic BAX and Bad (BCL-2 gene family)

Chapter 1: Literature Review 91 resulted in a significant anti-tumour response in vitro and in vivo (620-625).

Additionally, the apoptosis inducing Fas ligand (620), tumour necrosis factor (TNF)- alpha (626), and TNF- related apoptosis inducing ligand (TRAIL) (620,627), have shown efficacy against PC.

1.7.6.2 Gene Directed Enzyme Pro-drug Therapy (GDEPT) and PC

Molecular therapy engendered by GDEPT is a tangible option for the treatment of prostate cancer. The mechanisms, advantages and disadvantages of GDEPT and different enzyme/pro-drug systems have been discussed in Section 1.4.2.2. For PC gene therapy, several combinations of non-mammalian enzymes/prodrugs have been explored (reviewed in (628). The most promising among them are thymidine kinase from Herpes Simplex virus (HSV-tk), E coli or yeast derived enzymes e.g. cytosine deaminase (CD), uracil phosphoribosyl transferase (UPRT), or a fusion of the two genes

(CDUPRT), purine nucleoside phosphorylase (PNP), and nitroreductase, and the human enzyme, cytochrome P450 (CYP). Generally two classes of pro-drugs have been exploited in GDEPT: antimetabolites, such as GCV, ACV or alkylating agents, e.g., cyclophosphamide. Both of these classes have their own advantages and disadvantages

(see Table 1.5). Drugs, which are clinically proven, are preferred as prodrugs over others due to complex regulatory issues. Some of key GDEPT systems in context of PC therapy are discussed below.

1.7.6.2.1 Herpes Simplex Virus -thymidine kinase (HSV-tk) and prodrugs

The HSV-tk/GCV is one of the most widely used GDEPT systems in prostate cancer gene therapy. The enzyme HSV-tk converts pro-drugs (GCV or ACV) to their toxic forms, which can result in prostate cancer cell death by apoptotic and non-apoptotic

Chapter 1: Literature Review 92 mechanisms. The therapeutic effects of this approach were successfully demonstrated in a wide variety of PC cell lines and animal models (629-632). Subsequently, the efficacy and safety profile of this system was assessed in a phase I-II trial in patients with clinically localised PC (633). The treatment included intraprostatic injections of virus

(one to four) containing HSV-tk followed by two weeks of GCV treatment. The results confirmed a favorable systemic and local antitumour immune response, antiangiogenic effect, and induction of apoptosis (633). In a Japanese phase I study, a decrease in PSA levels was achieved with Ad mediated HSV-tk/GCV in patients suffering from local recurrence of PC after hormonal therapy but with no metastasis (634). In a preclinical study, a PC specific mouse caveolin-1 (cav-1) promoter was used to achieve tumour specific cell killing with acceptable toxicities in an orthotopic mouse prostate cancer model (635). In a subsequent phase I study, PC patients were injected with Ad vector carrying osteocalcin promoter-driven HSV-tk in PC lymph nodes and bone metastases followed by GCV treatment (636). Although, a favorable tumour specific response was achieved with a tolerable toxicity, the levels of osteocalcin driven HSV-tk were compromised, suggesting that further enhancement of gene delivery would be crucial in future studies. More recently, a number of new combination approaches have been proposed to enhance the PC cell killing effects of this GDEPT system. Specifically, additional therapeutic benefits have been achieved when this therapy was combined with castration (637), radiation therapy (638-640), immunotherapy (641-643) or virotherapy (641,644-647).

Chapter 1: Literature Review 93

1.7.6.2.2 Cytosine deaminase (CD) and 5-fluorocytosine

Cytosine deaminase (CD) is the second most widely exploited gene for GDEPT studies in PC (648). Bacterial CD gene products can convert a non-toxic 5-fluorocytosine (5FC) into the toxic metabolite 5-fluorouracil, which can further result in tumour cell killing by inhibiting RNA and DNA synthesis (48, 85). The effects of CD-GDEPT have been successfully studied in vitro and in vivo using several prostate cancer models (649-652).

In addition to this, a phase I study conducted in patients with locally recurrent PC has evaluated the safety and toxicity of this therapy in combination with HSV-tk GDEPT

(638). CD-GDEPT has shown some considerable advantages over HSV-tk system as

5FC and 5FU can penetrate tumour cells more effectively compared to GCV by passive diffusion and can also expand the local toxic effects to neighbouring cells without using cellular connexins. It has also been reported that when UPRT was used in conjunction with CD and 5FC, GDEPT was more effective than CD-GDEPT alone against DU145 human prostate cancer cells (651). The use of CD-GDEPT to sensitise cells to radiation therapy has been reported in a variety of cancers (648). More specifically, therapeutic benefits of a combination of CD-GDEPT and irradiation have been shown in mice with

PC in several studies (653,654). The successful results of these preclinical studies have been translated to the clinic; with published reports of PC phase trials that have used therapeutic modalities of CD-GDEPT either alone or in combination to HSV-tk/GDEPT with or without irradiation (638,655)

1.7.6.2.3 Purine nucleoside phosphorylase (PNP) and prodrugs

PNP-GDEPT strategy is an effective approach to treat PC. The system involves PNP based enzymatic conversion of pro-drugs, fludarabine phosphate and 6-methylpurine

Chapter 1: Literature Review 94 deoxyriboside (MPDR) to their toxic metabolites. This is associated with an extensive bystander effect, which attains very efficient cell killing (327). Since, the PNP-GDEPT based cell killing is independent of proliferation status of cancer cells (348), it is an additional advantage in the context of PC where smaller proportion of cells may be in S- phase (582). Although HSV-tk based GDEPT has a very widespread application in PC therapy PNP-GDEPT may offer additional advantages as follows: (334,335). First,

PNP-GDEPT induces a more potent bystander effect than any other GDEPT system since its cell killing properties are not dependent upon cell to cell based junctions or connexins, which are often downregulated in cancer cells. Second, apoptosis induction as a result of PNP-GDEPT, is independent of p53 status (348) as shown by cell killing in the prostate cancer cell lines (340) LNCaP (wild type p53) and PC-3 (p53 null)

(656). Since the cancer progression is often associated with mutations in the p53 gene in early as well as late stage PC (657,658), PNP-GDEPT could be an effective therapy in patients having an aberrant expression of p53. When compared with HSV-tk/GCV,

PNP/GDEPT showed better therapeutic affects both in vitro (334) as well in vivo (335).

PNP-GDEPT was highly effective when the PNP gene was delivered by an ovine atadenovirus (now in phase I trial) in both androgen-dependent and HRPC cell lines grown as xenografts in nude mice (186) or in immunocompetent mice (337). In addition to this, PNP-GDEPT treatment was also associated with significant suppression of PC progression and improved survival in immunocompetent TRAMP mice (338).

Furthermore, PNP-GDEPT when tested in an aggressive RM1 tumour model suppressed local PC growth and also inhibited the formation of lung metastases by a distant bystander effect (339). Use of PC-specific promoters such as PSA and rat probasin promoter has been successfully exploited in a number of preclinical studies (335,336).

In particular, the use of the Pb promoter together with an enhancer from the PSMA gene

Chapter 1: Literature Review 95 allows targeting of androgen-independent as well as androgen-sensitive cells (Wang, et al, our lab). It is anticipated that these promoters will eventually play an important role in the design of novel gene therapy approaches, which may possibly combine PNP-

GDEPT and oncolytic viruses/Virotherapy to achieve a better a therapeutic effect.

1.7.6.2.4 Other GDEPT systems

Other GDEPT systems using genes nitroreductase (NTR) (318,659-661) or cytochrome p450 (662,663) have also been explored with favourable outcomes against PC.

Although, there are some new and relatively less developed GDEPT systems such as the ones based on deoxycytidine kinase (dCK), Pseudomonas carboxypeptidase and horseradish peroxidase enzymes, they have yet to find applications in PC targeted gene therapy approaches.

1.7.6.3 Virotherapy (oncolytic viral vectors)

The basic theory and the rationale behind the development of oncolytic and conditionally replicative adenoviruses (CRAds) for cancer therapy have been discussed in Section 1.4.2.3. Hence, specifically, gene therapy exploring the use of oncolytic viruses for PC treatment is discussed in this section. Of several oncolytic viruses that have been exploited for their use in cancer gene therapy (reviewed in (664,665)), a few are specifically developed for treating localised and advanced stage PC. Replicating oncolytic adenovirus (638,666-669) and herpes virus (644,670-672) are two major vectors that have been developed and tested for their efficacy against PC. Both have been successfully translated to the clinic, however, conditionally replicative oncolytic

Chapter 1: Literature Review 96

Ads have proven to be the most successful for PC treatment. In an early Phase I trial,

DeWeese et al (673) treated twenty patients with a prostate-specific antigen (PSA)- selective, replication-competent adenovirus, CV706. The results from this study confirmed that intraprostatic delivery of CV706 is highly efficacious (as seen by reduction in PSA levels) without any significant adverse effects. More recently, a novel

CRAd CG7870 (formerly CV787) has also proven to be safe and effective in phase I/II trial against localized and advanced stage PC (666). Although oncolytic virotherapy has shown impressive results in different PC gene therapy studies, its use, as a single agent treatment is still not expected to cure metastatic HRPC. Thus, use of CRAds in combination with other therapeutic modalities has been explored extensively. To date synergistic interactions of CRADs with chemo- & radiation therapy have been shown effectively in preclinical and clinical studies (164,638,674-676).

1.7.6.3.1 Oncolytic Adenoviruses and radiation therapy

Synergistic interactions between oncolytic Ads and radiation therapy have also been reported in variety of cancers (373,677). Combining these two modalities may augment cell killing significantly, as these effect different cell populations using independent cell killing mechanisms. Initial studies have revealed that combination therapy was associated with enhanced antitumour effects compared to monotherapy in animal models of glioma/glioblastoma (678-680), prostate cancer (675), pancreatic cancer

(681) and lung cancer (682). More recently, two phase I trials established the safety and feasibility of this combination approach in prostate cancer patients (638,673). More importantly, in contrast to chemotherapy, radiation did not result in impaired viral

Chapter 1: Literature Review 97 replication (678-680), suggesting that radiation may be a better ally of oncolytic vectors.

1.7.6.3.2 Oncolytic Adenoviruses and chemotherapy

The combined use of oncolytic viruses with chemotherapy against PC has been reported in several studies. In an animal study using CV787, a prostate-specific CRAd in combination with taxanes (paclitaxel and docetaxel) has demonstrated synergistic effects (164). Notably, toxicity studies did not show a synergistic increase of virus and taxane related toxicities and 1000-fold less virus was needed when the combination was used to achieve a complete effect. Importantly, in this study, healthier animals (body weight) were observed in the combination treatment group than with either agent alone; transient weight loss observed in the case of docetaxel alone was missing after combination treatment. Systemically administrated oncolytic Ad OAS403 also resulted in 80% complete tumour regressions in a pre-established LNCaP prostate tumour model

(674), and these therapeutic effects were significantly improved when this therapy was combined with doxorubicin. Improving CRADs by arming them with GDEPT is another potent strategy that can enhance their oncolytic properties. The results from a phase I trial conducted by Freytag et al (638) have demonstrated that CRAds armed with cytosine deaminase (CD)-TK (double suicide gene therapy) and can be combined safely in patients with intermediate to high risk PC.

In summary, the combination of oncolytic virotherapy with chemo-, radiation and suicide-gene therapy has shown a greater antitumour response with acceptable toxicities and holds promise for the complete cure of PC in the near future. The expected outcome of these combinations may be due to the complementary cell killing mechanisms and distinct toxicity profiles of the participating modalities. It is anticipated that the future

Chapter 1: Literature Review 98 mechanistic studies with a focus to understand the complex tumour cell killing interactions associated with CRAd based combination therapy will help to form a strong rationale and hence, better design for use in the clinic.

1.7.6.4 Genetic immunotherapy

Current available therapies are unable to deliver therapeutic gene to all metastatic sites efficiently. One approach to circumvent this situation would be to mobilize the body’s own immune response against cancer. A number of immunotherapy based gene therapy approaches have been used to achieve this goal in PC (659,683-686). One potential approach is to design therapies to enhance body’s immune response, which can ultimately prevent the immune evasiveness of PC cells. The main approaches used here include the activation or delivery of a variety of cytokines (587,687) or co-stimulatory molecules (688), expression of exogenous foreign immunogens and cytoreductive gene therapy e.g., HSV-tk/GCV for local and systemic immune cell activation (632). Most of these strategies have been tested at a preclinical level with very few reaching successive clinical trials for PC treatment. Out of these approaches the results obtained from several phase II/III trials (reviewed by Moon et al (683)) using vaccines based on GM-

CSF-secreting cancer cells, PSMA or prostatic acid phosphatase (PAP) have shown very promising results both in terms of efficacy and safety.

1.7.6.5 Anti-angiogenesis therapy

Like any other solid tumour angiogenesis is a marked feature of prostate cancer progression and metastasis (689). Angiogenesis is often considered as a complex multi-

Chapter 1: Literature Review 99 step process, which results in the formation of new blood vessels necessary for the tumour growth. Under a variety of circumstances PC cells can secrete substances that can stimulate angiogenic factors responsible for the development of a poorly coordinated network of thin walled and leaky blood vessels (690). However, it may be noted that angiogenesis is also related to some normal physiological processes including growth, fertility and wound healing (691-694). Hence, gene therapies that deliver antiangiogenesis inhibitors to tumour sites in a specific manner without showing any notable effect on other physiological events need to be developed. Strategies have been designed to inhibit the activity of angiogenesis-inducing factors (695-697). In a preclinical study it was shown that Ad Flk1-Fc, an antiangiogenic gene therapy vector, combined with an oncolytic virus, dl922/947 was capable of inhibiting tumour angiogenesis and growth in animal models of prostate cancer (698). Vascular endothelial growth factor (VEGF) is one of the most important growth factors with angiogenesis promoting activity in PC (699). In a significant finding, Duque et al reported that plasma levels of VEGF were considerably higher in patients with metastatic disease compared to patients with localized disease or healthy controls (700).

To investigate the role of VEGF in PC progression, both preclinical and clinical studies have been conducted with an ultimate aim to inhibit VEGF activity (519,701). In conclusion, angiogenesis can serve as an ultimate target to stop disease progression in

PC. It is predicted that clinical studies with carefully designed anti-angiogenesis gene therapy either alone or in combination with other modalities may change the paradigm of treatment of HRPC.

Chapter 1: Literature Review 100

1.7.6.6 Transcriptional targeting

Most of the therapeutic approaches used to date are non-specific and often struggle with overall therapeutic index. The basic theory behind the transcriptional targeting of cancer has been discussed in Section 1.4.2.5. The main utility of this approach has been reported in the development and characterization of viral vectors applied in strategies based on oncolytic virotherapy and suicide gene therapy. With the current availability of

PC specific promoters (mainly PSA, PSMA based), these strategies either alone or in combination with other modalities have made a significant impact in the development of PC targeted therapies. Regardless of the vector type and gene therapy approach used, a wide variety of promoters have been exploited for PC targeting (Table 1.11). To date, the most promising promoters are based on a composite of PSA promoter/enhancer elements (PSE) or a promoter of the gene encoding osteocalcin (OC), a major noncollagenous bone matrix protein. More importantly, a study from our lab has shown that combined use of PSME enhancer and Pb promoter can achieve high levels or prostate cell-specific expression both in androgen-sensitive (LNCaP-LN3 cells) and androgen-in sensitive (PC-3 cells) human PC cell lines grown as xenografts in nude mice (340). As discussed earlier (see Section 1.7.6.3), adenoviral vectors have a more frequent use in PC targeted oncolytic therapies. A number of type II CRADs based on prostate specific promoters/enhancers have been developed and tested in both clinical and preclinical studies (165,374,668,702-707). In two different preclinical evaluations, suicide gene therapy approaches were able to utilise promoters/enhancers from the prostate specific membrane antigen (PSMA) gene effectively to target PC (340,708). In another study, novel chimeric enhancers (PSES) composed of two modified regulatory elements controlling the expression of PSA and PSMA were associated with high prostate specific activity sparing normal tissues (709). The majority of the promoters

Chapter 1: Literature Review 101 reported to date are active in androgen-dependent PC only (probasin (PB, (710), PSA,

PSMA, (711,712), which clearly represents a dire need to find novel promoters that are androgen independent and can target HRPC. Collaborative studies carried out in this laboratory have shown the specific efficacay of promoter/enhancer combination consisting of a partial promoter from the PB gene together with an enhancer from either

SV40 virus (337) or more effectively, from PSMA gene (PSME) (340) in androgen- dependent and CRPC xenografts. Osteocalcin (OC) may is of particular interest for oncolytic virotherpy approaches for PC as it has specific activity in bone metastases

(704,705,707) (713). Indeed, its successful use to drive HSV-tk based GDEPT in PC- specific manner has been evaluated in a phase I/II trial to treat HRPC patients with all patients tolerating this therapy without any adverse effects (636,714,715).

It may be noted that the transcriptional strategies to target PC are not just limited to the use of PSA/PSMA or osteocalcin promoters, as a significant number of preclinical studies have also shown impressive progress with other available promoters such as telomerase (hTERT) (374,706,716-719), Uroplakin II (165), Kallikrein 2 (720), Cox-2

(721), Caveolin-1(635), survivin (722) and more recently M6 (723). Although, most of these promoters have shown a unique potential to drive the expression of a desired therapeutic or reporter gene, in some cases promoter activity was severely compromised due to some unknown reasons. In this context, the strategies that could lead to a better vector design with the use of novel enhancer and genetic insulation regions (BGH,

SV40 polyA) may be crucial to retain or improve the promoter activities specifically in the tumour environment.

Chapter 1: Literature Review 102

Table 1.11 List of promoters/enhancers used in PC gene therapy

PROMOTER VECTOR TRANSGENE STATUS REF.

Osteocalcin Adenovirus HSV-tk Phase I/II (636,714,715) Adenovirus HSV-tk In vitro/In vivo (713,724) Adenovirus E1 In vitro/in vivo (704,705,707) Plasmid Nitric oxide synthase (iNOS) In vitro (725) PSE-BC Lentivirus EGFP1/Luc2 In vitro/In vivo (726,727) PSMA3 Adenovirus EGFP/CD In vitro (728) PSMA Adenovirus EGFP/CDUPRT4 In vitro/In vivo (729) PSME5 Adenovirus Luc In vitro/In vivo (709) M6 Adenovirus HSV-tk In vitro/In vivo (723) A modified PSME Rat Probasin (Pb4), PSA Adenovirus eGFP-CAT6 In vitro (730)

ARR(2)PB Adenovirus CAT/ BAX and BAD (pro- In vivo (623,624) apoptotic) PSA7 Lentivirus EGFP/Diptheria Toxin A In vitro/In vivo (703) Adenovirus HSV-tk In vivo (dogs) (731) Rat probasin (Pb) Adenovirus PNP In vitro/In vivo (336)

Rat Probasin (Pb4) plus Adenovirus PNP In vitro/In vivo (340) PSME enhancer 102

Chapter 1: Literature Review 103

PROMOTER VECTOR TRANSGENE STATUS REF.

ARR(2)PB Lentivirus EGFP/HSV-tk In vitro (732)

Progression-elevated gene-3 Adenovirus EGFP/p53/mda7/ IL-24 In vitro/In vivo (287,733) (PEG-3 Promoter) PSME Adenovirus E1A (CRAd) In vitro/In vivo (734) COX-28 Plasmid/poly – GFP/Caspase-3 and 9 In vitro (721) ethylenimine hTERT9 Adenovirus E1A (CRAd) In vitro (718) Adenovirus E1A (CRAd) In vitro/In vivo (706) Adenovirus E1A (CRAd) and GFP under In vitro (374) CMV promoter in E3 region Adenovirus GFP/E1A (CRAd) In vitro/In vivo (668) Adenovirus HSV-TK In vivo (735) Retrovirus CXCR-410 small hairpin RNA In vitro/In vivo (716) Plasmid Noradrenaline transporter In vitro (719) (NAT) Vascular endothelial growth Adenovirus Caspase 9 In vitro (736) factor receptor-2 (VEGFR2) GDEP Plasmid In vitro (737) PC-1 (Prostate and colon gene-1) Plasmid Luciferase In vitro (738) TARP11 Adenovirus Luciferase In vitro/In vivo (739,740) Synthetic beta-catenin- Adenovirus LacZ12 Primary cultures (741) dependent promoter (CTP) (patient samples) 103

Chapter 1: Literature Review 104

PROMOTER VECTOR TRANSGENE STATUS REF.

PSP94 (prostate secretory protein of Plasmid LacZ In vivo (742) 94 amino acids) Uroplakin II Adenovirus E1 In vitro (165)

Kallikrein 2 Adenovirus EGFP In vitro/In vivo (720)

Survivin Plasmid GFP In vitro (722)

1GFP, green flourescent protein; 2Luc, luciferase; 3PSMA, prostate specific membrane antigen; 4CDUPRT, cytosine deaminase gene and uracil phosphoribosyltransferase gene; 5PSME, prostate specific membrane enhancer; 6CAT, chloramphenicol acetyl transferase; 7PSA, prostate specific antigen; 8COX-2, cyclooxygenase-2; 9hTERT, human telomerase reverse transcriptase; 10CXCR-4, alpha chemokine CXC motif receptor-4; 11TARP, T cell receptor gamma-chain alternate reading frame protein; 12LacZ, beta galactosidase. 104

Chapter 1: Literature Review 105

Aims of the study

It is clear from the review of the fields of OC and PC therapy that combination regimens employing different agents to target different populations of cells with beneficial synergies need to be developed for treating these diseases. Although, a number of combination-based approaches have been explored, the clinical output is still suboptimal. From the OC literature review, it can be concluded that OC is a chemosensitive disease, where docetaxel and carboplatin are playing an important role in the patient treatment. Given that, docetaxel is successfully used for the treatment of different types of solid cancers, its potential application in prostate cancer (PC) has been shown in a couple of landmark trials, indeed, it is the only chemotherapeutic with activity against CRPC.

Of different gene therapy approaches reported to date, sucide gene therapy has shown an excellent promise in the treatment of a variety of solid tumors. Given its promise in preclinical studies, the potential role of PNP-GDEPT to treat OC and PC is now being assessed in two phase I trials that were recently intiated (OC, USA and PC, Australia; personal communication).

The applicability of docetaxel and PNP-GDEPT in PC treatment provides a strong rationale for their combined use in clinic. The imporatnce of combined therapy approach to target cancer hetrogeneity is obvious and is a marked feature of OC and PC.

Broadly, the primary object of this study is to explore novel synergistic combination regimens to target ovarian and prostate cancer heterogeneity at different levels. For this

Chapter 1: Literature Review 106 purpose we will evaluate the combined use of traditional and molecular chemotherapy

(gene therapy) in vitro as well as in vivo. If we establish a therapeutic advantage of the combination regimen, we will explore potential mechanisms behind these synergies. An important goal of this project is to improve the therapeutic index of molecular gene therapy by making it more cancer specific via developing cancer-targeted transcriptionally and transductionally modified adenoviral vectors. Hence, to enhance safety and selectivity of gene therapy, we will use viral vectors with 1. Modified tropism to specifically target Her-2/neu (transductionally targeted Ad.ZZ virus developed by our Sweden collaborator) overexpressing OC or PC cells/tumours and 2.

Survivin/Her-2 neu promoter to ensure that gene-expression only occurs in cancer cells/tumours (OC, PC).

As a general approach, the primary aim of this study is to explore the potential synergies between the novel Ad- mediated PNP-GDEPT and chemotherapeutic regimens used for treatment of clinical PC and OC, in vitro and in vivo. An investigation of apoptotic mechanisms involved will also be carried out through protein analyses. Given the synergies between CRAds and chemotherapy, the next aim will be to construct and test cancer-specific CRAds (either survivin or Her-2/neu promoter) armed with PNP- GDEPT against PC or OC. If time permits, CRAds, transductionally targeted to Her-2/neu ligand over-expressing cancer cells will be constructed and tested

(collaboration, Dr Leif Lindholm, Sweden). Once successfully constructed and tested, these CRAds will then be tested for potential synergies with traditional chemotherapy for specific targeting of PC or OC

Chapter 1: Literature Review 107

Specifically, for PC studies the combination of the novel as yet clinically unexplored

PNP-GDEPT with docetaxel will be explored, which alone has not provided a cure.

Keeping in mind that docetaxel is the only chemotherapeutic drug to have shown a marginal survival benefit in CRPC patients, we hope that this drug will provide synergism with gene therapy for targeting aggressive cancer. From the different available gene therapy approaches, we will use a type of suicide gene therapy called

PNP-GDEPT. The previous pre-clinical studies from our lab have already proven that

PNP-GDEPT has excellent potential for the treatment of PC; this and other similar studies have led to the initiation of Phase I clinical trials to treat OC (in Alabama, USA) and PC (in Australia: personal communication). It is anticipated that a positive outcome showing the promise of combining docetaxel and PNP-GDEPT in the laboratory will form a stong indicator for translation of such treatment for patients with PC, especially, the ones given concurrent or prior chemotherapy.

For OC studies, we will explore the potential synergies between PNP-GDEPT, docetaxel and carboplatin as a tri-modality approach. Docetaxel/carboplatin regimen is a standard form of therapy used to treat advanced stage OC patients. Given that a very little is known about the type of interactions between these two drugs, this study will add to our knowledge to elucidate the complex cell killing mechanisims of this drug combination. Using OC model cell lines representing the most common adenocarcinoma of epithelial OC, we will investigate the effects of combining these with PNP-GDEPT. Following this, a mechanisim-based study will be performed in an attempt to understand the molecular changes involved in cell apoptosis due to combined effect of hese modalities. The overall objective of this aspect of this study is to explore

Chapter 1: Literature Review 108 if this tri-combination may serve as an option for future combination therapy based drug regimens to treat OC.

Hypothesis

The combined use of PNP-GDEPT mediated via cancer-targeted Adenoviral vectors and chemotherapy (docetxael and or carboplatin) will result in synergistic and systemic therapeutic effects leading to a significantly improved therapeutic index against PC and

OC. Use of Adenoviral vectors with Her-2/neu tropism and with PC/OC specific survivin promoter will improve the safety and selectivity of gene therapy.

Specific Aims of Thesis:

The specific aims of this body of work are:

OC Studies

1. To evaluate individual therapeutic effects of Taxotere, carboplatin and Ad-mediated PNP-GDEPT in OC cell lines. 2. To evaluate synergy between these modalities in OC cell lines. 3. To elucidate the molecular changes involved in cell apoptosis associated with these synergistic interactions.

PC Studies

1. To evaluate individual therapeutic effects of Taxotere and Ad-mediated PNP-GDEPT against PC cell lines. 2. To evaluate synergy between Taxotere and Ad-mediated PNP-GDEPT against PC cell lines. 3. To evaluate the synergy between Taxotere and Ad-mediated PNP- GDEPT against PC in vivo in immunocompetent and immunodefficient mouse models of PC.

Chapter 1: Literature Review 109

4. To evaluate the effects of treatment on the condition of the host and on toxicity profiles. 5. To evaluate the effects of treatment on immune status of the host; e.g. infiltration of the tumours by immune cells and and serum cytokine profiles in treated mice.

Transcriptional and transductional targeting of gene-therapy vectors

1. To evaluate Her-2/neu and survivin status of OC and PC cells. 2. To evaluate the tumour-specificity and therapeutic potential of transductionally targeted Her-2/neu Adenovirus (Ad.ZZ) (collaboration with Dr Leif Lindholm, Sweden). 3. To construct and characterise transductionally (Her-2 neu) and transcriptionally (survivin/Her-2/neu) targeted Adenoviral vectors for OC and PC therapy.

Chapter 2: Material and Methods 110

MATERIALS AND METHODS

Chapter 2: Material and Methods 111

2.1 Molecular Biology Techniques

2.1.1 DNA based molecular methods

These include the preparation and purification of DNA fragments, polymerase chain reaction to amplify DNA sequences, agarose gel electrophoresis, restriction enzyme digestion, DNA quantification, ligation, transformation of bacteria (chemical and electroporation methods).

Table 2.1shows a list of buffers and solutions used in DNA based molecular techniques.

Chapter 6: Transcriptional and Transductional Targeting 112

Table 2.1 Buffers and solutions used in DNA based molecular techniques Method Buffer/Solution Composition/Storage Manufacturer/ Supplier

Plasmid Preparations Buffer P1 50 mM Tris-Cl, pH 8.0 Qiagen, Hilden, Germany (resuspension buffer) 10 mM EDTA, 100 g/mL RNase A Buffer P2 200 mM NaOH, 1% SDS (w/v) (lysis buffer) Buffer P3 3.0 M Potassium acetate, pH 5.5 (neutralisation buffer) 10-25% acetic acid Buffer QBT 750 mM NaCl, 50 mM MOPS, pH7.0 (equilibration buffer) 15% v/v isopropanol, 0.15% v/v Triton X-100 Buffer QC 1.0 M NaCl, 50 mM MOPS, pH 7.0 (wash buffer) 15% v/v isopropanol Buffer QF 1.25 M NaCl, 50 mM Tris-Cl, pH 8.5 (elution buffer) 15% v/v isopropanol Ethanol 70-100% ethanol Crown Scientific, Gilman, SA Isopropanol 100% isopropanol BDH, Kilsyth, VIC DNA gel preparation Tris-acetate-EDTA buffer Tris: 10 mM (2 mL of 1 M stock), 1mM EDTA Amresco, OH, USA (TAE) (800 L 0.25M stock), Make volume to 200 mL with dH2O Ethidium Bromide 50mg/mL (I drop/50 mL) Gene Choice, MD, USA Loading buffer 10X loading buffer Fermentas, MD, USA Loading dye 6X loading dye Molecular weight EcoRI Lambda Markers Hyper Ladder III, IV Bioline, Alexandria, NSW 112

Chapter 2: Material and Methods 113

DNA gel purification NaI solution 6M Sodium Iodide Q-Biogene/MP-Pharma, OH, USA GLASSMILK Silica matrix New Wash Buffer NaCl, Tris-EDTA, water and 100% ethanol Restriction digestion Restriction buffer 10X restriction buffer Blue, Green, Orange, MBI Fermentas, MD, USA Red and Yellow (Tango), stored at -20oC Restriction enzymes BamHI, BglII, EcoRI, EcoRV, HinDIII, KpnI, MssI (PmeI), NotI, SacI, SalI, SmaI, SphI, Xbai and XhoI supplied in storage buffer, stored at -20oC Restriction buffer 10X restriction buffer 1 at -20oC New England Biolab, MA, USA Bovine serum albumin 100X, stored at -20oC Restriction enzyme PacI, stored at -20oC Restriction digestion Buffer PN Binding buffer Qiagen Gmbh, Hilden, Germany purification Buffer PE Wash buffer Elution Buffer Elution buffer (TE) Ligation Ligation buffer 10X reaction buffer stored at -20oC MBI Fermentas, MD, USA Ligase enzyme T4 DNA ligase PCR Reaction Reaction Buffer 10X reaction buffer Stratagene, CA, USA Enzymes Polymerase PFU polymerase 2.5u/l Primers Used as 100 ng/L per PCR reaction Sigma genosys/Sigma-Aldrich, Castle Hills, NSW dNTPs dNTPs (deoxy N-triphosphate: N; adenosine, Bioline, Alexandria, NSW thymine, cytosine, guanidine used as 1:1:1:1) Magnesium Chloride 10mg/ mL PCR purifications Binding Solution (H1) Concentrated guanidine hydrochloride, EDTA, Fermentas, MD, USA Tris-HCl and isopropanol Wash Buffer (H2) NaCl, EDTA and Tris-HCl 113 TE buffer 10 mM Tris-HCl (pH 8.0), 0.1 mM EDTA

Chapter 2: Material and Methods 114

2.1.1.1 Polymerase Chain Reaction (PCR) amplification of DNA sequences

For amplification of selected regions of DNA sequences, PCR was employed. PCR reactions were routinely performed using a Thermo Hybaid MBS 0.2S cycler (Hybaid,

Middlesex, UK). Primers used in PCR reactions were synthesised by Sigma-Genosys

(New South Wales, Australia). Proof reading enzyme, Pfu polymerase was used for gene amplifications and reagents and conditions used for these reactions are summarised in Tables 2.2 and 2.3. The reactions were generally carried out in a final volume of 25-50 μL. The PCR products were analysed on 1-2% agarose gel stained with ethidium bromide (see 2.1.1.4), and the desired product/s were subsequently purified using Marligen’s PCR purification kit (see 2.1.1.6).

Table 2.2 PCR conditions

Segment Step Number of Temperature Duration Cycles 1 Denaturation 1 95°C 2min 2 Amplification 30 95°C 30sec Primer Tm1 minus 5°C 30sec 72°C 60sec 3 Annealing 1 72°C 10min 1Tm, Melting temperature

Table 2.3 Reagents and their amounts used in a PCR cycle

Reagents used Amounts /Reaction (μL) Distilled water 19.25 10 × cloned Pfu reaction buffer 2.5 dNTP1s (25 mM each dNTP) 1.25 DNA template (100 ng/L) 1 Fwd Primer (100 ng/L) 0.25 Rev Primer (100 ng/L) 0.25 PfuTurbo DNA polymerase (2.5 U/L) 0.5 Total Reaction Volume 25 1dNTP, Deoxyribonucleotide triphosphate

Chapter 2: Material and Methods 115

2.1.1.2 Plasmid preparation (Mini-prep)

Small-scale plasmid DNA was prepared using the alkaline lysis method using Qiagen buffers/protocols. Generally, chemically competent or electrocompetent bacteria were grown in LB (2 mL) overnight at 37°C with a shaking speed of 18 g. Next day, cells were harvested by centrifugation at 15000 g for 5 minutes at room temperature. The cell pellet was resuspended in 200 μL of P1 buffer (Qiagen: 50 mM Tris-Cl, pH 8.0,10 mM

EDTA 100 μg/ mL RNase A) followed by lysis with 200 μL of P2 buffer (NaOH-SDS

Buffer) for no more than 4 minutes. Exposure of the bacterial suspension to the strongly anionic detergent at high pH opens the cell wall, denatures chromosomal DNA and proteins, and releases plasmid DNA into the supernatant (743). The lysis time of 4-5 minutes allows maximum release of plasmid DNA from the cell without release of cell- wall-bound chromosomal DNA. The lysate was neutralised by the addition of 200 μL of acidic potassium acetate (Buffer P3) for 15 min on ice. The high salt concentration of buffer P3 results in the formation of salt-detergent complexes, which are then removed by centrifugation at 15000 g at 4°C for 20 min. Plasmid DNA is recovered from the supernatant by precipitation with two volumes of absolute ethanol, washed with 70% ethanol and then air dried until ethanol has evaporated (RT for 30 minutes). The DNA is then resuspended in autoclaved MiliQ water (30-40 μL) and ~500 ng was used for restriction enzyme based screening.

2.1.1.3 Maxi-prep plasmid preparation

Large-scale plasmid DNA preparations of bacterial overnight cultures (150 mL) were done according to Qiagen protocols. Briefly, overnight cell cultures were spun at 3970

2570 g for 60 minutes at 4 C and the cell pellet was resuspended in P1 buffer followed

Chapter 2: Material and Methods 116 by incubation with 12 mL of P2 (5 minutes, RT) and then in P3 buffer (15 minutes, ice).

The supernatant containing the plasmid DNA was harvested after centrifugation at 2570 g for 45 minutes at 4 C and subsequent filtration through sterile gauze to remove remaining debris. Plasmid DNA from this solution was purified using QIAGEN-tip 500 column as follows: after equilibration of the column using QBT buffer (12 mL), filtered lysate was allowed to pass trough the column by gravity flow. Plasmid DNA trapped in column was washed with QC buffer (2X 30 mL) followed by elution using warm QN buffer (15 mL). The DNA was precipitated in 0.7 volumes of isopropanol (10.5 mL), pelleted by centrifugation at 15,000 g (1h), washed with 70% ethanol and then air dried for 30 minutes. The DNA was resuspended in TE buffer (400μL), quantitated by spectrophotometry (see Section 2.1.1.7) and ~500ng used for restriction enzyme digestion for validation.

2.1.1.4 Restriction digestion

Cleavage of DNA using restriction enzymes was routinely carried out using ~500ng of substrate DNA and 5-10 units of the appropriate enzyme along with supplied buffer in a final volume of 20 μL. The reaction was generally set at 37°C unless otherwise recommended by the manufacturer. Typically, the analytical restriction digest incubations were carried out for 1h while preparative restriction reactions were incubated for 3 h.

Chapter 2: Material and Methods 117

2.1.1.5 Agarose gel electrophoresis

The DNA fragments were analysed using agarose gel electrophoresis. Gels were prepared by dissolving agarose (0.7%-3%) in 1x Tris-acetate-EDTA (TAE) buffer. For

DNA visualisation ethidium bromide was added to the agarose solution. DNA samples mixed with 6X loading dye were loaded on the gel and electrophoresis was performed at

80 Volts (Bio-Rad, Regents Park, NSW, Australia). After the run (run time based on size of the fragment of interest; generally 1h), DNA was detected under UV and size determined based on the standard Lambda DNA markers. Gel images were taken using

MiniBis DNR (MiniBis DNR BioImaging Systems, Jerusalem, Israel).

2.1.1.6 Purification of DNA fragments

(I) Restriction digestion product purification

i. From solution

ii. From gel

(II) PCR product purification

(I) Restriction digestion product purification i. From Solution: DNA from the restriction digest mix was purified using Qiagen’s

Nucleotide Removal Kit in accordance with the kit protocol. This protocol ensures removal of DNA <10 bases, enzymes, salts, and unincorporated nucleotides. Briefly, 10 volumes of PN buffer were added to the reaction mixture. After 1-minute’s incubation at RT, sample was applied to QIAquick column and then centrifuged (4000 g for 1min

Chapter 2: Material and Methods 118 at RT). The DNA bound to the column was washed by PE buffer twice and then eluted

(18,000 g for 2 min at RT) in 30-50 μL of autoclaved MilliQ water (Millipore, USA). ii. From Gel: After resolution using TAE agarose gel electrophoresis, the DNA fragment of interest (visualised on non-mutagenic UV trans-illuminator: 365 nm,

Ultraviolet Products, Inc. USA) was purified using Q-Biogen’s Gene Clean Kit as per the manufacturer’s protocol. Briefly, gel piece containing DNA was melted in three volumes of NaI solution at 55 °C (5-10min with mixing at regular intervals of 1-2 minutes) followed by addition of pre-mixed EZ-GLASSMILK (1μL/μg of DNA). The reaction was incubated for 5 mins to ensure the appropriate binding of DNA to silica matrix. The DNA bound to the silica slurry was pelleted by centrifugation (18000 g for

5 seconds at RT) and the supernatant was discarded. The pellet was washed using New

Wash buffer by centrifugation (18000 g for 5sec at RT). The wash step was repeated and the pellet was air-dried to remove residual ethanol followed by elution in 30-50 μL of warm TE or sterile MilliQ water.

(II) PCR product purification

PCR fragments were checked for appropriate band size using a 5 μL reaction mix by agarose gel electrophoresis. Once verified to be a clean reaction (i.e. single product), the

DNA was purified from the remaining solution using Marligen’s PCR purification kit as per the manufacturer’s protocol. Briefly, PCR reaction was mixed with 4 volumes of

Binding Buffer, and then passed through the column by centrifugation in the microfuge

(18000 g for 1 min at RT). The column was washed with 700 μL of washing buffer

(18000 g for 1 min at RT) and residual washing buffer was removed by additional

Chapter 2: Material and Methods 119 centrifugation for 2 mins. The DNA was eluted by centrifugation (15000 g for 2 mins at

RT) in 30 μL of warm (55oC) elution buffer.

2.1.1.7 Spectrophotometry

The concentration (ng/μL) and purity of DNA samples were determined by measuring absorbance at 260 and 280 nm using a NanoDrop® ND-1000 UV-Vis

Spectrophotometer (Thermo Scientific, USA). The ratio of absorbance at 260 and 280 nm was used to assess the purity of the DNA sample. A ratio of ~1.8 was considered as

“good quality” DNA without protein/RNA contamination.

2.1.1.8 Molecular techniques involving use of bacteria

2.1.1.8.1 Bacterial strains and reagents

Table 2.4 shows the bacterial strains used in ligation, transformation and electroporation reactions. The reagents used to culture these cells have been listed in Table 2.5.

Chapter 2: Material and Methods 120

Table 2.4 Bacterial strains

Bacterial Strain Genotype Features Manufacturer/Supplier

E.coli DH10B F- mcrA (mrr-hsdRMS-mcrBC) High transformation efficiency, Invitrogen, CA, USA

80lacZ M15 lacX74 recA1 endA1 chemically competent cells

ara 139 (ara, leu)7697 galU galK

- rpsL (Strr) nupG

E.coli BJ5183 endA1 sbcBC recBC galK met thi-1 Recombination proficient electroporation Stratagene, TX, USA

bioT hsdR (Strr) competent cells

E.coli BJ5183 endA1 sbcBC recBC galK met thi-1 Recombination proficient electroporation

Adeasy-I bioT hsdR (Strr) [pAdEasy-1 (Ampr)] competent cells with a plasmid containing

adenovirus 5 genome (E1/E3 deleted)

120

Chapter 2: Material and Methods 121

Table 2.5 Media and solutions for bacterial culture

Medium/Solutions Composition/Storage Manufacturer/ Supplier Luria-Bertani Medium 20g/litre USB, OH, USA or L-Broth (LB) LB agar 32g/litre Terrific Broth (TB) A KH2PO4 2.31g BDH/Merck, Kilsyth, K2HPO4 12.54g VIC Distilled water to 100 mL B Tryptone 12g GE Healthcare, Yeast Extract 24g Castle Hills, NSW Glycerol 4 mL BDH/ Merck, Distilled water to 900 mL Kilsyth, VIC Autoclave separately and mix A and B after cooling SOC medium Pre-formulated /available as 10 Invitrogen, CA, USA mL vials Selection Antibiotics Kanamycin Sulphate at 4 oC Invitrogen, CA, USA Sodium salt of Ampicillin at 4 oC Sigma-Aldrich, Genticin Sulphate (G-418) Castle Hill, NSW Glycerol 80% glycerol BDH, Kilsyth, VIC (for stock preparations) (autoclave before use)

2.1.1.8 Ligation reactions

Linear DNA fragments representing vector and insert were ligated to form new recombinant DNA molecule using standard ligation techniques. Ligation reactions between plasmid vectors and DNA inserts were routinely performed in a final volume of 10-20 μL. Generally, fragments to be inserted were in 3-5 fold molar excess over that of destination vector. The ligation reaction mixture contained 10X ligation buffer and

T4 DNA ligase (2-3U) and the reaction was carried out overnight at 15oC (ice/water bath, 50% ice + 50% water). Subsequently, ligation mix (3 μL) was then used for transformation of E. coli DH10B competent cells (50 μL).

Chapter 2: Material and Methods 122

2.1.1.9 Preparation of competent cells

Chemical and electro-competent cells were used for different applications. Chemically competent strains were purchased from Invitrogen and electro-competent cells were prepared using a protocol described in “Molecular Cloning; A Laboratory Manual”

(744). Briefly, a single bacterial colony was used to inoculate 25 mL of LB medium, grown overnight with vigorous shaking and next day added to an aliquot of 475 mL of pre-warmed sterile LB medium. The culture was incubated with continuous shaking at

37°C until the OD550 reached 0.6 to 1.0. Cells were then pelleted by centrifugation

(1300 g for 5min at 4°C) and resuspended in 500 mL ice-cold DI water. The process of resuspension and pelleting was repeated with 250 mL ice-cold DI water and then with

10 mL of 10% glycerol. The final suspension of cells was prepared in 1 mL of ice-cold sterile GYT (10% [vol/vol] glycerol, 0.125% [wt/vol] yeast extract, and 0.25% [wt/vol] tryptone, pH 7.0) medium. The cell aliquots (50 μL) were then snap-frozen in ethanol/dry ice bath and stored at -80°C.

2.1.1.10 Transformation of competent cells

The chemically competent cells were transformed with plasmid DNA using the heat shock method. E. coli DH10B cells (Invitrogen) were thawed on ice (50 μL/reaction) and then incubated with ~10-50 ng of DNA for 30 minutes at 4oC. The heat shock was performed at 42°C in a water bath for 45seconds followed by incubation on ice for 2 minutes and subsequent addition of nutrient enriched SOC medium (500 μL). The transformed cell-mix was then transferred to white cap falcon tubes and incubated at

37°C for 1-2 h with continuous shaking (18 g). The incubated cells were plated on LB

Chapter 2: Material and Methods 123

Agar plates with relevant antibiotic selection (Kanamycin Sulphate or Ampicillin). The agar plates were incubated overnight in 37°C incubator.

The electroporation method was performed using electro-competent cells. Briefly, an aliquot of 40 μl E. coli BJ5183 AdEasy electrocompetent cells was thawed on ice before adding to a chilled tube containing 100 ng of PmeI linearised pShuttle vector. The mixture was then transferred to an ice-cold cuvette (0.2 cm gap, Bio-Rad) and pulsed at

25 μF, 2.5 kV and 250 ohms (Gene Pulser; Bio-Rad, Regents Park, NSW, Australia). A time constant of 4-5 indicated successful electroporation. 1 mL of SOC medium was immediately added to the pulsed cells followed by incubation at 37°C for 1-2 h with continuous shaking. The incubated cells were plated on LB Agar plates containing 50

μg/mL of Kanamycin Sulphate and then incubated O/N at 37°C to grow single colonies.

2.1.1.11 Preparation of glycerol stocks

Glycerol stocks of transformed cultures (positive clones) prepared to the final concentration of 15% glycerol were made by mixing bacterial culture (750 μL) with 750

μL of sterile glycerol (80%) and after thorough mixing, these were immediately stored at -80oC.

Chapter 2: Material and Methods 124

2.1.2 Molecular techniques for protein based analyses

These include preparations of cell lysates, BCA assay, SDS-PAGE, Western blot analysis and mass spectrophotometry.

Table 2.6 shows list of buffers and solutions used in protein analysis.

2.1.2.1 Whole cell protein extraction

Cell monolayers grown to 70-80% confluence were washed once with PBS followed by

20 min incubation in lysis buffer (M-PER® mammalian protein extraction reagent) containing protease inhibitor cocktail (1:100) (Fermentas). Cells were harvested by scraping (sterile scraper (BD Falcon, USA) and debris removed by centrifugation at

21000 g for 20 mins at 4oC. The cell lysates were stored at –80°C until use.

2.1.2.2 Protein quantitation using BCA assay

The protein concentration of cell samples was estimated using the bicinchoninic acid assay (BCA) kit (Pierce) according to the manufacturer’s protocol (745). The experiments were performed in a 96 well plate using triplicate samples. Briefly, 10 μL of test cell lysate or BSA standard was incubated with 200 μL of BCA assay reagent

(solution A: B 50:1) at 37 °C in dark. After 30-min incubation, absorbance was measured at 570 nm after a 5 sec pre-shake on the Tecan Sunrise microplate reader

(Phenix Research Products, North Carolina, USA). The standard curve was generated using different concentrations (two fold dilutions; concentrations of 2,000, 1,000, 500,

250, 125 and 0 μg/mL) of supplied BSA standard and then used to estimate the unknown protein concentrations of cell lysates using the Microsoft Excel software.

Chapter 2: Material and Methods 125

Table 2.6 Reagents for protein analysis Methods Reagent/Material/Use Manufacturer/Supplier Cell lysate M-PER Mammalian Protein Extraction detergent in Piercenet/Thermo-Scientific, IL, preparation for 25 mM bicine buffer (pH 7.6) USA protein determination Protease inhibitor cocktail 100X used as 1X (inhibit protein digestion Sigma-Aldrich, Castle Hills, NSW by cell proteases) Bicinchoninic Acid BCA Assay Reagents Solution A and B Piercenet/Thermo-Scientific, IL, (BCA)- based protein Albumin Standards Bovine Albumin in 0.9% NaCl solution USA concentration (2 mg/ mL) containing sodium azide determination assay SDS–PAGE and Gel Contents for two Separtaing (10% Stacking (4% Western Blot Preparation standard gels (10 wells) polyacrylamide) polyacrylamide) 40% Acrylamide 2.5 mL 1.0 mL Bio-Rad, Regents Park, NSW 1M Tris-HCl pH 8.8 3.75 mL - BDH, Kilsyth, VIC 1M Tris-HCl pH 6.8 - 1.25 mL BDH, Kilsyth, VIC 10% Sodium Dodecyl 100l 100 l Gibco/Invitrogen, USA Sulphate (SDS) 10% Ammonium 50l 50 l Bio-Rad, Regents Park, NSW Persulphate (APS) Water 3.6 mL 7.5 mL MilliQ-Millipore, USA N,N,N’,N’- 12.5l 12.5 l Bio-Rad, Regents Park, NSW Tetramethylethylene- diamine (TEMED) Laemmli buffer Glycine 188 g BDH, Kilsyth, Australia (Stock 1X running buffer) Tris Base 30 g Sigma-Aldrich, Castle Hills, NSW SDS (10%) 100 mL Gibco/Invitrogen, USA Distilled water to 10 L MilliQ-Millipore, USA 125

Chapter 2: Material and Methods 126

SDS–PAGE and Transfer buffer Glycine 29 g BDH, Kilsyth, VIC Western Blot (Stock 1X running buffer) Tris Base 58 g Sigma-Aldrich, Castle Hills, NSW SDS (10%) 37 mL Gibco/Invitrogen, USA Methanol 2 L BDH, Kilsyth, VIC Distilled water to 8 L MilliQ-Millipore, USA Phosphate Buffered Saline 1X Stock made from tablets MP Biomedicals, USA (PBS) PBSTween (PBST) 1X PBS with 1% Tween-20 MP Biomedicals, USA Butanol (Water–saturated) Butanol saturated with water BDH, Kilsyth, VIC DTT Dithiothreitol reducing agent at -20oC Fermentas, USA 5X sample buffer 200mM tris HCl (ph 6.8), 8% SDS, 40% Sigma-Aldrich, Castle Hills, NSW glycerol, 0.4 % bromophenol blue Porous Pads Contents of ‘wet’ protein transfer sandwich Bio-Rad, Regents Park, NSW Filter paper Whatman, Oxon, UK Nitrocellulose membrane Bio-Rad, Regents Park, NSW ECL detection Reagent Solution 1 and 2 Piercenet, IL, USA Developing reagents Developer and replenisher solutions Sigma/Kodak GBX, VIC Fixative solution Fixative solution Kodak Biomax cassettes Kodak Biomax cassettes

Fuji diagnostic X-ray film SuperRx (18X24cm) Fuji Corporation, Tokyo, Japan Coomassie Staining Coomassie stain Coomassie blue G-250 stain, 1 L bottle Bio-Rad, Regents Park, NSW 126

Chapter 2: Material and Methods 127

2.1.2.1 Whole cell protein extraction

Cell monolayers grown to 70-80% confluence were washed once with PBS followed by

21000 g for 20 mins at 4oC. The cell lysates were stored at –80°C until use.

2.1.2.2 Protein quantitation using BCA assay

(solution A: B 50:1) at 37 °C in dark. After 30-min incubation, absorbance was measured at 570 nm after a 5 sec pre-shake on the Tecan Sunrise microplate reader

(Phenix Research Products, North Carolina, USA). The standard curve was generated using different concentrations (two fold dilutions; concentrations of 2,000, 1,000, 500,

250, 125 and 0 μg/mL) of supplied BSA standard and then used to estimate the unknown protein concentrations of cell lysates using the Microsoft Excel software.

Chapter 2: Material and Methods 128

2.1.2.3 Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-

PAGE)

Proteins were separated by gel electrophoresis using SDS-PAGE based on the method developed by Laemmli (746) using Mini-PROTEAN II gel electrophoresis system (Bio-

Rad). Polyacrylamide gel (1mm thick) composed of a resolving and stacking gel was routinely used for protein separation. Gels were prepared using acrylamide and bis- acrylamide solution at 10% for resolving and 4% for stacking gel (see Table 2.6). The separating buffer/gel mix was mixed with N,N,N’,N’-tetramethylethylenediamine

(TEMED) prior to loading in the gel caster assembly. The water-saturated butanol was used to overlay the resolving gel to ensure the integrity of gel formation, which was removed once the gel polymerised (~45 minutes) by washing with de-ionised water. A mixture of stacking buffer/gel mix and N,N,N’,N’-tetramethylethylenediamine

(TEMED) was added on top of this gel and a 10-well comb was placed in solution prior to polymerisation. The comb was removed after polymerisation (~30 mins) and the glass sandwich was assembled onto gel electrode system. The unit was then placed in the gel tank filled with Laemmli’s running buffer. The protein samples (30-50 μg) or pre-stained protein markers diluted with 5X sample buffer were denatured by heating at

95oC for 5 min in a thermal cycler (Hybaid, Middlesex, UK) and were electrophoresed at 100 V using a PowerPac (Bio-Rad, Regents Park, NSW) until the dye front reached the bottom of the gel. After electrophoresis, gel was either used for Western blotting or stained with Coomassie Blue solution (see Section 2.1.2.5).

Chapter 2: Material and Methods 129

2.1.2.4 Western blot analysis

The proteins resolved on SDS-PAGE gel were then transferred electrophoretically onto nitrocellulose membranes (747,748). Briefly, the ‘wet’ protein transfer sandwich comprised of porous pads, filter papers, SDS-PAGE gel and nitrocellulose membrane

(0.45 μm) sandwiched together and then loaded in a chamber containing transfer buffer.

The blotting was conducted at a constant current of 250 mA for 60 min. After the transfer was complete, membranes were incubated in blocking buffer (5% skim milk in

PBST) for 60 min at RT, and subsequently washed in 0.1% Tween-20 wash buffer for 5 mins. The membrane was then incubated in relevant primary antibodies (see details in

Appendix I) diluted in blocking buffer (10 mL), overnight with shaking followed by three washes of 5, 10 and 5 mins using 0.1% Tween-20 wash buffer. The secondary antibodies (anti-rabbit IgG Horse Radish Peroxidase (HRP) conjugated, 1:1000 or anti- mouse IgG HRP, 1:5000) (see details in Appendix I) diluted in blocking buffer (10 mL) were added onto the membrane and incubated for 1 hr.

Enhanced chemi-luminescence (ECL) based reagents were used for protein detection.

Briefly, the ECL treated membranes were exposed to X-ray film for 1 minute in an X- ray cassette. If bands were not detected, exposure for 5, 15 and 30 and 60 minutes was carried out. X-ray films were developed using Kodak GBX Developer, followed by rinsing in tap water and fixing with Kodak GBX Fixer. After a thorough final rinse in tap water, X-ray films were air-dried for at least 1h. The protein bands on X-ray films were quantified by densitometry and analysis was done using the program Quantity One

(Bio-Rad, Hercules, CA).

Chapter 2: Material and Methods 130

2.1.2.5 Coomassie staining

Cell lysates (50 μg) were resolved on 4-10% SDS-PAGE as described in Section

2.1.2.3. After electrophoresis, the gel was washed twice (5 mins per wash) with water to remove traces of SDS-containing buffers, followed by incubation in 100 mL of

Coomassie stain at room temperature for 2 h with gentle agitation. The staining solution was then aspirated and replaced with water for de-staining. The water was changed several times with rocking until clear blue protein bands were seen with no background staining (generally overnight).

2.1.2.6 Mass spectrometry

Untreated cells treated and those treated with PNP-GDEPT were analyzed for protein profiles using shotgun proteomics approach (749-751). Cell lysates (50 μg) were electrophoresed on 10% polyacrylamide gel as described (Section 2.1.2.3). Immediately after Coomassie staining, gel (stored in water at RT) was taken for mass spectrometry analyses to Mass Spectrometry Unit, BMSF at UNSW, where Dr Mark Raftery performed this part of the protocol. Gel bands were incubated with NH4HCO3/CH3CN

(10 mM, 1:1, 200 μl) until clear (~2-4 hr) then CH3CN (2 x 50 μl, 10 min) and dried under vacuum (SpeedVac, Savant, Farmingdale, NY). Trypsin (~100 ng) in NH4HCO3

(10mM, 25 μl) was added and the solution left at 37°C for 14 h. The gel pieces were washed with H2O (0.1% formic acid) (50 μl) and H2O: CH3 CN (1:1) (0.1% formic acid) (50 μl) for 10 min and the combined extracts dried and peptides dissolved in H2O

(0.1% HFBA, 20 μl) (752).

Chapter 2: Material and Methods 131

Digest peptides were separated by nano-LC using an Ultimate 3000 HPLC and autosampler system (Dionex, Amsterdam, Netherlands). Samples (2.5 μl) were concentrated and desalted onto a micro C18 precolumn (500 μm x 2 mm, Michrom

Bioresources, Auburn, CA) with H2O: CH3 CN (98:2, 0.05 % HFBA) at 20 μl/min.

After a 4 min wash the pre-column was switched (Valco 10 port valve, Dionex) into line with a fritless nano column (75μ x ~10cm) containing C18 media (5 μ, 200 Å

Magic, Michrom) manufactured according to Gatlin (753). Peptides were eluted using a linear gradient of H2O: CH3 CN (98:2, 0.1 % formic acid) to H2O: CH3 CN (64:36, 0.1

% formic acid) at 350 nl/min over 30 min. High voltage 1800 V) was applied to low volume tee (Upchurch Scientific) and the column tip positioned ~ 0.5 cm from the heated capillary (T=200°C) of a LTQ FT Ultra (Thermo Electron, Bremen, Germany) mass spectrometer. Positive ions were generated by electrospray and the LTQ FT Ultra operated in data dependent acquisition mode (DDA).

A survey scan m/z 350-1750 was acquired in the FT ICR cell (Resolution = 100,000 at m/z 400, with an initial accumulation target value of 1,000,000 ions in the linear ion trap). Up to the 7 most abundant ions (>2500 counts) with charge states of +2 or +3 were sequentially isolated and fragmented within the linear ion trap using collisionally induced dissociation with an activation q = 0.25 and activation time of 30 ms at a target value of 30,000 ions. M/z ratios selected for MS/ MS were dynamically excluded for

30 seconds.

Peak lists were generated using Mascot Daemon/extract_msn (Matrix Science, London,

England, Thermo) using the default parameters, and submitted to the database search

Chapter 2: Material and Methods 132 program Mascot (version 2.1, Matrix Science). Search parameters were: Precursor tolerance 4 ppm and product ion tolerances ± 0.6 Da; Met (O) and Cys- carboxyamidomethylation specified as variable modification, enzyme specificity was trypsin, 1 missed cleavage was possible and the non-redundant NCBI protein database

(September 2008) was searched.

2.1.2.7 Protein identification after mass spectrometry

Scaffold (version Scaffold_2.02.01, Proteome Software Inc., Portland, OR) was used to validate MS/MS based peptide and protein identifications. Scaffold is a program that compares two or more sets of data after mass spectrometry and database searches

(http://www.proteomesoftware.com/index.html). Scaffold peptide identifications were performed based on the Peptide Prophet algorithm (754). Protein identifications were assigned by the Protein Prophet algorithm (755).

2.2 Mammalian Cell Culture

2.2.1 Maintenance of mammalian cell lines

Cancer or non-cancer (293-A) cell lines were maintained either in DMEM or RPMI media supplemented with 10% foetal calf serum (FCS), 50 U/mL Penicillin and

50μg/mL Streptomycin (see Tables 2.7 and 2.8 for details).

In general, cells were fed twice weekly and were passaged when monolayers were 70% confluent. Unless specifically mentioned, the passaging involved trypsinisation using

0.2% Trypsin-EDTA in PBS; a portion of the trypsinised cells as adequate for a

Chapter 2: Material and Methods 133 particular cell type was seeded into fresh tissue culture flasks. Cells were routinely

o maintained at 37 C, 5% CO2, in a humidified atmosphere (Sanyo CO2 Incubator;

Quantum Scientific, Queensland, Australia).

Table 2.7 Reagents used in routine maintenance and culturing of mammalian cell lines

Reagent Concentration/Storage Manufacture/ Supplier Dulbecco's modified Available as powder form, GIBCO/Invitrogen, Eagles's medium (DMEM) dissolved in MilliQ water; Melbourne, VIC Roswell Park Memorial storage at 4oC Institute medium-1640 (RPMI) Phosphate Buffer Saline 1X solution made from PBS (PBS) tablets Foetal Calf Serum (FCS) Final concentration to 10% (50 mL FCS plus 450 mL media) Penicillin-Streptomycin 50 U/mL Penicillin and (Pen-Sterp) 50g/mL Streptomycin in a final volume of 500 mL Trypsin-EDTA Available as ready to use (0.2%)

Note: All plasticware used in mammalian cell culture (cell culture flasks, petri plates, 6 or 96 well plates, 15 or 50 mL tubes, pipettes) was purchased from BD Falcon™, USA (otherwise mentioned)

Chapter 2: Material and Methods 134

Table 2.8 Mammalian cell lines and culture conditions

Type Name Description/use Media conditions Source Ref.

Ovarian SKOV-3 Ovarian adenocarcinoma; high expression of Her-2/neu RPMI supplemented ATCC1 (756,757) cancer receptor; often used as a positive control in Her-2/neu with FCS and target based strategies Penicillin/Streptomycin OVCAR-3 Ovarian adenocarcinoma; derived from a patient resistant antibiotics ATCC (758) to cisplatin therapy; often used in studies looking at mechanisms of platinum drug resistance; highly permissive to Ad infections A-2780 Ovarian adenocarcinoma; derived from a patient never Kindly provided by (759) Dr. Anna de Fazio, treated with chemotherapy; very fast growing Millennium Institute, Westmead, NSW Caov-3 Ovarian adenocarcinoma; minimal expression of integrins DMEM supplemented ATCC (756) and CAR receptor; non-permissive to Ad infection with FCS and Pen- Strep antibiotics Prostate PC-3 Prostate adenocarcinoma; originated from bone RPMI supplemented ATCC (760) cancer metastases; androgen in-sensitive; osteolytic phenotype in with FCS and Pen-strep bone antibiotics PC-3M- Luciferase-expressing cell line derived from PC3M human -Same as above plus Caliper Life (761) luc-C6 adenocarcinoma cells by stable transfection of the North Genticin (G-418) Sciences, MA, USA American Firefly Luciferase gene expressed from the 50μg/mL (Promega) SV40 promoter 134

Chapter 2: Material and Methods 135

RM1 Prostate adenocarcinoma; androgen-insensitive; highly DMEM supplemented Dr. Timothy C. (762) (Murine) aggressive and fast growing with FCS and Pen- Thompson (Baylor Strep antibiotics College of Medicine, Houston, TX, USA Lung A549 Lung adenocarcinoma; highly permissive for Ad5 ATCC (763) cancer infections: used as a positive control in Ad5 gene transduction studies Breast MCF7 Breast carcinoma; single gene copy number of Her-2/neu ATCC (764,765) cancer gene; used as a negative control in Her-2 targeted strategies Non- HEK293A Human embryonic kidney cells, provide E1 gene in trans ATCC (766) cancer for the production of replication deficient Ad virus HEK293A. In addition to features of HEK293A it is also stably DMEM supplemented Kindly provided by (767) Her-2/neu transfected with Her-2/neu gene; demonstrates a very high with FCS and Pen- Dr. Leif Lindholom, expression of Her-2/neu receptor; used in the production Strep antibiotics plus University of of Her-2/neu targeted ZZ viruses Genticin (G-418) Gothenburg, Sweden 50μg/mL 1ATCC, American Type Culture Collection, Rockville, USA

135

Chapter 2: Material and Methods 136

2.2.2 Cryopreservation of mammalian cell lines

The frozen cell stocks were preserved in liquid nitrogen for future use. Cells (70% confluent) were trypsinised and counted using a haemocytometer (Weber Scientific

International Ltd, Middlesex, UK). The cells were pelleted (200g/5minute) and the resulting pellet was gently resuspended in FCS containing 10% DMSO (@ 107 cells/mL) followed by quick aliquotting (1 mL each) into pre-chilled/pre-labelled cryovials. The cryovials were transferred to a cell-freezing device ‘Mr. Frosty’

(Nalgene, USA) (allows slower rate of cooling @1°C per minute) and cooled overnight at -80oC. After 24 to 48 h, cryovials were transferred into a liquid nitrogen storage tank

(Taylor-Wharton, New South Wales, Australia) for long-term maintenance of these cell lines.

2.2.3 Determination of cell viability using trypan blue dye exclusion test

Mammalian cell viability was determined using trypan blue exclusion method (see

Table 2.9). The trypsinised cells, diluted (2X) in trypan blue stain were loaded on haemocytometer chamber and viable cells (cells that did not take up the trypan blue stain) were counted at 100X magnification. Cells that stain blue are non-viable. The cell number/viability was calculated using the following formula:

Viable cell count = (number of viable cells/number of grids counted) X 1x104

X dilution factor X total cell volume (mL)

Chapter 2: Material and Methods 137

2.2.4 Mammalian Cell Based Assays

2.2.4.1 Transduction of cells with plasmids/Adenoviral vectors

In general, cells seeded in 24 well plates/96 well plate 24 h before virus infection were infected with Ad vectors at different MOIs. At 48h-72post infection (pi), the assays were carried based on transgene expressed in the by the viral vector.

GFP: Number of GFP expressing cells was determined by flow-assisted cell sorting (FACS) using CellQuestTM Version 3.0 for Mac Software (Becton Dickinson, San Jose, CA).

Luciferase: Luciferase activity was measured in OC and PC cell lines using a luciferase reporter assay (Promega). Briefly, 5X104 cells/well cultured in a 24 well plate in triplicate were infected with adenoviruses with different promoters regulating the luciferase gene at different multiplicity of infections (MOIs). After 48 h, cells were washed twice with PBS followed by 20-min incubation in lysis buffer. Cell lysates were clarified by centrifugation (18,000 g for 20 min at 4°C) followed by protein estimation using BCA assay as described (see Section 2.1.2.2). Luciferase activity was measured by mixing 20 μL of cell lysate with 100 μL of luciferase assay reagent followed by measurement of bioluminescence using TD-20/20 luminometer (Turner Designs,

California, USA). The bioluminescence measurements were presented as relative light units/mg of protein.

PNP: Cells infected with Ad/CMV/PNP at given MOIs were assessed for viability after 48 h. At each time point, virus was removed and the cells were further incubated in

Chapter 2: Material and Methods 138 complete growth medium (with or without prodrug, Fludarabine phosphate (Fludara) and cell viability assessed as described below.

2.2.4.2 Cell viability assays

Two different methods were used to evaluate the cell killing/growth inhibitory effects of gene therapy (GDEPT) and/or traditional chemotherapy (Taxotere and/or Carboplatin).

2.2.4.2.1 WST-1 Assay

2.2.4.2.2 Clonogenic Assay

Details of the reagents and drugs used in these assays are shown in Tables 2.9 and 2.10.

Chapter 2: Material and Methods 139

Table 2.9 List of reagents and cytotoxic drugs used

Assay/Method Protocol Reagent Concentration/ Manufacture/ Storage Supplier Cytotoxicity Cell proliferation WST-1 premix reagent 10μl per reaction/per well in a Takara Pty Ltd. Otsu Assays and cell cytotoxicity [Tetrazolium based dye 96 well plate, store at -20oC Shiga, Japan (4-[3-(4-Iodophenyl)-2-(4- nitrophenyl)-2H-5-tetrazolio]-1,3- benzene Disulfonate)] Cell viability Trypan blue exclusion dye 0.4%, storage in dark Sigma-Aldrich, Castle Hill, NSW Crystal violet foci Crystal violet 0.5% crystal violet solution Sigma-Aldrich, Castle formation assay (made in 25% methanol) Hill, NSW (clonogenic assay) Cytotoxic drugs Cell growth Taxotere Stocks 10mg/mL in absolute Sanofi Aventis, France inhibition studies ethanol, stored at –80oC Carboplatin Available as 10mg/ mL, stored Pfizer, North Ryde, at 4oC NSW Fludarabine Phosphate Stocks 10mg/mL in sterile Schering-Plough, water, stored at –80oC Germany

139

Chapter 2: Material and Methods 140

Table 2.10 Detailed Information about cytotoxic drugs used in this study

Type Docetaxel Carboplatin Fludarabine Phosphate Class Taxane DNA alkylating agent Purine analogue/pro-drug for PNP based GDEPT Trade name Taxotere Paraplatin (1989: Bristol-Myers Fludara Squibb) & Carboplatin (Generic) IUPC name (2R,3S)-N-carboxy-3- Azanide; cyclobutane-1,1-dicarboxylic [(2R,3R,4S,5R)-5-(6-amino-2-fluoro- phenylisoserine,N-tert-butyl ester, 13- acid; platinum purin-9-yl)- 3,4-dihydroxy-oxolan-2- ester with 5ß-20-epoxy- yl]methoxyphosphonic acid 1,2,4,7ß,10ß,13-hexahydroxytax-11-en- 9-one 4-acetate 2-benzoate, trihydrate

Chemical C43H53NO14•3H2O C6H14N2O4Pt C10H13FN5O7P Formula Molecular 861.9g/mol 371.2g/mol 365.2g/mol Mass Structure

140

Chapter 2: Material and Methods 141

2.2.4.2.1 WST-1 based cell viability assay

The cytotoxic effects of different treatments were determined by measuring the cell viability and proliferation using a REDOX sensitive tetrazolium-based WST-1 (4-[3-(4-

Iodophenyl)-2-(4-nitrophenyl)-2H-5-tetrazolio]-1, 3-benzene Disulfonate) dye based in vitro assays. This colorimetric assay is based on the cleavage of tetrazolium salts by mitochondrial dehydrogenase in viable cells. At the time of assay, the media were replaced by 100 L of fresh medium + 10 L of WST-1 dye. The absorbance was measured at 450 nm using Tecan Sunrise microplate reader (Phenix Research Products,

North Carolina, USA).

2.2.4.2.2. Clonogenic assays to assess cell cytotoxicity

Cells plated in triplicate in 96 well tissue culture plates were infected with either

Ad/CMV/PNP or Ad/CMV/GFP. After 48 h, virus-containing media was replaced with drug containing media (Fludarabine and/or Taxotere and/or carboplatin). The un- infected cells were treated with Taxotere and/or carboplatin. After 3 days, cells were harvested and plated in 6 well six-well tissue culture plates. The cells were incubated for two weeks (6-9 doublings) and then cell colonies were stained with crystal violet in absolute methanol (0.5%). Colonies containing more than 50 cells were counted and plating efficiency (number of surviving cells/number of cells plated) and surviving fraction (plating efficiency of cells treated /plating efficiency of the control cells) were determined.

Chapter 2: Material and Methods 142

2.2.4.3 Evaluation of synergy between drugs and PNP-GDEPT

Cells were infected with viruses followed by drug treatment as mentioned above (see

Section 2.2.4.2.2). WST-1 based cells viability assay was performed on day 7 (2 days of virus infection and 5 days of drug treatment) as described in Section 2.2.4.2.1. All treatments were performed in triplicate. Mean values and standard deviations were calculated and graphs were plotted using graph pad prism (version 5) and Microsoft

Excel (version 1997).

2.2.4.4 Evaluation of therapeutic interactions

The therapeutic interactions between Taxotere, carboplatin and PNP-GDEPT were analyzed using the isobologram method of Chou,T.C. AND Talalay, P (768) with the help of Calcusyn software (Biosoft, Cambridge, United Kingdom) (769-771) that allows statistical evaluation of interactions between 2 or more drugs (n). Chou and Talalay’s derivation is based on the median effect principle of mass action law (1864), which explains that the rate of any given chemical reaction is proportional to the product of the activities (or concentrations) of the reactants. This method is considered superior as it applies to both mutually exclusive (SAME OR SIMILAR mode of action) and non- exclusive drugs (INDEPENDENT mode of action).

The median effect equation correlating drug and its effects was developed and is used to derive the accurate value of relative potencies of different drugs (e.g. IC50 etc). The median effect plot (based on the logarithmic form of Chou’s median effect equation) forms the basis of quantification of synergism, summation and antagonism of drug combinations: log (fraction affected/ fraction unaffected) vs. log (Dose).

Chapter 2: Material and Methods 143

This plot helps determine:

• Dm value: The median effect dose , X intercept of the median effect plot

• m: The slope of the median effect curve that signifies the sigmoidicity of

the drug effect curve: m=1(hyperbolic) m>1(Sigmoid)

• Linear correlation coefficient (r): Goodness of the fit of the data to

median effect equation (For tissue culture r>0.90 and animal systems

r>0.85)

Using the software an important value called Combination index (CI) is generated that helps quantify the interactions: synergism, summation and antagonism for mutually exclusive and non-exclusive drugs (1983) (768).

• CI<1: Synergism (more than the expected additive effect)

• CI=1: Summation (Additive)

• CI>1: Antagonism (less than the expected additive effect)

Chou and Talalay further refined these ranges and denoted symbols for each kind of interaction to reduce discrepancy associated with data e.g. synergy may be mild, strong or very strong depending upon the CI values (Table 2.11)

Chapter 2: Material and Methods 144

Table 2.11 Recommended symbols for describing synergism, additivity or antagonism in drug combination studies analyzed with the Combination Index

(CI) Method1

Range of CI Symbol Description

<0.1 +++++ Very strong synergism

0.1-0.3 ++++ Strong synergism

0.3-0.7 +++ Synergism

0.7-0.85 ++ Moderate synergism

0.85-0.90 + Slight synergism

0.90-1.10 ± Nearly additive

1.10-1.20 – Slight antagonism

1.20-1.45 – – Moderate antagonism

1.45-3.3 – – – Antagonism

3.3-10 – – – – Strong antagonism

>10 – – – – – Very strong antagonism

1The combination index method is based on that described by Chou and Talalay (768) and the computer software of Chou and Chou and CalcuSyn (769-772)

Chapter 2: Material and Methods 145

Overall the following steps are followed in these statistical analyses:

• Calculate Dm and m values for drug/s from the median effect plot

• Calculate Dx for a given degree of effect (dose response curve)

• CI using the above values.

• Generate the isobolograms: A graph indicating the interactions between

different combinations of various doses to obtain a certain level of cell killing.

Illustrates synergy, additive and antagonism

• Dose reduction index (1988): represents fold reduction in individual doses in

the combination to achieve a certain effect (generally DR1>1 is beneficial; does

not necessarily indicate synergy). The software calculates Dose-reduction Index

(DRI), from this given equation (772).

CI = (D)1/(Dx)1 + (D)2/(Dx)2 = 1/(DRI)1 + 1/(DRI)2

Where:

CI denotes combination index

(D)1 and (D)2 are doses of drug 1 and 2 in combination, which result in x%

growth inhibition.

(Dx)1 and (Dx)2 are doses of drug 1 and 2 alone, which result in x% growth

inhibition

Chapter 2: Material and Methods 146

2.2.4.5 M30 CytoDEATHTM Apoptosis assay

Cells were analyzed for apoptosis using M30 CytoDEATHTM antibody, which binds to a caspase-cleaved epitope of cytokeratin 18-cytoskelatal protein (Peviva AB, Bromma,

Sweden). Briefly, cells (1X105) (24 well plate) were infected for two days with

Ad/CMV/PNP or Ad/CMV/GFP followed by treatment with either Fludara, Taxotere, carboplatin or their respective combinations. After 48 h, cells were harvested and fixed in methanol at -20°C for 30 mins followed by two washes with PBS containing 0.1%

Tween 20. The cells were then incubated with 100 μl of M30 CytoDEATHTM (1:100) or isotype control IgG2b (1:125) (Sigma-Aldrich) (see details in Appendix I) antibodies in incubation buffer (PBS containing 1% bovine serum albumin (Invitrogen) and 0.1%

Tween 20). Next, cells were incubated with a fluorescein-labelled secondary antibody

(FITC 1:70) (Silenus) in 100L incubation buffer for 1 h at 40C followed by a wash as described above. Immunostained cells resuspended in 500 L of osmosol sheath fluid

(LabAids) were then analysed by flow cytometry. Analysis was performed using a

FACScan (Becton Dickinson) and data were analysed using FlowJo Version 7.2.2 for

Windows (Tree Star, Inc., California, USA).

2.2.4.6 Cell-cycle analysis

Subconfluent OVCAR-3 cell cultures were treated with different treatments. At indicated time points, cells were harvested using 0.025% EDTA, washed in ice-cold

PBS and fixed by using ice-cold ethanol at 4°C for 30 mins followed by 2x wash in

PBS. The cellular DNA was stained with propidium iodide (50 g/mL propidium iodide, 0.1mg/mL RNase A and 0.25% Tween 20 (Sigma-Aldrich) in PBS) for 1 h at

37°C. The percentage of cells in the G0/G1, S and G2/M phases was assessed using a

Chapter 2: Material and Methods 147

FACScan (Becton Dickinson) and data was analyzed using Flow Jo Version 7.2.2 for

Windows (Tree Star, Inc., California, USA).

2.3 Therapeutic Effects in vivo

All experiments were performed with permission from the Animal Care and Ethics

Committee, University of New South Wales (AEC 08/91A and 07/123A).

Table 2.12 Materials and methods used in animal studies

Type Material/reagent Source/Supplier

Mice Athymic BALB/c nude Biological Resource Centre, Ethics number 08/91A Little Bay, NSW C57BL/6 Animal Resources Centre, Ethics number 07/123 Canning Vale, WA Anaesthesia Isoflurane (4%) Abbott Australasia Pty Ltd, Botany NSW Intraperitoneal Syringes Terumo Medical Corp, USA injections (i.p.) Cotton swabs Mutigate Medical Products Yennora, NSW Subcutaneous Syringes BD Biosciences, USA injections (s.c) Cotton swabs Mutigate Medical Products Yennora, NSW Intraprostatic Syringes Terumo Medical Corp, USA injections (iprost) Sutures Tyco Healthcare, Norwalk, USA Instruments e.g. forceps, Vetquip, Castle Hill, NSW scissors, needle holder etc. Temgesic (pain killer) Schering Plough, (0.05 mg/kg) Amstelveen, Netherlands Blood and serum Syringes Terumo Medical Corp, USA collection Bioluminescent Luciferin (150mg/kg) Xenogen Corp., Alameda, Imaging CA, USA Sacrifice Isoflurane Abbott Australasia Pty Ltd, Botany NSW

Chapter 2: Material and Methods 148

2.3.1 Evaluation of synergy between Taxotere and PNP-GDEPT in BALB/c nude mice

PC-3M-Luc cells were grown in routine media conditions (see Table 2.8) and when

50% confluent, these were infected with 10 moi of Ad/CMV/PNP. After 24 h, cells were harvested by trypsinisation and were kept on ice until injection. Transduced cells

(2X106/50 μl of PBS) were injected subcutaneously (sc) on the top flank of 5-6 week old male BALB/c nude mice. Mice were randomly divided into four different groups;

Group I Vehicle Treated (n=8), Group II Taxotere alone (n=9), Group III GDEPT

(n=10) alone and Group IV combination of Taxotere and GDEPT (n=12). Next day onwards, different groups of mice received Fludarabine Phosphate (50 mg/metre2/day) intraperitonially (ip) for 5 consecutive days. Taxotere was administered intravenously

(iv) at 12.5 mg/kg on day 1 and 7. Mouse weights were recorded twice a week as a control for the treatment related toxicity. Tumour sizes were measured twice a week using digital callipers. Tumour volumes were determined using the formula, V =

3/2 /6(d1.d2) , where d1 and d2 are diameters at right angles (773). At necropsy, when tumours reached to 15 X 15mm, mice were sacrificed and the tumours and other organs

(lungs, lymph nodes, spleen, liver and heart) were fresh frozen or paraffin embedded for subsequent histogical and immunohistochemical studies. Mouse sera were collected and stored at -80°C until analysis.

Chapter 2: Material and Methods 149

2.3.2 Bioluminescencent imaging of PC-3M-luc-C6 cells or tumours in mice

In vitro: For detection of bioluminescence in cultured cells, PC-3M-luc-C6 cells were grown O/N at different densities ranging from 1000, 2000, 4000, 10,000 and 20,000 cells/well of a 96 well plate in triplicate. Next day, media were replaced by 100 μl of fresh media containing 1l of luciferin (15mg/ mL; Xenogen Corp.) and then imaged using the IVIS 200 imaging system (Living Image®software, Xenogen Corp., CA,

USA).

In vivo: For animal studies, BALB/C nude mice were given Luciferin i.p. (150 mg/kg) then imaged after 7 mins using the IVIS 200 imaging system at 10 sec-1min time exposure. During the imaging session mice were continuously sedated with 3%

Isoflurane. Image analysis and bioluminescent quantification was performed using imaging software provided by Xenogen (Living Image® software, Xenogen Corp., CA,

USA).

2.3.3 Evaluation of synergy between Taxotere and GDEPT in C57BL/6 mice

Orthotopic RMI tumours were grown in 6-10 week old male C57BL/6 mice by implanting RMI cells in the subcapsular region of the prostate. Briefly, intraprostatic

(Iprost) injections were performed with 5 × 103 RM1 cells/50 μl of PBS using a 250 μL insulin syringe with an attached 29-guage 1/2 inch needle surgically after opening the abdomen in the mice. Animals were re-sutured and were monitored carefully for the next three days. On day 4 mice were given an Iprost injection of Ad/CMV/PNP (109 pfu/25 μl PBS) into the prostate tumours by opening the previous incision. Next day

Chapter 2: Material and Methods 150 onwards (day 5 to 10), Fludarabine phosphate or saline was administered i.p. daily at

200-400 mg/m2/mouse/day in a 200 μL volume for 5 consecutive days. On days 5 and

12 Taxotere (10-12.5 mg/kg/day) or vehicle control injections were given iv. On day 6, mice received an iv injection of 5 × 105 RM1 cells to establish the experimental lung pseudo-metastasis (except for survival experiment). Mouse weights were recorded every day until drug treatments stopped and thereafter recorded twice/week. The animals in experiments other than survival studies were killed on day 16 (study end point). Mice were sacrificed if a >20% weight loss or if any form of severe distress was observed. After harvesting, prostate tumours were weighed and measured. Tumour

3/2 volumes were determined using the formula, V = /6(d1.d2) , where d1 and d2 are diameters at right angles (773). The lung sections were fixed in Bouin’s reagent for facilitating lung colony counting under the dissecting microscope. The tumours and other organs (kidney, liver, heart, and spleen) were formalin fixed,-paraffin-embedded or fresh frozen for subsequent histological and immunohistochemical studies. Mouse sera were stored at -80 °C until analysis.

Animal survival: Orthotopic RM1 tumours were grown in mice (n=50) as described above. On day 4 animals were divided into five groups; virus alone/control (n=9),

GDEPT alone (n=10), Taxotere alone (n=9), Taxotere plus Fludarabine phosphate

(n=9) and combination of GDEPT and Taxotere (n=13). Treatments were performed as above. One-day post treatment, mice were tail bled for serum collection. Mice were culled if there were signs of distress or loss of condition, at which point, the tumours and other organs were harvested and stored as mentioned above.

Chapter 2: Material and Methods 151

2.3.4 Toxicity analysis

Treated and un-treated tumour bearing mice were weighed before and after different treatments. Mouse weights were used as a primary measure for toxicity analysis. Serum based toxicity analysis was performed at SEALS, Prince of Wales Hospital, Randwick-

NSW. Serum samples (150 l) of mice from four different groups (Ad alone, GDEPT alone, Taxotere alone and a combination of GDEPT and Taxotere) were used to assess renal and liver toxicity profiles. Following four different markers were analysed based on their standard use in mice/human toxicity analyses.

1. Urea

2. Creatinine

3. ALP: Alkaline Phosphatase

4. ALT: Alanine Amino Transferase

The corresponding values for a normal mouse were used as a reference/standard (774).

Chapter 2: Material and Methods 152

2.4 Immunohistochemical Analysis

2.4.1 Evaluation of expression of HER-2/neu in OC cell lines

A monoclonal antibody specific for mouse anti-human Her-2/neu cytoplasmic domain for immunostaining was used in this evaluation. Briefly, cells (3x105) were permeablized to expose cytoplasmic domain of Her-2/neu receptor using 100 L of permeablization buffer (0.1% saponin + 1% FCS in phosphate buffered saline, pH 7.2) in a 5 mL polystyrene FACS tube (Becton Dickinson, NJ, USA) followed by centrifugation at 200 g for 5 minutes at 4oC. Permeablised cells were then incubated with 1 g of primary anti-Her-2 antibody (100 g/mL, Chemicon, CA, USA) or Isotype

IgG1 (200 g/mL, DAKO Cytomation, CA, USA) (see details in Appendix I) for 30 mins on ice. The cells were washed with permeablization buffer (2 mL) and further incubated with 10 g/mL of fluorescein-labelled secondary antibody (FITC-rabbit-anti- mouse serum, Silenus, Melbourne, Australia) in 100 L of permeablization buffer for

30 minutes at 40 C on ice. The cells were then washed in sheath fluid (2 mL) and resuspended in 300 L sheath fluid. Flow cytometry was performed using FACScan

440 (Becton Dickinson, Mountain View, CA, USA) with a 5-W argon ion laser tuned to

488 nm at 200 nW. The fluorescence associated with each cell line was measured and expressed as the mean of fluorescence intensity (MFI), using the “Cell-Quest” software.

Mean fluorescence intensity above that of the control group represented a positive immunofluorescence-staining event.

Chapter 2: Material and Methods 153

2.4.2 Immunohistochemical (IHC) analysis of orthotopic prostate tumours

IHC analyses were performed on OCT-embedded frozen tumours, sectioned into 5 sections using Shandon Cryo-microtome (USA). Sections were placed on positively charged microscope slides (Menzel Superfrost UltraPlus) followed by fixation in cold acetone (2 min). Slides were air-dried (30 min) and rinsed in PBS (Ix). Endogenous peroxidase activity and non-specific binding were blocked by quenching with hydrogen peroxide (0.03% in water) (10 minutes) followed by incubation in avidin, biotin and 2%

IgG free BSA (10 mins each). After blocking, slides were rinsed in PBS wash buffer and sections were incubated with primary antibodies (details in Appendix II) for 1 h at RT in humidifying conditions. After rinsing in PBS wash buffer (2X5min), sections were incubated with secondary antibodies (30 min) (details in Appendix II). Specific intracellular immunoreactivity was detected by incubation with avidin-biotin/HRP complex (Vector Laboratories, CA, USA) at RT (30 min) followed by colour development in diaminobenzidine (DAB) chromogen (20 min). Cells were lightly counterstained in Harris hematoxylin (4 min), dehydrated in a graded series of alcohol

(70% EtOH for 1 minute; 95% for 2x1 minutes; 100 % for 2x1 minutes) cleared in xylene, and mounted in Eukitt for analyses by light microscopy. Scoring was done (n=3) by determining % of positively stained cells in 10 fields at x40 magnification.

Chapter 2: Material and Methods 154

2.5 Construction and Characterization of Recombinant Ad

Vectors

Recombinant, replication defective E1/E3 deleted Adenoviruses were constructed using the AdEasyTM adenoviral vector system (Stratagene) (775,776). This involves homologous recombinations between an adenoviral backbone plasmid vector and a shuttle vector carrying the gene of interest, performed in E. coli cells (777). A complete protocol beginning from construction of recombinant Adenoviral plasmid to viral rescue, purification and its titration is illustrated in Figure 2.1.

Chapter 2: Material and Methods 155

Figure 2.1 Flowchart showing construction and characterization of

Recombinant Adenoviral vector

Recombinant Adenoviral Vector Development And Characterization

Generation of Recombinant Ad plasmids

Shuttle Vector Development Bio-safety guidelines Homologous Recombinations to generate Ad plasmids

Generation of Recombinant Ad Virus

Standard Lipofection method

Virus Production in 293A cells

Initial Virus Production (7-9 days) ; P0

Virus Amplification 2 X T-75 Flasks; P1 Virus Amplification 20 X T-75 Flasks; P2

Virus Preparation and Purification

CsCl Density Centrifugation

Purification using NAP columns

10% Glycerol Stocks (-80degreeC)

Virus Quantification/Titrations

Traditional Plaque Assay

Virus Particle Count VP/mL

Chapter 2: Material and Methods 156

2.5.1 Overview of AdEasy system

The AdEasy system uses a three-step method for Ad construction (see Figure 2.2). In the first step, the gene of interest is cloned into the multiple cloning sites (MCS) of a shuttle plasmid. The second step involves homologous recombination between PmeI linearized shuttle plasmid and super-coiled adenoviral backbone vector plasmid performed in BJ5183 cells (778). The final step results in the generation of recombinant

Ads by transfecting recombinant Ad plasmid DNA in to E1-complementary, HEK-

293A cells (766). The new viral vectors are amplified in 293A cells. The production and purification was performed by standard methods using Cesium Chloride (CsCl) gradient ultracentrifugation. The viral titres (plaque-forming unit [pfu]/ mL) were determined by standard plaque assays.

Chapter 2: Material and Methods 157

Figure 2.2 A schematic overview of the production of recombinant Ad

L-ITR Promoter PolyA

ES Gene of Interest Kanar

pShuttle Vector pBR322 ori PacI Left arm homology Right arm homology

ClaI

pBR322 ori Ampr Left arm homology Right arm homology Regions of PacI Homologous Recombination

pAdEasy-I

Ad5, E1 and E3 deleted

PacI digestion

PacI

L-lTR ES Promoter Gene of interest pA Adenoviral DNA R-lTR

Transfect HEK-293A cells

Virus Production

Chapter 2: Material and Methods 158

2.5.2 Vectors used for new recombinant Adenoviral vectors

Three different vectors were used in general for Ad vector production; two types of shuttle (with or without CMV promoter) and backbone pAdEasy-I vector (see Appendix

IV). Shuttle vector/s with the gene of interest were recombined with the backbone pAdEasy-I vector to generate recombinant Ad DNA with the required gene. These vectors differ in their size and antibiotic resistance gene cassettes but have a common origin of replication represented as pBR322 gene. The regions indicated as right and left arm homology sequences are the potential sites for homologous recombination between the shuttle and backbone vectors (see Figure 2.3). The regions shown as R-ITR and L-

ITR are short inverted terminal repeats from the Ad genome, which play an important role in virus replication.

pShuttle vector: The shuttle vector contains a multiple cloning site (MCS), which offers a number of restriction sites to facilitate cloning process. This vector can take up to ~7.5kb of foreign DNA, which may include a promoter (Her-2/neu or survivin) with or without a stop signal (polyA or BGH), some specialized genes (PNP) or tracer elements (Luciferase or GFP).

pShuttle-CMV: This shuttle vector contains a multiple cloning site in between the CMV promoter and the SV-40 stop signal and it can accommodate up to 6.6 kb of foreign DNA. pAdEasy-I vector: This vector is ~33.4 kb and it can accommodate up to ~7.5 kb of foreign DNA. The vector contains most of the human adenovirus serotype 5 (Ad5) genome and has a deletion in E1 and E3 region making the recombinant Ad replication-

Chapter 2: Material and Methods 159 incompetent. During homologous recombination, gene expression cassette from a shuttle vector is inserted in E1 region and ampicillin antibiotic resistance gene is replaced by kanamycin resistance gene.

2.5.3 Biosafety

Adenovirus is an infectious respiratory virus and its use as a genetic vector requires the use of adequate containment equipment and practices. All the experiments involving any type of adenovirus were conducted according to the protocols and SOPs prepared according to the Office of Gene Technology Regulator (OGTR) guidelines. The experimental work was limited to a Physical Containment 2 (PC-2) laboratory approved by an UNSW Institutional Biosafety Committee (IBC).

2.5.4 Construction of pShuttle vector with gene of interest

A number of plasmids with elements of interest were obtained from different sources

(see Appendix III). The plasmids were amplified and stored after characterisation

(restriction enzyme based) using standard molecular biology techniques (see Sections

2.1.1.2 - 2.1.1.5).

Plasmid restriction profiles were generated using New England’s online NEB restriction cutter http://tools.neb.com/NEBcutter2/index.php. Depending upon the availability of restriction sites, strategies were planned to generate shuttle vectors with expression cassettes of interest. Mainly three different promoters (CMV, Her-2/neu and survivin) were used to derive the expression of therapeutic (PNP) or reporter genes (GFP or Luc).

Once constructed, these were linearised using PmeI (10 g shuttle gene + 10 units of

Chapter 2: Material and Methods 160

PmeI for 4 h @ 37oC). After purification (Qiagen nucleotide purification kit; Section

2.1.1.6) shuttle DNA was ready for use in recombination reactions (see below).

2.5.5 Generation of recombinant Ad plasmid with gene of interest

2.5.5.1 Electroporation in BJ5183 bacterial cells

Once the new shuttle vector with required elements was constructed, recombinations between purified PmeI linearised pShuttle gene (500ng) with a final volume of no more than 2 L were performed in E. coli BJ5183 AdEasy electrocompetent cells

(Stratagene) by electroporation as described in Section 2.1.1.10.

2.5.5.2 Miniprep and restriction digestion confirmation of Ad plasmids

Given the large size of Ad backbone in the new recombinant AdDNA, the smaller sized colonies were anticipated to be positive (the replication of bacteria with large size DNA is likely to be slower than those containing smaller plasmids). Twenty-four smallest colonies were grown for 24 h in LB medium and minipreps performed (see Section

2.1.1.2). First round of screening was on the basis of DNA size, unrestricted DNA was run on 0.7% agarose gel and the clones showing high molecular weight bands as observed with positive control, pAdeasy were likely to be positive for the large

Adenoviral plasmid. Further screening on selected clones was performed using Pac1 and/or SphI restriction digests. Using the electronic sequence of adenoviral plasmid, an expected SphI restriction pattern was obtained for the new recombinant construct (NEB

Chapter 2: Material and Methods 161 restriction cutter software). The clones showing the expected PacI and SphI restriction patterns were selected for further work. pAdEasy was used as the negative control for the second screening .

2.5.5.3 Large-scale production of recombinant Ad plasmid in DH10B cells

The BJ5183 cells are RecA positive to facilitate recombination. While this is of use for recombination, propagation of clones in these cells may yield unwanted recombination events leading to loss of integrity during propagation. To avoid this, once the positive clones are selected, the DNA is propagated in RecA negative DH10B cells using standard cloning techniques (see Section 2.1.1.8). Briefly, six clones are picked and screened further as mentioned earlier (see Section 2.5.5.2). A maxi prep (see section

2.1.1.3) is then performed to amplify DNA from the selected positive clone, followed by screening by restriction digestion and positive DNA stored at –20oC until further use

(i.e. transfections for rescue of recombinant Adenoviral containing the required elements).

2.5.6 Rescue of recombinant Adenovirus

Once pAd.gene was validated, the recombinant Ad was rescued in HEK 293A cells using lipofectamine based transfections of the relevant plasmid in accordance with the manufacturer’s protocol (see Figure 2.3). Routinely, 5X105 HEK 293A cells were plated in a six well plate overnight. Next day, media were changed to 2% FCS containing antibiotic free media and cells transfected with a complex of 2μg of PacI digested recombinant Ad plasmid and 6 μl of lipofectamine reagent (Invitrogen). After

Chapter 2: Material and Methods 162 overnight incubation with DNA-lipofectamine complexes, these were replaced with complete media containing 10% FCS and antibiotics, incubated for 48 h and then transferred to T-75 flasks. The media were changed every third day until visible cytopathic effects (CPE) were seen; CPE is an indication of injury to cells and ultimately cell death and thus indicates viral replication in the host cell. It is typically indicated by the dissociation of the adherent cells (7-9 days). Once the CPE reached

75%, cells were harvested (most of new recombinant Ad produced is likely to be associated with cells at this point), centrifuged (200 g for 5 mins at 4oC) and cell pellets were stored at –20oC.

Chapter 2: Material and Methods 163

Figure 2.3 Rescue of recombinant Ad with the elements of interest in HEK 293A cells

+ + + + + 1. Lipofection + + + -- - - Plasmid-Lipofectamine Anionic complex - - - - HEK-293A - - - -

2. Virus Production

3. Cell Lysis

Steps involved:

1. Plasmid (pAd.gene)-Lipofectamine complex infects 293-A cells

2. Production of recombinant Ad in 293A cells

3. Release of virus after cell lysis.

Chapter 2: Material and Methods 164

2.5.7 Production and purification of high titer Ad viruses

The virus was released from the virus-containing cells by lysis involving three to four

o cycles of freezing (ethanol/dry ice bath), thawing (37 C water bath) and vortexing (1 min to shear genomic DNA). The lysate was then centrifuged at 10,000 g for 15 mins at

o 4 C in a microfuge to remove cell debris and supernatants collected for subsequent use.

Confluent cultures of HEK 293A cells (2XT-75 flasks) (low passage number <40) with flattened morphology) were infected with viruses at ~5-10 pfu/cell. The virus producing cells were harvested when CPE (see Section 2.5.6) affected about 70-80% cells (2-3 days post infection). The pelleted cells (centrifugation at 201 g for 5 mins) were resuspended in 1 mL of cell culture media and stored at –20oC.

The virus released from 2XT-75 flasks (freeze/thaw/vortex X 4 cycles) was used to infect 20X T-75 flasks (90-95% confluency) for the large-scale production of adenovirus. At 70-75% CPE, virus-containing cells were stored in 50 mL tubes at –20oC until being purified by CsCl density centrifugation.

2.5.7.1 CsCl density banding

The recombinant virus was released into supernatants (500 L/t75 flask) as mentioned.

(freeze/thaw/vortex X 4 cycles) (see Section 2.5.7). Virus from these lysates was purified using ultracentrifugation using a CsCl concentration gradient. Supersaturated

CsCl solution was made in TRIS-EDTA solution at pH 8.0, (Invitrogen) and sterilized by autoclaving. The viral supernatants (8.2 mL) and supersaturated CsCl solution (5 mL) were mixed in 14 mL ultracentrifuge tube (Becton–Dickinson, NJ, USA) and covered with 1 mL of mineral oil to prevent leakage during ultracentrifugation. The

Chapter 2: Material and Methods 165 tubes containing the mix were balanced to three decimal points and centrifuged for 20 h using the swing bucket SW41 rotor (Beckman Instrument, CA, USA) at 176000 g (SW

o 41 Ti rotor at 32000 rpm) at 10 C. The virus band (at the density of 1.34 g/mL) was harvested with a 19-guage needle attached to a 5 mL syringe in 2-3 mL volume and

CsCl was removed from the virus solution using Nap 25 column chromatography.

2.5.7.2 Nap 25-column chromatography

Virus in CsCl solution was dialyzed using a Nap 25 column according to the instructions of the supplier (Amersham Bioscience, Uppsala, Sweden). At all times during this procedure, the virus containing solution was kept on ice. The Nap 25 column was equilibrated with 25 mL of PBS solution and 2.5 mL of CsCl-virus containing solution was loaded, due to size exclusion, the virus is trapped in the column and CsCl is eluted. The purified virus was then eluted in 3.5 mL PBS solution and stored in 10%

o sterile glycerol in PBS at –80 C.

2.5.8 Characterisation and titration of recombinant Adenoviruses

Accurate quantification of adenoviral stocks is very important for consistency between the different viral batches and reproducibility of gene transfer experiments both in vitro as well as in vivo. Virus titration was achieved using two different methods;

2.5.8.1 Physical viral particle number method

2.5.8.2 Infectious viral count using traditional plaque assay

Chapter 2: Material and Methods 166

2.5.8.1 Physical viral particle number (VP) method

The number of physical particles present in the viral preparation was routinely estimated from the DNA content, using the measurement of absorbance at 260 nm. The DNA was extracted using Hirt’s extraction method (779,780). The adenoviruses (100 L of 10- fold dilution of the virus stock) were lysed using 100 L lysis buffer (0.1% SDS in 10

o mM Tris HCl). The solution was heated at 56 C for 20 minutes with intermittent vortexing. The lysate was allowed to cool for 5 minutes and absorbance measured at

260, 280, and 320nm on a spectrophotometer (UV-160 UV-visible spectrophotometer,

GMI, Minnesota, USA). The values at 260 nm, 280 nm/260 nm, and 320 nm provided an indication of the particle number, protein contamination and non-protein contamination, respectively. The virus particle number (VP) was estimated based on the following formula:

VP = OD260 x dilution factor x extinction coefficient (1.3 x 10^12)

2.5.8.2 Infectious viral titre using traditional plaque assay

Plaque assay is the traditional method used for functional titration of Adenoviral stocks.

5 Typically, 24 h before starting, 293 cells were plated at a density of 5 x 10 (70-80% confluent) cells/well in 2 mL of growth medium in 6-well plates in triplicates. Serial

-5 -12 dilutions of Ad vectors were made in sterile cold PBS in the range of 10 –10 . Cells were infected with these dilutions and plates were left in a humidified CO (5%) 2 incubator overnight at 37°C. Next morning media was replaced with 2 mL of DMEM containing 1% agarose. Agar overlaying (2 mL each time) was done every third day to

Chapter 2: Material and Methods 167 replenish the cells. Plaques were visible within 6-9 days and were counted on day 10-

11 and viral titer estimated:

dilution factor Titre (PFU/ mL) = Number of plaques counted at highest dilution X 10 X

1000/volume of the viral stock

2.6 Statistical Analysis

The data analysis was done using GraphPad Prism version 5.00 (San Diego CA, USA).

The analytical tests used were: (1) Chi-square test; (2) one-way ANOVA with

Dunnett’s or Tukey’s multiple comparison post test; (3) students t-test, unpaired; or (4)

Kruskal-Wallis test.

Chapter 3: Combination Therapy for Ovarian Cancer 168

PROSPECTS OF COMBINING CONVENTIONAL AND MOLECULAR CHEMOTHERAPY FOR THE TREATMENT OF OVARIAN CANCER

Chapter 3: Combination Therapy for Ovarian Cancer 169

3.1 Introduction

OC is not an outcome of a single gene defect or mechanism, which is why single agents

(targeting one gene/pathway) are unable to cure most solid tumors (Chapter 1). Further, in order to achieve therapeutic efficacy with a single agent, high doses are required which can entail severe side effects and poor clinical outcome and quality of life.

Clearly, there is a need to explore combination therapies that can potentially increase efficacy and minimise side effects. The components of combination regimens are chosen to, 1) achieve enhanced tumour cell killing (components should have potential to act synergistically) 2) avoid the risk of tumour cell resistance (components should work independently on different cell populations) and finally 3) reduce dose related side effects (modalities should have non-overlapping toxicities). A combination of new therapies (such as GDEPT) with traditional therapies may have potential given that patients that enroll in new trials are undergoing or have undergone some form of therapy.

With the current limitations of effective gene delivery in situ, GDEPT provides a potent strategy for the treatment of local and metastatic disease (287,649,781,782). As discussed in previous sections (see Sections 1.4.2.2 and 1.7.6.2), among different enzyme-pro-drug combinations, HSV-tk/Ganciclovir (GCV) system is the most widely tested so far (634,655,717). In fact, this is the only GDEPT system, which has been tested in a Phase III clinical trial for Glioblastoma. However, results from this trial did not demonstrate any benefits (783). Subsequently though, a better outcome was achieved when this was tried in combination with topoisomerase inhibitor I, topotecan, in a Phase I clinical trial conducted on ten patients with recurrent OC. This

Chapter 3: Combination Therapy for Ovarian Cancer 170 combination therapy led to an enhancement of overall median survival (OS); treated patients displayed an OS which was one-third longer in comparison to patients given traditional chemotherapeutic treatments. Overall a better outcome is obtained when combination regimens are used (Chapter 1). Given that OC is often diagnosed at a late stage, chemotherapy remains the mainstay for treatment; especially platinum drugs in combination with taxanes now form the standard of care for these patients. Recently, the carboplatin/docetaxel combination has attracted interest due to relatively lower toxicities than the paclitaxel/cisplatin combination.

This study will explore the prospective synergies between molecular chemotherapy engendered by PNP-GDEPT and chemotherapeutics, Taxotere and Carboplatin against

OC cells. Specifically, GDEPT based on the E. coli enzyme, PNP (323), will be explored in combination with the FDA approved pro-drug, Fludarabine Phosphate. The primary features of this system are discussed in Section 1.4.2.2.2 and 1.7.6.2.3. The fact that E. coli PNP has a strikingly different active site and binding features to its substrates compared with that of mammalian PNP makes it a good candidate for application to humans (784). PNP-GDEPT is engendered by PNP-mediated conversion of systemically administered Fludarabine Phosphate into active toxic metabolites (2-

Fluoroadenine (2FA) (also see Figure 1.8). Its potential for tumor-directed gene therapy is proven pre-clinically (308,343). The premier features of PNP-GDEPT include its potential to kill both dividing and quiescent cells (327) and superior potency of bystander cell killing effects due to gap-junction independent passive diffusion of toxic metabolites to surrounding cells (785). Its advantage over other GDEPTs has been shown; unlike other GDEPT systems (e.g. HSV-tk), strong ‘bystander effects are

Chapter 3: Combination Therapy for Ovarian Cancer 171 achieved even when only 1 in 100 to 1 in 1000 cells express the PNP transgene

(308,328,329,341). Indeed, several preclinical comparisons have shown PNP-GDEPT to be more effective then HSV-tk/Ganciclovir based GDEPT (334,347). Further, PNP-

GDEPT delivered using Ad vectors is effective against prostate, ovarian, melanoma, colon carcinoma, hepatocellular carcinoma and human glioma in in vitro and in vivo studies (see Sections 1.4.2.2.2 and 1.7.6.2.3). Hence, we selected Ad-mediated PNP-

GDEPT for testing as a first modality.

Taxotere (commercial name for docetaxel) has been chosen as the second modality; its efficacy as second line therapy in treatment of ovarian cancer is well established.

Taxotere offers both symptomatic and survival benefits to those who respond to the treatment (76,786). Unfortunately, this is associated with significant toxicity leading to neutropenia, severe fluid retention, diarrhea and acute hypersensitivity.

Carboplatin has been chosen as the third modality. Its use in combination with Taxotere has been explored to improve the therapeutic outcome of OC but with limited success.

Synergistic interactions between CP and Taxotere have already been shown in vitro in

OC cell lines (69). In clinical studies this combination resulted in significant toxicities mainly leading to grade 3-4 neutropenia and other neutropenic complications (47)

(details in Section 1.3.2). Clearly, a reduction in individual doses will be a desirable advantage.

While Taxotere and carboplatin as single therapeutic agents or in combination have been evaluated in several preclinical and clinical studies, potential application of PNP-

Chapter 3: Combination Therapy for Ovarian Cancer 172

GDEPT in the context of OC is still in its infancy and has been tested only in one preclinical study conducted by Gadi et al (308).

Hence in this study, the combination of PNP-GDEPT with Taxotere and carboplatin was evaluated as a multimodality approach to maximize efficacy and to reduce individual doses to minimize treatment-associated cytotoxicity. It is anticipated that results from this study will form a basis for the development of future combination regimens for the treatment of clinical OC.

The specific aims of this study are:

1) To evaluate dose responses to individual modalities; PNP-GDEPT, Taxotere and

Carboplatin

2) To assess the therapeutic efficacy of a combination of Taxotere and carboplatin

in vitro.

3) To evaluate bystander effects of Ad-mediated PNP-GDEPT and correlate cell

killing with Ad-transduction efficiency in OC cell lines in vitro.

4) To evaluate and analyse therapeutic interactions between PNP-GDEPT,

Taxotere and carboplatin.

Chapter 3: Combination Therapy for Ovarian Cancer 173

3.2 Results

The OC cell lines used for this study represent different histological subtypes (see Table

2.8). Apart from individual modalities, combinations evaluated include,

1. PNP-GDEPT plus carboplatin or Taxotere (bi-modal)

2. Taxotere plus carboplatin (bi-modal)

3. PNP-GDEPT plus carboplatin plus Taxotere (tri-modal)

3.2.1 Optimisation of cell plating densities for dose response studies

Prior to evaluation of dose responses of different OC cells to different modalities, the optimal plating density was determined using cell proliferation assays (WST-1, see

Section 2.2.4.2.1) for a 96 well format. Based on absorbance readings the growth curves were generated for four different OC cell types after culture for 7 days (duration of most drug response experiments) (Figure 3.1). The optimal plating densities (cell numbers/well) were chosen from exponential or log phase of cell growth for future cytotoxicity experiments (Table 3.1). Depending upon their doubling times, these cell lines displayed differences in growth properties. OVCAR-3, A2780 and Caov-3 were slow growing (doubling time of 32-35 hrs) and hence, a higher seeding density was needed for OVCAR-3/Caov-3 compared to SKOV-3.

Chapter 3: Combination Therapy for Ovarian Cancer 174

4 A B 4

3 3

2 2

1 1 Absorbance at at 450nm Absorbance Absorbance at 450nm at Absorbance

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 000 0 0 3 6 9 2000 4000 6 8 12000 1500 10000

Cell Number/well Cel l Number/wel l

C D

4 4

3 3

2 2

1 1 Absorbance at 450nm at Absorbance Absor bance at 45 0nm

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3000 6000 9000 2 5 8000 3 6 9000 5 1 1 1 12000 1 Cell Number/well Cell Number/well

Figure 3.1 Cell growth curves for different ovarian cancer cell lines: WST-1 assay was performed on cells plated at different cell densities in a 96 well plate. Growth curves were generated on day 7 of culture. Each graph shows variation of absorbance (450 nm) with increasing plating density of OVCAR-3 (A), SKOV-3 (B), A-2780 (C) and Caov-3 (D). Cell numbers chosen for future studies are shown as the dotted line in the middle of logarithmic or exponential growth phase. Each value is the mean (±SEM) of three experiments.

Chapter 3: Combination Therapy for Ovarian Cancer 175

Table 3.1 Optimal Plating densities for different OC cell lines

OVCAR- 3 SKOV-3 A-2780 Caov-3

Plating Density 7,000 3,000 10,000 9,000 (Number of Cells /well)*

* These numbers were optimised for a 96 well plate format

3.2.2 Effects of Taxotere treatment on OC cell lines

To determine OC cell growth inhibition by Taxotere, cells cultured in 96 well plates were treated with Taxotere at different doses (0.1, 0.2, 0.3, 0.6, 1, 3.1, 10, 31.6 and 100 nM) in triplicate and cell viability was determined after 2, 3, 4 and 5 days using WST- assay (see Section 2.2.4.2.1). The values (absorbance measured at 450 nm) were normalised to vehicle treated (corresponding concentration of poly 80 and ethanol as used in highest concentration of Taxotere tested) control cells. Data were analysed using nonlinear regression analyses generating sigmoid dose response curves (GraphPad

Software, Inc., Version 5, San Diego, California, USA). The growth inhibitory effects of Taxotere were found to be time and dose dependent in all cell lines (Figure 3.2).

Taxotere concentrations needed for 50% inhibition of cell growth (IC50) on 2, 3, 4 and 5 days of exposure are shown in Table 3.2. Overall, all cell lines showed growth inhibition in response to Taxotere, albeit to a variable level, suggesting differential sensitivity to treatment. IC50 values for different cell types calculated on day 5 showed

2 that the A-2780 cell line (IC50-0.06 nM ± 0.3; R = 0.97), which was derived from a patient who was never treated with chemotherapy, was the most sensitive, followed by cisplatin resistant SKOV-3 (0.31 nM ± 0.7; R2 = 0.96), OVCAR-3 (0.61 nM ± 1.1; R2 =

0.99), and Caov-3 (1.21 nM ± 1.4; R2 = 0.97).

Chapter 3: Combination Therapy for Ovarian Cancer 176

Docetaxel dose response curves of OC cell lines

SKOV-3 OVCAR-3 Caov-3 A-2780

100

100 100 100

45 45 45 45 Cell Survival (% of vehicle control) Cell Survival (% of vehicle control) vehicle of (% Cell Survival Cell Survival (% of vehicle control) of (% Cell Survival Cell Survival (% of vehicle control) of (% Cell Survival

-10 -10 -10 -10 Control 0.1 1 10 100 Control 0.1 1 10 100 Control 0.1 1 10 100 Control 0.1 1 10 100

Docetaxel Concentrations (nM)

Day 2 Day 3 Day 4 Day 5

Figure 3.2 Response of OC cells to Taxotere treatment: Four OC cell lines were exposed to a range of Taxotere concentrations (0.1–316 nM). WST-1 assay was performed to analyse cell viability on days 2, 3, 4 and 5. Cell survival, which is the percentage of vehicle control cells (cells treated with corresponding concentrations of poly 80 + ethanol), was determined using GraphPad Prism. Dose response curves for A-2780, SKOV-3, OVCAR-3 and Caov-3 as generated on days 2, 3, 4 and 5 are shown. From the dose effect curves it was concluded that the A-2780 cell line was the most sensitive followed by SKOV-3, OVCAR-3 and Caov-3. Values represent a mean (±SEM) of three experiments.

176

Chapter 3: Combination Therapy for Ovarian Cancer 177

Table 3.2 Taxotere (nM) needed to kill 50% of ovarian cancer cell populations (IC50 values)

1 OC Cell Type IC50 ±SEM (nM)

Day 2 Day 3 Day 4 Day 52

(R2 )3 (R2 ) (R2 ) (R2 )

SKOV-3 1.459±1.1 0.498±0.7 0.375±0.6 0.310±0.7

(0.96) (0.93) (0.970 (0.96)

OVCAR-3 2.901±1.7 1.255±1.7 1.020±1.1 0.614±1.1

(0.94) (0.98) (0.98) (0.99)

Caov-3 3.511±2.1 1.494±1.9 1.467±1.6 1.212±1.4

(0.92) (0.98) (0.97) (0.96)

A-2780 0.685±0.7 0.479±1.1 0.186±0.4 0.066±0.3

(0.97) (0.96) (0.96) (0.97)

1 Calculated from dose response curves shown in figure 3.2 2 The IC50 values obtained after 5days of drug treatment were used in drug combination studies 3 R2 values >0.9 suggest that data is reliable and fits the statistical considerations

Chapter 3: Combination Therapy for Ovarian Cancer 178

3.2.3 Effects of Carboplatin treatment on OC cell lines

The cell growth inhibition by carboplatin were assessed on multidrug resistant (including cisplatin) SKOV-3 and OVCAR-3 cell lines (158). Cells treated for 5 days with an increasing range of drug concentrations (5-400 M) were analysed for cell viability on day 5. These data were acquired only on day 5 based on facts that Taxotere and PNP-

GDEPT were at their most effective on this time point. Cell viability data obtained were normalised with vehicle (sterile water) treated cells. For each cell line, non-linear sigmoidal dose response curves (Figure 3.3) were generated as described in Section 3.2.2.

The IC50 values generated from dose response curves are shown in Table 3.3. OVCAR-3 cell line (43.12 M ± 6; R2 = 0.97), which has been established from a patient resistant to platinum therapy, displayed a slightly higher IC50 value compared to the SKOV-3 cell line (38.73 M ± 4; R2 = 0.96), which was originally obtained from a patient with intrinsic resistance to clinically achievable doses of cisplatin (787).

Chapter 3: Combination Therapy for Ovarian Cancer 179

Carboplatin dose response curves of OC cell lines

SKOV-3 OVCAR-3 105 105

50 50 Cell Survival (% of vehicle control) of (% Cell Survival Cell Survival (% of control)vehicle of (% Cell Survival

-5 -5 Control 5 10 25 50 100 200 400 Control 5 10 25 50 100 200 400

Carboplatin ( M) Carboplatin (M) Dose Response Curves on day 5

Figure 3.3 Response of OC cell lines to carboplatin treatment: SKOV-3 and

OVCAR-3 cell lines were exposed to different carboplatin concentrations (5–400M) in triplicate. IC50 values were determined using WST-1 assays and dose response curves generated (Graph Pad Prism Ver. 5). The graphs show cell viability normalised with vehicle treated control cell Vs. increasing levels of drug concentrations. Results showed that almost similar levels of growth inhibition were displayed by SKOV-3 and OVCAR-3 cell lines (see Table 3.3). The values represent mean (±SEM) of three experiments.

Chapter 3: Combination Therapy for Ovarian Cancer 180

Table 3.3 Carboplatin (M) required to kill 50% of OVCAR-3 and SKOV-3 cell populations (IC50 values)

OVCAR- 3 SKOV-3

* IC50 ± SEM 43.12 ± 6 38.73 ± 4 (R2 = 0.97) (R2 = 0.96) (M)

*IC50 values were calculated from dose response curves shown in Figure 3.3

3.2.4 Efficiency of Ad-transduction in different OC cell lines

A prerequisite for a successful gene therapy approach is to achieve high gene transduction efficiency. Hence, before evaluating the Ad-PNP-GDEPT, we assessed efficiency of Ad5 transductions in different cell types. For this, percentage of GFP expressing cells in Ad5/CMV/GFP infected cell lines were assessed (after 48 h) using flow cytometry. The quantitative estimation of GFP positive cells showed a variable level of Ad-permissivity in different cell lines (Figure/Table 3.4); at an moi of 100 pfu/cell,

OVCAR-3 cells were the most permissive (~% GFP expressing cells: 80±5) followed by

A-2780 cells ((% GFP expressing cells: 15±4) and SKOV-3 ((% GFP expressing cells:

12±4). A lung cancer cell line A-549, which is highly permissive for Ad5 infections, was used a positive control. OVCAR-3 cells displayed played highest Ad-permissivity at all

Ad/CMV/GFP-doses tested. Caov-3 cells were found to be almost refractory to Ad- infections with only 3% GFP expressing cells even at high moi of 500 pfu/cell.

Chapter 3: Combination Therapy for Ovarian Cancer 181

Transduction of OC cell lines with Ad/CMV/GFP

100 A-549 OVCAR-3 SKOV-3 80 A-2780 Caov-3

%GFP Expressing Cells 20

0 500 100 50 10 Viral Dose (moi*)

Percent GFP Expressing Cells

Viral dose(moi*) A-549 OVCAR-3 SKOV-3 A-2780 Caov-3 500 98 92 55 42 3 100 75 80 12 15 1 50 46 57 6 8 1 10 7 12 2 2 1 *multiplicity of infection

Figure/Table 3.4 Evaluation of Ad-transduction in different OC cell lines: To check the permissiveness of cancer cell lines for Ad5 transduction, cells infected with

Ad5/CMV/GFP for 48 h were analyzed for GFP expression by flow cytometry. OVCAR-

3 cells were the most permissive (comparable to the positive control, A-549 cells) followed by A-2780 and SKOV-3 while Caov-3 cells were non permissive to this virus. Values represent mean (±SEM) of three experiments.

Chapter 3: Combination Therapy for Ovarian Cancer 182

3.2.5 Bystander effects of PNP-GDEPT correlate with the efficiency of gene transduction

It has been shown that success of the PNP-GDEPT system would depend upon a successful bystander effect, which is directly proportional to levels of PNP expression to liberate enough toxins to produce a measurable anti-tumor effect (785). Our data (Figure

3.5) clearly demonstrate that cytotoxicity due to bystander effects mediated by PNP-

GDEPT increased with increasing doses of Ad/CMV/PNP virus. The cytotoxic effects (% cell death compared to untreated controls ± SEM) were maximum in OVCAR-3 cells

(50% ± 5.1 at moi of 4 pfu/cell) followed by SKOV-3 (25% ± 5 at moi of 100 pfu/cell) and A-2780 (15% ± 7 at moi of 100 pfu/cell). IC50 values were calculated as moi of

Ad/CMV/PNP (+1 μg/mL of Fludara) needed to cause 50% of cell growth inhibition

(dotted lines in graphs in Figure 3.5). The relative potency of PNP-GDEPT (IC50 ± SEM,

Table 3.5) against different cancer cell lines was maximal in OVCAR-3 (4±3) followed by SKOV-3 (153 ± 12) and then A-2780 cells (225 ± 14). However, cell growth inhibition was not observed in Ad refractory Caov-3 cells. Further, the ‘bystander effects’ were observed in all cell lines except Caov-3. In highly permissive OVCAR-3 cells (Figure 3.5), a significant level of cell inhibition was observed at low viral doses of

1 or 2 moi and up to 90-100% cell growth inhibition was noted when only 12% (achieved at moi of 10, Figure 3.4) of the cells expressed PNP. The ‘bystander effects’ in other cell lines were also proportional to their level of Ad5-permissivity. However, despite similar levels of gene transduction in SKOV-3 and A-2780 (Figure 3.4), trends in cell growth inhibitions were different. A viral dose of 150-200 moi (+ Fludara) demonstrated 40-60% of cell growth inhibition in SKOV-3 but only 30-40% in A-2780 cells (Figure 3.5). This could be attributed to other differences such as diffrence of origin and hence different

Chapter 3: Combination Therapy for Ovarian Cancer 183 levels of sensitivity to Fludara and its metabolites. Control treatment with Ad/CMV/GFP and 1 g/mL of Fludara did not show any significant toxicity in all cell types suggesting non-toxicity of Fludara to these cells at 1 g/mL, in vitro.

Chapter 3: Combination Therapy for Ovarian Cancer 184

A: A-2780 B: OVCAR-3

Ad/CMV/PNP+Fludara Ad/CMV/GFP+Fludara Ad/CMV/PNP+Fludara Ad/CMV/GFP+Fludara 110 100

50 50 Cell survival (% of control) Cell survival (% of control)

0 -10 0 50 100 150 200 250 300 350 400 450 0 2 4 6 8 10 12 14 16 18 20 Virus Dose (moi) Virus Dose (moi)

C: SKOV-3 D: Caov-3

Ad/CMV/PNP+Fludara Ad/CMV/GFP+Fludara Ad/CMV/PNP+Fludara Ad/CMV/GFP+Fludara

100 100

50 50 Cell survival (% of control) Cell survival (% of control)

0 0 -50 0 50 100 150 200 250 300 350 400 450 -50 0 50 100 150 200 250 300 350 400 Virus Dose (moi) Virus Dose (moi)

Figure 3.5 Evaluation of bystander effects associated with PNP-GDEPT in OC cells: Cells were infected with Ad/CMV/PNP or Ad/CMV/GFP (control) at different mois followed by prodrug treatment (Fludara 1 g/mL). Cell viability was evaluated on day 5 using WST-1 reagent. Graphs show changes in cell viability relative to control (percentage of control cells), for different cell lines. The data demonstrate that bystander effects and resulting cytotoxicty increased with increasing doses of test virus. The cytotoxic effects were maximal in OVCAR-3 cells (Graph B) followed by SKOV-3 (Graph C) and A-2780 cells (Graph A). Significant ‘bystander effects’ due to diffusion of the drug, 2FA into non-transduced cells, were observed in all except Caov-3 cells (Graph D). Values represent mean (±SEM) of three experiments.

Chapter 3: Combination Therapy for Ovarian Cancer 185

Table 3.5 IC50 values of PNP-GDEPT in different OC cell lines

PNP-GDEPT OVCAR- 3 SKOV-3 A-2780 Caov-3 Virus moi plus pro-drug1

4 ± 3 153 ± 12 225 ± 14 None 2 IC50 ± SEM

1 Ad/CMV/PNP moi plus 1 g/ml of Fludarabine Phosphate 2 Estimated values based on dose response curves (Figure 3.5)

3.2.6 PNP-GDEPT, Taxotere and Carboplatin act synergistically in OC cells in vitro

To evaluate interactions between Taxotere, carboplatin and PNP-GDEPT when used in combination, two different methods were used to evaluate the efficacy of the combination treatments:

1. Clonogenic assay

2. WST-1 based tetrazolium assay

Chapter 3: Combination Therapy for Ovarian Cancer 186

3.2.6.1 Clonogenic assay

Clonogenic or colony formation assay is based on a single cell’s ability to grow into a colony. This assay was done to correlate the short term responses based on cell viability

(WST-1 assay) with long term responses based on toxicity and % cell survival to different treatments. Representative data for one cell line (OVCAR-3) are shown (Figure

3.6). Due to difficult logistics of this assay only OVCAR-3 cells (aggressive cisplatin resistant phenotype) were used to assess cell killing for different combinations: Taxotere

(1.3 nM) or carboplatin (40 M) or PNP-GDEPT (Ad/CMV/PNP at an moi of 4 pfu/cell plus 1 g/mL Fludara) either alone or in combination. After 3 days, cells were transferred to 6 well plates and grown for 10 days under normal cell growth conditions. In comparison to individual treatments, % of surviving cells was significantly reduced when all three were used in combination (Figure 3.6). Percentage of cell death (% ± SEM) achieved using Taxotere, carboplatin or PNP-GDEPT was 58 ± 14, 64 ± 16 and 78 ± 8, respectively compared to ~100% tumor cell killing achieved in combination.

Chapter 3: Combination Therapy for Ovarian Cancer 187

A B 700 P=0.0043 Control Taxotere Control 600 Carboplatin Colony count 560 ± 123 PNP-GDEPT 500 Tricombination

Taxotere 400 (1.3 nM) * Colony count 234 ± 78 300 *

Carboplatin 200 * (40 M) colonies of Number Colony count 202 ± 89 100 * PNP-GDEPT 0 (Ad/CMV/PNP at 4 moi plus 1 g/mL of Fludara) Colony count 123 ± 67 C Tri-combination 60 (Taxotere, Carboplatin P < 0.0001 Taxotere And PNP-GDEPT) * Carboplatin Colony count 13 ± 7 50 PNP-GDEPT * Tricombination Figure 3.6 Clonogenic assay for OVCAR-3 cells given different 40 treatments: Cell killing effects of Taxotere, carboplatin and PNP-GDEPT either alone or in combination on OVCAR-3 cells were analysed using 30 * colony formation assay. Panel A shows a photograph of crystal violet stained colonies of OVCAR-3 cells given different treatments in a 6 well 20 plate. Panel B graph represents number of colonies/well for different treatment groups and Panel C graph shows percentage of cell survival in ofCellcontrol) (% Survival 10 cells given different treatments. Values represent mean (±SEM) of two * independent experiments. Values were compared to control by one-way 0 Anova using Dunnett’s multiple comparison test. A P value < 0.05 was

considered significant represented by *. 187

Chapter 3: Combination Therapy for Ovarian Cancer 188

3.2.6.2 Evaluation of cell growth inhibition in cells given combination treatment

Cisplatin resistant, SKOV-3 and OVCAR-3 cell lines were selected to assess inhibition of cell growth by combination treatments. For these experiments, five different doses (as x

IC50) of Taxotere, carboplatin and PNP-GDEPT were used in fixed ratios (e.g. 1:1, 1:2,

2:1, 1:4, 4:1) (see layout template, Table 3.6) and cell viability was analyzed by WST-1 assay after 5 days of treatment. The treatment related effects (mean values from three experiments) were plotted as 3-dimensional graphs using Microsoft Excel and interactions between different modalities were assessed using Calcusyn software based on Chou and Talalay’s method (see Section 2.2.4.4 for details).

Four combinations were evaluated and the general scheme, drug doses, data analyses are described in this section.

Combinations evaluated: Taxotere plus carboplatin (see Section 3.2.6.2.1), Taxotere plus PNP-GDEPT (Section 3.2.6.2.2), carboplatin plus PNP-GDEPT (Section 3.2.6.2.3) and combination of all three regimens (Section 3.2.6.2.4).

Chapter 3: Combination Therapy for Ovarian Cancer 189

Table 3.6 Design of a combination therapy experiments

Experimental designs showing the 96 well layout displaying dose range of different treatments for drug combination. All treatments were done in triplicate.

TREATMENT I (XIC50)

Control IC50 ¼IC50 IC50 ½IC50 IC50 TREATMENT IC50 II (XIC50) ¼IC50

IC50

½IC50

IC50

Doses used for different modalities: For SKOV-3 and OVCAR-3 cells, Taxotere was used in dose range of 0.125 nM to 2 nM. Carboplatin was used in the dose range 5-40

μM for SKOV-3 cells and at 2.5-40 μM for OVCAR-3 cells. Given that the Ad-PNP-

GDEPT dose required for the same level of killing was significantly different for both cell lines (see Section 3.2.5), a different PNP-GDEPT-dose range was used for each

(SKOV-3, 9-150 moi plus 1 μg/mL of Fludara; OVCAR-3, 0.5-6 moi plus 1 μg/mL of

Fludara).

Analyses: For each combination tested, cell growth inhibition was analysed as percentage of vehicle treated controls. Values in final dose effect plots represent the mean of two independent experiments. Using 3-dimensional graphs, cell survival was plotted with respect to different drug doses either alone or in combination. For synergy analysis,

Chapter 3: Combination Therapy for Ovarian Cancer 190 the fraction affected (100 - % of cell survival; normalised to 1) at a given dose was used to generate dose effect curves (not shown). Data from these dose effects curves are used by the calcusyn software to generate IC50 (Dm) values based on the median effect principle (Chou and Talalay). Given the variation between experiments (cell passage, cell counts, batch related changes of reagents), IC50 values for each modality were calculated for each experiment and then these were used to back-calculate the drug concentrations in the format of XIC50 and resulting data were processed to accurately assess the type of interactions in combination. In general, combination treatments were given in constant ratios ranging form 1:1, 1:2, 1:4, 2:1 and 4:1. To simplify, the main representative data are shown for drug ratios of 1:1. Subsequently, isobolograms were constructed and analyses were performed using Calcusyn software. Isobolograms represent additivity, synergy or antagonism between two or more drugs (see Section 2.2.4.4 for details) and they can be generated to represent different levels of cytotoxic effects (e.g. ED50 (50% cell killing), ED70 (70% cell killing) and ED90 (90% cell killing). However, if too many effect levels are selected, the graphical representation becomes difficult. For this reason, to maximise the data representation, data are represented as a plot of fraction affected

(Fa) vs. combination index (CI; as this represents a numerical measure of additive effect

(CI = 1), synergism (CI < 1), or antagonism (CI > 1) between different modalities) as recommended by Chou and Talalay. For all combinations tested, combination index values to achieve 50%, 75% and 90% cell killing were assessed (Table 3.7). A statistical significance (p< 0.05) was obtained when combined effects were compared with either alone (as a group and not individual doses) (mentioned only if P > 0.05).

Chapter 3: Combination Therapy for Ovarian Cancer 191

3.2.6.2.1 Combined effects of Taxotere and carboplatin

Cell growth inhibition by Taxotere and carboplatin (alone or in combination) were tested in SKOV-3 and OVCAR-3 cells. A significant dose dependent inhibition of cell growth was seen using either treatment which was further enhanced when these were combined

(Figure 3.7). Analysis of CI-Fa plot generated for SKOV-3 cells (Figure 3.8 Panel I) shows that the combined efficacy of Taxotere and carboplatin was additive at most combinations tested. However, for OVCAR-3 cells (Figure 3.8 Panel II), mild synergy was observed especially at higher doses. Overall, the effects generated by the combined use of these regimens were mildly synergistic in OVCAR-3 cells (CI 0.76 at ED75; R value 0.99) and additive in SKOV-3 cells (CI 0.86 at ED75 R value 0.98) (Table 3.7).

Statistical analyses further revealed the dose reduction index (DRI) values for each modality in combination to achieve a specific effect for the two cell lines (tabulated in

Figure 3.8). The data indicated that when Taxotere and carboplatin were used in combination, lower doses could yield the same effect as achieved by higher individual doses as single agents; a dose reduction of ~2.7 folds for Taxotere and ~1.7 fold for carboplatin was needed to achieve 50% cell killing in SKOV-3 cells (Figure/Table 3.8

Panels I and III). Similarly, a dose reduction by ~2 fold for Taxotere and carboplatin was predicted to be adequate, when given together to achieve 50% cell killing in OVCAR-3 cells (Figure/Table 3.8 Panel II and IV).

Chapter 3: Combination Therapy for Ovarian Cancer 192

A: SKOV-3 B: OVCAR-3 90 90

80 80

70 70

60 60 50 50 40 40 rowth inhibition rowth

30 g 30 20 20

10 % of cell 10 inhibition growth cell of % 0 0 2 . 40 1. 00 2. 20 00 0 0 0.5 0 10 0 1.000 0 C 0.2 0 a 5.0 0 0.500 rb 0. 5 op 5 12 0 e 20 la 2. 0 er 0. tin 0 5 ot 10 25 e ax er T Ca 0. 0 t Carboplatin Taxotere (nM) rbopl 5 12 axo 5 T ati 0 0 (M) n 0 0.125 0.250 0.500 1.000 2.000 Carboplatin Taxotere (nM) 0 0 1016354853 (M) 0 0.125 0.250 0.500 1.000 2.000 2.5 8 1012394954 0 0 11192430365.0 20 25 26 36 49 57 5 5 202035404610 28 31 34 41 52 64 10 9 152135455220 38 42 46 56 63 76 40 55 57 68 68 78 81 20 23 26 30 32 46 61

Figure 3.7 Evaluation of cell growth inhibitory effects of combination of Taxotere and carboplatin: Cells treated with different doses of Taxotere and/or carboplatin were analysed for cell viability using WST-1 assay on day 5. Three-dimensional graphs representing inhibition of cell growth plotted as a function of increasing doses of Taxotere and carboplatin for SKOV-3 (graph A) and OVCAR-3 (graph B) cells are shown. Some combinations led to slightly greater cell growth inhibition compared with either alone. Values represent mean (±SEM) of three independent experiments. 192

Chapter 3: Combination Therapy for Ovarian Cancer 193

I 1.50 II 1.50

1.25 1.25 Antagonism Antagonism

1.00 Additivity 1.00 Additivity

Synergism Synergism 0.75 0.75

0.50 0.50 Combination Index Combination (CI) Combination Index (CI) Index Combination 0.25 0.25

0.00 0.00 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Fraction Affected (Fa) Fraction Affected (Fa)

III SKOV-3 IV OVCAR-3 Fraction Drug Alone Dose Reduction Index Fraction Drug Alone Dose Reduction Index affected (xIC50) (xIC50) affected (xIC50) (xIC50) (Fa) Taxotere CarboplatinTaxotere Carboplatin (Fa) Taxotere Carboplatin Taxotere Carboplatin 0.10 0.31 0.14 1.87 1.45 0.10 0.22 0.28 1.54 1.73 0.25 1.25 0.43 2.25 1.56 0.25 0.79 0.85 1.79 2.05 0.50 5.01 1.34 2.70 1.68 0.50 2.76 2.16 2.06 2.44 0.75 20.16 4.18 3.24 1.81 0.75 9.70 8.99 2.39 2.89 0.90 81.09 12.98 3.89 1.95 0.90 34.07 31.34 2.76 3.44

Figure 3.8 Analysis of combined drug effects of Taxotere and carboplatin: CI/Fa plots were generated based on Chou and Talalay’s method by plotting combination indices (CIs) for different combinations of Taxotere and carboplatin against the fraction affected (Fa). Additive effects are indicated for SKOV-3 cells (Panel I) as most of CI values are ~ 1(region of additivity as shown) while for OVCAR-3 cells (Panel II) a moderate level of synergy was indicated (CI<1) especially, for combinations achieving >50% of cell killing. Dose reduction index values for each drug to achieve different levels of cell killings by combination treatments are tabulated in panel III (SKOV-3) and IV (OVCAR-3) for the two cell lines. Significant levels of individual dose reductions were predicted to be adequate when these drugs were combined to achieve a specific effect Vs. doses when used alone.

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Chapter 3: Combination Therapy for Ovarian Cancer 194

Table 3.7 Combined effects of Taxotere and carboplatin in OC cells (drugs added as constant ratio of 1:1)

Cell Line Combination index (CI value) 1 R3 Effect4

ED2 50 ED75 ED90 SKOV-3 0.964 0.860 0.769 0.98 Additivity + OVCAR-3 0.895 0.764 0.653 0.99 Moderate Synergy ++

1 Combination index values generated when drugs were plotted as constant ratios 1:1 e.g. IC25 of Taxotere

2 3 with IC25 of carboplatin; ED, Effective dose, which can result in 50, 75 and 90% of cell killing; The linear correlation coefficient, R, of the median-effect plot. The acceptable range of ‘R’ values varies with the type of system used; Enzyme or receptor systems (r > 0.96), tissue culture systems (r > 0.90) and animal experiments (r > 0.85); 4Combination effects, CI value 0.90–1.10 signifies additivity (+); CI 0.7-0.85 moderate synergism (++); CI 0.85-0.9 slight synergies (+++); CI 0.30–0.70 synergism (++++); CI 0.10– 0.30 strong synergism (+++++) and CI 0.01–010 very strong synergism (++++++).

Chapter 3: Combination Therapy for Ovarian Cancer 195

3.2.6.2.2 Combined effects of PNP-GDEPT and Taxotere

Next, PNP-GDEPT and Taxotere (alone or in combination) were tested in SKOV-3 and

OVCAR-3 cells. The general scheme/analyses were performed as described in Section

3.2.6.2.1 with some differences. As with Taxotere, a significant dose dependent inhibition of cell growth using PNP-GDEPT was seen, this effect was significantly enhanced when combined with Taxotere (Figure 3.9). Analysis of the CI-Fa plot generated for SKOV-3

(Figure 3.10 Panel I) and OVCAR-3 (Figure 3.10 Panel II) shows that the combined efficacy was synergistic at most combination ratios tested in both cell lines. However, the synergistic cell killings were evidenced to a greater extent in OVCAR-3 than in SKOV-3 cells More specifically, the combined use of these regimens led to strong synergism in

OVCAR-3 cells (CI 0.13 at ED75; R value 0.93) with relatively lower synergistic effects in SKOV-3 cells (CI 0.32 at ED75; R value 0.98) (Table 3.8)

The dose reduction index (DRI) values for Taxotere and PNP-GDEPT in combination

(tabulated in Figure 3.10) was in accord with the CI based synergy data and showed that lower doses could achieve the same effect Vs individual doses. These analyses showed that a dose reduction of ~4 fold for Taxotere and ~6 fold PNP-GDEPT was needed to achieve 50% cell killing in SKOV-3 cells (Table/Figure 3.10 Panel I and Panel III). In comparison, a greater reduction in effective doses for Taxotere (~11 fold) and PNP-

GDEPT (~8 fold) (in combination) were predicted to achieve 50% cell killing in

OVCAR-3 cells (Table/Figure 3.10 Panel II and Panel IV).

Chapter 3: Combination Therapy for Ovarian Cancer 196

A: SKOV-3 B: OVCAR-3 100 100 90 90 80 80 70 70 60 60 50 50 40 40 30 30 20 20 % of cell growth inhibition 10 10 inhibition growth cell % of 0 0

0 15 0 6 00 0 00 2. 0 75 2. 0 4 00 00 1. 0 37 1. 0 2 0.50 18 50 1 0 0. 50 T 25 9 EPT 2 0 T a 0. 5 Ta 0. 5 . EP xo .12 GD xo 12 5 D te 0 0 Control P- te 0. C -G re PN re 0 ontrol P PN Taxotere Ad/CMV/PNP (moi) + 1g/mL Fludara Taxotere Ad/CMV/PNP (moi) + 1g/mL Fludara (nM) (nM) Control 9 18 37 75 150 Control 0.5 1 2 4 6 0 0 10121723340 0 1428364661 0.125 11 16 22 28 35 45 0.125 10 30 35 46 62 68 0.250 19 21 23 40 53 62 0.250 16 39 42 69 71 76 0.500 24 41 41 45 53 68 0.500 35 51 59 62 75 77 1.000 30 47 53 53 59 76 1.000 48 58 63 78 85 95 2.000 45 55 61 65 71 89 2.000 53 69 75 93 94 100

Figure 3.9 Evaluation of cell growth inhibitory effects of combination of PNP-GDEPT and Taxotere: Cells treated with different doses of Taxotere and/or PNP-GDEPT were analysed for cell viability using WST-1 assay on day 5. Three-dimensional graphs representing plots of % inhibition of cell growth with increasing doses of Taxotere and PNP-GDEPT are shown for SKOV-3 (graph A) and OVCAR-3 (graph B) cells. Most drug combinations led to significantly lower cell viability compared with either alone. Values represent mean (±SEM) of three independent experiments. A statistical significance (p< 0.5) was obtained when combined effects were compared with either alone (as a group and not individual doses).

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Chapter 3: Combination Therapy for Ovarian Cancer 197

1.50 1.50 I II 1.25 1.25 Antagoni sm Antagoni sm

1.00 Additivity 1.00 Additivity

Synergism Synergism 0.75 0.75

0.50 0.50 Combination Index (CI) Index Combination Combination Index (CI) Index Combination 0.25 0.25

0.00 0.00 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Fraction Affected (Fa) Fraction Affected (Fa)

III SKOV-3 IV OVCAR-3 Fraction Drug Alone Dose Reduction Index Fraction Drug Alone Dose Reduction Index (xIC ) (xIC ) (xIC ) affected (xIC50) 50 affected 50 50 (Fa) GDEPT Taxotere GDEPT Taxotere (Fa) GDEPT Taxotere GDEPT Taxotere 0.10 0.44 0.31 3.18 2.23 0.10 0.17 0.22 3.24 4.15 0.25 1.91 1.25 4.41 2.88 0.25 0.60 0.79 5.08 6.70 0.50 8.22 5.01 6.12 3.73 0.50 2.03 2.76 7.97 10.82 0.75 35.46 20.16 8.49 4.83 0.75 6.93 9.70 12.49 17.48 0.90 152.91 81.09 11.78 6.25 0.90 23.64 34.07 19.59 28.23

Figure 3.10 Analysis of combined drug effects of Taxotere and PNP-GDEPT: CI/Fa plots were generated as described above for different combinations of Taxotere and PNP-GDEPT against the fraction affected (Fa). Synergistic effects are indicated for both SKOV-3 (Panel I) and for OVCAR-3 (Panel II) cells as CI values are significantly lower than 1 at most drug combinations. Dose reduction index values to achieve different levels of cell killings by combination treatments are tabulated in panel III (SKOV-3) and IV (OVCAR-3) for two cell lines. Significant levels of individual dose reductions were predicted when these drugs were combined to achieve a specific effect Vs. doses when used alone.

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Chapter 3: Combination Therapy for Ovarian Cancer 198

Table 3.8 Combined effects of Taxotere and PNP-GDEPT in OC cells (drugs added as constant ratio of 1:1)

Cell Line Combination index (CI value) R Effect

ED2 50 ED75 ED90 SKOV-3 0.431 0.324 0.244 0.98 Synergistic +++ OVCAR-3 0.217 0.137 0.086 0.93 Strong Synergy ++++

See footnote of Table 3.7 for more details.

Chapter 3: Combination Therapy for Ovarian Cancer 199

3.2.6.2.3 Combined effects of PNP-GDEPT and carboplatin

In these experiments, cytotoxic effects of PNP-GDEPT and carboplatin (alone or in combination) were tested generally as described above in SKOV-3 and OVCAR-3 cells.

An enhancement in dose-dependent inhibition of cell growth was noted when the two modalities were combined Vs that observed with either (Figure 3.11). Similar to

Taxotere/PNP-GDEPT combination, CI-Fa plot generated for SKOV-3 (Figure 3.12

Panel I) and OVCAR-3 (Figure 3.12 Panel II) also showed synergy between PNP-

GDEPT and carboplatin. Strong synergies were obtained irrespective of the cell line used and were stronger than that achieved with PNP-GDEPT and Taxotere combination (Table

3.11). Overall, the combined use of these regimens leads to strong synergism in both

OVCAR-3 (CI 0.21 at ED75; R value 0.97) and SKOV-3 cells (CI 0.19 at ED75; R value

0.96) (Table 3.9). Further, the corresponding DRI values indicated that in combination, lower doses of PNP-GDEPT and carboplatin could achieve the same effect; a dose reduction of ~12 fold for PNP-GDEPT and ~5 fold for carboplatin was needed to achieve

50% cell killing in SKOV-3 cells (Table/Figure 3.12 Panel I and III). Similarly, a dose reduction by ~6 fold for PNP-GDEPT and ~9 fold for carboplatin was predicted to be adequate when given together to achieve 50% cell killing in OVCAR-3 cells

(Table/Figure 3.12 Panel II and IV). The data also indicated that OVCAR-3 cells were more sensitive to carboplatin when combined with PNP-GDEPT in comparison to

SKOV-3 cells. Similarly sensitivity of SKOV-3 cells to PNP-GDEPT in presence of carboplatin was more enhanced in comparison to OVCAR-3 cells.

Chapter 3: Combination Therapy for Ovarian Cancer 200

90 100 80 90 80 70 70 60 60 50 50 40 40 30 30 20 20 10 % of cell growth inhibition growth cell of % 10 growth inhibition % of cell 0

0 6 40 0 4 150 2 2 10 75 .0 1 T C 5 0. EP 37 ar D 20 bo 2.5 5 G pla co P- 0 18 T ti 0 nt N 1 EP n r P 9 ol C 5 -GD ar P bo C PN Ad/CMV/PNP (moi) + 1g/mL Fludara pla 0 ontrol Carboplatin tin (μM) control 0.5 1 2 4 6 Carboplatin Ad/CMV/PNP (moi) + 1g/mL Fludara 0 0 1428364661 (μM) Control 9 18 37 75 150 2.5 8 2841465671 0 0 10121723475.0 20 33 49 56 60 74 5 5 101319406410 28 47 53 58 70 79 10 9 141931527520 38 54 67 72 79 98 20 23 25 37 57 75 88 40 55 67 76 97 99 99 Figure 3.11 Evaluation of cell growth inhibitory effects of combination of carboplatin and PNP-GDEPT: Cells treated with different doses of carboplatin and/or PNP-GDEPT were analysed for cell viability using WST-1 assay on day 5. Three-dimensional graphs representing % inhibition of cell growth with increasing doses of carboplatin and PNP-GDEPT for SKOV-3 (graph A) and OVCAR-3 (graph B) cells are shown. Almost all drug combination

led to a greater cell growth inhibition compared with either alone. Values represent mean (±SEM) of three independent experiments. A statistical 200 significance (p< 0.5) was obtained when combined effects were compared with either alone (as a group and not individual doses).

Chapter 3: Combination Therapy for Ovarian Cancer 201

1.50 1.50 I II 1.25 1.25 Antagoni sm Antagoni sm

1.00 Addi ti vi ty 1.00 Additivity

Synergism Synergism 0.75 0.75

0.50 0.50

Combination Index (CI) Index Combination 0.25 (CI) Index Combination 0.25

0.00 0.00 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Fraction Affected (Fa) Fraction Affected (Fa)

III SKOV-3 IV OVCAR-3 Fraction Drug Alone Dose Reduction Index Fraction Drug Alone Dose Reduction Index affected (xIC50) (xIC50) affected (xIC50) (xIC50) (Fa) GDEPT Carboplatin GDEPT Carboplatin (Fa) GDEPT Carboplatin GDEPT Carboplatin 0.10 0.44 0.14 5.21 2.84 0.10 0.17 0.28 2.79 3.99 0.25 1.91 0.43 8.02 3.65 0.25 0.60 0.85 3.97 6.02 0.50 8.22 1.34 12.36 4.70 0.50 2.03 2.16 5.66 9.08 0.75 35.46 4.18 19.03 6.05 0.75 6.93 8.99 8.08 13.70 0.90 152.91 12.98 29.30 7.78 0.90 23.64 31.34 11.51 20.68

Figure 3.12 Analysis of combined drug effects of carboplatin and PNP-GDEPT: CI/Fa plots were generated for different combinations of carboplatin and PNP-GDEPT against the fraction affected (Fa). Synergistic effects are indicated for both SKOV-3 (Panel I) and for OVCAR-3 (Panel II) cells as most CI values are significantly lower than 1(CI<1) at all drug combinations. Dose reduction index values to achieve different levels of cell killings by combination treatments are tabulated in panel III (SKOV-3) and IV (OVCAR-3) for the two cell lines. Significant levels of individual dose reductions were indicated when these drugs were combined to achieve a specific effect Vs. doses when used alone.

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Chapter 3: Combination Therapy for Ovarian Cancer 202

Table 3.9 Combined effects of carboplatin and PNP-GDEPT in OC cells (drugs added as constant ratio of 1:1)

Cell Line Combination index (CI value) R Effect

ED2 50 ED75 ED90 SKOV-3 0.293 0.217 0.162 0.97 Strong Synergy ++++ OVCAR-3 0.286 0.196 0.135 0.96 Strong Synergy ++++

See footnote of Table 3.7 for more details

3.2.6.2.4 Combined effects of PNP-GDEPT, carboplatin and Taxotere

After demonstration of synergies between PNPGDEPT and Taxotere or carboplatin, the synergies between the three were evaluated in the two cell lines. As before, dose dependent inhibition seen with either modality was significantly amplified when the three were combined (Figure 3.13). Overall, OVCAR-3 cells displayed greater sensitivity to the combination treatment, the cytotoxicity observed in OVCAR-3 cells at higher doses of carboplatin and Taxotere (20 μM of carboplatin + 1nM of Taxotere and 40μM of carboplatin + 2nM) was absolute and led to 100% cell killing. Analysis of the CI-Fa plot generated for both cell lines showed very strong synergies between PNP-GDEPT, carboplatin and Taxotere (Figure 3.14). Specifically, the combined use of these regimens led to very strong synergism in OVCAR-3 (CI 0.09 at ED75; R value 0.94) and strong synergism in SKOV-3 cells (CI 0.27 at ED75; R value 0.96) (Table 3.10). In accord with this the DRI values showed that if PNP-GDEPT, carboplatin and Taxotere are used in

Chapter 3: Combination Therapy for Ovarian Cancer 203 combination, a significantly lower doses of each would be needed in combination to achieve the same effect; a dose reduction of ~14 fold for PNP-GDEPT, ~5 fold for carboplatin and ~9 fold for Taxotere was predicted to achieve 50% cell killing in SKOV-

3 cells (Table/Figure 3.14 Panel I and III). Relatively stronger synergies were observed in OVCAR-3 cells, with a dose reduction by ~20 fold for PNP-GDEPT, ~32 fold for carboplatin and ~27 fold for Taxotere being indicated to yield 50% cell killing, in combination (Table/Figure 3.14 Panel III and IV). All data indicated that the trimodal synergies obtained for OVCAR-3 cells were stronger compared to that obtained with bimodal combinations of PNP-GDEPT with Taxotere or with carboplatin (Table 3.11). In comparison, while levels of trimodal synergies (CI, DRI values) obtained in SKOV-3 cells were enhanced compared to bimodal combination of PNP-GDEPT plus Taxotere but were similar to those obtained with PNP-GDEPT plus carboplatin combination

(Table 3.11).

Chapter 3: Combination Therapy for Ovarian Cancer 204

A: SKOV-3 90 B: OVCAR-3 100 80 90

70 80 70 60 60 50 50 rowth inhibition

40 g 40

30 30 20 20 % of cell growth inhibition growth cell % of % of cell% of 10 10 0 0 0 6 2.00 0 4 1 0+ 00 5 4 1. 0 2 0 0+ 50 75 2 0. 0 1 0+ 25 37 1 0. 0.5 0 Car 5 EPT 50 5.0+ .12 contr GD 0. 1 T + 0 0 P- 0+ 0 8 EP Ta .5+ PN 2 .25 D x 2 o +0 9 -G l 10 25 NP Car (M) + Ad/CMV/PNP (moi) + 1g/mL Fludara 0.1 P C 5+ 0 Co ar nt Tax (nM) +Ta rol x control0.51246 Car (M) + Ad/CMV/PNP (moi) + 1g/mL Fludara 0 0 1428364661 Tax (nM) Control 9 18 37 75 150 2.5+0.125 13 48 55 61 72 73 0 0 10121723475.0+0.250 36 55 67 72 81 92 5+0.125 16 32 33 42 53 70 10+0.500 47 61 66 91 91 93 10+0.250 26 41 45 57 68 75 20+1.000 67 97 99 99 99 99 20+0.500 42 47 53 61 72 89 40+2.000 88 100 100 100 100 100

Figure 3.13 Evaluation of cell growth inhibition by combination of Taxotere, carboplatin and PNP-GDEPT: Cells treated with different doses of Taxotere + carboplatin and/or PNP-GDEPT were analysed for cell viability using WST-1 assay on day 5. Three-dimensional graphs representing inhibition of cell growth were plotted as a function of increasing doses of Taxotere + carboplatin and PNP-GDEPT for SKOV-3 (graph A) and OVCAR-3 (graph B) cells. All combinations led to a greater cell growth inhibition compared with either modality alone. Values represent mean (±SEM) of three independent experiments. A statistical significance (p< 0.5) was obtained when combined effects were compared with either alone (as a group and not individual doses).

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Chapter 3: Combination Therapy for Ovarian Cancer 205

I 1.50 II 1.50

1.25 1.25 Antagoni sm Antagoni sm

1.00 Addi ti vi ty 1.00 Additivity

Synergism Synergism 0.75 0.75

0.50 0.50 Combination Index (CI) Combination Index (CI)Combination 0.25 0.25

0.00 0.00 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Fraction Affected (Fa) Fraction Affected (Fa)

III SKOV-3 IV OVCAR-3 Fraction Drug Alone Dose Reduction Index Fraction Drug Alone Dose Reduction Index (xIC50) affected (xIC50) (xIC50) affected (xIC50) (Fa) GDEPT Tax Car GDEPT Tax Car (Fa) GDEPT Tax Car GDEPT Tax Car 0.10 0.44 0.31 0.14 5.76 4.04 3.14 0.10 0.17 0.22 0.28 12.58 16.12 18.00 0.25 1.91 1.25 0.43 8.97 5.86 4.08 0.25 0.60 0.79 0.85 15.82 20.87 23.96 0.50 8.22 5.01 1.34 13.96 8.51 5.31 0.50 2.03 2.76 2.16 19.89 27.02 31.87 0.75 35.46 20.16 4.18 21.73 12.36 6.91 0.75 6.93 9.70 8.99 25.00 34.98 42.41 0.90 152.91 81.09 12.98 33.83 17.94 8.99 0.90 23.64 34.07 31.34 31.43 45.29 56.43

Figure 3.14 Analysis of combined drug effects of Taxotere, carboplatin and PNP-GDEPT: CI/Fa plots were generated for different combinations of Taxotere + carboplatin and PNP-GDEPT against the fraction affected (Fa). Significant synergistic effects are indicated for both SKOV-3 (Panel I) and OVCAR-3 (Panel II) cells as all the CI values are significantly lesser than 1(CI<1) at all drug combinations. Dose reduction index values for individual modality to achieve different levels of cell killings when combined are tabulated in panel III (SKOV-3) and IV (OVCAR-3) for the two cell lines. Significant levels of individual dose reductions were indicated when these drugs were combined to achieve a specific effect Vs. doses when used alone.

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Chapter 3: Combination Therapy for Ovarian Cancer 206

Table 3.10 Combined effects of Taxotere + carboplatin and PNP-GDEPT in OC cells (drugs added as constant ratio of 1:1)

See footnote of Table 3.7 for more details

Cell Line Combination index (CI value) R Effect

ED2 50 ED75 ED90 SKOV-3 0.37744 0.27171 0.19660 0.9634 Strong Synergy ++++ OVCAR-3 0.11867 0.09217 0.07163 0.9407 Very Strong Synergy +++++

Chapter 3: Combination Therapy for Ovarian Cancer 207

Table 3.11 A comparative account of four different drug combination effects in OC cells (ratio: 1:1)

Modalities Cell Line Combination index (CI value) R Effect

ED2 50 ED75 ED90 Taxotere + carboplatin SKOV-3 0.96494 0.86077 0.76999 0.9852 Additivity + OVCAR-3 0.89505 0.76455 0.65320 0.9912 Moderate Synergy ++ GDEPT+ Taxotere SKOV-3 0.43155 0.32492 0.24491 0.98145 Synergistic +++ OVCAR-3 0.21792 0.13725 0.08647 0.93145 Strong Synergy ++++ GDEPT+ carboplatin SKOV-3 0.29370 0.21792 0.16264 0.97079 Strong Synergy ++++ OVCAR-3 0.28668 0.19681 0.13522 0.96079 Strong Synergy ++++ GDEPT + Taxotere + carboplatin SKOV-3 0.37744 0.27171 0.19660 0.9634 Strong Synergy ++++ OVCAR-3 0.11867 0.09217 0.07163 0.9407 Very Strong Synergy +++++

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Chapter 3: Combination Therapy for Ovarian Cancer 208

3.3 Discussion

Heterogeneity of OC cannot be adequately treated using single agent based therapies, hence, the primary aim of this study was to assess the potential of combining a novel

PNP-GDEPT based molecular therapy with chemotherapy conventionally used for treatment of OC (Taxotere & carboplatin). The results from this study unequivocally show the synergistic anti-tumour interactions between the three therapies against OC cell lines, representing subtypes of the most common epithelial adenocarcinomas. Over

80% of OC patients have epithelial OC of which >90% are adenocarcinomas. Further since these represent different subtypes, origin, growth properties and drug resistance

(described in Table 3.12), an initial screening evaluation using these lines would generate data that may have broad relevance with respect to the clinical disease.

Overall, cell killing efficacy of combination of PNP-GDEPT, carboplatin and Taxotere were significantly higher compared with either alone. Using Chou and Talalay’s analyses, these synergies were proven at a quantitative level and were shown to be significantly strong, especially for the trimodal combination. Dose reduction index

(DRI) values associated with the combined use of these modalities yielded clinical relevance to this data, clearly showing the potential for substantial dose reduction of individual treatments when used in combination. It may be noted that DRI is important in clinical situations, where dose-reduction leads to reduced toxicity toward the host while retaining the therapeutic efficacy.

Chapter 3: Combination Therapy for Ovarian Cancer 209

Table 3.12 Properties of OC cell lines used in this study

Cell Line Features* Ref.

SKOV-3 Cystadenocarcinoma; cells are resistant to tumor necrosis (756,757) factor and to several cytotoxic drugs including diphtheria toxin, cis-platinum and Adriamycin; high expression of Her- 2/neu receptor; often used as a positive control in Her-2/neu target based strategies; p53 null OVCAR-3 Cystadenocarcinoma; derived from malignant ascites of a (758) patient with progressive adenocarcinoma resistant to cisplatin therapy; resistant to clinically relevant concentrations of adriamycin, melphalan and cisplatin; both cultured cells and xenografts exhibit androgen and oestrogen receptors; often used in studies looking at mechanisms of platinum drug resistance and presence of hormone receptor is useful to evaluate hormonal therapy; highly permissive to Ad infections; mutations in p53 (mut R 248 Q) A-2780 Serous cystadenocarcinoma; derived from a patient never (759) treated with chemotherapy; very fast growing; wild type p53 Caov-3 Cystadenocarcinoma; cisplatin resistant, minimal expression (756) of integrins and CAR receptor; non-permissive to Ad infection; mutations in p53(mut Q 136 term)

* Source American Type Culture Collection, U.S.A (www.atcc.org)

Chapter 3: Combination Therapy for Ovarian Cancer 210

In vitro assessment does not mimic the in vivo scenario e.g. effects of drug metabolism, half-life, distribution and interactions with host macro/microenvironment are not addressed by in vitro analyses. However, a well-designed, exhaustive, in vitro assessment (experimental design, methodology and analyses) may provide the first reliable screen for designation of future directions. Indeed, in vitro findings are often reflected in the clinical studies (158).

The use of Chou and Talalay’s method, which is extensively used and has been continually proven for quantitative estimation of drug interactions gives credence to our in vitro data. The prime advantage of this method is that it overcomes the assumption that drug interactions are linear across different dosages and their resultant inhibitory effects (788). For simplicity, mutually exclusive assumptions, for all drugs, are generally assumed in data analysis. Hence, in this analysis, mutual exclusivity of the component drugs was assumed; this is especially recommended when more than two drugs are involved in combination (768,770,788). Further the individual doses in combinations were chosen on the basis of their potency (i.e. concentrations to achieve a particular effect e.g. at the ratio of their IC50’s), which yielded efficiency and importantly accuracy to our data analyses. As we know that there is no general equation that fits all of the dose–response curves, there is a clear need to evaluate results over a range of effects (50%–90 % inhibition) (789). Keeping this in mind, the drug interactions were evaluated at three different levels e.g. ED50, 75 and 90 and the data were fitted in accordance to median effects equation (mean r value 0.95), rendering calculation of the CIs and DRIs valid (788).

Chapter 3: Combination Therapy for Ovarian Cancer 211

Synergy evaluations in complex biological systems such as cells grown in culture can be affected by 1. accuracy of measurement and biological variability 2. desired dose levels or effect levels 3. experimental conditions, e.g. temperature, oxygen tension, pH, etc. may affect the data and conclusions and finally 4. whether synergy is treatment schedule dependent or combination ratio dependent.

The WST-1 based cell viability assay was primarily used to assess the response to different regimens, as it allowed an exhaustive and reliable assessment of different drug combinations at different doses with relatively easy logistics (790). The issue of variability between data acquired in different experiments was minimised through ensuring the same passage number of cells and other conditions such as reagents/incubators. In addition, the reliability of data was enhanced through including the controls every time and re-calculation of Dm values (the median-effect dose; dose causing 50% growth inhibition) for individual drugs in each experiment. These Dm values were subsequently used for further analyses. Although, synergies were undeniably proven using combinations in multiple ratios, an assessment of sequential administration of different treatments was not done.

Further exploration of treatments given in tandem may lead to better synergies; it has been indicated that a tumour containing both wild-type p53 cells as well as p53 mutants could be treated with platinum followed by a taxane. In such a tumour, platinum would first eradicate the wild-type p53 cells after which the taxane would kill the mutants

(791). Thus the optimum dose of each drug can eliminate specific cells without the potential toxicity that chemotherapy entails. Indeed, the feasibility of sequential

Chapter 3: Combination Therapy for Ovarian Cancer 212 carboplatin followed by docetaxel as a first line therapy in OC patients has been investigated in a SCOTROC Phase 2B trial (792). The overall response rate of 50% was consistant with 58.7% achieved with carboplatin–docetaxel in the SCOTROC 2A trial and the median progression-free survival figures of 17.1 months were also comparable to those found in earlier studies (160,793).

The relevance of the data is enhanced if the tested dose range covers the physiologically acceptable range (as in the clinic). Typically, docetaxel is used at 75mg/m2 in phase III trial based on representative surface area to weight ratio (47), which is equivalent to

~1.9 g/mL or 2.33 X 103 nM. Such high concentrations could not be used in in vitro assays, the maximum Taxotere concentration (range 0.1-316 nM) was approximately 9 fold less compared to the levels of drug given in patients since concentrations higher than 100 nM led to complete cell killing. However, this did not interfere with the ultimate accuracy of these assessments, as the aim of the study was to evaluate the therapeutic interactions between different regimens.

The efficiency of Taxotere against all OC cell lines correlated with preclinical and clinical reports (69,144,145,158). This efficacy was observed irrespective of their origin and growth properties but a variation in sensitivity conformed to the variable drug resistant phenotype of OC cell lines and suggested the reliability of these data. For example, the A-2780 cell line derived from a patient never treated with chemotherapy, was the most sensitive compared with those derived from chemotherapy treated patients

(OVCAR-3 and SKOV-3).

Chapter 3: Combination Therapy for Ovarian Cancer 213

As explained earlier, carboplatin and cisplatin are two major platinum compounds that are used to treat ovarian cancer patients. At a clinical level, efforts have been done to treat cisplatin resistant patient with carboplatin but with a very limited success.

However, the relevance between carboplatin and cisplatin resistance could not be established due to lack of research in this area. Given that carboplatin is effective against cisplatin resistant OC (794-796), for carboplatin assessment studies, cisplatin resistant OVCAR-3 and SKOV-3 lines were tested using a range commonly used in other studies (IC50 range ~5 μM-35 M (158). The fact that the two cell lines did not show a significant difference in carboplatin sensitivity was correlated with the similarity in their multidrug resistant phenotype displaying resistance to platinum drugs (see Table

3.12). Compared to previous reports, the IC50 values obtained in this study were slightly higher and ranged between 38-43 M (158). This could be attributed to differences in experimental design, initial plating density, incubation time (e.g. 24 h in

(24) Vs 5 days in this study), % active drug in a specific formulation (batch differences) and changes in phenotype of the same cell line in different laboratories. However, while a direct comparison is not possible, high IC50 values obtained in this study correlated with those observed for these two lines compared to other less drug resistant OC lines in other studies.

Use of PNP-GDEPT to treat ovarian cancer is still in its preliminary stages; a Phase I trial has been initiated to treat OC patients (personal communication) in USA and one preclinical study has been published reporting the efficacy of PNP-GDEPT against ovarian cancer in vivo (308). The success of this approach will depend upon its ability to elicit a stronger ‘bystander effect’ in situ. This is an important parameter, especially

Chapter 3: Combination Therapy for Ovarian Cancer 214 since most OC gene therapy approaches have shown limited anti-tumour efficacy owing to a poor gene transduction rate in OC cells (797,798).

Given that Ad vectors are those most explored for cancer therapeutics, Ad-mediated

PNP-GDEPT (using Fludarabine phosphate) was used. Its variably efficacy against different cell lines could be due to variable expression of Ad receptors, CAR (for Ad binding) or integrin (v3 or v5, for Ad intrenalisation) (Chapter 1) on different cell types. Variations in levels of CAR and integrins in different OC cancer cell lines have been reported (799-801). While CAR/integrin status was not determined for OC cell lines in this study, their differential Ad-permissivity was established using

Ad/CMV/GFP transduction studies (see Section 3.2.4), correlating with reported

CAR/Integrin status for these cell lines. Further, it has been shown that the bystander effects of PNP-GDEPT are directly proportional to PNP-transduction efficiency (785).

In line with this, PNP-GDEPT efficacy was the most in OVCAR-3 and the least in

Caov-3 cells further correlating with data showing bystander effects of PNP-GDEPT in all cell lines except Caov-3. Further, relatively higher levels of synergy generally that were noted in OVCAR-3 cells (Vs. SKOV-3 cells) could also be correlated to greater

Ad-PNP-GDEPT efficacy due to greater Ad permissivity of these cells.

Our in vitro data also correlated with efficacy of PNP-GDEPT against SKOV-3 cells by

Gadi et al who also demonstrated its anti-tumour effects in vivo, but using the prodrug,

MeP-dR, which is yet to be FDA approved (308). Hence, if proven effective, use of

FDA approved Fludara, as prodrug will yield greater clinical relevance to this study.

Chapter 3: Combination Therapy for Ovarian Cancer 215

To the best of our knowledge this is the first demonstration of synergy between:

1. PNP-GDEPT and Taxotere

2. PNP-GDEPT and carboplatin

3. PNP-GDEPT, Taxotere and carboplatin

These data have great clinical implications; testing of potential synergies in either bi- or tri-modal regimens is likely to have great significance for quick translation to the clinical scenario. A synergy between modalities means greater efficacy than the two added together. In the clinical context this will translate to potential use of lower individual doses with lower toxicity. Further, any new therapy regimen is generally tested in late stage patients, who have received prior therapy. In the context of OC, generally the patients would have undergone cisplatin/carboplatin and docetaxel as first/second line therapy. Synergy between PNP-GDEPT, Taxotere and carboplatin against cisplatin resistant SKOV-3 and OVCAR-3 cell lines has the potential for easy extrapolation to patients with drug refractory OC.

An estimation of an important and clinically more relevant DRI was possible and suggested that significant lowering of individual doses is a real possibility especially, when PNP-GDEPT is given to patients who have had prior- or are undergoing chemotherapy with Taxotere/carboplatin treatment. Taxotere dose reduction ranging from ~4-48 fold and importantly a dose reduction ranging from 3-56 folds was obtained for carboplatin in the trimodal combination. Given the toxicities associated with high dosing of these drugs alone and in combination (43,70,72,188), these are worthwhile

Chapter 3: Combination Therapy for Ovarian Cancer 216 observations for development of the trimodal combination regimen for clinical application. While an accurate estimation of potential efficacy and combined toxicities is only possible in vivo, these data are promising and reliable and definitely warrant further confirmation in vivo.

Synergies between Ad-mediated PNP-GDEPT and Taxotere could also be explained by mutual enhancement engendered by both when used together, ie. Ad transduction enhances docetaxel effects and docetaxel enhances Ad transduction (802,803).

However, interactions between PNP/Fludara and Taxotere remain to be elucidated.

Similarly, carboplatin and Ad-PNP-GDEPT displayed synergy; however, the exact nature of this interaction is not clear, as there are no prior studies reporting such synergies. Further, while mutually beneficial interactions between Ad and Taxotere may play an important role in the enhancement observed in trimodal synergies, the exact nature of the interaction is yet to be elucidated. Overall, it appears as though the levels of synergies vary between cell types and that trimodal therapy may not be as beneficial for some cell types as expected (e.g. in SKOV-3 cells, bimodal, carboplatin + PNP-

GDEPT was as effective as trimodal treatment). Once proven preclinically, our data will form the basis for using PNP-GDEPT together with chemotherapy in OC patients. A better understanding of these interactions will help in the design of new regimens in cohorts who have undergone pre-existing treatment.

Chapter 4: Apoptotic Effects of Combination Therapy 217

PNP-GDEPT, TAXOTERE AND CARBOPLATIN IN COMBINATION AGAINST OVARIAN CANCER: ROLE OF APOPTOSIS

Chapter 4: Apoptotic Effects of Combination Therapy 218

4.1 Introduction

Different cancer treatments including chemotherapeutic drugs may differ in their primary mode of action but ultimately activation of apoptosis is the convergence point.

The sensitivity of cancer cells to various forms of anti-cancer therapies is contributed by several quantitative and qualitative changes in genes/proteins that encode apoptosis. The balance between pro-apoptotic and apoptotic signals is critical for determining cell survival (Figure 4.1). In this regard, the potential roles of various members of BCL-2,

Caspase and inhibitor of apoptosis (e.g. survivin) families are crucial in determining the efficacy of different regimens (804-806).

Impressive synergies between Taxotere, carboplatin (CP) and Ad-mediated PNP-

GDEPT against OC cells were clearly demonstrated for the first time in the previous in vitro experiments (Chapter 3). The data clearly indicate the promise of developing these regimens for future clinical application. This would be greatly facilitated by an improved understanding of the molecular events leading to synergistic apoptosis engendered by the three modalities. While synergies between Adenoviruses and

Taxotere or Taxotere and carboplatin have been reported and their mechanisms explored, there are no reports of synergies between PNP-GDEPT and Taxotere and/or carboplatin. Further, while individual modes of action for Taxotere and carboplatin are quite well understood, the molecular nature of the PNP-GDEPT mode of action is unclear.

Chapter 4: Apoptotic Effects of Combination Therapy 219

A schematic showing the pathways involved in Apoptosis The mitochondrial and death receptor pathways are two important pathways that regulate apoptosis. The mitochondrial pathway is controlled by members of the BCL-2 family that can inhibit or promote apoptosis. Upon activation, the BH3-only proteins (e.g. BID) associate with the pro-apoptotic members, BAX or BAK, and translocate to the outer mitochondrial membrane. After the pore formation in the membranes, the DNases, apoptosis inducing factor (AIF) and endonuclease G, translocate to the nucleus to induce DNA damage/fragmentation. In addition to this, release of cytochrome c results in the formation a multiprotein complex called the apoptosome. Proteolytic Pro-casp-3 & 7 cleavage of caspase-9 in the apoptosome results in activation of effector caspases (e.g. caspase-3 & 7). Dimerization of antiapoptotic BCL-2 and BCL- xL to proapoptotic BAX or BAK leads to inhibition of apoptosis. IAP proteins Casp-3 & 7 act during the execution phase of apoptosis through inhibition of caspases. The death-receptor pathway: Triggering members of the death-receptor PARP family may result in both apoptotic and survival signals. The pathway gets activated upon the interaction of a death receptor with its death-inducing ligand that results in the recruitment of Fas-associated death domain protein (FADD) and pro-caspase-8. The proteolytic activation of pro-caspase-8 results in the activation of a cell-signalling cascade connecting this pathway with its mitochondrial counterpart (caspase 3 & 7). Caspase-3 further cleaves PARP, which primarily inactivates the enzyme by destroying its ability to respond to DNA strand breaks during apoptotic cell death.

Figure 4.1: Apoptotic pathways in cancer: a general view (Adapted from Bremer et al, TRENDS in Molecular Medicine (2006) 219

Chapter 4: Apoptotic Effects of Combination Therapy 220

Docetaxel acts as a spindle poison that inhibits microtubule dynamics, ultimately arresting neoplastic cell proliferation (64) (Figure 1.3) with apoptosis mediated cell death now recognised as the key feature of its activity. This involves activation or inactivation of apoptotic or anti-apoptotic pathways, mainly involving members of

Caspase or BCL-2 family proteins (141,142,423,450). Further, an increase in taxane- sensitivity of OC cells with abrogated or mutant p53 status has established that docetaxel acts in a p53 independent manner (77,146-148). Distinct from its role as a potential microtubule inhibitor or apoptosis inducer, docetaxel also leads to a favourable immune response by stimulating various anticancer and pro-inflammatory genes and proteins such as granulocyte /macrophage–colony stimulating factor (GM-CSF), tumour necrosis factor alpha (TNF-), interferon gamma (IFN), lymphokine activated killer)(LAK) cells (reviewed in (71,149).

Carboplatin leads to cell killing through binding with cellular DNA to form cross-links and intra-strand adducts resulting in loss of DNA function (Figure 1.5) (168,807). As with docetaxel, CP has the potential to trigger a number of pro- and anti-apoptotic responses to harness apoptosis, generally leading to modulation of BCL-2 or p53 related gene-expression and activation of different caspases (175-177). This is also proven clinically, - caspase-3 dependent apoptosis was evident in 5/7 patients with chemo- sensitive OC treated with a combination of CP and paclitaxel (175). Unlike docetaxel,

CP activity is dependent upon p53 as shown in the dependence of CP efficacy on p53 status of cervical and breast cancer cells (172,173).

Chapter 4: Apoptotic Effects of Combination Therapy 221

The cell toxicity of PNP-GDEPT is shown to be due to inhibition of DNA and RNA synthesis mediated by the toxic metabolites (Figure 1.8). However, relatively little information is available with regards to molecular events involved. Keeping this in mind, in this study, the aim was to identify various genes/proteins, which may be differentially expressed in PNP-GDEPT treated OC cells.

It is expected that a mechanistic understanding of effects of combination regimens on apoptosis regulation will help in strategic design to establish a tangible treatment option in the clinical scenario. Hence, this study investigates if modulation of proapoptotic or anti-apoptotic factors is involved in mutual enhancement of toxic effects engendered by

PNP-GDEPT, Taxotere or carboplatin. Further, the primary problem with the se of chemotherapeutic regimens is “disease recurrence” due to development of a chemoresistant phenotype. Hence, to enhance the clinical relevance of these analyses, multidrug resistant OVCAR-3 or SKOV-3 cells were used (discussed in Chapter 3).

The specific objectives of this study were:

1. To evaluate the extent of apoptosis engendered by different treatments

2. To evaluate treatment related effects on normal cell cycling in treated cells

3. To profile protein expression in PNP-GDEPT treated cells (Proteomic analyses),

Chapter 4: Apoptotic Effects of Combination Therapy 222

4.2 Results

The extent of involvement of apoptosis in cytotoxic effects due to different treatments on OC cells was evaluated using the M30 CytoDEATH assay.

Treatment related effects on cell cycle progression were measured by PI staining.

Shotgun proteomics was performed in order to identify various proteins, which may be differentially expressed in PNP-GDEPT treated OC cells. The modulation in the expression of various pro- and anti-apoptotic genes/proteins in response to combination therapy was evaluated using western blot analysis.

Chapter 4: Apoptotic Effects of Combination Therapy 223

4.2.1 Evaluation of early apoptosis in OC cells after different treatments

M30 cytoDEATH antibody was used to identify and quantitatively estimate cells undergoing early apoptosis. The M30 antibody specifically detects the cytokeratin 18-

Asp 396-caspase-cleavage site (neo-epitope (M30)), which allows the detection of early apoptotic cells. Use of M30 CytoDEATH™ monoclonal antibody which does not cross react with viable or necrotic cells ensures that only apoptotic and not necrotic cells are detected (808-811). SKOV-3 cells were treated with Taxotere (1.5 nM), carboplatin (20

M) and PNP-GDEPT (Ad/CMV/PNP moi of 150 pfu/cell plus 1g/mL Fludara) either alone or in combination. Fludara (alone) treated cells were used as a control. Doses that yielded the best synergy in combination were selected on the basis of data from previous experiments. Cells harvested after 2 or 3 days of treatment were immunostained with M30 CytoDEATH antibody and flow-cytometry (FACS) was used to assess the percentage of apoptotic cells. An increase in apoptosis was achieved with all three modalities and this was further enhanced when therapies were combined

(Figure 4.2). The levels of apoptosis increased in a time dependent manner with increasing number of apoptotic cells in combination treated cells (Table 4. 1). The % of

M30 positive cells after 3 days of treatment was maximal in tri-combination treated cells (49 ± 7) followed by bi-modal (Taxotere plus carboplatin (17 ± 5), Taxotere plus

GDEPT (23 ± 6), carboplatin plus GDEPT (31 ± 5), and then single modality treatments

(PNP-GDEPT (11 ± 4), Taxotere (14 ± 4), carboplatin (16 ± 6), (Table 4. 1). Apoptosis achieved in Fludara only treated control cells was low (1.5 ± 1), whilst cells treated with, the combination therapy involving PNP-GDEPT displayed a relatively higher proportion of apoptotic cell death irrespective of the time used to treat these cells.

Chapter 4: Apoptotic Effects of Combination Therapy 224

Fludara Alone GDEPT TAX CAR TAX+ CAR 60 TAX+ GDEPT CAR+GDEPT TAX+CAR+GDEPT ***

** 40 ** P = 0.0052 * P = 0.0003

* *

* 20 % of M30 Positive Cells M30 of %

0 Day 2 Day 3

Figure 4.2 Quantitative estimation of Apoptosis in OC cells given different treatments (M30 CytoDEATH assay): SKOV- 3 cells were treated with Taxotere (1.5 nM), carboplatin (20 M) and PNP-GDEPT (Ad/CMV/PNP moi of 150 pfu/cell plus 1g/mL Fludara) either alone or in combination. Cells harvested 2 and 3 days post treatment were immunostained with M30 cytoDEATH antibody (detects early apoptosis) followed by flow cytometry. Graph shows the percent of M30 positive cells on different days post-treatment with different modalities (alone or in combination). A clear increase in treatment related apoptosis with time (2 days Vs. 3 days) was seen in combination treated cells. The combined use of therapies led to a significantly higher proportion of apoptosis when compared with either alone. Values were compared to Fludara control by one-way Anova using Dunnett’s multiple comparison test. P values: *<0.05, **<0.01 and ***<0.001 224

Chapter 4: Apoptotic Effects of Combination Therapy 225

Table 4.1 Quantitative estimation of apoptosis in SKOV-3 cells in response to different treatments

Time Fludara GDEPT Taxotere Carboplatin Taxotere + GDEPT + GDEPT + GDEPT + point Alone Alone Alone Alone carboplatin Taxotere carboplatin Taxotere + carboplatin

% of M30 antibody positive staining cells*

Day 2 1 ± 1 9 ± 3 11 ± 4 13 ± 5 15 ± 4 26 ± 9 23 ± 7 37 ± 6

Day 3 1.5 ± 1 11 ± 4 14 ± 5 16 ± 6 17 ± 5 23 ± 6 31 ± 5 49 ± 7

* Results shown are mean of % of apoptotic cells (M30 positive) associated with different treatments in three independent experiments (Mean ± SEM)

225

Chapter 4: Apoptotic Effects of Combination Therapy 226

4.2.2 Effects of different treatments on cell cycle in treated cells

Propidium iodide (PI) staining based analyses were performed to assess treatment related effects at different phases of cell cycle in treated OVCAR-3 cells. Cells were treated with Taxotere (0.6 nM), carboplatin (10 M) and PNP-GDEPT (Ad/CMV/PNP moi of 10 pfu/cell plus 1 g/mL Fludara) either alone or in combination. The combinational doses that yielded the best synergy were used. Cells infected with Ad

(alone) and treated with Fludara (alone) were used as a negative control. After 48 h, cells stained with PI (DNA stain) were analyzed by FACS to determine the fraction of cells in different phases of the cell cycle. The data showed that irrespective of the treatments applied, the cells showed a decline in % cells in G1 phase (20-35%) in comparison to control treated cells (Figure 4.3). As expected from previously reported cell cycle studies (142,812-816) carboplatin (G2/M: 33% ± 9) and Taxotere (G2/M:

43% ± 8) treatments led to an increase in cell fractions in the G2/M phase of the cell cycle. However, the combined use of different drug combinations led to an increase in the sub-G1 population (represents apoptosis) (Figure 4.3). The trends showed that the percentage of apoptotic cells (sub-G1phase) for different treatments was maximum in tri-combination treated cells (37% ± 6) followed by bi-modal (carboplatin plus Taxotere

(28% ± 6) < PNP-GDEPT plus Taxotere (32% ± 6) < PNP-GDEPT plus carboplatin

(34% ± 7) and then least in single agent treated cells (carboplatin (9% ± 3)< Taxotere

(12% ± 6)< PNP-GDEPT (20% ± 5) with negligible apoptosis in control treated cells.

Once again, as with M30 analyses, the % of apoptosis was greater when treatments included PNP-GDEPT as one of the modalities. Results were statistically siginificant when combination treatment was compared with single treatment alone or control treated cells (P = 0.002).

Chapter 4: Apoptotic Effects of Combination Therapy 227

Sub-G1: 0.6% Sub-G1: 2% ± 0.5 Sub-G1: 9 % ± 3 Sub-G1: 12% ± 6 Sub-G1: 28% ± 6 G1: 54% ± 9 G1: 32% ± 11 G1: 28% ± 7 G1: 20% ± 5 G1: 63% S: 24% ± 4 S: 26% ± 6 S: 17% ± 3 S: 15% ± 4 S: 12% G2/M: 20% ± 6 G2/M: 33% ± 9 G2/M: 43% ± 8 G2/M: 37% ± 9

Untreated Control Fludarabine Alone Carboplatin Taxotere Carboplatin+Taxotere

Different phases of cell cycle in normal cells

Sub-G1: 2% ± 1 Sub-G1: 20% ± 5 Sub-G1: 34% ± 7 Sub-G1: 32% ± 6 Sub-G1: 37% ± 6 G1: 56% ± 11 G1: 35% ± 8 G1: 35% ± 9 G1: 34% ± 8 G1: 31% ± 9 S: 23% ± 6 S: 19% ± 6 S: 9% ± 3 S: 9% ± 1 S: 15% ± 3 G2/M: 19% ± 5 G2/M: 26% ± 6 G2/M: 22% ± 5 G2/M: 25% ± 7 G2/M: 17% ± 6

Adenovirus Alone PNP-GDEPT PNP-GDEPT+Carboplatin PNP-GDEPT+Taxotere PNP-GDEPT+Carboplatin+Taxotere

Figure 4.3 Cell cycle analysis in ovarian cancer cells given different treatments: Cells treated with different modalities (either alone or in combination) were assessed for cell cycle progression and apoptosis. Cells were harvested 48 h post-treatment, RNA was digested and DNA was stained with Propidium iodide. The histograms represent the fractions of cells in different phases of the cell cycle after different treatments as determined by flow cytometry. The first histogram is representative of different phases of cell cycle in normal untreated cells. While data from one representative experiment are shown; numbers in each panel show the % distribution of cycling cells as mean ± SEM from three independent experiments. Carboplatin and Taxotere treatments resulted in an increase in cell fractions in G2M phase of cell cycle. The % of cells in sub-G1 (apoptosis) was increased in all treatment groups and to a greater extent after combination treatments. 227

Chapter 4: Apoptotic Effects of Combination Therapy 228

4.2.3 Proteomic studies using PNP-GDEPT treated OVCAR-3 cells

While the mode of action of PNP-GDEPT is basically understood, the molecular changes underlying this novel GDEPT are still unknown. Hence, shotgun proteomics were performed to identify differential expression of various proteins in PNP-GDEPT treated OVCAR-3 cells compared to untreated cells (Figure 4.4). Peptides and proteins in different samples were identified from extracted tandem mass spectra based on an extensive database searching (see Section 2.1.2.6 and 2.1.2.7). Scaffold (a program that compares two or more sets of data after mass spectrometry and database searches) was used to validate these MS based peptide and protein identifications. For these Scaffold analyses, peptide identifications were accepted if they could be established at greater than 95% probability as specified by the Peptide Prophet algorithm (754). Protein identifications were accepted if they could be established at greater than 90% probability and contained at least 2 identified peptides. Protein probabilities were assigned by the Protein Prophet algorithm (755). Proteins that contained similar peptides and could not be differentiated based on MS analysis alone were grouped to satisfy the principles of parsimony which is a novel way of handling the noise (false positives) in the protein interaction data (817).

Chapter 4: Apoptotic Effects of Combination Therapy 229

Shotgun proteomics was performed to evaluate 1. Untreated differentially expressed proteins 2. PNP GDEPT 1 in PNP-GDEPT treated 1 2 2 OVCAR-3 cells. Briefly, the following steps were taken:

1. SDS-PAGE was performed using cell lysates from PNP- GDEPT (moi of 10 pfu/cell plus 1 g/mL of Fludara) treated and untreated OVCAR-3 cells.

OVCAR-3 protein extracts / SDS PAGE Mass Spectrometry 2. Bands stained with Coomassie blue were excised 3 (10 bands/lane) and after proteolytic digestion, mass spectrometry was performed. 4 Computer based data analysis 3. Tandem mass spectra were extracted and peptides/ proteins identified.

4. Proteomics software, Scaffold (ver. 2.02.01) was used to validate MS/MS based peptide and protein identifications followed by statistical analysis. Protein identification / conformation Proteomics software

Figure 4.4 Shotgun proteomics to evaluate PNP-GDEPT inducted effects in treated OVCAR-3 cells

229 Note: Most figures have been adapted from internet for illustration purposes only. The gel image is from the actual experiment.

Chapter 4: Apoptotic Effects of Combination Therapy 230

For statistical analyses of the MS data, datasets (hit values based on scaffold analyses) representing PNP-GDEPT treated and un-treated samples were normalised by square root transformations; log2 transformation was carried out and the data plotted as treated vs. un-treated (Figure 4.5). Normalisation of data showed symmetrical distribution around the diagonal (Figure 4.5), which shows that that majority of proteins are similar in both samples; however, some clear distinctive data points were obvious distinguishing the two samples. These may represent proteins that may be either unique to each samples, or relatively differentially abundant in one of the two.

2 PNP-GDEPT treated (log)

0 012345 Untreated (log)

Figure 4.5 A normalised plot showing log2 transformations of PNP-GDEPT treated vs. un-treated data points

Chapter 4: Apoptotic Effects of Combination Therapy 231

To check the relevance of these data, statistical analysis was performed as described below. Briefly, ratios of log2-transformed data of both samples were obtained to assess up or downregulated proteins (whole ratio- based dataset was treated as a single population; zero values were changed to 0.0001 to avoid division by zero error). The following are the details of the analysis performed

Values entered:

X = log2 transformed ratios

Summary of results (values):

Number of proteins (N) = 745

-X = 173557.55299999984

-X2 = 2186160044.0213213

Mean = 232.9632

Variance = 2884042.3768

Std. dev. = 1698.2469

Std. error = 62.219

df = 744

tcrit(.05) = 1.99

tcrit(.01) = 2.63

Confidence intervals for estimated mean of population:

For 0.95 CI: 232.9632±123.8158

For 0.99 CI: 232.9632±163.636

At 95% confidence interval, values of 232.9632±123.8158 were considered significant.

Due to very little variance in the data from two data sets, there is not much difference at

Chapter 4: Apoptotic Effects of Combination Therapy 232 the 99% confidence interval except for the variation in standard error values (Figure

4.5). In the absence of replicates, the statistical significance of the data could not be predicted; however, the stringency of analyses and the very little variation between the two data sets suggested the accuracy and reliability of the data analyses. Ratio values of treated to untreated cells indicated that clear upregulation of 16 proteins (including purine nucleoside phosphorylase (PNP) in PNP-GDEPT treated cells Vs untreated cells

(ratios varied between 7925-26529), which are significantly higher than the those predicted for 99% confidence (232.9632 ± 163.636). The fact that abundant expression of Escherichia coli enzyme, purine nucleoside phosphorylase (PNP mol weight 28

KDa; protein accession no. gi|117626742), was detected only in PNP-GDEPT treated samples (hit value of 37 in treated Vs. none in untreated samples) suggested the reliability of these data and also provided evidence of production of enzyme PNP in

Ad/CMV/PNP infected samples.

Tables 4.2 and 4.3 display a list of differentially expresses proteins in PNP-GDEPT treated and untreated OVCAR-3 cells. Although, a number of proteins displayed modulated expression, only those, which were significantly modulated (only proteins which present in only one of the samples) (Hit values Table 4.2 and 4.3) and may have a potential role in cancer progression or apoptosis, are discussed in this study.

Overall, PNP-GDEPT treatment lead to general downregulation of cellular metabolism as proteins involved in lipid, amino acid, carbohydrate and glycolysis were downregulated (e.g. polymerase (RNA) II (DNA directed), dihydrolipoamide S- succinyltransferase (E2 component of 2-oxo-glutarate complex), ribosomal protein L4,

Chapter 4: Apoptotic Effects of Combination Therapy 233 mitochondrial trifunctional protein; see Table 4.2). Further some proteins involved in oncogenesis or cancer progression (e.g. cadherin, desmoplakin, plakoglobin, karyopherin, spondin, agrin, GTP binding protein and cadherin 6 ) or resistance to drugs

(e.g. antiquitin, epoxide hydrolase) exhibited downregulation (Table 4.2). Generally, proteins involved in apoptosis and tumour suppression (PARP and dead box polypeptide 3) and general DNA synthesis were upregulated (Table 4.3).

Chapter 4: Apoptotic Effects of Combination Therapy 234

Table 4.2 List of proteins that were significantly down regulated in PNP-GDEPT treated samples and their role in cancer

Name of the Protein Hit Value Ratio Properties Identified (Untreated / Transformed treated) log (untreated :treated)1 Keratin gene family; less defined role in cancer; connect with Keratin 5 13/0 19,306 desmosomes (desmoplakin) to form extensive cadherin-mediated cytoskeletal architectures (818) Keratin 77 12/0 18,502 Keratin gene family; less defined role in cancer

Cadherin 6 7/0 14,999 Cell adhesion molecule that maintains tissue integrity; Also known as K-cadherin; may lead to an aggressive phenotype during carcinogenesis; overexpression shown in OC patient specimens and established cell lines e.g. OVCAR-3; prognostic marker for OC and renal cell carcinoma (819-825) Desmoplakin 6/0 14,037 Cell adhesion protein associated with desmosomes (desmosomes are intercellular junctions that tightly link adjacent cells); a marker for epithelial cancers; progesterone receptor mediated up regulation in breast cancer (826-833) 234

Chapter 4: Apoptotic Effects of Combination Therapy 235

Plakoglobin 3/0 10,000 A component of desmosome; close association with cadherins; also called -catenin; an inducer of c-Myc and BCL-2 protein in human squamous carcinoma cells; nuclear accumulation of plakoglobin with concomitant increase in BCL-2 shown in CRPC (833-835) Spondin 1 3/0 10,000 Extracellular matrix protein (ECM), also known as SPON1; overexpressed in OC and in OVCAR-3 cells ; a potential diagnostic marker for OC; a predictive marker for palliative 5-FU-based chemotherapy in metastatic colorectal cancer (836-839) Dynactin 1 2/0 7,925 Inhibitor of p53 mediated apoptosis: Macromolecular complex consisting of 10-11 subunits ( from 22 to 150 kDa); binds to microtubules and cytoplasmic dynein; involved in a diverse array of cellular functions and cell cycle progression; being a ‘microtubule- associated protein’ serves as a potential target for cancer chemotherapy e.g. taxanes (840-843) Agrin 2/0 7,925 Angiogenesis and cell proliferation; A key component of Heparan sulfate proteoglycans (HSP) that hax implications in cancer cell growth, invasion, metastasis, and angiogenesis; associated with the formation of septal blood vessels in liver cirrhosis, and neoangiogenesis in the hepatocellular carcinoma (HCC); a triggering

factor for cell proliferation in osteosarcoma; associated with aggressive 235

Chapter 4: Apoptotic Effects of Combination Therapy 236

phenotype of glioblastoma multiforme, an aggressive form of brain cancer (844-849) Filaggrin 2/0 7,925 Intermediate filament-associated proteins (IFAP) that bind to keratins bundles in epithelial cells; based on their role on cell morphology and nuclear integrity may have a potential role in apoptosis (850-853) Karyopherin alpha1 2/0 7,925 Oncogene; Involvement in nucleo-cytoplasmic trafficking and found to be crucial for protein and RNA subcellular localization; a well defined role in nuclear envelope component assembly, mitosis and replication; overexpressed in cervical cancer and is critical for cancer cell survival and proliferation; karyopherin alpha2 expression predicts poor survival in patients with advanced breast cancer; a potential oncogenic role by the activation of PI3-kinase/AKT- pathway (854-857) Antiquitin (ALDH7A1) 2/0 7,925 Detoxification molecule; a key member of aldehyde dehydrogenase (ALDH) gene family; encodes enzyme that causes detoxification of various pharmaceutical compounds via NAD(P)(+)-dependent oxidation; overexpressed in various tumours and has a potential role in resistance to multiple chemotherapeutic drugs (858-860) Epoxide hydrolase 2/0 7,925 Detoxification: Also known as Epoxide hydratase; functions in detoxication during drug metabolism; expressed in several cancers and activity shown in cancer cell lines e.g. SKOV-3, ES-2, A-549, PC-3 236

Chapter 4: Apoptotic Effects of Combination Therapy 237

and DU-145; potential implication in anti-cancer drug resistance more specifically in hepatocellular carcinoma and prostate cancer (861-863) Insulysin 2/0 7,925 Insulin degrading enzyme (IDE); activity detected in breast and ovarian tumour tissues and cell lines e.g. OVCAR-3 cell line is positive for expression (864-867) BRI3 binding protein 3/0 10,000 Often named as endoplasmic reticulum (ER) resident protein; mediates (Cervical cancer 1 cell fate by interacting between ER and mitochondria (868,869) proto-oncogene-binding protein KG19) Ribosomal protein L4 5/0 12,924 Protein synthesis; belongs to the L4E family of ribosomal proteins that is a component of the 60S subunit; overexpressed in doxorubicin resistant colon cancver cell lines; overexpression shown in PC cell lines e.g. PC-3 and Du 145; serves as target for anti-cancer therapies that are directed against protein synthesis (870-872) Eukaryotic translation 3/0 10,000 Also known as EIF3S2 or (TGF-beta receptor-interacting protein 1) initiation factor 3 (TRIP-1), an initiation factor that regulates mRNA translation and cell subunit 2 (eIF-3 beta) growth; abnormal expression detected in various cancers; relatively less studied; potential implications in diagnosis, prognosis, and treatment of human cancers (873,874) 237

Chapter 4: Apoptotic Effects of Combination Therapy 238

Mitochondrial 3/0 10,000 Regulates mitochondrial beta oxidation pathways; not related to cancer trifunctional protein, as yet but but as a general fact mitochondrial defects have been related beta subunit to a variety of cancer (875,876) Polymerase (RNA) II 3/0 10,000 RNA synthesis: A multi-subunit complex which mediates (DNA directed) ribonucleotide synthesis; role in cancer is not reported, PNP-GDEPT polypeptide E inhibits RNA synthesis

Dihydrolipoamide S- 5/0 12,924 A defined role in carbohydrate metabolism (Tri-carboxylic acid cycle) succinyltransferase (E2 (877) component of 2-oxo- glutarate complex) v-ral simian leukemia 2/0 7,925 Oncogene; RalA and RalB are members of Ras family; RalA is viral oncogene homolog required for tumorigenesis and RalB is important for tumor survival; a B (ras related; GTP definitive role of Ral proteins has also been shown in cancer cell binding protein) (RalB) migration and metastatic tumor invasion (878-882)

1 Confidence intervals for estimated mean of population: For 0.95 CI: 232.9632±123.8158; For 0.99 CI: 232.9632±163.636

238

Chapter 4: Apoptotic Effects of Combination Therapy 239

Table 4.3 List of proteins that were significantly up regulated in PNP-GDEPT treated samples and their role in cancer Name of the Protein Hit Value Ratio Properties Identified (untreated/ Transformed log treated) (Treated: untreated)1 Purine nucleoside 0/37 26,239 Enzyme used in this GDEPT approach (323) phosphorylase [E. coli] Poly (ADP-ribose) 0/4 11,609 PARP is involved in DNA repair in response to some forms of polymerase (PARP) stress; can be cleaved by caspase-3 both in vitro and in vivo; helps cells to maintain their viability; cleavage of PARP facilitates cellular disassembly; a marker for cells undergoing apoptosis (883-893)

Progesterone receptor 0/3 10,000 Role is controversial if its favours or opposes cancer activities; membrane component overexpression shown in several cancers and its related with cancer cell survival: also known as PGRMC; in spite of its name, PGRMC1 is not a progesterone receptor; PGRMC1 plays an important role in promoting OC cell viability and attenuating PGRMC1's action increased OC cell sensitivity to CDDP mediated apoptosis; reported as a biomarker in breast cancer (894-899) 239

Chapter 4: Apoptotic Effects of Combination Therapy 240

Angiotensinogen 0/3 10,000 Serpins (SERine Proteinase Inhibitors); functional expression in OC precursor (Serpin A8) and involved in tumor progression and angiogenesis; involved in the regulation of tumor angiogenesis especially in receptor negative breast cancer (900-902)

Rab13 0/3 10,000 Ras family related; Rab13 may play an important role in the assembly of tight junctions and thus in the establishment of polarity in epithelial cells; Detected in several types of epithelia, including intestine, kidney, liver and in endothelial cells; a specific role in cancer is yet to be determined (903,904)

DEAD Box polypeptide 3 0/2 7,925 Tumour suppressor gene; belongs to DEAD box RNA helicase family; inhibits colony formation activity of HCC, cervical carcinoma, colon cancer, and murine fibroblast cells

1 Confidence intervals for estimated mean of population: For 0.95 CI: 232.9632±123.8158; For 0.99 CI: 232.9632±163.636 240

Chapter 4: Apoptotic Effects of Combination Therapy 241

4.2.5 Treatment related effects on pro- and anti-apoptotic proteins

Next, an evaluation of relative expressions of pro- and anti-apoptotic proteins was carried out in differentially treated OC cells by western blot analyses. Based on synergy evaluations, OVCAR-3 cells were treated with carboplatin (CP) (20 M), Taxotere (3 nM) and PNP-GDEPT (Ad/CMV/PNP moi of 10 pfu/cell plus 1 g/ ml Fludara) either alone or in combination to achieve best synergies. At 48 h, cell lysates (50 g) were generated and analysed for seven candidate proteins shown to play a key role in apoptosis (BCL-2, survivin, BAX, Bik, Bok, Caspase-7 and -9; details in Table 4.3). These are members of three distinct families, including BCL-2, inhibitors of apoptosis (IAP) and caspases and are significant because of their frequent up or downregulation in OC progression or in response to treatment.

By and large, a significant but variable downregulation of anti-apoptotic genes/proteins and up-regulation of pro-apoptotic genes was achieved when modalities were combined

(Table 4.4). Specifically, the expression of BCL-2 (anti-apoptotic) was downregulated particularly in response to combination treatments with PNP-GDEPT as one of the components (Figure 4.6). Interestingly, CP and Taxotere alone did not effect BCL-2 expression.

Survivin, which is an important member of IAP family was downregulated in all combinations including CP + Taxotere, GDEPT + CP, GDEPT + Taxotere and GDEPT +

CP + Taxotere (Figure 4.7). The levels of protein down-regulation were the highest in tri- combination treatment. Also CP alone or Taxotere alone did not induce any specific effects on survivin expression, however, this was notably lower in PNP-GDEPT alone treated

Chapter 4: Apoptotic Effects of Combination Therapy 242 cells. BAX, Bik and Bok are pro-apoptotic members of BCL-2 family. These proteins promote cancer cell death using multiple mechanisms (Figure 4.1). The protein expression of BAX was enhanced with different treatments (Figure 4.8); however the level of expression was significantly higher when therapies were combined with maximum increases being seen in tri-combination treated cells. A similar trend was observed in Bik and Bok protein expression (Figure 4.9 and 4.10).

Caspases are involved in the execution phase of apoptosis; these regulate apoptosis by cleaving target proteins within a proteolytic cascade. To assess the involvement of caspases in effects of different treatment, caspase-7 (‘executioner caspase) and caspase-9 (‘initiator’ caspase) were evaluated for their potential pro-apoptotic role in these effects. While the levels of pro-caspase-7 and 9 were not affected by any of the treatments, the expression of both cleaved caspase-7 and -9 were markedly enhanced in samples given the combination treatments with maximum increase in tri-combination treated cells (Figure 4.11 and 4.12).

Given that caspase mediated proteolysis of PARP is a biochemical marker of apoptosis and it denotes the final stages of apoptosis leading to DNA fragmentation (Figure 4.1). PARP

(cleaved and un-cleaved) expression was evaluated in cells given different treatments. This was of particular interest as this protein was also implicated in PNP-GDEPT mediated apoptosis according to the proteomics analyses. The data showed that both un-cleaved

(especially 116 kDa band) and cleaved PARP are upregulated in response to combination treatments (Figure 4.13). Once again this increase was particularly pronounced when

GDEPT was part of the combination treatment. Further, GDEPT alone led to a greater increase than Tax and CP alone or combined.

Chapter 4: Apoptotic Effects of Combination Therapy 243

Table 4.4 Summary of treatment related effects on different pro and anti-apoptotic proteins (western blot analysis)

Protein Potential role in Cancer Relative levels of proteins (up or down regulation in response to different treatments* U1 C2 T3 CT4 G5 GC6 GT7 GCT8 BCL-2 Anti-apoptotic - - - -

Survivin Belongs to Inhibitor of Apoptosis (IAP) - - - - - family BAX Pro-apoptotic; helps to release cytochrome c - - - from mitochondria and also results in the activation of caspase-9 BCL-2-Interacting Pro-apoptotic; able to bind to and - Killer (Bik) antagonize anti-apoptotic BCL-2 family members including BCL-2, Bcl-xL BCL-2 related Pro-apoptotic; promotes both caspase- - - - Ovarian Killer dependent and caspase-independent (Bok) apoptosis Pro-caspase-7 ------Cleaved caspase-7 Pro-apoptotic; ‘executioner’ caspase - 243

Chapter 4: Apoptotic Effects of Combination Therapy 244

Pro-caspase-9 ------

Cleaved caspase-9 Pro-apoptotic; ‘initiator’ caspase - - -

PARP DNA repair in response to some form of - - - - stress Cleaved PARP Final stage of apoptosis and a marker for - - - cells undergoing apoptosis

U1, Untreated; C2, carboplatin; T3, Taxotere; CT4, carboplatin + Taxotere; G5, PNP-GDEPT; GC6, PNP-GDEPT + carboplatin; GT7, PNP-GDEPT + Taxotere; GTC8, PNP- GDEPT + carboplatin + Taxotere *Symbols used Un-effected -; Up regulated ; moderately up regulated ; strongly up regulated ; Down regulated ; moderately down regulated ; strongly down regulated 244

Chapter 4: Apoptotic Effects of Combination Therapy 245

PNP-GDEPT - - - - + + + +

Taxotere - - + + - - + +

Carboplatin - + - + + + - +

Bcl-2 26 kDa A ß-Actin 42 kDa

0.8

0.6

B 0.4

0.2 Bcl-2 ratio to beta actin to Bcl-2ratio

0.0

in e X X X ed t er PT CP la A E + eat p xot tr GD n rbo Ta CP+T U Ca GDEPT PT+CP+TA GDEPT+TAE GD

Figure 4.6 Evaluation of treatment related effects on BCL-2 expression in OVCAR-3 cells: Cell lysates (50 g) from treated and untreated cells were analysed by SDS- page/western blotting (Panel A), quantified by densitometry relative to -actin (loading control, to test the integrity of protein sample) and expressed as ratio of BCL-2 to beta- actin for different treatments (mean ± SEM, n=2 for two separate experiments) (Panel B). Expression of BCL-2 (anti-apoptotic) was significantly down regulated involving treatments with PNP-GDEPT as one of the components.

Chapter 4: Apoptotic Effects of Combination Therapy 246

PNP-GDEPT - - - - + + + +

Taxotere - - + + - - + +

Carboplatin - + - + + + - +

Survivin A 16 kDa ß-Actin 42 kDa

0.8

0.6

B 0.4

0.2 Survivin ratio to beta actin 0.0 X A TAX EPT TAX D + +T P+ G P Taxotere C Untreated DEPT+CPEPT Carboplatin G D G GDEPT+C Figure 4.7 Evaluation of treatment related effects on survivin expression in OVCAR- 3 cells: Cell lysates (50 g) from treated and untreated cells were analysed by SDS- page/western blotting (Panel A), quantified by densitometry relative to -actin (loading control, to test the integrity of protein sample) and expressed as ratio of survivin to beta- actin for different treatments (mean ± SEM, n=2 for two separate experiments) (Panel B). Expression of survivin (inhibitor of apoptosis) was significantly down regulated in cells treated with a combination of GDEPT, CP and Taxotere. PNP-GDEPT alone led to significant downregulation of survivin.

Chapter 4: Apoptotic Effects of Combination Therapy 247

PNP-GDEPT - - - - + + + +

Taxotere - - + + - - + +

Carboplatin - + - + + + - +

Bax A 20 kDa ß-Actin 42 kDa

0.8

0.6

B 0.4

0.2 Bax ratio to beta actin beta to ratio Bax

0.0

d n re X X te ti la TA TA p + T+CP bo GDEPT P T+ r Taxote CP P Untrea Ca GDE GDE

GDEPT+CP+TAX

Figure 4.8 Evaluation of treatment related effects on BAX expression in OVCAR-3 cells: Cell lysates (50 g) from treated and untreated cells were analysed by SDS- page/western blotting (Panel A), quantified by densitometry relative to -actin (loading control, to test the integrity of protein sample) and expressed as ratio of BAX to beta-actin for different treatments (mean ± SEM, n=2 for two separate experiments) (Panel B). Expression of BAX (pro-apoptotic) was up regulated in cells treated with a combination of GDEPT with CP and Taxotere

Chapter 4: Apoptotic Effects of Combination Therapy 248

PNP-GDEPT - - - - + + + +

Taxotere - - + + - - + +

Carboplatin - + - + + + - +

Bik A 20 kDa

ß-Actin 42 kDa

0.5

0.4

0.3 B 0.2

Bik ratio to beta actin 0.1

0.0

d e P X X e er C t latin t EPT + A p TAX rea + D +TA G T P+T nt rbo Taxo CP EPT P U D Ca G GDE EPT+C GD

Figure 4.9 Evaluation of treatment related effects on Bik expression in OVCAR-3 cells: Cell lysates (50 g) from treated and untreated cells were analysed by SDS- page/western blotting (Panel A), quantified by densitometry relative to -actin (loading control, to test the integrity of protein sample) and expressed as ratio of Bik to beta-actin for different treatments (mean ± SEM, n=2 for two separate experiments) (Panel B). Expression of Bik (pro-apoptotic) was enhanced in most of the treatments especially in tri- combination treated cells.

Chapter 4: Apoptotic Effects of Combination Therapy 249

PNP-GDEPT - - - - + + + +

Taxotere - - + + - - + +

Carboplatin - + - + + + - +

Bok A 18 kDa ß-Actin 42 kDa

0.8

0.6

B 0.4

0.2 Bok ratio to beta actin

0.0

d re e e AX AX latin T T op +TAX treat b P+ GDEPT T P+ n r Taxot C U EP +C Ca GDEPT+CPD G DEPT G

Figure 4.10 Evaluation of treatment related effects on Bok expression in OVCAR-3 cells: Cell lysates (50 g) from treated and untreated cells were analysed by SDS- page/western blotting (Panel A), quantified by densitometry relative to -actin (loading control, to test the integrity of protein sample) and expressed as ratio of Bok to beta-actin for different treatments (mean ± SEM, n=2 for two separate experiments) (Panel B). Expression of Bok (pro-apoptotic) was up regulated in cells treated with a combination of GDEPT and CP and also in tri-combination.

Chapter 4: Apoptotic Effects of Combination Therapy 250

PNP-GDEPT - - - - + + + + Taxotere - - + + - - + +

Carboplatin - + - + + + - +

Cleaved Caspase-7 20 kDa A Caspase-7 35 kDa

ß-Actin 42 kDa

1.5

1.2

0.9 B 0.6

0.3

0.0 Cleavedcaspase-7 ratio tobeta actin d re T X e e AX P AX A T T T oplatin + DE T+CP + + b P G P T P Taxot C E P C Untreat D E Car G GD EPT+ D G Figure 4.11 Evaluation of treatment related effects on caspase-7 expression in OVCAR-3 cells: Cell lysates (50 g) from treated and untreated cells were analysed by SDS-page/western blotting antibodies specific to caspase-7 (35 kDa) and cleaved caspase- 7 (20 kDa) (Panel A), quantified by densitometry relative to -actin (loading control, to test the integrity of protein sample) and expressed as ratio of cleaved caspase-7 to beta-actin for different treatments (n=1, results from one experiment only) (Panel B). Expression of pro Caspase-7 was un-affected while cleaved form (pro-apoptotic) was up regulated in cells treated with GDEPT alone and its combination with CP & Taxotere.

Chapter 4: Apoptotic Effects of Combination Therapy 251

PNP-GDEPT - - - - + + + +

Taxotere - - + + - - + +

Carboplatin - + - + + + - +

Cleaved Caspase-9 A 17 kDa Caspase-7 47 kDa ß-Actin 42 kDa

0.8

B 0.6

0.4

0.2

0.0 Cleaved caspase-9 ratio to beta actin

ated latin e p +TAX +TAX bo GDEPT T r Taxotere CP+TAX CP Untr Ca GDEPT+CP GDEP GDEPT+

Figure 4.12 Evaluation of treatment related effects on caspase-9 expression in OVCAR-3 cells: Cell lysates (50 g) from treated and untreated cells were analysed by SDS-page/western blotting using antibodies specific to caspase-9 (47 kDa) and cleaved caspase-9 (17 kDa) (Panel A), quantified by densitometry relative to -actin (loading control, to test the integrity of protein sample) and expressed as ratio of cleaved caspase-9 to beta-actin for different treatments (n=1, results from one experiment only) (Panel B). Expression of pro caspase-9 was un-affected while the cleaved form (pro-apoptotic) was increased in cells treated with tri-combination (GDEPT + CP + Taxotere).

Chapter 4: Apoptotic Effects of Combination Therapy 252

PNP-GDEPT - - - - + + + +

Taxotere - - + + - - + +

Carboplatin - + - + + + - +

Cleaved PARP 89 kDa A 116 kDa PARP 89 kDa 3 bands 24 kDa ß-Actin 42 kDa

1.0

0.8 B 0.6

0.4

0.2

Cleaved PARP ratio to beta0.0 actin

X P ed tere C AX at o + T x a GDEPT PT T CP+TA Untre DE +CP+ Carboplatin G GDEPT+TAXPT DE G Figure 4.13 Evaluation of treatment related effects on PARP expression in OVCAR-3 cells: Cell lysates (50 g) from treated and untreated cells were analysed by SDS- page/western blotting using antibodies specific to PARP (116, 89 and 24 kDa) and cleaved PARP (89 kDa) (Panel A), quantified by densitometry relative to -actin (loading control) and expressed as ratio of cleaved PARP to beta-actin for different treatments (mean ± SEM, n=2 for two separate experiments) (Panel B). Expression of PARP was un-affected while its cleaved form was enhanced by all treatments and effects were more pronounced in all combinations that included GDEPT.

Chapter 4: Apoptotic Effects of Combination Therapy 253

4.3 Discussion

Mutations in pathways involved in apoptosis lead to the malignant phenotype of cancer cells and modulate their responses to therapy. Especially with respect to chemoresistance, a number of processes may be involved including activation or blocking of signal pathways, cell cycle arrest, DNA repair, drug detoxification mechanisms and apoptosis. Apoptosis or

“programmed cell death” is a genetically regulated biological process that involves the activation of an intracellular protease cascade that cleaves several intracellular proteins leading to membrane-blebbing, chromatin condensation and DNA fragmentation. It is now obvious that modulation of genes controlling apoptosis plays a crucial role in the response of cancer cells to various forms of anticancer therapies. While platinum based drugs

(cisplatin and carboplatin) are the mainstay of current treatments for OC patients with advanced disease, 5-year survival is only seen in 20-30% of patients (188). The main problem is disease recurrence due to development of chemotherapy resistant disease.

While this issue has been partially addressed by combination current therapies with taxanes

(paclitaxel, Taxotere) resulting in improved efficacy and survival, development of the chemo-resistant phenotype still remains an issue.

Although, individual anti-cancer drugs/regimens have a unique mode of action, ultimately, the aim is to achieve adequate levels of apoptosis to trigger cell death. Platinum drugs such as carboplatin act through the formation of DNA adducts, which interfere with cell cycling and if the DNA damage is adequate, apoptosis is initiated. Taxanes, on the other hand, induce stabilisation of microtubules to interfere with cell mitosis, subsequently triggering apoptosis. PNP-GDEPT causes cell death through inhibition of DNA and RNA synthesis,

Chapter 4: Apoptotic Effects of Combination Therapy 254 thus targeting dividing and non-dividing cells. The ultimate aim of combining PNP-

GDEPT with Taxotere and carboplatin in this study was to achieve a sufficient stimulus to initiate apoptosis and ultimately, cell death.

Evaluation of levels of apoptosis in OC cells after different treatments has clearly shownthat apoptosis plays a significant role in cell death triggered by combining two or three modalities. The percentage of cells undergoing apoptosis (sub G1) significantly increased when PNP-GDEPT was included in the regimen. Subsequently, for the first time, through the use of tools for proteomic studies and western blotting, protein changes underlying the efficacy of PNP-GDEPT were examined; data showed involvement of proteins implicated in cancer oncogenesis and apoptosis (PARP, BCL-2, survivin, caspase-

7 and -9) in PNP-GDEPT mediated cell killing. The data also clearly indicated increasing involvement of pro-/anti-apoptotic proteins and caspases taking the effects of treatments from initiation through to execution of apoptosis especially when more than one regimen was combined.

These molecular analysis were carried out in multidrug resistant OC cell lines OVCAR-3 and SKOV-3 because, firstly, two way and three way synergies were proven in these previously and secondly, an assessment in these OC lines would address specific issues related to hard to obtain tumour tissues at the time of relapse (after first round of chemotherapy) or in the acquisition and culture of primary cell lines. In addition, often the available tissue is not representative of the mechanisms that mediate drug responses early in the time course of treatment (905). Further, mechanistic studies such as this have the potential to offer valuable insights into the processes involved in drug action especially

Chapter 4: Apoptotic Effects of Combination Therapy 255 since the validity of in vitro assessment of gene/protein expression is often reflected in the clinical setting. Such an insight may be useful in establishing and designing regimens to address drug resistance related issues (905) and to establish novel second-line therapies for treatment of OC (906).

For assessment of early and late apoptotic events in response to different treatments, all analyses were carried out at 48 h post treatment in this study. This was on the basis of early time course studies done in this study (Chapter 3). While the impact of most modalities is visually obvious at 48 h. cytopathic effects are by no means complete at this time. In addition, given that synergies were being evaluated, time points beyond 48 h were not included as significant increases in cellular toxicity (apoptosis/cell death) observed with combination regimens (especially tricombination) could potentially obscure the molecular responses to different treatments (905).

As mentioned earlier, an interference with cell reproduction (cell cycle) through processes like DNA damage/microtubule-stabilisation, initiates apoptosis. Both carboplatin and docetaxel lead to accumulation of cells in G2/M phase (94,142,812-816,907). Cell cycle analyses were performed to assess the impact of combining these with PNP-GDEPT. As expected, Taxotere and carboplatin treatments led to cell cycle arrest in G2/M phase, the combination of two led to increased apoptosis (sub G0/G1 phase) suggesting that the combination led to irreversible DNA damage. This is also supported by the success of the combination regimen in the clinic; however long-term data on the development of chemoresistant phenotype of OC treated with the two is as yet inadequate (44,47). The interference of DNA/RNA synthesis mediated by PNP-GDEPT led to a considerable increase in cells in G0/G1 phase and a slight increase in G2/M arrested cells suggested that

Chapter 4: Apoptotic Effects of Combination Therapy 256 at 48 h after treatment, cells were in an apoptotic phase. In fact, early apoptosis was significantly enhanced (M30 positive fraction) especially in response to combinations involving PNP-GDEPT at all time points examined. The increase in percentage of cells in apoptosis when PNP-GDEPT was given with either Taxotere and/or carboplatin showed the ability of these combinations to enhance cell death with the most effective apoptotic stimulus occurring when tri-combination treatment was given. This was also reflected in the synergistic killing observed when bi- or tri-combination treatments were employed in our previous studies. Frrther support for this was provided by the proteomics based analyses of molecular effects of PNP-GDEPT suggesting shutdown of most metabolic pathways by 48 h post-treatment.

While DNA expression based analysis contributes significantly to the understanding of gene changes in response to various forms of therapy (908-912), these provide static data and need to be validated at the protein expression level for confidence in the interpretations. Recently, with the exponential development of protein analytical tools, high throughput protein expression profiling (proteomics) have become an integral part of such exploratory studies (913,914). Such an analysis provides direct protein- expression/interaction based evaluations and overcomes the major limitation of gene-based analyses that does not allow the study of post-translational modifications (e.g. phosphorylation, glycosylation etc), protein-protein interactions and cellular and subcellular distribution of protein products (915). Especially, recently developed Shotgun proteomics (749-751) involving mass spectrophotometry based analyses allow a quick but accurate preliminary assessment of protein changes in differentially treated samples.

Hence, this methodology was used to assess differential protein levels in OVCAR-3 cells

Chapter 4: Apoptotic Effects of Combination Therapy 257 in response to PNP-GDEPT treatment. Although, due to time and financial restraints the replicates were not done, the information generated through these analyses is significant as the first screen and is reliable especially since it was validated at a functional level (PNP shown as overexpressed & through proven PNP activity) and by western blotting (e.g.

PARP) analyses. However, further confirmation by more repeats and western blotting analyses and for more specific evaluation using techniques such as two-dimensional gel- chromatography coupled with mass spectrometry is warranted for better dissection of the data. This is the first study to identify the protein changes in response to PNP-GDEPT.

Lists of proteins, which were up or down regulated with PNP-GDEPT treatment, and their respective role in general/cancer have been shown in Table 4.2 and 4.3. It appears as though PNP-GDEPT may be acting through involvement in numerous processes ultimately leading to shutdown of cell metabolism and downregulation of some key oncogenes and genes involved in drug detoxification with finally an upregulation of apoptosis. Some observations that warrant future exploration are mentioned:

1. A downregulation of genes implicated in carcinogenesis was noted (e.g. cadherin,

desmoplakin, plakoglobin, karyopherin, spondin, agrin; more details in Table 4.2)

2. Downregulation of genes involved in detoxification or drug resistance (e.g. antiquitin,

epoxide hydrolase) also occurred. It may be expected that such downregulation of

expression of these genes/proteins would have increased the sensitivity to

chemotherapeutic drugs used in this study e.g. Taxotere and carboplatin (OVCAR-3 is

considered as a platinum resistant cell line). This would also provide a tangible

explanation for enhanced apoptosis observed when PNP-GDEPT was included in

combination regimens and predict its promise for synergies with chemotherapy in the

clinic (Chapter 3).

Chapter 4: Apoptotic Effects of Combination Therapy 258

3. Downregulation of proteins involved in RNA and protein synthesis corroborating its

mode of action, which involves an inhibition of DNA/RNA synthesis.

4. In addition, proteins representing “a desmosome model of carcinogenesis” proposed

by Chidgey et al (833) were generally downregulated in PNP-GDEPT treated samples;

these include desmoplakin, cadherins, plakoglobin (-catenin), filaggerin (intermediate

filament-associated proteins that bind to keratins bundles).

Figure 4.14: A model outlining how desmosomes could contribute to tumorigenesis (Plakoglobin (yellow), ß-catenin (blue), plakophilin (red). -cat, -catenin; DP, desmoplakin; E- cad, E-cadherin; IFs, intermediate filaments). Figure adapted from Chidgey et al 2007 (833)

5. According to this model (Figure 4.14), plakoglobin is released from desmosomes as a

result of either loss or modulation of expression of desmosomal cadherins or

desmoplakin and displaces -catenin from the adherens junctions. The latter

translocates to the nucleus, stimulates transcription of -catenin-responsive genes and

ultimately results in cell proliferation. Alternatively, plakoglobin liberated from

desmosomes translocates to the nucleus, stimulates transcription of genes, such as c-

myc or BCL-2, and promotes uncontrolled cell growth. This also correlated with the

Chapter 4: Apoptotic Effects of Combination Therapy 259

BCL-2 downregulation associated with PNP-GDEPT treatment (Figure 4.6). Hence,

downregulation of this pathway may be one of the major features of PNP-GDEPT

efficacy.

6. Upregulation of proteins which mark apoptotis (e.g. PARP) or tumour supressor

proteins (e.g. Dead box polypetide 3) suggesting proapoptotic effects.

7. Upregulation of proteins involved in purine and pyrimidine metabolism coupled with

the downregulation of metabolic pathways (e.g. lipid, amino acid, carbohydrate and

glycolysis), which suggests that cells are directing all processes towards replication in

response to stress. In addition, the upregulation of DNA synthesis proteins could also

be a result of use of theAdenoviral vector used in this study that can also trigger the

cells into synthesis phase.

Understanding apoptosis is a complex process, which requires involvement of several key pathways. Apoptosis is dependent upon three essential phases, which include initiation, effector and execution pathways (916). In the initiator phase, an apoptotic stimulus is received (e.g. chemotherapeutic or biological agent), which is followed by an effecter phase where the fate of the cell is decided. The BCL-2 family of proteins generally governs the effecter phase where the ratio of different anti- and pro-apoptotic proteins determines if a cell is heading towards survival or death. The final or “execution” phase is controlled by caspases, which cause the specific degradation of a series of proteins. Although the modalities used in this study differ in their primary mode of action, apoptosis was the final outcome (as shown by M30, cell cycle and protein expression analyses). It has been proposed that that growing resistance to DNA binding drugs (especially platinum drugs e.g. cisplatin) might be due to a defective apoptotic program rather than processes like drug

Chapter 4: Apoptotic Effects of Combination Therapy 260 efflux/influx ratios, or DNA repair mechanisms. Further, platinum drugs such as carboplatin may also interact with proteins, which could lead to the direct execution stage of apoptosis. It is known that docetaxel acts by direct action on microtubule proteins with apoptosis recognised as being the key feature of its action. According to our proteomics data and previous studies, PNP-GDEPT operates through inhibition of DNA/RNA synthesis ultimately leading to shutting down of most metabolic pathways and upregulation of apoptosis (PARP).

To assess the extent of modulations in different apoptotic proteins due to different treatments, genes/proteins that play an important role in the apoptostic pathways that are often mutated in cancer cells were evaluated (Table 4.4 and 4.5). Protein members representing effector phase BCL-2, Inhibitor of apoptosis (survivin) and execution phase

(caspase-7/9), were evaluated. In line with the cell killing synergies obtained with different therapeutic combinations, the protein data from this study indicated a clear relationship between the extent of apoptosis and levels of expression of various pro- and anti apoptotic proteins which generally regulate the effector phase of apoptosis (917).

Overall, proteins BAX, Bik, Bok, Cleaved Caspase-7 & -9 (all pro-apoptotic) were up regulated and BCL-2 and Survivin (anti-apoptotic) were down regulated when modalities were combined, albeit to variable levels based on given treatments.

Significant dowregulation of BCL-2, an oncoprotein frequently overexpressed in a variety of cancers including OC (570,918), was seen especially when PNP-GDEPT was given and the effects were more prominent when combined with Taxotere or carboplatin. The anti- apoptotic nature of BCL-2 is well established in OC (919-922). In addition to p53, BCL-2

Chapter 4: Apoptotic Effects of Combination Therapy 261 levels are also used as a prognostic marker and often regarded as a predictor of chemosensitivity in OC patients (920,923-926). While, the potential of docetaxel and carboplatin to down-regulate or inactivate BCL-2 in OC cell lines has been shown in some studies (142), in this study, levels of BCL-2 remained unaffected in response to Taxotere or carboplatin treatment. These differences may be attributed to the differences in tumour types, dose ranges or exposure time of the drugs, although the lower levels of BCL-2 achieved with the combined use of Taxotere and carboplatin suggested involvement of

BCL-2 pathway in these interactions.

Chapter 4: Apoptotic Effects of Combination Therapy 262

Table 4.5 List of selected genes/proteins used for western blot analysis based on their role in OC progression and treatment Family Member Role in OC progression/treatment* Ref. Protein Genes/Proteins whose down regulation is a favourable outcome for OC Anti-apoptotic BCL-2 Anti apoptotic; promotes cell survival in response to apoptotic stimuli (451,804,918- 921,923-928) members of B-Cell through inhibition of mitochondrial cytochrome c release; frequently CLL/Lymphoma-2 overexpressed in OC; Inhibits drug-induced apoptosis; a prognostic (BCL-2) family marker and predictor of chemosensitivity Inhibitor of Apoptosis Survivin Anti apoptotic; inhibition of apoptosis and promotion of cell division by (929-934) (IAP) binding and inhibiting Caspase-3 in G2/M phase of cell cycle; frequently overexpressed in different histological types of OC; a prognostic marker and predictor of chemosensitivity

Genes/Proteins whose up regulation is a favourable outcome for OC

BCL-2 BAX Pro-apoptotic; tumor suppressor; results apoptosis in both p53 dependent (381,382,408, Pro-apoptosis and independent pathways; BAX sensitises ovarian cancer cell lines to 918,921,935- paclitaxel in vitro; a predictor of responsiveness to paclitaxel or platinum 937) based chemotherapy in OC patients 262

Chapter 4: Apoptotic Effects of Combination Therapy 263

BCL-2- A proapoptotic gene often named as Nbk/bik (Natural Born Killer); (938-942) interacting contains only one of the BCL-2 homology regions, the BH33 domain; killer (Bik) forms heterodimers with various antiapoptotic proteins, such as BCL-2

and Bcl-XL, to inhibit their antiapoptotic function; tumor cell sensitiser to chemotherapy e.g., doxorubicin BCL-2- Proapoptotic; absence of BH4 domain, which is found only in anti- (943-945) related apoptotic BCL-2 proteins; heterodimerizes only with selective anti- ovarian killer (Bok) apoptotic BCL-2 proteins; does not bind to BCL-2 (increased expression of BCL-2 does not affect its proapoptotic nature); a cell cycle regulator, which sensitises cells to stress induced apoptosis e.g., Flavopiridol Caspases Caspase-7 The ‘executioner’ caspase-7; activation leads to apoptosis; activated in OC (946-949) cells in response to a variety of chemotherapeutic or biologic agents; may help to evaluate the patient’s responsiveness to chemotherapy Caspase-9 The ‘initiator’ caspase-9; activation leads to apoptosis; activated in OC (948-950) cells in response to a variety of chemotherapeutic or biologic agents; may help to evaluate the patient’s responsiveness to chemotherapy * The potential role has been discussed in other types of cancer when a relevant reference to OC was not found. 263

Chapter 4: Apoptotic Effects of Combination Therapy 264

Given that survivin, an important member of IAP family, is often up-regulated in a variety of cancers including OC (930,933), a significant downregulation in the levels of survivin, after treatment with the combinations (Taxotere and carboplatin and tri- combination) suggested that especially the tri-combination may have efficacy against

OC. Adding to the significance of this finding is the fact that recently, knockout of the survivin gene led to improved survival in mice with OC (951).

The general upregulation of proapoptotic members of the BCL 2 family, BAX, BCL-2 interacting killer (Bik) and BCL-2 related ovarian killer (Bok) after combination therapy, especially the tri-combination, further confirmed the promise of these synergies. Individually, BAX can result in both p53 dependent and independent apoptosis (451,937). BAX is also considered as a tumor suppressor gene and has a well- defined role as a predictor of chemo-responsiveness in OC patients (935). In correlation with observations made in this study, previous reports have shown that BAX based gene therapy can synergise with a variety of chemotherapeutic agents to generate favourable responses (381,382,408). Hence, increased levels of BAX may have strong clinical implications in combination-based therapy, as was seen in cells treated with bi and tri- combination treatments (Figure 4.8) especially when PNP-GDEPT was involved.

Similar trends were seen with regards to Bik expression; this in concert with downregulated BCL-2 correlated with Bik mediated influences on regulation of anti- apoptotic members of the BCL-2 family including BCL-2 and Bcl-xL (938,939,941).

Accumulation of Bik in response to bortezomib leads to significant levels of cell death in SKOV-3 cells (940). Further, similar trends as observed with BAX correlate with the fact that apoptosis driven by Bik is BAX dependent (952).

Chapter 4: Apoptotic Effects of Combination Therapy 265

Bok, the newest pro-apoptotic member of BCL-2 family (943-945), also showed trends similar to that seen with BAX and Bik. Specifically, upregulation generated with the tri- combination of GDEPT, carboplatin and tri combination was more pronounced than with single or bimodal treatments.

Sufficient induction of proapototic proteins (BAX, Bik, and Bok) can lead to the execution phase of apoptosis, marked by induction of caspase (a family of cysteine proteases) mediated cell death (451). This was evidenced in this study where caspase 7 and 9 upregulation was seen in cells treated with combinations (bi and tri-) of drugs.

Activation of caspases suggests an irreversible commitment to cell death (953). As mentioned earlier, caspases play an essential role in the execution phase of apoptosis

(949), and are divided into two categories; the initiator (caspase-8, -9, -10) and executioner caspases (caspase-3, -6, -7) (948). Hence, caspase 9, which represents initiation and caspase 7 which represents execution of apoptosis were chosen for examination in this study specifically. Their role in response to various forms of anticancer therapies has been evaluated at both pre-clinical and clinical levels (946). They are also used to evaluate a patient’s responsiveness to various forms of chemotherapy

(947,950). While levels of caspase 8 were not evaluated, caspase 3 levels (both pro- and cleaved forms) were found to be enhanced in cells treated with GDEPT and its combinations (data not shown). This caspase is implicated in the activity of both docetaxel and carboplatin; however it is possible that caspase-3 independent mechanisms may operate in this particular instance (954). Overall, strong protein expression of both caspase-7 and -9 in responses to combination therapy suggests that pathways involving these caspases (initiated through release of cytochrome c from

Chapter 4: Apoptotic Effects of Combination Therapy 266 mitochondria) involving BCL-2 family of pro and anti apoptotic proteins) may be more active in these synergies.

Hence, the data indicate that the apoptosis involved in the three way synergy between

Taxotere, CP and PNP-GDEPT involves the effector phase mediated by the BCL-2 family of proteins (pro- and anti-apototic) and execution phase involving cleaved caspase 9 and caspase 7. The proteomics data point to involvement of the BCL-2/PARP pathway but the individual apoptotic family protein evaluations strongly indicate that involvement of PNP-GDEPT in the treatment potentiates a more active involvement of pathways involving downregualtion of BCL-2, survivin and drug resistance proteins, leading to a high apoptotic index as achieved in the synergies involving PNP-GDEPT.

The data generated are strongly supportive of using synergistic treatments in the clinic for OCs that show drug resistance to first line therapies.

Chapter 5: Combination Therapy for Prostate Cancer 267

PROSPECTS OF COMBINING CONVENTIONAL AND MOLECULAR CHEMOTHERAPY FOR THE TREATMENT OF PROSTATE CANCER

Chapter 5: Combination Therapy for Prostate Cancer 268

5.1 Introduction

Given the heterogeneity of Prostate cancer (PC), major issue is the inadequacy of currently available treatments, especially against late stage, castration resistant PC

(CRPC) (955,956). This problem is accentuated by increasing incidence of PC in men at a relatively younger age. Hence, watchful-waiting is not an option for these men and it is even more crucial to find an effective therapy. Surgical resection followed by radiation therapy is most commonly used as first line therapy for most PC patients

(957). Recently, for the first time, the chemotherapeutic, docetaxel was found to be active against CRPC with increased patient survival (by 2 months) in 40% of the patients (445,958,959). Although, this finding has changed the standard of care for late stage PC patients, it is not enough (436,479). Further, at the therapeutic doses, side effects occur which are especially not well tolerated by the elderly patients (74,570).

As a result, in addition to traditional therapies, several alternative biological therapies are also being explored e.g. suicide gene therapy, immunotherapy and vaccines to boost anticancer responses against PC (576,577,683-686). A number of target based therapies e.g. targeting pathways/key molecules (e.g. PI3 kinase pathway or Aurora kinases) have also been exploited, but efficiency is still suboptimal when used as single agents

(960,961). Hence, the focus has shifted towards developing rationale-based combinations that can activate divergent or complementary pathways of apoptosis leading to an enhanced therapeutic efficacy. Combinations of therapy can sometimes show synergy, allowing each component to be given at a lower dose than is required when they are used alone, which may have significant impact on quality of life and general clinical outcome. Hence, as the current status of PC oncology stands, improved

Chapter 5: Combination Therapy for Prostate Cancer 269 understanding and exploiting potential interactions between the conventional and novel therapies are increasingly becoming important for better management of the disease.

In this study, we are exploring potential synergies between traditional chemotherapy using docetaxel and “suicide” gene therapy based on PNP-GDEPT, which is has been approved for testing in a phase I trial against CRPC patients in Australia (to start this year, 2009).

PNP-GDEPT: Preclinical studies done in our laboratory have clearly shown the efficacy of Adenovirus mediated PNP-GDEPT against hormone refractory murine RM1 and human PC-3 tumours. Overall, these studies have established the efficacy of PNP-

GDEPT against growth of human xenografts in nude mice and murine PC in immunocompetent mice (335,336,339,340). These studies also showed that PNP-GDEPT conferred survival advantage to treated mice in xenograft, syngeneic and transgenic model (TRAMP) of prostate cancer (335,336,338-340). Hence, based on these findings, a dose finding phase I clinical trial determine the safety and tolerability of Ad mediated

PNP-GDEPT has been initiated recently in Australia (personal communication and http://clinicaltrials.gov/ct; clinical trial number-NCT00625430). The study is titled “A phase I gene therapy study of FP253/Fludarabine for Prostate Cancer (FP253-GDEPT)”

(FP253: ovine atadenovirus that expresses E. coli PNP under the control of Androgen independent prostate-specific promoter). Fludarabine phosphate, the prodrug used for this system is a FDA approved drug with established safety profiles and pharmacokinetics. Primarily, inhibition of DNA and RNA synthesis lead to PNP-

GDEPT mediated efficacy and that modulation of apoptotic pathways involving BCL-2/

Chapter 5: Combination Therapy for Prostate Cancer 270 caspase/IAP family of proteins may be involved was shown in previous studies carried out in OC cells (Chapter 4).

Docetaxel: As discussed before, docetaxel is the only chemotherapeutic agent that has shown a marginal survival benefit in CRPC patients (962). It now forms the new standard of care for treating PC both as a monotherapy and in combination with other drugs e.g. Prednisone (see Sections 1.6.2-1.6.4). Several studies investigating docetaxel against PC have confirmed that it induces tumour cell killing by several apoptotic pathway including but not limited to BCl-2 inactivation (459,460,464).

To explore the potential anti-tumour effects of PNP-GDEPT and/or docetaxel

(Taxotere), two model PC cell lines representing aggressive late stage disease (RM1

(murine) and PC-3 (human), were chosen. RM1 animal model (originally developed by

Dr. Timothy C. Thompson; Baylor College of Medicine, Houston, TX) was used for in vivo evaluations of these synergies. This model mimics multi-step carcinogenesis by activating the ras and myc oncogenes and it is used to form aggressive tumours when xenografted subcutaneously or in prostate (in situ) (762). More importantly, this cell line retains some specific features of PC including androgen responsiveness early in culture, androgen receptor expression and progression to androgen independence with time. Several studies, including some in our laboratory have successfully used this model to evaluate different anticancer therapies raised against local and metastatic PC

(337,338,649,963,964). Similarly, PC-3 cells also exhibit several characteristic of late- stage, androgen-depletion independent (ADI) PC and provide a clinically relevant phenotype to assess anti-tumour responses of various therapies both in vitro as well as xenografts in immunodeficient mice (335,600,630,760).

Chapter 5: Combination Therapy for Prostate Cancer 271

Based on the unequivocal synergy shown between PNP-GDEPT and Taxotere in OC cells (Chapter 3) and their individual efficacy against PC in preclinical or clinical evaluations, it is anticipated that combination of PNP-GDEPT and docetaxel (Taxotere, in this study) may help to generate better anticancer effects and may be more effective against both local and metastatic PC. The specific aims of this study are:

1. To evaluate individual therapeutic effects of Taxotere and PNP-GDEPT against

RM1 and PC-3 cells in vitro.

2. To evaluate and analyse therapeutic interactions between Taxotere and PNP-

GDEPT in vitro

3. To evaluate therapeutic effects of Taxotere and PNP-GDEPT either alone or in

combination against local and metastatic PC in vivo (immunocompetent and

immunodeficient mouse models).

4. To evaluate the effects of treatment on the condition of the mice and on toxicity

profiles.

5. To evaluate the effects of treatment on immune status of the host; e.g.

infiltration of the tumours by immune cells and serum cytokine profiles in

treated mice.

Chapter 5: Combination Therapy for Prostate Cancer 272

5.2 Results

Combined effects of Taxotere and PNP-GDEPT were evaluated in PC cell lines of murine (RM1) and human (PC-3) origin that represent late stage androgen refractory PC

(Table 2.8). Experimental design and data analysis in vitro was done as described in

Section 2.2.4.2 to 2.2.4.4. Once proven, the effects of combination therapy were tested in immunocompetent and immunodeficient mice with PC.

5.2.1 Optimisation of cell plating densities for dose response studies

Prior to evaluation of dose response of PC-3 (human; androgen independent) and RM1

(murine; androgen independent) cell types to different modalities, the optimal plating density was determined using cell proliferation assays as defined in Section 3.2.1.

Depending upon their doubling times, these cell lines displayed differences in growth properties. Compared to RM1 cells, a much higher seeding density of PC-3 cells was needed to optimally last the duration of seven-day drug response experiments. Due to fast growth rates i.e. short doubling time (~11hrs), most favourable seeding density for

RM1 cells was very low (~300 cells/well in a 96 well plate).

Chapter 5: Combination Therapy for Prostate Cancer 273

A 2

1 Absorbance at 450nm at Absorbance

0 0 0 000 000 2 400 6000 8 Cell Number/well

2 B

1 Absorbance at 450nm at Absorbance

0 0 0 200 40 600 800

Cell Number/well

Figure 5.1 Cell growth curves for prostate cancer cell lines: WST-1 assay was performed on cells plated at different cell densities in a 96 well plate. Growth curves were generated on day 7 of culture. Each graph shows variation of absorbance (450nm) with increasing plating density of PC-3 (A) and RM1 cells (B). Cell number chosen for future studies is shown as the dotted line in the middle of logarithmic or exponential growth phase. Each value is the mean (±SEM) of three experiments

Chapter 5: Combination Therapy for Prostate Cancer 274

Table 5.1 Optimal plating densities for different PC cell lines

Plating Density PC-3 RM1

(Number of cells/well)* 3000 300

* These numbers were optimised for 96 well plate format

5.2.2 Effects of Taxotere treatment on PC cell lines

To determine cell growth inhibitory effects of Taxotere on OC cell lines, cells cultured in 96 well plates were treated with Taxotere at different doses (0.1, 0.2, 0.3, 0.6, 1, 3.1,

10, 31.6 and 100 nM) in triplicates and cell viability was determined after 5 days using

WST- assay (see Section 2.2.4.2.1). The data was analysed as mentioned in Section

3.2.2. The growth inhibitory effects of Taxotere were found to be dose dependent in both cell lines (Figure 5.2). Taxotere concentrations needed for 50% inhibition of cell growth (IC50) on 5 days of exposure are shown in Table 5.2. The data revealed that there was a significant variation in Taxotere drug response in the two cell lines suggesting different levels of Taxotere sensitivity. Based on their IC50 values human PC-3 cell line

2 (IC50: 0.57 nM ± 0.15; R = 0.97) was significantly more sensitive (by~5.5. fold)

2 compared to murine RM1 cells (IC50: 3.05 nM ± 1.21; R = 0.95).

Chapter 5: Combination Therapy for Prostate Cancer 275

PC-3 RM1

105 105

50 50 CellSurvival (% ofvehicle control) CellSurvival (% ofvehicle control)

-5 -5

Control 0.1 1 10 100 Control 0.1 1 10 100

Taxotere (nM) Taxotere (nM)

Dose Response Curves on day 5

Figure 5.2 Response of PC cells to Taxotere treatment: PC lines, PC-3 and RM1 were exposed to Taxotere concentrations ranging from 0.1–100 nM. WST-1 assay was performed to analyse cell viability. Cell survival, which is the percentage of vehicle control cells (cells treated with corresponding concentrations of polysorbate 80 and ethanol), was determined using GraphPad Prism. Dose response curves for PC-3 and RM1 as generated after 5 days of treatment are shown. From the dose effect curves it was concluded that PC-3 cell line was more sensitive to Taxotere treatment than RM1. Values represent a mean (±SEM) of three experiments.

Chapter 5: Combination Therapy for Prostate Cancer 276

Table 5.2 Taxotere (nM) needed to kill 50% of PC-3 and RM1 cell populations

(IC50 values)

Taxotere PC- 3 RM1

* IC50 ±SEM 0.57 ± 0.15 3.05 ± 1.21 (nM) (R2 = 0.97) (R2 = 0.95)

* IC50 values were calculated from dose response curves shown in Figure 5.2

5.2.3 Efficiency of Ad-transduction in two different PC cell lines

PC-3 and RM1 cells were checked for their permissivity to Ad infections using

Ad/CMV/GFP as mentioned in Section 3.2.4. Both cell lines showed different levels of

Ad-transduction (GFP expression) (Figure 5.3); at moi of 500 pfu/cell, PC-3 cells were moderately permissive (~% GFP expressing cells: 35 ± 6) while RM1 cells were almost refractory (% GFP expressing cells: 8 ± 2). A lung cancer cell line A-549, which is highly permissive for Ad5 infections, was used as a positive control.

Chapter 5: Combination Therapy for Prostate Cancer 277

100 A-549 PC-3

80 RM1

% GFP% Expressing Cells 20

0 500 100 50 10 Viral Dose (moi*)

Percent GFP Expressing Cells Viral dose(moi*) A-549 PC-3 RM1 500 98 35 8 100 75 6 1 50 46 2 0 10 7 1 0

*multiplicity of infec tion

Figure 5.3 Evaluation of Ad-transduction in cancer cell lines: To check the permissiveness of cancer cell lines for Ad5 transduction, cells infected with Ad5/CMV/GFP for 48h were analyzed for number of cells expressing GFP by flow cytometry. Graph shows % GFP expressing cells at different Ad/CMV/GFP doses (moi) and the numerical values corresponding to different data points are tabulated in the lower panel. PC-3 cells were moderately permissive while RM1 were almost refractory to Ad infections. Values represent mean (±SEM) of three experiments.

Chapter 5: Combination Therapy for Prostate Cancer 278

5.2.4 Effects of Prodrug alone (Fludara), treatment on PC cell lines

Prior to the evaluation of PNP-GDEPT based cell cytotoxicity, a non- toxic range of pro-drug, Fludara was determined in PC cells. Briefly, PC-3 and RM1 cells treated for 5 days with an increasing range of Fludara concentrations (0.25-2.0 g/mL) were analysed for cell viability on day 5. Cell viability data was analysed as described in

Section 3.2.2. As shown in Figure 5.4, the cytotoxicity was noticeable at doses higher than 1.5 g/mL; concentration range of 0.25-1.5 g/mL (shaded grey in Figure 5.4) was shown to be non-toxic for both cell types. From this data, it was concluded that Fludara at a concentration of 1.0 g/mL would be safe for assessment of PNP-GDEPT in both cell types.

Chapter 5: Combination Therapy for Prostate Cancer 279

Non-Toxic

100

A 50 Cell survival (% of control) of (% survival Cell 0 5 5 0 00 2 .50 7 0 0. 0. 0.50 0.75 1.00 1.25 1 1. 2. Fludarabine (g/mL)

Non-Toxic

100

B 50 Cell survival (% of control) of (% survival Cell 0 5 5 0 50 75 00 25 0.00 0.2 0. 0. 1. 1. 1.50 1.7 2.0 Fludarabine (g/mL)

Figure 5.4 Response of PC cells to Fludara treatment: RM1 and PC-3 cells were exposed to Fudarabine at concentrations ranging from 0.25–2.0 g/mL. Cell viability was evaluated on day 5 using WST-1 reagent. Graphs show changes in cell viability relative to control (percentage of control cells), for PC-3 (Graph A) and RM1 cells (Graph B). The data demonstrated that Fludara concentrations ranging from 0.25-1.5 g/ml were non- toxic to both cell types (shown as grey shaded area). The dotted lines represent the concentration (1 g/mL) that was used in GDEPT based cell cytotoxic assays. Values represent a mean (±SEM) of three experiments.

Chapter 5: Combination Therapy for Prostate Cancer 280

5.2.5 Bystander effects of PNP-GDEPT correlate with the efficiency of gene transduction

The cell cytotoxic effects generated by PNP-GDEPT and the resulting bystander effects were seen in both cell lines and increased with increasing doses of Ad/CMV/PNP virus

(Figure 5.5). The cytotoxic effects (% cell death compared to untreated controls ±

SEM) were significantly higher in PC-3 cells (at moi of 300 pfu/cell, 68% ± 4) compared with RM1 cells (moi of 300 pfu/cell, 25% ± 4). IC50 values were calculated from the graphs as moi of Ad/CMV/PNP (+1μg/mL of Fludara) needed to cause 50% of cell growth inhibition (dotted lines in Figure 5.5). The relative potency of PNP-GDEPT

(as IC50 ± SEM) (Table 5.3) against PC-3 cells (IC50: 150 ± 8) was higher than that against RM1 cells (IC50: 600 ± 15). Further, the ‘bystander effects’ were observed in both cell lines, which correlated their levels of Ad5-permissivity. In PC-3 cells

(moderately permissive; Figure 5.3), a significant level of cell inhibition was observed at a viral doses of 100 moi and up to 25% cell growth inhibition was noted even though

6% of cells of the cells expressed PNP (achieved at moi of 100, Figure 5.3). In comparison, doses lower than 100 moi of Ad/CMV/PNP virus (+ 1μg/mL of Fludara) were not able to show any cell growth inhibition in RM1 cells. These effects were attributed to poor gene transduction levels in RM1 cells at these mois’ (1 cells are transduced; Figure 5.3). Control treatment with Ad/CMV/GFP and 1 g/mL of Fludara did not show any noticeable toxicity in both the cell types.

Chapter 5: Combination Therapy for Prostate Cancer 281

A Ad/CMV/PNP+Fludara Ad/CMV/GFP+Fludara

100

50 Cell control) survival of (%

0 0 50 100 150 200 250 300 350 400 Virus Dos e (moi)

B Ad/CMV/PNP+Fludara Ad/CMV/GFP+Fludara

100

50 Cell control) survival of (%

0 0 100 200 300 400 500 600 700 800 Virus Dos e (moi)

Figure 5.5 Evaluation of bystander effects associated with PNP-GDEPT in PC cells: Cells were infected with Ad/CMV/PNP or Ad/CMV/GFP (control) at different mois’ followed by prodrug treatment (Fludara @ 1 g/mL). Cell viability was evaluated on day 5 using WST-1 reagent. Graphs show changes in cell viability relative to control (percentage of control cells), for the two cell lines. The data demonstrate that bystander effects and resulting cytotoxicty increased with increasing doses of test virus. The cytotoxic effects were higher in PC-3 cells (Graph A) when compared with RM1 cells (Graph B). Significant ‘bystander effects’ due to diffusion of the toxic metabolite, 2FA into non-transduced cells, were observed for both cell types. Values represent mean (±SEM) of three experiments.

Chapter 5: Combination Therapy for Prostate Cancer 282

Table 5.3 IC50 values of PNP-GDEPT in two different PC cell lines

PNP-GDEPT PC-3 RM1 Virus moi plus pro-drug1

2 IC50 ± SEM 150 ± 8 600 ± 15

1 Ad/CMV/PNP moi plus 1g/ml of Fludara 2 Estimated values based on dose response curves generated in Microsoft Excel (Figure 5.5)

5.2.6 PNP-GDEPT and Taxotere act synergistically in PC cells in vitro

To evaluate interactions between PNP-GDEPT and Taxotere when used in combination, a range or IC50 values of these agents was selected based on the experiment. Two different methods were used to evaluate the efficacy of the combination treatments:

3. Clonogenic assay

4. WST-1 based tetrazolium assay

5.2.6.1 Clonogenic assay

Clonogenic assay was performed to assess the effects of Taxotere and PNP-GDEPT on survival of human PC cell line only. The experiment and data analysis was performed as mentioned in Section 3.2.6.1. Briefly, PC-3 cells (96 well plate, 3000 cells) were treated with different treatments (Taxotere (0.3 nM) and PNP-GDEPT (Ad/CMV/PNP moi of

150 pfu/cell plus 1 g/mL Fludara; either alone or in combination) and after 3 days, these were transferred to 6 well plates and grown for 10 days in normal cell growth conditions. In comparison to individual treatments, % of surviving cells was significantly reduced when used in combination (Figure 5.6); percentage of cell death

(% ± SEM) achieved using Taxotere or PNP-GDEPT was 37% and 42%, respectively compared to ~ 85% achieved when used in combination.

Chapter 5: Combination Therapy for Prostate Cancer 283

700 Control P = 0.008 Taxotere Control 600 PNP-GDEPT Colony count 490 ± 108 Taxotere plus 500 PNP-GDEPT

Taxotere 400 * * (0.3 nM) Colony count 311 ± 50 300

200 PNP-GDEPT colonies of Number * (Ad/CMV/PNP 150 moi plus 100 1g/mL of Fludara) Colony count 285 ± 67 0

Taxotere plus PNP-GDEPT Colony count 78 ± 34 100 Taxotere 90 P = 0.009 PNP-GDEPT 80 Taxotere pl us * PNP-GDEPT Figure 5.6 Clonogenic assay for PC-3 cells given different 70 * treatments: Cell survival aftertreatments with Taxotere and PNP- GDEPT either alone or in combination on PC-3 cells were analysed 60 using colony formation assay. Panel A shows a photograph of crystal 50 violet stained colonies of PC-3 cells given different treatments in the 6 40 well plate. Panel B graph represents number of colonies/well for 30 * different treatment groups and Panel C graph shows percentage of cell 20 survival in cells given different treatments. Values represent mean of control)Cell (% Survival (±SEM) of two independent experiments. Values were compared to 10 0 control by one-way Anova using Dunnett’s multiple comparison test. A 283 P value < 0.05 was considered significant.

Chapter 5: Combination Therapy for Prostate Cancer 284

5.2.6.2 Evaluation of combined effects using WST-1 based tetrazoium assay

Cell growth inhibition by Taxotere and PNP-GDEPT, either alone or in combination were tested using multiple combinations in PC-3 and RM1 cell lines. For this experiment, five different doses (as folds IC50) of Taxotere and PNP-GDEPT were used in fixed ratios (see layout template, Section 3.2.6.2) and cell viability was analyzed by WST-1 assay after 5 days of treatment. Given that Taxotere and PNP-GDEPT effects were significantly different for both cell types (see Section 5.2.5), relevant dose ranges of Taxotere (PC-3, 0.075 - 0.6 nM; RM1, 0.25 - 5 nM) and GDEPT (PC-3, 9-150 moi plus 1 μg/mL of Fludara; RM1, 37 - 600 moi plus 1 μg/mL of Fludara) were chosen for the two.

The treatment related effects (mean of values (% of untreated control) from three experiments) were plotted as 3-dimensional graphs using Microsoft Excel software and the combined drug interactions were evaluated as mentioned in Section 3.2.6.2. The results showed a significant dose dependent inhibition of cell growth using either modalities, this was further enhanced when these were combined (Figure 5.7).

Analysis of the Combination index/Fraction affected (CI-Fa) plot generated for PC-3

(Figure 5.8 Panel I) and RM1 (Figure 5.8 Panel II) showed that the combined efficacy of PNP-GDEPT and Taxotere can be attributed to synergistic interactions at most combination ratios tested for both cell lines. Equivalent levels of synergies were obtained for PC-3 (CI 0.46 at ED75; R value 0.99) and RM1 cells (CI 0.39 at ED75; R value 0.98) (Table 5.4). The dose reduction index (DRI) values to achieve a specific effect (tabulated in Figure 5.8 panel III) showed that when used in combination, much

Chapter 5: Combination Therapy for Prostate Cancer 285 lower doses of Taxotere and PNP-GDEPT can achieve the same effect than individual doses; a dose reduction of ~3 folds for Taxotere and PNP-GDEPT was predicted to achieve 50% cell killing in PC-3 cells (Table/Figure 5.8 Panel I and III). Similarly, a dose reduction by ~3 fold for Taxotere and ~6 fold for PNP-GDEPT was adequate when given together to achieve 50% cell killing in RM1 cells (Table/Figure 5.8 Panel II and

IV). A dose reduction of upto ~6 fold for both agents was predicted in PC-3 cells and upto ~7 fold for Taxotere and 8 fold for PNP-GDEPT for RM1 cells. Synergistic effects in relatively more Ad-refractory/Taxotere resistant RM1 cells were significant as this could have implications in targeting relatively hard to infect (most cancer cells have lowered CAR expression) drug resistant PC cells.

Chapter 5: Combination Therapy for Prostate Cancer 286

100 100

90 90

80 80

70 70

60 60

50 50

40 40

30 30

20 20

10 inhibition growth cell of % 10

0 0

150 600 .00 0.600 75 5 3 .50 00 .450 37 2 0 150 00 1.25 0.3 0 18 T 5 75 T P T 7 EP T .15 DE a 0. 3 D ax 0 9 xo 7 G oter 075 P-G ter .25 P- 0. C N e 0 C N e 0 P 0 o P on ntro trol l Taxotere Ad/CMV/PNP (moi) + 1g/mL Fludara Taxotere Ad/CMV/PNP (moi) + 1g/mL Fludara (nM) (nM) Control 9 18 37 75 150 Control 37 75 150 300 600 0 0 10152834530 0 1 9 10 20 39 0.075 11 12 15 35 45 55 0.25 16 12 21 21 34 46 0.150 15 18 25 35 51 57 0.75 27 34 36 43 57 59 0.300 27 33 41 47 52 62 1.25 34 40 45 55 56 62 0.450 35 49 52 54 65 67 2.50 45 56 59 64 70 75 0.600 55 64 70 73 75 77 5.00 65 70 70 79 89 89 Figure 5.7 Evaluation of cell growth inhibition by the combination of PNP-GDEPT and Taxotere in PC cells: Cells treated with different doses of Taxotere and/or PNP-GDEPT were analysed for cell viability using WST-1 assay on day 5. Three-dimensional graphs representing inhibition of cell growth were plotted as a function of increasing doses of Taxotere and PNP-GDEPT for PC-3 (Graph A) and RM1 (Graph B) cells. Most drug combinations led to significantly greater cell growth inhibition compared with that achieved with either alone. Values represent mean (±SEM) of three independent experiments. 286

Chapter 5: Combination Therapy for Prostate Cancer 287

2.5 I 2.0 II

2.0 1.5

Antagonism 1.5 Antagoni sm 1.0 Additivity 1.0 Addi ti vi ty Synergism Synergism 0.5 0.5 Combination Index (CI) Combination Index (CI)

0.0 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Fraction Affected (Fa) Fraction Affected (Fa)

III PC-3 IV RM1 Fraction Drug Alone Dose Reduction Index Fraction Drug Alone Dose Reduction Index (xIC ) (xIC ) (xIC ) affected (xIC50) 50 affected 50 50 (Fa) GDEPT Taxotere GDEPT Taxotere (Fa) GDEPT Taxotere GDEPT Taxotere 0.1 0.26 0.24 1.33 1.26 0.1 0.96 0.12 5.08 0.65 0.25 0.98 0.93 1.99 1.89 0.25 2.27 0.51 5.45 1.22 0.50 3.74 3.57 2.95 2.82 0.5 5.38 2.11 5.83 2.29 0.75 14.20 13.61 4.39 4.21 0.75 12.75 8.80 6.25 4.31 0.9 53.90 51.87 6.53 6.28 0.9 30.16 36.54 6.69 8.11 Figure 5.8 Analysis of combined drug effects of Taxotere and PNP-GDEPT in PC cells: CI/Fa plots were generated based on Chou and Talalay’s method by plotting combination indices (CIs) for different combinations of Taxotere and PNP-GDEPT against the fraction affected (Fa). Synergistic effects are indicated for both PC-3 (Panel I) and for RM1 cells (Panel II) as most of CI values are significantly lesser than 1(CI<1) at almost all drug combinations. Dose reduction index values to achieve different levels of cell killings by combination treatments are tabulated in panel III (PC-3) and IV (RM1) for the two cell lines. Significant levels of individual dose reductions were predicted when these drugs were combined to achieve a specific effect Vs. doses when used alone. 287

Chapter 5: Combination Therapy for Prostate Cancer 288

In addition to evaluation of combinations at the ratio of 1:1, testing at other ratios e.g.

1:2, 2:1, 1:4, was also carried out (data summarised in Table 5.4). Overall, the trends

(CI and DRI values) were similar to those obtained when drugs were combined at 1:1 ratio with some variations (Table 5.4 and data not shown for DRI values). In conclusion, at all drug combinations, drug interactions were moderately synergistic at effective dose of 50 (i.e. ED50) and synergistic at ED75 and ED90 for both cell types.

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Table 5.4 A comparison between efficacies of drug combinations at different ratios in PC cells

Modalities Cell Line Combination index (CI value)1 R3 Effect4

GDEPT:Taxotere ED2 50 ED75 ED90

1:1 PC-3 0.6924 0.4648 0.3120 0.9954 At all ratios, effects

RM1 0.6069 0.3917 0.2726 0.9813 were moderately

1:2 PC-3 0.6378 0.4329 0.3485 0.9891 synergistic at ED50

RM1 0.5671 0.4309 0.3012 0.9721 (++) & synergistic

1:4 PC-3 0.6678 0.4540 0.3149 0.9870 at ED75 and ED90

RM1 0.6092 0.3306 0.3019 0.9759 (+++)

2:1 PC-3 0.5598 0.3259 0.2631 0.9901

RM1 0.6634 0.5185 0.3284 0.9824

1 2 Combination index values generated when drugs were plotted as constant ratios 1:1 e.g. IC25 of Taxotere with IC25 of carboplatin; ED:Effective dose, which can result in 50, 75 and 90% of cell killing; 3The linear correlation coefficient, R, of the median-effect plot. The acceptable range of ‘R’ values varies with the type of system used; Enzyme or receptor systems (r > 0.96), tissue culture systems (r > 0.90) and animal experiments (r > 0.85); 4Combination effects, CI value 0.90–1.10 signifies additivity (+); CI 0.7-0.85 moderate synergism (++); CI 0.85-0.9 slight synergies (+++) m; CI 0.30–0.70 synergism (++++); CI 0.10–0.30 strong synergism (+++++) and CI 0.01– 010 very strong synergism (++++++) 289

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5.2.7 Effects of different treatments on Apoptosis

M30 cytoDEATH antibody was used to quantitate cells undergoing early events of apoptosis in human PC-3 cells given different treatments. Cells were treated with

Taxotere (0.3 nM) and PNP-GDEPT (Ad/CMV/PNP moi of 150 pfu/cell plus 1g/mL

Fludara) either alone or in combination. Fludara (alone) treated cells were used as a control. Cells harvested after 2 days of treatment were immunostained with M30

CytoDEATH antibody and FACS analysis was performed. The apoptosis is represented by fraction of M30 positive cells and data analysed as mentioned in Section 4.2.1.

An increase in apoptosis was achieved with individual treatments and these were further enhanced when therapies were combined (Figure 5.9). Fractions (percentage) of M30 positive cells after 2 days of treatment with combination was the most (29 ± 5) followed by Taxotere (15 ± 2) and then PNP-GDEPT (11± 2) (Table 5.5). Apoptosis achieved in

Fludara (1g/mL) treated control cells was insignificant (1 ± 1).

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40 Fludara Alone GDEPT TAX TAX + GDEPT

P=0.0021 20 *

10 % of M30 Positive Cells Positive M30 of %

0 Day 2

Figure 5.9 Quantitative estimation of apoptosis in response to different treatments: PC-3 cells were treated with Taxotere (0.3 nM) and/or PNP-GDEPT (Ad/CMV/PNP moi of 150 pfu/cell plus 1g/mL Fludara). Cells harvested 2 days post-treatment were immunostained with M30 cytoDEATH antibody (detects early apoptosis) followed by FACS analysis. The percent of M30 positive cells represented apoptotic cell death. The combined use of therapies led to a significantly higher proportion of apoptosis in comparison to that obtained with either alone. Significance of the trends was calculated using one-way Anova using Dunnett’s multiple comparison test. “*” represents significance compared to Fludara treated controls. A P value < 0.05 was considered statistically significant.

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Table 5.5 Quantitative estimation of apoptosis in PC-3 cells in response to different treatments.

Time point Fludara GDEPT Taxotere GDEPT + alone alone alone Taxotere

% of M30 cytoDEATH antibody positive cells Day 2 1 ± 1 11 ± 2 15 ± 2 29 ± 5

Results shown are mean of three independent experiments (Mean ± SEM)

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5.2.8 Effects of PNP-GDEPT and/or Taxotere treatments on growth of subcutaneous PC-3M-luc-C6 tumours in nude mice

Effects of combination therapy (Taxotere and PNP-GDEPT) were evaluated on local tumour growth of subcutaneously (s.c) grown PC-3M-luc-C6 cell. The following steps were involved:

1. Evaluation of permissivity of PC-3M-luc-C6 cells to Ad transduction

2. Confirmation and evaluation of bioluminescence in PC-3M-luc-C6 cells in vitro

3. Evaluation of therapeutic effects of Taxotere and/or PNP-GDEPT on s.c PC-

3M-luc-C6 tumour growth

5.2.8.1 Evaluation of permissivity of PC-3M-luc-C6 cells to Ad transduction

This evaluation was done to determine the dose of Ad/CMV/PNP for in vivo experiments. Cells infected with moi of 10, 50, 100, 200 and 500 pfu/cell of

Ad/CMV/GFP were analysed for percentage of GFP expressing cells (after 24 hrs) using flow cytometry (i.e. FACS). GFP expression increased in a dose dependent manner with increasing moi of Ad/CMV/GFP (Figure 5.10). The permissivity of PC-

3M-luc-C6 was highest at the moi of 500 pfu/cell (% GFP expressing cells: ~81%) and the lowest at 10pfu/cell (% GFP expressing cells: ~6%) (Table 5.6).

Further, comparison with data for PC-3 cells showed that PC-3M-luc-C6 cells are more permissive than PC-3 cells (at moi of 100 only ~6 % GFP expression in PC-3 cells Vs.

~53% in PC-3M-luc-C6 cells, Figure 5.3, Section 5.2.3) for Ad infection. The moi of

~15 pfu/cell was selected for infecting PC-3M-luc-C6 to achieve 11-12% cell transduction efficiency for the in vivo study (Figure 5.10).

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Figure 5.10 Evaluation of efficiency of Ad-transduction in PC-3M-luc-C6 cells: To check the permissiveness of PC-3M-luc-C6 cells for Ad5 transduction, cells infected with Ad5/CMV/GFP were analysed for GFP expression after 24h by flow cytometry. The dot plots generated using FlowJo software are shown at different mois’ of Ad/CMV/GFP, GFP-fluorescence is shown on Y axis and forward scatter (cell distribution according to size) on X axis. GFP positive cells are represented in upper right quadrant. Cells showed a higher level of permissiveness to Ad virus in comparison to PC-3 cells.

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Table 5.6 Permissivity of PC-3M-luc-C6 cell for Ad infections

Viral dose of Ad/CMV/GFP moi : pfu/cells

500 200 100 50 10

% of GFP 81 69 53 30 6 Expressing cells*

* Estimated values from one experiment (Figure 5.10)

5.2.8.1.2 Evaluation of bioluminescence in PC-3M-luc-C6 (in vitro)

Prior to injections in mice, PC-3M-luc-C6 cells were checked for levels of bioluminescence. Briefly, cells plated at different cell densities in a 96 well plate were imaged using IVIS system® (1 min, binning at 10, Field of View (FOV) 15cm), approximately, 3 minutes after addition of luciferin (substrate for luciferase gene expressed by PC-3M-luc-C6 cells). The data plotted as Beer’s law graph (mean photons emitted/sec vs. cell numbers, Figure 5.10) showed a strong co-relation between cell number and bioluminescence (R2 = 0.9914). Further, the data showed that a minimum of 1000 cells are required to generate sufficient signal for visual detection.

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Cell Number 20,000 10,000 5,000 1,000 0

1.80E+07 B R2 = 0.9914 1.60E+07

1.40E+07

1.20E+07

1.00E+07

8.00E+06

6.00E+06

Mean Photons/ second 4.00E+06

2.00E+06

0.00E+00 0 5000 10000 15000 20000

Cell Number

Figure 5.11 In vitro bioluminescence in PC-3M-luc-C6 cells: The bioluminescent activity of cells was analysed after adding luciferin (substrate for luciferase) using Xenogen IVIS® system. Panel A shows bioluminescent image taken by Xenogen IVIS® system. The signal was quantified using Live Image® software (Xenogen) in terms of photons emitted/sec. Panel B: The graph shows photons emitted/sec with increasing number of cells. A strong co-relation between cell number and bioluminescence (R2 = 0.9914) was shown by Beer’s law equation.

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5.2.8.1.3 Evaluation of therapeutic effects of Taxotere and/or PNP-GDEPT on s.c

PC-3M-luc-C6 tumour growth

Cells infected at an moi of 15 pfu/cell of Ad/CMV/PNP (test virus) or Ad/CMV/GFP

(control virus) overnight were injected subcutaneously in the top right flank of BALB/c nude male mice. One day post-implantation, mice were treated according to experimental plan shown in Figure 5.12. Briefly, mice were injected intravenously (i.v.) with Taxotere on day 1, 6 and 12 (suboptimal dose of 10 mg/kg every four days, thrice)

(nude mice can tolerate upto 12.5 mg/kg/day if given every three days thrice (personal communication, Prof. Pamela J Russell). Fludara was administered intraperitoneally

(i.p.) for 5 consecutive days starting from day 1 to 5 (75 mg/metre2/day; dose established in previous studies (337). Keeping in mind the PC-3M-luc-C6 take rate of

90% in nuce mice the mice (according to experimental notes of commercial supplier,

Xenogen), from 8-11 mice were included in different groups. The treatment groups were as follows:

Group 1: Ad/CMV/GFP (n = 8)

Group 2: Ad/CMV/PNP + Fludara (PNP-GDEPT) (n = 9)

Group 3: Taxotere (n = 10)

Group 4: PNP-GDEPT + Taxotere (n = 11)

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Figure 5.12: The experimental plan for evaluation of different therapies in PC-3M-luc-C6 tumour bearing BALB/c nude mice

PC-3M-luc-C6 s.c. injection Group Name Treatments Number (n)

Control/ Vehicle Saline/Water for injection I 8

II Taxotere alone Taxotere (intravenous) 10 mg/kg on day 1, 6 and 12 9 Animals divided III PNP-GDEPT Fludarabine Phosphate (intraperitoneal) randomly into 2 alone 75 mg/metre /day for 5 days 10 four groups on day 1, 2, 3, 4 and 5 Day 1 2 Day 0 IV PNP-GDEPT plus Fludarabine Phosphate 75mg/ metre /day for 5 days on day (n=38) Taxotere 1, 2, 3, 4 and 5 + Taxotere 12.5mg/kg on day 1, 6 & 12 11

Tumor measurement using 6

bioluminescence (IVIS, Xenogen) 4

(Week 2, 3, 4 and 5) 2 Total Flux[Log(p/s)]Total

0 Xenogen IVIS 200 ) Control

3 1000 Docetaxel 800 GDEPT Combination Tumor measurement using 600

vernier calliper 400

(Day 5, 10, 15, 20, 25, 30 and 35) 200 Tumor volume (mm volume Tumor

0 0 5 10 15 20 25 30 Days

298

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The tumours became palpable (visible, ~5x5mm) at ~ two weeks post-implantation in control treated mice. Subsequently, tumour growth was monitored by bioluminescence based imaging (Xenogen IVIS® Lumina on week 2, 3, 4 and 5) and vernier callipers

(every 5 days till day 35). Overall, the bioluminescent data showed a strong correlation with manual tumour measurements. Tumour growth in response to different treatments is shown using both types of measurements (Figure 5.13, Table 5.7 and 5.8). The data obtained using Xenogen® system based imaging is represented as Mean Tumour

Bioluminescence (MTB) on day 35 (Table 5.7 and Figure 5.13 Panel A and C).

Although, a decrease in light emission (relative to tumour size) (Control MTB:

3.81+010 ± 7.92E+009; n = 7) was noted in Taxotere (MTB = 3.61+009 ±

1.124E+009; P < 0.001; n = 7) and PNP-GDEPT (MTB: 1.90E+009 ± 4.55E+008; P

< 0.001; n = 8) treated mice but the decrease in mice treated with combination therapy

(MTB: 3.11+008 ± 2.32E+008; P < 0.001; n = 3) was significantly higher.

Importantly, there was no detectable tumour growth in 8 mice in combination group with only 3/11 combination treated mice displaying visible tumours.

The trends observed using calliper based tumour measurements (Table 5.8) correlated well with those observed using bioluminescence data (Fig 5.13, panel B). At necropsy

(day 35), mice given the combination treatments showed the best efficacy (Mean

Tumour Volume (MTV) = 341 ± 123; P < 0.001; n = 11) both in terms of rate of growth and size of tumours in comparison with control treated mice (MTV = 1645 ± 179; n =7)

(Fig 5.13, panel B). As expected, only 3/11 combination treatment mice showed tumour growth. Tumour volumes in mice treated with Taxotere alone (MTV = 1003 ± 165; P <

Chapter 5: Combination Therapy for Prostate Cancer 300

0.001; n = 7) or PNP-GDEPT alone (MTV = 761 ± 145; P < 0.001; n = 8) were also significantly lower than those in control mice.

Note: The luminescence/calliper data in combination treated mice is given as an average of measurements from three mice only (Figure5.13 Panel A, B and C).

In addition, the weight loss, which is also a measure of treatment related toxicity, was not over 10% in any of the groups till day 35. However, some weight loss (~5-8% loss) was evident in Taxotere treated groups initially, but the differences were not significant and all mice recovered within next five days (Figure 5.14) (Note: mice were monitored/weighed everyday especially when being subjected to procedures). From day

30 onwards, there was a gradual decrease in mouse weights in the control group (mainly due to tumour burden). All mice were sacrificed at day 35. Importantly, although not significant, a clear trend towards weight gain was displayed by mice given the combination treatment from day 14 onwards suggesting a lack of overlapping toxicities and overall reduction in toxicity in these mice, especially, in comparison to individual treatment groups.

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5.0E+10 A C P<0.001 Control Bioluminescence (IVIS image) Taxotere 6.0E+09 PNP-GDEPT Control * Combination 4.0E+09

Photons/ second Photons/ 2.0E+09 * GDEPT

Mean Tumour Bioluminescence

B Taxotere 1800 Control P=0.0023 ) 3 Taxotere 1500 GDEPT 1200 Combination 900 Combination 600

Tumor volume (mm 300

0 0 7 14 21 28 35 Days

Figure 5.13 The effects of combination therapy on s.c PC-3M-luc-C6 tumours in BALB/c nude mice: Nude mice were injected subcutaneously with PC-3M-luc-C6 cells infected with Ad/CMV/PNP at an MOI of 15 such that only ~10-15% of the cells were expressing. The prodrug, Fludara was given intraperitoneally at 75mg/kg for five days and Taxotere was given at 10mg/kg thrice at day 1, 6 and 12. Mice given Ad/CMV/GFP expressing tumours served as the controls. The growth of luciferase expressing tumours was monitored by imaging using Xenogen IVIS Lumina® regularly every week and by measuring the tumours using callipers. Panel A shows the light emission (photon-flux (photons/s/cm2/steradian (steradian is a unit of solid angle) measured on day 35 and Panel B represents the tumour volumes (calliper measurements) at different times during the course of experiment. Panel C shows the visual bioluminescent images of mice with tumours given different treatments on week 5. Mice given the combination treatments showed the best efficacy, rate of growth and size of tumours was the minimum in these mice. 301

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Table 5.7 Effects of treatments on growth of s.c PC-3M-luc-C6 tumours in BALB/c nude mice (Mean Tumour

Bioluminescence (MTB)

Control Taxotere PNP-GDEPT Taxotere + PNP-GDEPT

Avg. St dev. Number Avg. St dev. Number Avg. St dev. Number Avg. St dev. Number

3.81+010 7.92E+009 7 3.61E+009 1.124E+009 7 1.90E+009 4.55E+008 8 3.11E+008 2.32E+008 3*

* Average is from three mice as other mice did not grow tumours.

302

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Table 5.8 Effects of treatments on growth of s.c PC-3M-luc-C6 tumours in BALB/c nude mice (Mean Tumour Volume (MTV)

Days Control (n=7) Taxotere (n=7) GDEPT (n=8) Combination (n=11)

Mean Tumour volume (MTV, mm2) Standard deviation

14 33156 24487 17698 10256

21 812128 624104 456115 291105

28 1013147 75498 567121 30395

35 1645179 1003165 761145 341123 303

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100

5-8% loss in Tax otere groups Gradual decrase in contol group(2-11%)

Control 50 PNP-GDEPT Taxotere GDEPT+Taxotere Mouse weight (Normalised to 100) to (Normalised weight Mouse Mice weight (Normalised to 100) Days 0 0 1 2 3 4 5 6 7 8 12 13 14 18 21 25 28 31 35

Fludara Harvest Taxotere Taxotere Taxotere PC-3M-luc-C6

Figure 5.14 Relative body weight changes in treated and un-treated PC-3M-Luc tumour bearing BALB/c nude mice: The tumour bearing mice given different treatments were weighed every 2-3 days during the course of the experiment. Graph shows the weight changes through the course of experiment in mice given different treatments. There were almost negligible toxicities associated with any treatment. A gradual decrease in mouse weights was noted when tumours in control group reached to ~15X15mm (day 35). Mice were sacrificed at this stage. Although, not significant but mice in the combination group displayed a gradual increase in weight from day 14 onwards

Chapter 5: Combination Therapy for Prostate Cancer 305

5.2.9 Effects of PNP-GDEPT on RM1 tumour growth in immunocompetent C57BL/6 mice

Synergy is truly shown if treatments given at otherwise suboptimal doses lead to enhanced efficacy. Since the ultimate aim of this study was to evaluate the combination effects of PNP-GDEPT and Taxotere, initially, to determine a suboptimal dose for future synergy experiments, a preliminary study was carried out to examine the therapeutic effects of different doses of PNP-GDEPT in RM1 tumours in mice. Studies done in our laboratory have clearly shown the successful use of RM1 prostate cancer model to test various forms of anticancer therapies (337,339,631,632,642,649,963).

These studies have also shown the successful use of Adenoviruses to deliver therapeutic genes in intraprostatic RM1 prostate tumours (337,339,631,632,642,649). Further, the highest non-toxic therapeutic dose of the prodrug, Fludara in C57BL/6 mice was established in these studies at 600 mg/metre2/day for 5 days (337,338).

Hence for this study, Adenoviral vector (Ad/CMV/PNP) was employed to deliver the suicide gene PNP. To establish the anticancer effects of PNP-GDEPT on local and metastatic tumour growth, mice were implanted iprost with RM1 cells and injected with

109 PFU of Ad/CMV/PNP on day 5 post implantation. On day 6, same mice were also injected i.v with RM1 cells to establish lung pseudometastates. The dose of PNP-

GDEPT was varied by systemic administration of Fludara at three different suboptimal doses of 100, 200 and 300 mg/metre2/day for 5 consecutive days (based on studies done in our lab and in other studies (337,338). Treatments groups included:

Group 1 Adenovirus alone (control) (n = 4)

Group 2 PNP-GDEPT (100 mg/metre2/day for 5 days) (n = 5)

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Group 3 PNP-GDEPT (200 mg/metre2/day for 5 days) (n = 5)

Group 4 PNP-GDEPT (300 mg/metre2/day for 5 days) (n = 5)

At necropsy (day 16), the harvested tumours and lungs were weighed and measured.

Comparisons of treatment groups verses the control virus alone/Fludara treated showed a significant difference in tumour growth among these groups (P = 0.0354).

Effects on local prostate tumour growth: The effects on local prostate tumour growth

(Figure 5.15, Panel B) were the best at the highest dose of Fludara tested (lowered by half in comparison to that used previously in our lab and other studies). Interestingly, local tumour growth in groups treated with lower doses of Fludara (100 and 200 mg/metre2/day) was higher compared to virus alone. In conclusion, PNP-GDEPT achieved a significant tumour regression at the highest dose of Fludara used in this study.

Effects on systemic RM1 tumour growth: The lung weight measurements showed that the systemic efficacy was higher only at the highest dose of PNP-GDEPT (Fludara at 300 mg/metre2/day) in comparison to lower doses (Figure 5.15, Panel A (P =

0.0138). Lung colony data further reinforced this trend (Figure 5.15, Panel C (P =

0.0854).

On the basis of PNP-GDEPT effects on local and metastatic tumour growth, Fludara dose of 250 mg/ metre2 was chosen for PNP-GDEPT in combination studies to achieve suboptimal effects.

Chapter 5: Combination Therapy for Prostate Cancer 307

P=0.0354 A B P=0.0138 1.0 5

0.8 4

3 0.6

* 2 0.4 Lung mass (grams) mass Lung Tumor MassTumor (grams) 1 0.2

0 0.0 e T T T e T T T P P P lon E lon s a a DEP u us 0 GDE 0 GD GDEP GDEP Vir 30 20 100 GDE Vir 300 G 200 100

P=0.0854 Figure 5.15 Effects of different doses of PNP-GDEPTC on C 600 RM1 tumours growing in the prostate or in the lungs in C57BL/6 mice: Tumours grown intraprostatically in mice were injected with 109 PFU of Ad/CMV/PNP and then systemically 400 treated with Fludarabine Phosphate at 100, 200 and 300 mg/metre2/day for 5 days. At necropsy, day 16, the harvested tumours were weighed/measured, lung were weighed and stored 200 for lung colony counting. Other organs and sera stored for other colonies of Number analyses. The effects on local prostate tumour growth (Panel A) 0 were the best at the highest dose of Fludara tested (lowered by e n T T T half in comparison to that used previously in our lab and other lo P P P s a u GDE GDE GDE studies). Systemic efficacy (Panel B and C) was also the best r 0 0 0 Vi 30 20 10 when highest dose of Fludara was used (300 mg/metre2/day).

The dose of 250 mg/ metre2 was chosen for combination studies.

307

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5.2.10. Effects of Taxotere alone on RM1 tumour growth in vivo

The efficacy of different doses of Taxotere on tumour growth was evaluated in mice with orthotopic RM1 tumours and on lung RM1 pseudometastases. The main objective of the experiment was to determine the suboptimal dose of Taxotere for combination therapy assessments. Briefly, RM1 tumour bearing mice were injected with 10, 15 and

20 mg/kg of Taxotere intravenously at two different time points (day 7 and 12). At necropsy (day 16), the harvested tumours and lungs were weighed/measured.

Treatments groups included:

Group 1 Control (vehicle) (n = 6)

Group 2 Taxotere (10mg/kg) (n = 6)

Group 3 Taxotere (15 mg/kg) (n = 6)

Group 4 Taxotere (20 mg/kg) (n = 6)

Although, all three doses achieved significant tumour regression (P = 0.0268), the effects were more pronounced at the higher doses of 15 and 20 mg/kg (Vs. 10 mg/kg) of

Taxotere (Figure 5.16 Panel A). The systemic efficacy of Taxotere was evaluated based on its effects on growth of lung pseudometastases (lung mass and lung colony count).

The lung mass/lung colony data showed no obvious differences between treated and untreated mice (Lung mass, P = 0. 9612; Lung colony, P = 0.8786 Figure 5.16: Panel B and C), which signifies that at the doses used, Taxotere did not have an impact against metastatic PC in these mice.

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Overall, an assessment of treatment related toxicity based on changes in mice weights before and after drug administration did not show any differences in mice in all treatment groups (data not shown). However, a marginal weight loss was occasionally observed in some mice at the highest dose of 20 mg/kg but mice recovered within 2-3 days after drug administration. Mice in groups treated with 15 mg/kg, and 10 mg/kg of

Taxotere or treated with vehicle/control (the corresponding concentrations of poly

80/ethanol used in diluting 20 mg/kg Taxotere) did not display any weight loss.

Based on these data, a dose of 12.5 mg/kg of Taxotere (an intermediate dose between 15 and 10 mg/kg) was chosen for combination experiments.

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A B P=0.9612 P=0.0268 1.0 5

0.8 4

* 0.6 3 *

2 0.4 Lung mass (grams) Tumor MassTumor (grams) 1 0.2

0 0.0 e e r r le re tere tere te ehic Vehicle V axo xo axo Taxote Taxotere Taxote T 20 15 10 20 15 Ta 10 T

Figure 5.16 Effects of different doses of Taxotere on P=0.8786 RM1 tumours growing in the prostate or in the lungs C 400 in C57BL/6 mice: Tumours grown intraprostatically in mice were injected with 10, 15 and 20 mg/kg of Taxotere 300 intravenously twice at 4 days interval. At necropsy, day 16, the harvested tumours were weighed/ measured, lung 200 were weighed and stored for lung colony counting. Other organs and sera stored for other analyses. The effects on 100 Number of colonies of Number local prostate tumour growth were the best at the higher doses of Taxotere, 15 and 20 mg/kg (Panel A). However, 0 e re as shown by lung mass/lung colony data Taxotere was not icle e h oter t able to induce any systemic effects at all doses used Ve ax axo T T (Panel B and C). A dose of 12.5mg/kg was chosen for 20 15 10 Taxotere combination experiments. 310

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5.2.11 Effects of combination therapy on RM1 tumour growth in vivo

To evaluate the potential benefit of combination therapy of PNP-GDEPT and Taxotere, treatments were given at suboptimal doses (established in optimisation experiments;

Sections 5.2.9 and 5.2.10). A complete schematic showing the plan of this study is shown in Figure 5.17. Briefly, on day 0, mice were implanted iprost with RM1 cells followed by an i.v injection of RM1 cells on day 6 to form lung pseudometastases. On day 5, the prostate tumours were injected with 109 PFU of either Ad/CMV/PNP or

Ad/CMV/GFP (control virus) followed by systemic administration of Fludara at 250 mg/metre2/day for 5 consecutive days. Taxotere was administered at 12.5 mg/kg/day on day 7 and 12. At necropsy (day 16), the harvested tumours and lungs were weighed and measured and stored for different analyses.

The treatment groups included;

Group 1 PNP-GDEPT alone (n = 9)

Group 2 Taxotere alone (n = 9)

Group 3 PNP-GDEPT plus Taxotere (n = 9)

Group 4 Taxotere plus Fludara (n = 8)

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Figure 5.17: Experimental plan for Taxotere and PNP-GDEPT combination therapy in C57BL/6 animal (RM1 model)

Group Name Treatments Number (n)

I PNP-GDEPT Fludarabine Phosphate (intraperitoneal) alone 250mg/ metre2/day for 5 days 9 on day 7, 8, 9,10 and 11 RM1 iprost Animals divided randomly into four II Taxotere alone Taxotere (intravenous) groups on day 1 12.5mg/kg on day 7 and 12 9

III PNP-GDEPT Fludarabine Phosphate 250mg/ metre2/day for 5 plus Taxotere days on day 7, 8, 9,10 and 11+ Taxotere 9 (combination) 12.5mg/kg on day 7 and 12

IV Taxotere plus Fludarabine Phosphate 250mg/ metre2/day for 5 Fludarabine days on day 7, 8, 9,10 and 11 + Taxotere 8 Phosphate 12.5mg/kg on day 7 and 12

day 1 (n=37)

Day 0 Day 5 Day 6 Day 7 Day 16

Iprost Inject with Ad RM1 cells (i.v) Fludarabine and Harvest Analyses implantation expressing PNP for lung Taxotere treatments •Lungs •Tumor volume/weights of RM1 cells or GFP pseudo- (day 7 onwards) •Prostate tumors •Lung colony count/mass metastases •Draining lymph nodes •Immunohistochemical •Serum •Cytokine profile 312

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Effects of combination treatment on Local prostate tumour growth: The data clearly showed the enhanced efficacy of combining PNP-GDEPT and Taxotere on local prostate tumour growth compared with either alone or a combination of Taxotere and

Fludara (Figure 5.18 Panel A). Comparisons of treatment groups showed a significant difference in the prostate tumour growth (P = 0.0354); negligible to very little tumour growth in 5 out of 9 combination treated mice compared to 3 out of 9 in Taxotere treated group and only one mouse in PNP-GDEPT alone- (1/9) or Taxotere plus Fludara treated group (1/8) was noted.

Effects of combination treatments on growth of RM1 lung pseudo-metastases:

To evaluate the systemic effects of combined therapy, lung colonies were counted and lung weights were measured in mice given different treatments at necropsy. Mice treated with PNP-GDEPT + Taxotere showed a clear reduction in lung colonies compared with those receiving either (i.e. PNP-GDEPT or Taxotere alone or

Taxotere/Fludara) (P = 0.0097, Figure 5.18 Panel C). In combination treated mice, less than 50 colonies were noted in 4 out of 9 mice compared to 1 out of 9 in PNP-GDEPT treated mice. As seen in dose optimisation experiments (see Sections 5.2.9 and 5.2.10), a negligible reduction was seen in Taxotere treated mice, however, a significant reduction in number of lung colonies was achieved with PNP-GDEPT treatments (P =

0.0356). The trend shown in lung colony count data was further reinforced by lung mass measurements (P = 0.008) (Figure 5.18 Panel B). Notably, a marked reduction in lung weight was seen in combination treated mice compared to PNP-GDEPT alone group.

There were no effects on lung tumour growth in (lung mass/ colony count) in mice treated with Taxotere alone or Taxotere/Fludara.

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In conclusion, combination of PNP-GDEPT and Taxotere led to a significant reduction in growth of intraprostatic RM1 tumours and lung pseudometastases showing a dramatic improvement in both local and systemic therapeutic effects.

Chapter 5: Combination Therapy for Prostate Cancer 315

P=0.0354 5 A B

4 600 3 *

2 400 P=0.0097 Tumor MassTumor (grams) * 1

0 re 200 xotere * e Alone a axote T Alone r T T P + + E a D xote G

Ta colonies of number App. ludar GDEPT F 0 P=0.0008 e 1.25 one ne ere oter l lo t C A A ax re 1.00 +T te ara xo DEPT * d G Ta DEPT+Taxo 0.75 Flu G

0.50 Figure 5.18 Effects of combination of PNP-GDEPT and Taxotere treatments on

Lung mass (grams) RM1 tumour growth in C57Bl/6 mice: Tumours grown intraprostatically in mice 0.25 were injected with 109 PFU of Ad/CMV/PNP and then systemically treated with Fludarabine Phosphate at 250 mg/metre2/day for 5 days. Docetaxel was given at 0.00 12.5mg/kg twice on day 7 and 12. At necropsy, day 16, the harvested tumours were re xote weighed/measured, lung were weighed and stored for lung colony counting. Other e Alone er EPT Alone a+Ta D xot organs and sera stored for other analyses. The effects on local prostate tumour growth G Ta dar lu GDEPT+Taxotere F (Panel A) were the best in mice given the combination regimen in comparison to mice given Fludara + Taxotere. Systemic efficacy was also the best in mice given the

combination treatment (Panel B and C). 315

Chapter 5: Combination Therapy for Prostate Cancer 316

5.2.12 Analysis of treatment related toxicity in C57BL/6 mice (RM1 model)

The major issue in development of combination-based regimens is the possibility of combined additive toxicity. An ideal combination is expected to have an enhanced antitumour activity without the same extent of increase in toxicity.

The physical well being of the host given any treatment is dependent upon the complex interactions between dose intensity, exposure time and the resultant toxicity (Figure

5.19). Based on this, an evaluation of potential toxicities of the treatments used in this study was done in treated mice. Given that the liver and kidneys are the primary organs that expel toxins that result from the body's metabolism, and effects of any treatment on their function would be a critical parameter in evaluation of the risks involved, the treatment related effects were tested in relation to kidneys (renal toxicity) and liver

(hepatotoxicity). Hence, the biochemical markers of kidney function, Urea and creatinine and markers of liver function, alkaline phosphatase (ALP) (to assess cholestatic injury), alanine aminotransferase (ALT) (specific to liver, to assess hepatocellular injury) were assessed in the sera of mice given various treatments. The data showed that values for all markers from all treatment groups were within the range for untreated age matched healthy control. Hence, no renal or hepatotoxicity were evidenced due to any of the treatments (Table 5.9).

Further, the toxicity was also assessed through regular monitoring of mice through the course of experiment based on clinical measures such as lethargy, poor responsiveness to stimulus, weight loss, and death. Monitoring of weights of mice in different

Chapter 5: Combination Therapy for Prostate Cancer 317 treatments groups in general did not show any significant differences in weights through the course of experiment (Figure 5.20). However, while not significant, a gradual decrease in mouse weights was noted in some mice from PNP-GDEPT and Taxotere group (mainly due to loss of condition due to tumour burden) from day 13 to 16. The general condition of mice given different treatments also did not vary significantly between groups.

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Figure 5.19 Toxicity analysis in mice treated with Taxotere/PNP-GDEPT either alone or in combination

Toxicity Analysis: Treated Vs untreated mice

Liver and kidney function

Toxicity Dose

Animal weight Exposure 318

Chapter 5: Combination Therapy for Prostate Cancer 319

Table 5.9 Serum analyses for biochemical markers of kidney and liver function in treated vs. untreated mice

Treatments Kidney function markers Liver function markers (Renal toxicity) (Hepatotoxicity)

Urea Creatinine ALP1 ALT2 (mmol/L) (mol/L) (U/L) (U/L)

Reference range3 8.3-8.84 8-28 42-157 30-31

Adenovirus alone (n=4) 6.4 ± 1.3 21.3 ± 3.8 41.5 ± 12.7 22.3 ± 5.6 PNP-GDEPT alone (n=4) 8.4 ± 1.3 18.5 ± 3.2 34.0 ± 6.2 26.0 ± 2.8

Taxotere alone (n=6) 17.8 ± 4.1 17.8 ± 2.1 46.8 ± 8.2 23.8 ± 3.0 GDEPT + Taxotere (n=4) 7.8 ± 0.9 16.8 ± 3.3 61.0 ± 31.2 30.5 ± 3.5 Taxotere +Fludara (n=4) 6.3 ± 0.7 13.8 ± 1 43.3 ± 14.8 25.8 ± 4.3

1ALP: alkaline phosphatase; 2ALT: alanine aminotransferase; 3 The reference represents the corresponding values for a normal healthy mouse (without tumour); 4 The values represented are Mean ± Standard deviation; 319

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100

PNP-GDEPT Taxotere 50 GDEPT+Taxotere Taxotere+Fludara Mouse weight (Normalised to 100) Mice weight (Normalised to 100) to (Normalised weight Mice Days 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Fludara iprost iprost st Harvest RM1 i.v nd 1 Taxotere Taxotere 2

Figure 5.20 The relative body weight changes in treated and un-treated RM1 tumour bearing C57BL/6 mice: The tumour bearing mice given different treatments were weighed every single day during the course of the experiment. There were almost negligible toxicities associated with any treatment. While not significant, a gradual decrease inmouse weights was noted in some mice from PNP-GDEPT and Taxotere group (mainly due to tumour burden) from day 13 to 16. Mice were sacrificed at day16.

Chapter 5: Combination Therapy for Prostate Cancer 321

5.2.13 Impact of combination therapy on animal survival

The long-term effects of combination therapy were evaluated through assessment of treatment effects on mouse survival. The study design was as mentioned in Section

5.2.11 but this time the mice were not implanted with i.v. RM1 cells to produce lung pseudometastases.

Treatment groups for this experiment:

Group 1 Virus alone (n=9)

Group 2 Taxotere plus Fludara (n=9)

Group 3 Taxotere alone (n=9)

Group 4 PNP-GDEPT alone (n=10)

Group 5 PNP-GDEPT plus Taxotere (n=15)

Kaplan Meier’s survival curve analysis indicated a statistically significant survival advantage by 60% in mice given the combination of PNP-GDEPT and Taxotere in comparison to mice given control treatment (Figure 5.21) (P < 0.0001, Mantel-Cox rank test). At 25 days, % of surviving mice was more than 60% in combination treated mice

Vs only 10% in PNP-GDEPT treated group and none in the rest. The median survival of these mice was 25 days compared to those given PNP-GDEPT (19 days) or Taxotere +

Fludara (18 days) or Taxotere (18 days) or virus alone (15 days) (Figure 5.21 Panel B).

Chapter 5: Combination Therapy for Prostate Cancer 322

A B

100 Treatment Groups Median Survival Vi rus Al one 90 Tax+Fludara 80 Tax alone Virus Alone 15 70 PNP-GDEPT Taxotere + Fludara 18 60 Tax+PNP-GDEPT p < 0.0001 50 Taxotere Alone 18 40 %Survival 30 PNP-GDEPT Alone 19 20 Taxotere + PNP-GDEPT 25 10 0 0 5 10 15 20 25 30 35 40 Days

Figure 5.21 Survival of RM1 tumour bearing C57Bl/6 mice given different treatments: Tumours grown intraprostatically in mice were injected with 109 PFU of Ad/CMV/PNP and then mice were systemically treated with Fludara at 250 mg/metre2/day for 5 days. Taxotere was given at 12.5mg/kg twice at 5 days interval. Mice were monitored until euthanasia (due to loss of > 20% weight or loss of condition). The Kaplan Meier’s analyses of survival show the best survival for combination treated mice with 60% better survival compared to the control mice (Panel A). The median survival for tumour bearing mice given combination treatment was also the highest (25 days Vs. 15 for the control group) (Panel B) (P < 0.0001, Mantel-Cox rank test). 322

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5.2.14 Immunohistochemical analysis of apoptosis and immune infiltration of RM1 tumours

The success of various anticancer therapies is dependent upon apoptotic tumour cell death and augmentation of favourable immune response against the tumour. An immunohistochemical analysis was performed to establish the role of apoptosis and infiltration of immune cells in tumours treated with different modalities (Figure 5.22 and Table 5.10).

Immune infiltration: Evaluation of the effects of different treatments on immune cell infiltration in local RM1 tumours revealed that the combination (Taxotere + PNP-

GDEPT) therapy led to a greater tumour infiltration by Cytotoxic T Lymphocyte

(CD8a+T) (P = 0.1349; 2.25 fold) and macrophages (F4/80+) (P = 0.0457, 1.3 fold)

(Figure 5.22, Table 5.10) Vs controls. The effects generated were substantially greater than that observed in tumours given either Taxotere or PNP-GDEPT alone. Although not significant, a higher level of T helper cell (CD4+) infiltration was also noted in combination treated tumour sections compared to Taxotere or PNP-GDEPT alone (P =

0.1661).

Apoptosis: Apoptosis is one of the key features of GDEPT/Taxotere mediated cell death. Hence, levels of apoptosis in treated tumours were assessed. Similar to the immune infiltration trends, a significant increase in apoptotic cells (M-30 cytoDEATH positive) was noticed in combination treated group (P = 0.0218) (Fig 5.22, Table 5.10) compared with all other groups. Surprisingly, despite notable anti-tumour efficacy, almost negligible apoptotic cells were noted in tumours treated with either PNP-GDEPT or Taxotere alone.

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Table 5.10 Immunohistochemical analyses of RM1 prostate tumour sections showing effects of different treatments on tumour infiltration by immune cells and apoptosis

Treatments Immunohistochemical scores1 ± SEM2

T helper cells Cytotoxic T Lymphocyte Macrophages Apoptosis (CD4+) (CD8a+) (F4/80+) (M30+)

Adenovirus alone 106 ± 47 40 ± 9 176 ± 58 152 ± 75

PNP-GDEPT alone 13 ± 6 26 ± 5 76 ± 21 2 ± 1

Taxotere alone 16 ± 4 9 ± 2 69 ±42 1 ± 1

GDEPT + Taxotere 68 ± 37 90 ± 43 233 ± 20 188 ± 34

Statistical significance 0.1661 0.1349 0.0457 0.0218

(P value; one-way ANOVA)

1 After initial scanning under x100 magnification, positive stained cells in ten fields under x400 (0.15 mm2) magnification were counted and the mean number/high power field (HPF + SEM) was determined; 2 SEM: Standard error of the mean. 324

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Adenovirus Alone PNP-GDEPT Alone Taxotere Alone GDEPT plus Taxotere

CD4+

CD8a+

F4/80+

M30+

x10 x40 x10 x40 x10 x40 x10 x40 Magnification

Figure 5.22 Effects of different treatments on tumour infiltration by immune cells and apoptosis in intraprostatic RM1 tumours: The images display the extent of infiltration by T cells (CD4+, CD8a+), macrophages (F4/80+) and apoptosis (M30 CytoDEATH) in RM1 tumours in mice treated with different modalities. Each treatment panel shows a representative 10x and 40 x-magnified images. The positive cells were scored through light microscopy; after initial scanning under 100x magnification, positive stained cells in 10 fields under 400 (0.15 mm2) magnification were counted and the mean number of stained cells/high-power field (FSE) was averaged over 10 fields. The results show an increased infiltration of immune cells (CD4+, CD8a+, F4/80+) in mice treated with a combination of GDEPT and Taxotere. Similarly, an increase in the apoptotic cells (M30+ cells) was also noticed in combination group. 325

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5.3 Discussion

Previously, combination therapy of Taxotere, and PNP-GDEPT led to a significant synergistic antitumour activity against OC (Chapter 3) and modulations in apoptosis pathways were found to be involved in the cytotoxicity resulting from these interactions

(Chapter 4). The data clearly showed the ability of combining these two modalities to target a range of phenotypes (represented by cell lines included in the study) and hence, a larger and more heterogeneous population of cells. Therefore, to target PC heterogeneity, the potential application of combination of PNP-GDEPT and Taxotere was tested against androgen insensitive human and murine PC, both in vitro and in vivo.

Although, the tricombination involving carboplatin were the most effective against OC cells (Chapter 3), this was not tried for this study as platinum compounds do not have a wide spread application in PC treatment (965). Additionally, since PNP-GDEPT is approved for a phase I trial and Taxotere is the only drug, which has showed a survival benefit in patients with CRPC, combined use of these two agents would be a realistic approach that can be quickly translated to the clinic (Chapter 1).

We are the first to show in vitro and in vivo synergistic interactions between PNP-

GDEPT and Taxotere against late stage PC. The synergies were obtained against PC cell lines representing late stage androgen depletion resistant human (PC-3) and murine

(RM1) PC. Importantly, the efficacy of synergy in Ad-refractory and Taxotere resistant

RM1 cells was unequivocally shown in vitro as well in vivo. A clinically relevant value, dose reduction index was generated that predicted up to 6 fold reductions in individual doses when the two modalities were used in combinations to achieve a certain effect.

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This has clinical significance especially, in context of side effects and patient management. In addition to the in vitro evidence, the potential of individual dose reduction in the combination regimen was also proven in immunocompetent mice with orthotopic and pseudometastatic lung PC; despite the sub-optimal doses used, the efficacy of combination far exceeded those observed with either alone. More importantly, there was no evidence of additive toxicity (toxicology, liver and kidney function and weight loss), in fact the trends showed that the weight reduction seen in individual regimen groups was not seen in the combination treated mice. Significantly, this was more obvious in nude mice with PC-3M-luc-C6 tumours. The data also indicated enhanced involvement of apoptosis (in vitro and in vivo) and immune stimulation (immune cell infiltration) when the modalities were combined. Enhanced immune infiltration is indicative of possible generation of systemic antitumour host immune responses and this was confirmed by long term survival benefits in combination treated mice which was significantly more than that obtained with either regimen; on day 20, 90% of combination treated mice were surviving Vs. none in the control treated group (P < 0.0001).

The fact that this synergy was effective against PC in immunodefficient as well as immunocompetent mice suggests that the combination therapy may be effective in severely immunocompromised patients. Efficacy of PNP-GDEPT has been shown in both xenogeneic PC-3 and syngeneic RM1 models by others and in studies done in our laboratory (334,335). That both cell types are sensitive to Taxotere, albeit to variable levels was clear from the in vitro analyses (Figure 5.2 and Table 5.2). Taxotere cell sensitivity of androgen insensitive PC-3 cells has already been shown in various studies

Chapter 5: Combination Therapy for Prostate Cancer 328

(514,554,966-969) and IC50 of Taxotere obtained in this study was comparable to that reported in literature (517,966-968). The in vivo data further confirmed the responsiveness of RM1 cells to Taxotere treatment (see Section 5.2.10 and and 5.2.11).

Our data and other studies have clearly shown the responsiveness of RM1 and PC-3 tumours to PNP-GDEPT. The moderate to almost Ad refractory nature of PC-3 and

RM1 lines (334,335,339) (see Figure 5.3 and 5.10 ) not only provided a good range of phenotypes but also offered an optimal window to evaluate PNP-GDEPT bystander effects which were clearly shown in vitro and in both in vivo models (see Sections 5.2.6,

5.2.8 and 5.2.11). Given the potential toxicities of systemically given Fludara (970) dose optimisation was done on the basis of variable Fludara doses rather than local

Ad/CMV/PNP dose (Ad dose used in this study are midrange and does not lead to any systemic toxicities based on our experience and other studies (336,971). In this study, the dose in nude mice (75 mg/metre2/day for 5 days) is only ~ 3 times higher and in

C57BL/6 mice (highest 300 mg/m2/day for 5 days) is ~12 times greater than that given to humans (25-30 mg/metre2/day for 5 consecutive days) (972). This is still well within the acceptable range given the high tolerance of mice to this drug; mice have fludarabine tolerance around 45 times higher than man (due to lower body distribution of deaminase and phopsphorylation enzymes that metabolise Fludarbine Phosphate

(339,973,974). Further, the highest dose used in this study was 2 fold lower than that used in previous studies done in our lab which used Fludara at 600 mg/metre2/day for 5 consecutive days with insignificant toxicities (337,338).

Chapter 5: Combination Therapy for Prostate Cancer 329

It appears as though the efficacy of PNP-GDEPT is depending on a fine balance between systemic toxicity/immunosuppressive effects of Fludara (proven previously

(970,975)) and curative effects of the GDEPT. The fact that local tumour growth in mice receiving 100 and 200 mg/metre2/day doses was greater than that observed for control mice suggested that Fludara at low levels may be incurring a proliferative effects on growth of tumour cells and rates of proliferation may be far exceeding the rates of apoptosis. Indeed the immune infiltration and apoptosis were lower/almost negligible in PNP-GDEPT treated groups. Given that stimulation of immune system is strongly implicated in efficacy of PNP-GDEPT, it is possible that below a certain dose levels the toxicity of Fludara to circulating immune cells may lead to lowered antitumour responses systemically and locally within the tumour microenvironment, thus giving a survival advantage to tumour cells and faster growth rates of these tumours.

Hence, it is likely that plasma concentrations of Fludara must be maintained above a critical minimum value to get therapeutically effective levels of the metabolites within the tumour mass (976). Importantly though, a suboptimal dose of PNP-GDEPT together with Taxotere overcame this effects and led to an enhancement of apoptosis and immune infiltration in local tumours, which was clearly reflected in significant reductions in tumour growth locally and systemically.

One of unexpected observation was that despite being given systemically, Taxotere was effective only against local tumour growth. Systemic efficacy was not seen at all doses used, this was confirmed in the combination study when Taxotere was used alone at

12.5 mg/kg. The dose of 10-12.5 mg/kg was chosen for combination studies (in nude and C57Bl/6 mice) as it was suboptimal (i.e. expected to yield intermediate effects)

Chapter 5: Combination Therapy for Prostate Cancer 330 based on our assessments and a dose of 10mg/kg has been shown to be the most appropriate when designing antitumour efficacy or drug interaction studies in mice as the plasma concentration falls within the range that is clinically relevant (same for humans given 75-100 mg/m2) studies (977). The reasons for lack of systemic efficacy at all doses are unclear, it is possible that relatively greater resistance of RM1 cells and toxicity of Taxotere to circulating immune cells led to lowered systemic effects. Further, relatively short half life of Taxotere in mice may have led to lowering of initially high

(upto 45 min) plasma levels to fall below the toxic threshold (977). Given that mice were given only two doses every 4 days, it is possible that between the two doses, the threshold level of the drug was too low to overcome systemic growth of tumours.

However, within the tumour, due to relatively lower penetration of drug into the tumour mass the toxicity to infiltrating immune cells may be lowered and an interaction with infiltrating immune cells (immune cells were noted in these tumours although to a lesser extent than in combination treated tumours) may have contributed its efficacy. It has been shown previously that docetaxel penetration within the experimental tumours depends upon the plasma levels reached shortly after administration (978,979). Further other factors within tumour microenvironment such as greater toxicity to stromal cells

(980) may have enhanced the localised anti-tumour effects.

Similar to the RM1 model, suboptimal doses of PNP-GDEPT (Ad/CMV/PNP at moi to generate 10-12% transduction) and Taxotere (at 10 mg/kg thrice every 4 days Vs 12.5 used earlier in our laboratory) were used against PC-3M-luc-C6 luciferase-expressing tumours in nude mice. Use of PC-3M-luc-C6, a luciferase-expressing cell line as a tumour model provided a sensitive and non-invasive monitoring of s.c growth of tumours (498,761). A strong correlation between bioluminescent signals and cell

Chapter 5: Combination Therapy for Prostate Cancer 331 viability/tumour size suggested the reliability of imaging based monitoring. Bystander effects due to PNP-GDEPT were obvious from delayed tumor growth in GDEPT treated mice despite only 10-12% of cells expressing PNP. Despite the lack of adaptive immune system (implicated in immunocompetent RM1 model) a dramatic reduction in rates of tumor growth was seen in combination treated animals with no tumor growth in

~70% of the mice in this group. This suggested that this synergy may be effective in immunocompromised patients as is often the case in patients undergoing chemotherapy.

Especially, with docetaxel, one of the major side effects is neutropenia (loss of circulating white blood cells) and Fludara is associated with immunosuppression mediated via profound lymphopenia (abnormally low level of lymphocytes). The efficacy in nude mice is also indicative of involvement of interactions other than those involving adaptive immune system when combination therapy was used. It is possible that enhancement of docetaxel sensitivity of Ad-transduced PC-3 cells may have contributed to the synergistic enhancement of combined cytotoxicity. While Fludara and docetaxel separately have shown better efficacy and pharmacokinetics when combined with other cytotoxic drugs, interactions between the two haven’t been explored as yet.

Fludara is a member of an emerging class of nucleoside-analogues that exhibit multiple mechanisms of action and these mechanisms are likely to be useful for modulation of the metabolism and action of other drugs such as docetaxel (Chapter 1 (981). Given the promising synergies obtained in this study, interactions between PNP-GDEPT metabolites and docetaxel need to be further explored to better understand the mechanistic of the synergies for future application.

Overall, the remarkable efficacy of the combination noted in this study may be mediated by:-

Chapter 5: Combination Therapy for Prostate Cancer 332

1. Docetaxel mediated enhancement of Ad transduction or Ad- mediated enhancement of docetaxel sensitivity; Previous studies have shown that docetaxel enhances

Adenoviral mediated gene transduction in PC-3 cells (802) and that Adenoviral transduction enhanced the sensitivity of cells to taxanes (164,165).

2. Modulations in apoptotic proteins favourable to tumour cell killing; M30 mediated apoptosis was significantly enhanced in combination treated tumour. High levels of apoptosis achieved in Ad alone control group could be related to inherent immunogenicity of these vectors. While the tumour growth was suppressed in Taxotere treated mice, negligible apoptosis in tumours groups was seen. The reasons for this are unclear and could be due to slow growth rates due to lower penetration of drug within the tumour mass (suboptimal doses were used) or due to technical error (further sections may have shown an effects or sampling bias). However, lack of apoptosis in GDEPT treated group was also associated with insignificant reduction in local tumour growth, which correlated with dose optimisation data and could be attributed to use of suboptimal dose.

3. Augmentation of a favourable immune response leading to enhanced systemic (lung colony growth) and long term efficacy (Survival); increased infiltration of CD4+, CD8+

(effecter T lymphocytes) and F4 80 cells (macrophages) was seen in combination treated tumours. Overall, it may be postulated that the improved therapeutic efficacy may be due to an increased cytoreduction (apoptosis; M30+), stimulation in antigen presentation (enhanced macrophage infiltration) and recruitment and activation of both helper (CD4+) and cytotoxic (CD8+) T lymphocyte cells. Although not explored in this study, a further exploration of sequential administration or order of the treatments may further modulate these effects.

Chapter 5: Combination Therapy for Prostate Cancer 333

An important observation from the immunohistochemical analysis is the higher influx of inflammatory cells in Ad alone group compared to PNP-GDEPT alone (Table 3.10 and Figure 5.22). The effect may be partly due to the myelosuppressive nature of

Taxotere (72) and Fludarabine (970,981). With the use of Taxotere alone, the longer persistence of Ads can result which may lead to significant toxicities especially when oncolytic Adenoviruses are used. However, given that Ad.PNP transduced cells will be eliminated through use of Fludara, persistence of Ad.PNP may not be an issue.

Additionally, it is expected that efficacy of treatment will rely on the balance between immunosuppressive effects of Fludarabine phosphate vs. cytotoxic effects of PNP-

GDEPT. Finally, with enhanced cytotoxicity of combination regimen (despite the immunosuppression by the two drugs), the persistence of Ad may not be an issue as the

Ad-transduced cells will most likely be eliminated. This was shown by lack of systemic toxicity in our in vivo studies for all treatment groups including mice treated with combination regimen.

An ideal combination therapy would be the one that can achieve an enhancement in the antitumour activity between its components but without any given additive toxicities.

Generally, the treatment related adverse reactions are due some kind of cellular injury or organ function impairment (982). In this study, combination regimens did not lead to any adverse reactions or loss of condition or weight in mice. As discussed in earlier studies toxicity/adverse reactions as a result of combined use of chemotherapeutic or biological agents (e.g. Ads) may be a serious issue in the development of a successful clinical approach (343). It may be noted that Fludara and its metabolites can lead to profound lymphopenia and significant bone marrow suppression. Docetaxel also leads

Chapter 5: Combination Therapy for Prostate Cancer 334 to netropenia and other adverse reactions, and some of these are dose limiting (Chapter

1). Fludara is mainly processed and excreted through renal/urinary tract system while docetaxel is processed through liver. In fact, patients with kidney or liver damage show greater toxicity to the relevant drug. Further, use of Ad vectors has been reported to cause hepatotoxicity in vivo (Chapter 1). Given that systemic doses of Fludara or

Taxotere were lower than maximum tolerated doses in C57BL/6 and nude mice, we did not anticipate significant side effects when either modality was used alone. However, given that all these three agents are part of the tested combination drug regimen, an assessment of combined toxicities was essential to prove the worth of this regimen. The gain or loss of weight in response to some form of stress (e.g. biological or chemotherapy) is a primary sign of toxicity in mice. Overall, a lack of significant toxic effects seen in both models suggested the promise of this approach. In fact, some weight loss was noted in individual regimen groups (Taxotere and GDEPT) but this was not seen when the two were combined. In nude mice, gain in weight towards the end suggested the improved condition of combination treated mice. That combination therapy can be given without any untoward toxicity to the host was finally confirmed by toxicology analyses of enzyme markers of liver and renal toxicity (based on previously shown toxicity profiles of individual regimens) in the combination treated mice. There are very few reports regarding the combined use of gene therapy and chemotherapy for

PC treatment, hence results from this study hold a definite promise to target PC heterogeneity. An oncolytic Ad CV787 combined with docetaxel and paclitaxel has already crossed a number of clinical hurdles to prove that gene therapy and chemotherapy can work in parallel to enhance the antitumour efficacy against PC (164).

Chapter 6: Transcriptional and Transductional Targeting 335

TRANSCRIPTIONAL AND TRANSDUCTIONAL TARGETING OF ADENOVIRAL VECTORS

Chapter 6: Transcriptional and Transductional Targeting 336

6.1 Introdcution

The two primary aims of Adenovirus mediated gene therapy are to engender efficient and safe gene delivery only to the target tissue. There are two main issues that need to be addressed with regards to Ad-based vectors; neutralization due to pre-existing anti

Ad-antibodies leading to its rapid clearance from the blood stream and its unwanted infection/expression in the normal cells (Chapter 1). To circumvent these, several researchers have modified the viral tropism to achieve cancer cell specific delivery while sparing normal cells. Hence, recently, the paradigm has shifted towards the development of transductionally and transcriptionally targeted vectors (Figure 1.1)

(983). Further, to allow safe and targeted systemic delivery specifically to tumour cells, recently, the field of Ad “vectrology” has shown a considerable shift towards improvement of vector features towards specificity and safety (580). Indeed, such genetic modifications in Ads have led to a remarkable safety profile in human subjects; some are now being tested in various phase III clinical trials.

Chapter 6: Transcriptional and Transductional Targeting 337

FIGURE 6.1 Key strategies to achieve targeted gene expression from Ad vectors

Thomas et al (2003) has discussed four different approaches, which aim to achieve tumour-specific and regulated gene expression with the use of Ad vectors.

a) Transcriptional targeting is generally achieved by putting the transgene under the control of a cancer cell specific promoter. Selective gene expression is achieved with the selective promoter activity, which in turn is dependent upon transcriptional elements over-expressed in cancer cells only.

b) Tumour-specific transcriptional targeting can also be achieved using a novel method described by Lieber et al. This approach used homologous recombination to conjugate a promoter sequence with a reporter gene; the process was dependent upon tumour cell specific Ad genome replication.

c) Conceptually, two different strategies can be used to achieve transductional targeting; non genetic (e.g. binding to bi-specific antibodies or peptides) or genetically (capsid modifications to direct virus to novel receptors e.g Her-2).

d) Both transcriptional and transductional approaches can be combined to achieve a higher level of cancer cell selectivity.

Adapted from Clare E. Thomas, Anja Ehrhardt & Mark A. Kay Nature Reviews Genetics 4, 346-358 (May 2003) 337

Chapter 6: Transcriptional and Transductional Targeting 338

Our data thus far has clearly shown the promise of combining the molecular therapy engendered by PNP-GDEPT with Taxotere and/or carboplatin. In the next phase of this study, the aim was to target PNP-GDEPT specifically to either prostate cancer or ovarian cancer cells. For this purpose, Adenoviral vectors transductionally/transcriptionally targeted to Her-2/neu (oncogene) displaying aberrant expression in various malignancies including PC and OC, were employed (767). Also, survivin (IAP) promoter based transcriptionally targeted vectors were focussed upon; to target gene expression to survivin overexpressing OC/PC cells, which co-relates with poor clinical outcome of various cancer types including but not limited to OC and PC.

Due totheir, selective expression in tumours and not in normal tissues, both Her-2/neu and/or survivin serve as an excellent target for selective cancer gene therapy. The rationale for the selection of these two is described below:

Why Her-2/neu based targeting?

HER-2/neu protein is a transmembrane tyrosine kinase receptor, which is overexpressed in about 30% of breast and ovarian cancers (923,984-987) and Her-2/neu gene amplification is often correlated with cancer progression and poor prognosis of the patient (984,988,989). Studies have shown that activation of Her-2/neu receptor can activate specific signal transduction pathways leading to various events of carcinogenesis and gene amplification can enhance tumorigenic and metastatic potential of cancer cells in experimental models (990,991). Furthermore, its overexpression has also been implicated in development of tumour cell resistance towards various forms of anti-cancer therapies e.g. chemotherapy in OC (992,993) and hormonal therapy in PC

(994,995). Although, it’s clinical significance in OC is well defined, its role in PC is

Chapter 6: Transcriptional and Transductional Targeting 339 still in debate. A variable level of expression has been reported in prostate carcinoma and its role in disease progression from androgen dependent to androgen independent stage is yet to be proven. Studies have also indicated that Her-2/ERBB3 kinase signalling can result in the modulation of Androgen Receptor (AR) function, which further signifies Her-2 pathway as a potential target for PC therapy (994,995). Some key features of Her-2/neu and its targeting strategies have been summarized in Figure 6.2.

Chapter 6: Transcriptional and Transductional Targeting 340

Her-2/neu: key features and approaches

Historical perspective Biochemistry

• 1980: Rat gene ‘ neu’ rep orted in animal mod els • The HER-2/neu proto-oncogene encodes a 185-kD transmembrane

• 19 84: ERBB -2 gen e prod uct rep orted Synonyms: E R B B-2 ; H ER -2 ; HE R -2/ neu glycoprotein receptor (tyrosine k inase gro wth factor recepto r) •1987: Dr Dennis Salmon signified amplification of • Located at the long arm of human chromosome 17(17q11.2 -q12) •ErbB2 is nam ed fo r its sim ilarity to E rbB (avian Her-2/neu gene in breast cancer patients erythro blastosis oncogene B) • Member of epidermal growth factor (EG F) family •1998: FDA approved trastuzumab breast cancer patients •HER2 is named due to its similar structure to • HER-2 is considered as an orphan receptor without its own distinct hum an epid ermal grow th factor recepto r •T he onco gene neu is nam ed du e to it s d eri vatio n ligan d bu t it f orm s di mers wit h th ree ot her m emb ers of E GF fam ily From a Neuro -gl iob last om a cell line in rat

Targeting Strategies Functional Biology

Transcriptional Approaches (H ER-2 promo ter based gen e therapies) •Activatio n of Her -2 dimers stim u lates d ifferent p athw ays includ in g MA PK , PI3K, pho sp holipase -C (PLC), p rotein k inase C, and th e Virotherapy (e.g Adenovirus E1A ) Janu s kinase (Jak-STAT ) path ways, which are associated with its onco genic p oten tial Immunotherapy (Monoclonal antibodies e.g Herceptin) • M igrat ion , cell surv ival, angi ogen esis , apo pt osi s

Combination Therapy (e.g Docetaxel plus Herceptin)

Clinical Trials Prognostic and clinical significance

• Gene over-expression associated with poor clinical outcome Potential Therapeutic Gain • Her-2 associated tumors are faster growing, more aggressive and less sensitive to chemotherapy and hormone therapy

HER-2 targeted therapies (both single agent and combination Research/Clinical and Pre -clinical studies HER-2 based drug development th erap ies) have sh own i mp rov ed su rviv al i n HE R -2 p osi ti ve cancer patients e.g. breast and ovarian cancer

Figure 6.2 Multiple aspects of Her-2/neu in cancer: key features and therapeutic approaches 340

Chapter 6: Transcriptional and Transductional Targeting 341

The functional characterization of Her-2/neu promoter has led to the development of various transcriptionally targeted gene therapy approaches (996,997). Use of Her-2/neu promoter for successful regulation of suicide genes has been reported in breast and pancreatic cancer studies (998,999). Some initial attempts have been made to use this promoter in context of Ad vectors but results are quite disappointing due to interference from E1A elements (1000,1001). In this study, the first aim was to develop Her-2/neu promoter based transcriptionally targeted Ad vectors. To minimise interference from

E1A elements, bovine growth hormone (BGH) elements were used to insulate Her-

2/neu promoter and MucI enhancer was used to enhance the promoter activity. MucI conjugated Her-2/neu promoter (obtained from Dr. Ian McNeish, John Vane Science

Centre, London-UK) was chosen as this has already been exploited in a Genetic Pro-

Drug Activation Therapy (GPAT) clinical trial in breast cancer patients (1002).

In addition to the Her-2/neu promoter based transcriptional targeting, in this study, a transductionally targeted Ad vector that specifically transduces cancer cells expressing

Her-2/neu receptor (767) (developed by our project collaborators (University

Gothenburg/ Got-a-Gene company, Sweden) was employed. This virus was developed through de-targeting of Ad5 fibre from its native receptor (CAR) with subsequent retargeting of Ad fibre to Her-2/neu receptor through insertion of a Her-2 receptor specific affibody molecule (ZH) in the fibre of Ad5 capsid. Some key features/structure of Ad.ZZ viruses developed by our Sweden lab has been shown in Figure 6.3.

Chapter 6: Transcriptional and Transductional Targeting 342

E1A E3 CAR CMV GFP ZHZH

HER-2 specific Affibody (ZH)

Figure 6.3 The structural features of Her-2/neu targeted Ad.ZZ vector: This study used a Her-2/neu targeted adenoviral vector developed and characterized by Got-a-Gene company/University Gothenburg, Sweden. The Ad.ZZ virus was de-targeted from its native receptor (CAR) and then retargeted to Her-2/neu receptor with the attachment of an affibody molecule. Some key features of this virus are represented in the structure shown above: The E1 region was replaced with the green fluorescent protein (GFP) gene under a CMV promoter A head-to-tail dimer of the ZH Affibody (ZH) was incorporated into the HI6-loop of a CAR binding domain Two amino acids were deleted from the HI-loop fiber in order to remove its CAR binding ability The ablated fiber was genetically modified to contain sequences for flexible linkers between the ZH and the knob sequences. 342

Chapter 6: Transcriptional and Transductional Targeting 343

Why Survivin based Targeting?

Survivin is a multifunctional molecule and a member of inhibitors of apoptosis (IAP) family, which is involved in a wide variety of cellular pathways including but not limited to cancer (reviewed in (1003-1006). Survivin upregulation has been shown in a number of human cancers, and its overexpression is often co-related with tumour aggression, shorter survival times, and resistance to various forms of anticancer therapies (e.g. chemotherapy) (1007,1008). Due to its negative regulatory roles in cancer progression and survival, survivin and its regulatory networks are considered as a prime candidate target of various anticancer therapies (1003,1009) (Figure 6.4).

Studies have shown that survivin is one of the most promising tumour-specific molecules with almost negligible expression in normal tissues (1010). Further, the transcriptional analysis of survivin gene and specific characterization of its promoter has opened several avenue of targeted gene therapy (1011,1012). The use of survivin promoter to derive cancer specific expression of a wide variety of therapeutic genes has been reported successfully (1011,1013,1014). Importantly, its transcriptional activation has also been reported under hypoxic conditions (oxygen deficient conditions) (1011).

Hypoxia is a common feature of various solid tumours such as those encountered in PC and OC, and often results in an aggressive tumour phenotype with a possible role in resistance towards various anticancer therapies (594,595,1013). Hence, a strong rationale underlies the use of survivin promoter in gene therapy approaches directed against OC and PC. Based on these findings, another aim of this study was to explore the use of survivin promoter in context of the Ad vectors to transcriptionally target

PNP-GDEPT expression to survivin overexpressing prostate or ovarian cancer cells.

Chapter 6: Transcriptional and Transductional Targeting 344

Figure 6.4 Multiples roles of survivin (adapted from Altieri, D. C. Mol Cancer Ther 2006;5:478-482) (1003) The multiple facets of survivin gene and its complex networks have been extensively reviewed (1003-1006). As shown in figure, Dario C. Altieri has also dissected survivin and its network pathways to develop rationale based targeted therapies. In particular, survivin signalling networks are implicated in cancer cell proliferation, apoptosis, angiogenesis, modulation of p53, response to cellular stress and control of spindle formation and proper kinetochore attachment during cell division. 344

Chapter 6: Transcriptional and Transductional Targetig 345

With increasing emphasis on Ad vector specificity and safety, especially to allow their regular use in the clinic, dual targeting strategies, which employ both transcriptional, and transduction modifications are now being employed. Such an approach can achieve a higher level of tumour specificity while leaving the normal tissues unscathed. In context of this study, interactions between survivin and Her-2/neu pathways make them susceptible for this exploitation. The cross talk between these pathways has only been reported in breast cancer studies (1015-1017) and future studies will still be needed to establish this in other cancers including OC and PC. However, previous studies have confirmed the co-expression of Her-2/neu and survivin in two model cell lines;

OVCAR-3 and SKOV-3. Given these features, the study was initiated to develop Ad vectors, which were transductionally directed against Her-2/neu receptor and controlled at a transcriptional level using survivin or Her-2/neu promoter. It is anticipated that results from this study will form a basis for the development of these genetically retargeted Ads for future clinical applications in cancer patients showing Her-2/neu and survivin over-expression.

The primary aim of this study was to evaluate the potential of these transcriptionally and transductionally modified Ad viruses to specifically target OC and PC cells in vitro.

Overall, the specific aims of this study were;

1. To evaluate the Her-2/neu receptor and survivin status of OC and PC cells.

2. To evaluate the tumour-specificity and therapeutic potential of transductionally

targeted Her-2/neu Adenovirus (Ad.ZZ).

3. To construct and characterise transductionally (Her-2/neu receptor) and

transcriptionally (survivin or Her-2/neu) targeted Adenoviral vectors for OC and PC

therapy.

Chapter 6: Transcriptional and Transductional Targetig 346

6.2 Results

6.2.1 Her-2/neu expression in OC cell lines

Four OC cell lines, SKOV-3, OVCAR-3, Caov-3 and A-2780, were analysed for Her-2/ neu expression using FACS analysis of immunostained cells. 293-Her-2/neu (a cell line stably infected with Her-2/neu gene to express the receptor) and MCF-7 (negative control line that displayes single gene copy number of Her-2/neu) and served as positive and negative controls respectively. The antibody used in this staining procedure detects cytoplasmic domain of Her-2/neu receptor. For this reason a saponin based permeablization buffer was used to expose cytoplasmic domain of Her-2/neu in cancer cells. As expected, 293-Her-2/neu showed a very high level of expression (78% ± 8).

OC cell lines showed a moderate to high level of Her-2/neu expression (Figure 6.5).

Maximum expression was observed in SKOV-3 cells (57% ± 6) followed by OVCAR-3

(32% ± 5), Caov-3 (23% ± 4) and A-2780 (16% ± 3). There was almost negligible expression in MCF-7 cells (2% ± 1). The cell lines thus represent a range of HER-2/neu expression, which would provide an optimal and diverse range to evaluate of Her-2 based targeting. It may be concluded that an antibody to HER-2/neu surface protein can be used for transductional targeting of viral vector to these cell lines.

Chapter 6: Transcriptional and Transductional Targetig 347

100 293-Her-2 neu SKOV-3 P < 0.0001 OVCAR-3 80 Caov-3 A-2780 MCF-7 60

20 % of% Her-2 neu antibody positive cells 0

Figure 6.5 HER-2/neu expression in OC cell lines: Cells (3x105) were incubated with

HER-2 and IgG isotype-control antibody, and then treated with FITC-secondary antibody. Flow cytometry was performed using a fluorescence-activated cell scanner.

293-Her-2/neu and MCF-7 and served as positive and negative controls, respectively.

All four OC cell lines showed a moderate to high level of HER-2/neu expression. Level of expression was highest in SKOV-3 cells (57% ± 6) followed by OVCAR-3 (32% ± 5),

Caov-3 (23% ± 4) and A-2780 (16% ± 3) cells. Results shown are mean of two independent experiments ± standard deviation (P < 0.0001).

Chapter 6: Transcriptional and Transductional Targetig 348

6.2.2 Evaluation of tumour-specificity of transductionally targeted

Her-2/neu Adenovirus (Ad.ZZ)

As explained earlier Ad.ZZ virus is genetically modified to target cells through the surface Her-2/neu receptor (767). Once the variable levels of Her-2/neu was proven in different cell lines, next, the potential of ZZ targetd Ad/CMV/GFP virus to specifically transducer these cancer cell lines was evaluated. Briefly, OC and PC cell lines infected with different doses of Ad.ZZ.GFP virus for 48 hwere analysed for GFP expression by

FACS analysis. The variable permissivity of these cell lines to Ad transduction is already established (see Section 3.2.4). Ad.ZZ.GFP infected cell lines showed different levels of GFP-expression (Figure 6.6 and 6.7) in accordance with their Her-2/neu receptor expression status; at an moi of 100 pfu/cell, 293-Her-2/neu was most permissive (~% GFP expressing cells: 71% ± 6) followed by SKOV-3 (45% ± 8),

OVCAR-3 (30% ± 5), Caov-3 (21% ± 5), PC-3 (15% ± 6), A-2780 (11% ± 2) while

MCF-7 (1% ± 1) and murine PC RM1 (0.5% ± 1) cells were almost refractory. Hence, a higher level of gene transduction was achieved in cell lines overexpressing Her-2/neu

(293-Her-2/neu and SKOV-3) compared to Her-2/neu negative cell lines (MCF-7).

Human PC lines, PC-3, DuCap and LnCap and murine PC lines, TC-1, TC- F1, TC-1

T5 were also evaluated, but these showed no permissivity (data not shown) suggesting a lack of Her-2/neu receptor on these.

It is to be noted that otherwise strongly permissive OVCAR-3 for Ad infection (at 100 moi >98%) showed much reduced Her-2 specific transduction (30%) and Ad-refractory

Caov-3 (<1%) (see Section 3.2.5) displays ~21% transduction in accordance with its

Her-2/neu receptor status. These indicate the specificity of Ad.ZZ.GFP based targeting.

Chapter 6: Transcriptional and Transductional Targetig 349

100 293-Her-2 neu SKOV-3 P < 0.0001 OVCAR-3 80 Caov-3 PC-3 A-2780 60 MCF-7 RM1 40

20 % of% GFP expressing cells

Figure 6.6 Evaluation of Ad.ZZ.GFP transduction in different cell lines: To check the permissiveness of cancer cell lines for Ad.ZZ transduction, cells infected with

Ad5/CMV/GFP/ZZ for 48 h were analyzed for number of cells expressing GFP by flow cytometry. Graph shows % GFP expressing cells at a viral dose of 100 moi and values represent mean (±ST Dev) of two independent experiments. 293-Her-2/neu and SKOV-

3 were highly permissive followed by OVCAR-, Caov-3, PC-3 and A-2780. MCF-7 and

RM1cells were almost refractory for the virus infections.

Chapter 6: Transcriptional and Transductional Targetig 350

Control

MCF-7 293-Her-2 neu SKOV-3 PC-3 RM1

Ad.ZZ moi of 100 pfu/cell

Figure 6.7 Evaluation of Ad.ZZ transduction in cancer cell lines: To check the permissiveness of cancer cell lines for Ad.ZZ transduction, cells infected with Ad5/CMV/GFP/ZZ for 48 h were analyzed for number of cells expressing GFP by flow cytometry. Dot plots show % GFP expressing cells (in the upper right quadrant) at moi of 100 pfu/cell. A high level of gene expression was observed in 293-Her-/ neu and SKOV-3 while PC-3 cells showed moderate level of expression. MCF-7 and RM1cells were almost refractory for the virus infections. 350

Chapter 6: Transcriptional and Transductional Targetig 351

Her-2/neu selective activity of Ad.ZZ was also shown at higher doses (Figure 6.8).

Gene transduction enhanced in a dose dependent manner in Her-2 positive 293-Her-

2/neu and SKOV-3 cells while in comparison MCF-7 (Her-2/neu negative cell line) did to not show any significant increase in GFP expression even a higher a dose of moi of

500 pfu/cell. In conclusion, Ad.ZZ.GFP based targeting is likely to achieve high selectivity for Her-2/neu expressing cells (Figure 6.9).

Chapter 6: Transcriptional and Transductional Targetig 352

MCF-7 293 HER-2neu SKOV-3

Control

Ad.ZZ moi of 10 pfu/cell

50 pfu/cell

100 pfu/cell

500 pfu/cell

Figure 6.8 Evaluation of effects of different doses of Ad.ZZ on Her-2/neu positive and negative cell lines: Cells infected with different doses of Ad5/CMV/GFP/ZZ for 48 h were analyzed for number of cells expressing GFP by flow cytometry. Dot plots show % GFP expressing cells (upper right quadrant) at different moi’s. The levels of gene expression were enhanced in doses dependent manner in 293-Her-2/neu and SKOV-3 cell lines. MCF-7 cells did not show any significant increase in GFP expression even at a higher dose of 500 moi.

Chapter 6: Transcriptional and Transductional Targetig 353

100 Her-2 Antibody Ad.ZZ (GFP) 80

20 Cells positivefor Antibody/GFP

0 293 Her-2 SKOV-3 OVCAR-3 Caov-3 A-2780 MCF-7

Figure 6.9 Expression of Ad.ZZ.GFP is Her-2/neu specific in OC cells: The graph displayes the combined data from Section 6.5 and 6.6 to correlate Ad.ZZ virus intake with Her-2/neu receptor expression in these cells. A strong co-relation between the two was obvious in all cell lines, which shows Her-2/neu receptor specific targeting potential of this virus.

353

Chapter 6: Transcriptional and Transductional Targetig 354

6.2.3 Development and functional characterization of transcriptionally targeted Her-2/neu Adenovirus

After the successful correlation of Her-2/neu receptor status of different cancer cell lines and their transductional targeting by Ad.ZZ.GFP virus, strategies were designed to achieve Her-2/neu promoter based transcriptional targeting in Adenoviral vectors. A number of plasmids were obtained from different sources to construct this virus (see details in Appendix III). Depending upon the available restriction sites, a strategy was planned to generate shuttle vectors with an expression cassettes containing different elements including insulating stop signals (bovine growth hormone (BGH) or SV40 poly Adenylation signal), promoter (Her-2/neu) and a reporter gene (Luciferase).

Chapter 6: Transcriptional and Transductional Targetig 355

6.2.3.1 Construction of Adenovirus containing BGH.MUC1.Her-2 promoter regulating the expression of Luciferase gene (Ad. BGH.MUC1.Her-2.Luc)

The aim was to construct a replication incompetent Adenovirus (E1A and E3 deleted) with Her-2/neu specific promoter regulating the expression of reporter, Luciferase (Luc) gene. In order to minimise interference by E1A region insulating BGH elements were introduced before the promoter elements.

Two main steps were involved in this strategy:

1. Step 1. Generation of a shuttle vector with BGH.MUC1.Her-2.Luc expression

cassette (pSc.BGH.MUC1.Her-2.Luc)

2. Step 2: Recombination of pSc.BGH.MUC1.Her-2.Luc with pAdeasy to generate

pAd.BGH.MUC1.Her-2.Luc and rescue Ad. BGH.MUC1.Her-2.Luc in 293A

cells

1. Generation of pSc.BGH.MUC1.Her-2.Luc

A three-step strategy was planned to generate pSc.BGH.MUC1.Her-2.Luc (Figure

6.10)

(i) Cloning MUC1/Her-2 promoter in pSc (shuttle vector).

(ii) Amplification of BGH fragment with required 5’ and 3’ restriction

sites by PCR from the relevant plasmid

(iii) Introduce BGH.Her-2 elements 5’ of the luciferase gene in

Luciferase expressing pGL3 commercial plasmid (Generate pGL-

3.BGH.Her-2 as an intermediate)

(iv) Generate pSc.BGH.MUC1.Her-2.Luc

Chapter 6: Transcriptional and Transductional Targetig 356

Chapter 6: Transcriptional and Transductional Targetig 357

(i) MUC1/Her-2 promoter elements excised as HindIII and XbaI fragment from

pMEEP-CAT (Dr Ian McNeish) was cloned into pSc. vector to generate

pSc.Muc1.Her-2

(ii) BGH stop signal elements were amplified from a plasmid pSVPB.PNP.BGH

(CSIRO, Dr G. Both) with PCR primers specifically designed to introduce Not1 at 5’

end and HindIII at 3” end using Pfu polymerase (see cloning methodology, Section

2.1.1.1). The amplified BGH fragment was gel- purified (Q-Biogene’s kit) and then

restricted to generate NotI and HindIII sites.

(iii) Three way ligation was done between BGH fragment (NotI/HindIII),

Muc1/HER-2 fragment (restricted from pSc.Muc1.Her-2 as HindIII/XhoI) and

Luciferase gene (NotI/XhoI fragment from PGl3 basic vector) to generate

pGL3.BGH.Her-2.Luc

(iv) Before moving to the next step, Her-2 promoter activity in pGL3.BGH.Her-

2.Luc was determined in Her-2 positive (SKOV-3) and negative (MCF-7) cell lines.

Two different clones (# 2.8 and # 3.7) were chosen and were evaluated for Her-2

promoter driven Luciferase gene expression. The transfections of cell lines with these

plasmids were done as described in Section 2.2.4.1. The promoterless pGL3 plasmid

containing the luciferase gene was used as the negative control. Luciferase activity

was determined in plasmid transfected SKOV-3 and MCF-7 cells. A higher level of

promoter activity was observed in SKOV-3 (~2500 RLU/mg for clone # 2.8)

compared to MCF-7 cells (~30 RLU/mg for clone # 2.8) (Table 6.1 and Figure 6.11

Chapter 6: Transcriptional and Transductional Targetig 358

Panel A). Further, when data was plotted as fold changes with respect to pGL3

plasmid, an ~ 20 fold increase was observed in SKOV-3 cells compared to 1.3 for

MCF-7 cells (Table 6.2 and Figure 6.11 Panel B). Clone # 2.8 showed a better

promoter activity than # 3.7 and was selected for future shuttle development. The data

clearly indicated that Her-2 promoter was specifically active in Her-2/neu-

overexpressing SKOV-3 cells and that this approach is suitable for Her-2/neu-specific

transcriptional targeting of cancer cells. This also correlated with the fact that cells

that overexpress Her-2/neu also display high activity of Her-2 promoter.

Table 6.1 Evaluation of Her-2 promoter activity in pGl3.BGH.Her-2.Luc transfected SKOV-3 and MCF-7 cells

Luciferase activity Relative Light Units (RLU)/mg Plasmids SKOV3 MCF7 pGL3 128 23 pGL3.BGH.Her-2.Luc # 2.8 2493 30 pGL3.BGH.Her-2.Luc # 3.7 882 31

Table 6.2 Fold changes in Her-2/neu promoter activity in pGL3.BGH.Her-2.Luc transfected cells in comparison to control plasmid (pGL3) transfected cells

Fold change compared to pGL3

Plasmid SKOV3 MCF7 pGL3.BGH.Her-2.Luc # 2.8 19.5 1.3 pGL3.BGH.Her-2.Luc # 3.7 6.9 1.3

Chapter 6: Transcriptional and Transductional Targetig 359

A B 3000 SKOV-3 SKOV-3 20 2500 MCF-7 MCF-7

2000 15

1500 10

1000

Fold change to GL-3 to change Fold 5 500 Luciferase activity (RLU/mg)

0 0 PGl3 Her-2 # 2.8 Her-2 # 3.7 Her-2 # 2.8 Her-2 # 3.7

Figure 6.11 Evaluation of Her-2 promoter activity in pGL3.BGH.Her-2.Luc transfected Her-2 positive and negative cell line: SKOV-3 and MCF-7 cells were transfected with different plasmids using lipofectamine method for 48 h Luciferase activity was determined as Relative Light Units/ milligram (RLU/mg). pGL3 plasmid (promega) was used as a negative control. Two different clones (# 2.8 and # 3.7) were tested to evaluate Her-2 promoter activity through its ability to drive Luciferase gene expression. A higher level of promoter activity was observed in Her-2 overexpressing, SKOV-3 cells compared to Her-2 negative, MCF-7 cells (Panel A). Almost similar trends were observed in these cell lines when data was plotted as fold change to basal levels of expression (pGL3) (Panel B). Clone # 2.8 was selected for future use. 359

Chapter 6: Transcriptional and Transductional Targetig 360

(v) Once the selective activity of Her-2/neu promoter was established , complete

expression cassette containing BGH.MUC1.Her-2.Luc excised from pGL3.BGH.Her-

2.Luc # 2.8 as NotI/SalI fragment was cloned into pSc vector (NotI/XbaI) resulting in

the final construction of pSc.BGH.MUC1.Her-2.Luc.

6.2.3.2 Recombination of pSc.BGH.MUC1.Her-2.Luc with pAdeasy to generate pAd.BGH.MUC1.Her-2.Luc and rescue of Ad.BGH.MUC1.Her-

2.Luc

PmeI linearised pSc.BGH.MUC1.Her-2.Luc vectors were used to make pAd.BGH.MUC1.Her-2.Luc by homologous recombination in BJ5183 cells (see Figure

2.2) (restriction confirmation shown in Appendix V and X). The constructed Ad plasmid was digested with PacI followed by its lipofection in 293A cells to rescue the recombinant virus, Ad.BGH.MUC1.Her-2.Luc. The rescued virus was then purified and titrated (see Section 2.5.7 and 2.5.8) for further use.

6.2.3.3 Evaluation of tumour specificity of Ad.BGH.MUC1.Her-2.Luc

Next, Ad.BGH.MUC1.Her-2.Luc was evaluated for its Her-2 promoter based transcriptional selectivity in SKOV-3 and MCF-7 cells. At relatively higher doses of virus (500 and 1000 moi) an enhancement in luciferase activity (Relative light units

(RLU)/mg) were observed in SKOV-3 cells (239 ± 36 RLU/mg at 1000 moi) compared to MCF-7 cells (27 ± 9 rlu/mg at 1000 moi) (Table 6.3). Despite very low promoter activity, (Figure 6.12 and Table 6.3), the virus retained its Her-2 specific expression.

Chapter 6: Transcriptional and Transductional Targetig 361

300

250 SKOV-3 MCF-7 200

150

100

50 Luciferase activity (RLU/mg) activity Luciferase

0 100 500 1000

Figure 6.12 Evaluation of Her-2/neu transcriptional activity of Ad.BGH.MUC1.Her-2.Luc in OC cells: SKOV-3 and MCF-7 cells infected with different doses (100, 500 and 1000 moi) of Ad.BGH.MUC1.Her-2.Luc for 48 h were analyzed for luciferase activity measured as Relative Light Units/ milligram (RLU/mg). Relatively a low level of luciferase expression was observed at all tested doses. Although, relatively lower level of promoter activity was achieved even at higher doses (500 and 1000 moi) but the virus was able to retain its Her-2 neu specific expression.

Chapter 6: Transcriptional and Transductional Targetig 362

Table 6.3 Evaluation of Her- 2 promoter activities in Ad.BGH.MUC1.Her-2.Luc infected SKOV-3 and MCF-7 cells

Luciferase activity Relative Light Units (RLU)/mg

Virus dose (moi) SKOV3 MCF7 100 0.1 ± 0.3 0.12 ± 0.03 500 15 ± 5 2 ± 1 1000 239 ± 36 27 ± 9

6.2.4 Construction and functional characterization of transcriptionally targeted survivin promoter containing Adenovirus (Ad

BGH.Survivin.Luc)

A plasmid containing survivin promoter (pSurvivin-269) was purchased from Dr. Feng

Zhi Li (Roswell Park Institute, Buffalo-NY). Given that the successful use of this promoter has been reported in a number of studies and it was obtained from a commercial source, promoter functional studies were not performed. Depending upon the available restriction sites, a strategy was devised to construct a shuttle vector containing an expression cassette with a survivin promoter, insulating stop signals

(BGH, 5’ to survivin promoter) and a luciferase reporter gene.

Two steps were involved in construction and rescue of Ad BGH.Survivin.Luc

Chapter 6: Transcriptional and Transductional Targetig 363

Step 1. Generation of a shuttle vector with BGH.Survivin.Luc expression cassette

(pSc.BGH.Survivin.Luc)

Step 2: Recombination of pSc.BGH.Survivin.Luc with pAdeasy to generate

pAd. BGH.Survivin.Luc and rescue Ad. BGH.Survivin.Luc in 293A cells

6.2.4.1 Generation of a shuttle vector with BGH.Survivin.Luc expression cassette (pSc.BGH.Survivin.Luc)

A three step strategy was planned to generate pSc.BGH.Survivin.Luc (Figure 6.13).

Three main steps were involved:

(i) Cloning BGH in pGL-3 Basic

(ii) Cloning Survivin promoter from pSurvivin-269 into pGL-3.BGH

(iii) Cloning BGH.Survivin.Luc.SV40 polyA in pShuttle

(i) The pfu polymerase PCR amplified BGH product was restricted with NotI to generate NotI/Blunt BGH fragment (given that PCR products of pfu polymerase are blunt ended, the other end of this fragment was blunt). The gel purified fragments, BGH fragment (NotI/Blunt) and pGL-3 Basic restricted with NotI/SmaI (SmaI is a blunt cutter) were ligated as described (see Section 2.1.1.8). The resultant plasmid (pGL-

3.BGH) was confirmed for the presence of Survivin promoter and BGH fragment by restriction digestion.

(ii) Survivin promoter excised from pSurvivin-269 was (BamHI/HindIII) was ligated to pGL-3.BGH restricted with BglII/HindIII (BglII and BamHI are ligation compatible).

Chapter 6: Transcriptional and Transductional Targetig 364

Chapter 6: Transcriptional and Transductional Targetig 365

The new plasmid, pGL-3.BGH.Survivin, was confirmed for the presence of ~550 bp

(BGH + Survivin promoter) and ~269 bp (Survivin promoter) fragments by appropriate restriction digest (~550 bp, Not/HindIII and ~269 bp, XhoI/HindIII).

(iii) The restriction fragment from pGL-3.BGH.Survivin (Not/SalI) containing whole gene expression cassette (BGH + Survivin + luciferase gene and SV40 polyA) was cloned into the multiple cloning site (MCS; NotI/SalI) of pShuttle by standard ligation method. Generation of pShuttle.BGH.Survivin.Luc was confirmed by relevant restriction digestions (e.g. Not/SalI, fragment size ~ 2500 bp).

6.2.4.2 Recombination of pSc.BGH.Survivin.Luc with pAdeasy to generate pAd. BGH.Survivin.Luc and rescue of Ad. BGH.Survivin.Luc in 293A cells

PmeI linearised pSc.BGH.Survivin.Luc vector was used to make pAd.BGH.Survivin.

Luc by homologous recombination in BJ5183 cells (restriction confirmation shown in

Appendix VI, VII and X). The newly constructed Ad plasmid, pAd. BGH.Survivin.Luc, was digested with PacI followed by lipofection in 293A cells to rescue Ad.

BGH.Survivin.Luc. The rescued virus was purified and titrated (as described earlier) for future use.

6.2.4.3 Evaluation of tumour specificity of Ad.BGH.Survivin.Luc

Next, the new virus was evaluated for survivin promoter based transcriptional specificity in a range of OC and PC cell lines. Briefly, cells infected for 48 h with 100 moi of either Ad.CMV.Luc or Ad.BGH.Survivin.Luc were analysed for luciferase

Chapter 6: Transcriptional and Transductional Targetig 366 activity (measured as Relative Light Units/ milligram (RLU/mg). A variable level of expression was achieved in these cell lines; Ad.BGH.Survivin.Luc showed highest transcriptional activity in OVCAR-3 (16242 ± 1504) followed by RM1 (1762 ± 345),

SKOV-3 (588 ± 156), PC-3 (112 ± 15) and MCF-7 (33 ± 6) (Figure 6.14 Panel A and

Table 6.4). To assess the specificity of this expression, the data is also presented as fold change in comparison to Ad.CMV.Luc activity (Figure 6.14 Panel B and Table 6.4). It has been shown that overexpression of survivin is associated with increased promoter activity, hence, for correlation with promoter activity, these cells were also analysed for survivin expression by western blot analyses ((Figure 6.14 Panel C). The luciferase activity/fold change data showed that transcriptional activity of Ad.Survivin.Luc directly correlated with the levels of survivin protein in these cells. In conclusion, survivin specific nature of Ad.BGH.Survivin.Luc was established in this study.

Chapter 6: Transcriptional and Transductional Targetig 367

20000 30 A 15000 Ad.CMV.Luc 2600 Ad.Survivin.Luc 25 B 1800 MCF-7 1000 20 200 PC-3 125 15 OVCAR-3 100 10 RM1 75 5 SKOV-3 50 Relative Light Units (RLU)/mg) Units Light Relative 0 25 Ad.CMV.Luc from chage Fold

0 OVCAR-3 RM1 SKOV-3 PC-3 MCF-7

Figure 6.14: Evaluation of tumour specificity of Ad.BGH.Survivin.Luc in different cell lines: OC and PC cells infected with 100 moi of either C Ad.CMV.Luc or Ad.Survivin.Luc for 48 h were analyzed for luciferase Survivin protein expression * activity. Panel A shows promoter driven luciferase expression measured as Relative Light Units/ milligram (RLU/mg). A variable level of expression was achieved in these cell lines with OVCAR-3 cells showing highest activity for both viruses followed by RM1 cells. Panel B represents transcriptional activity of Ad.Survivin.Luc represented as a fold change from that obtained from Ad.CMV.Luc expression. Ad.Survivin.Luc activity was highest in SKOV-3 MCF-7 PC-3 SKOV-3 OVCAR-3 cells followed by RM1, OVCAR-3 and PC-3 cells. In MCF-7 cells, Ad.CMV.Luc led to graeter luciferase activity compared to Ad.BGH.Survivin.Luc. Panel C displayes the western blot image analysing 367 survivin expression in various cell lines. As shown by Panel B and C transcriptional activity of Ad.BGH.Survivin.Luc correlated with the level of survivin protein. “*”survivin protein data for RM1 cells is not available.

Chapter 6: Transcriptional and Transductional Targetig 368

Table 6.4 Comparison of Ad.BGH.Survivin.Luc and Ad.CMV.Luc activities in OC and PC cell lines

Luciferase activity Fold change from Cell Lines (Relative Light Units (RLU)/mg) Ad.CMV.Luc

Ad.CMV.Luc Ad.BGH.Survivin.LucAd.CMV.Luc/ Ad.BGH.Survivin.Luc OVCAR-3 2206 ± 267 16242 ± 1504 7.3 ± 1.5

RM1 108 ± 12 1762 ± 345 16.4 ± 2.1

SKOV-3 24 ± 5 588 ± 156 24.5 ± 3

PC-3 54 ± 14 112 ± 15 4 ± 1

MCF-7 101 ± 13 33 ± 6 -3 ± 1

6.2.5 Construction of transcriptionally targeted survivin promoter containing Adenovirus plasmid that expresses PNP (pAd BGH.Survivin.PNP)

As shown in the previous section (see Section 6.2.4.3), survivin promoter successfully drove the transgene expression specifically in survivin overexpressing cell lines. Hence, step was to use this promoter to regulate PNP expression the Ad vector. Briefly, a shuttle vector containing an expression cassette containing survivin promoter, insulating stop signals (BGH, 5’ to survivin promoter) and PNP gene (suicide gene) was constructed. Since survivin promoter and BGH were already cloned in

Chapter 6: Transcriptional and Transductional Targetig 369 pSc.BGH.Survivin.Luc, the subsequent cloning stemmed from this plasmid. A single step was involved to generate pSc.BGH.Survivin.PNP by replacing luciferase fragment with PNP gene (MfeI/BamHI fragment from pBKS.PNP) via blunt end ligation.Restriction digest to confirm the right orientation of the insertion was done

(restriction confirmation shown in Appendix VII, VIII and IX ). Subsequently, PmeI linearised pSc.BGH.Survivin.Luc vector was used to make pAd.BGH.Survivin.PNP by homologous recombination in BJ5183 cells (described earlier) (restriction confirmation shown in Appendix X).

Due to time constraints this study was stopped at this point. The virus generation and functional characterization is needed to confirm its potential to direct PNP-GDEPT in

Survivin positive cancer cells.

Chapter 6: Transcriptional and Transductional Targetig 370

6.3 Discussion/Concluding Remarks

Natural tropism of Ads leads to significant unwanted toxicities in situ due to uptake by non-target cells, especially liver. A number of strategies have been devised in an effort to direct Ads to tumour tissues effectively. Transcriptional and transductional targeting have proven to be effective and appear to be the best way to confer higher levels of tumour specificity and safety to these vectors. Given the tumour specific expression of

Her-2/neu and survivin proteins (displayed both in OC and PC), justified their use in this study for these purposes. Infact to support this, the potential use of Her-2/neu and survivin promoter to regulate the expression of various genes has also been reported with a lot of optimism. Transduction targeting through the use of Her-2/neu affibody containing Ads to specifically infect cancer cells have been convincingly shown by project collaborators (from Sweden) (767). Survivin was of particular interest as apart from displaying “tumour on /liver off” phenotype (good for Ad vectors as these often display hepatotoxicity) (1010, 1012, 1013), it has been shown to be triggered by hypoxia, which is often encountered in solid tumours such as PC and OC (1010). The recently shown correlation between Her-2/neu expression and survivin (1014-1017) led to our decision to use the two together for transductional and transcriptional targeting, respectively. Given that Her-2/neu overexpression is found in majority of OC cells

(983-986), attempts were made to make Ad-vectors that are transductionally (Her-2/neu affibody) and trancriptionally (MUC1/Her-2 promoter) targeted to Her-2/neu overexpressing cells.

Chapter 6: Transcriptional and Transductional Targetig 371

In this study, a number of Ad vectors containing an expression cassette in which survivin or Her-2 neu promoter were used to derive the expression of either a reporter gene (Luc) or suicide gene (PNP) were successfully constructed. The specificity of the promoters in context of these vectors (expressing a reporter gene) was clerarly shown in both OC and PC cancer cell lines. It was encouraging when use of insulating BGH elements allowed Luc-expression regulated by Her-2 promoter in context of the Ad vectors, given in the past attempts, Her-2 promoter activity was inhibited by the E1A elements (even in E1A deleted vectors) (999, 1000). Importantly, although weak, the activity was specific. This may not be a limiting factor in context of tis study given the potency of PNP-GDEPT mediated bystander effects, which have the potential to amplify its cytotoxicity in situ even when <1% of cells are expressing the gene. In addition, these vectors can be further engineered to enhance the promoter activity, through use of enhancers (e.g PSME for PC (340) and other insulating elements (e.g synthetic poly A adenylation signal).

The use of Ad.ZZ virus to selectively target cancer cells expressing Her-2/neu receptor has showed a cancer specific transduction in preclinical studies. The data from this study also showed a strong co-relation between the levels of Ad.ZZ.GFP virus transduction (GFP expression) and Her-2/neu receptor expression (Her-2/neu immunostaining) by these cells. As reported in Chapter 1, CAR (Ad5 native receptor) downregulation in cancer cells is one of the major limitations for Ad5 mediated gene therapy. It may be noted that an OC cell line, Caov-3, represents this well as it is non- permissive for Ad/CMV/GFP infection (Chapter 3) but displayed moderate levels of

Chapter 6: Transcriptional and Transductional Targetig 372 infection with Ad.ZZ.GFP virus in accordance with its Her-2/neu receptor expression levels. Given, that the new virus with Her-2/neu promoter driven luciferase was able to retain its specificity even at relatively higher doses (e.g. 500 moi), use of Her-2/neu targeted vectors, that are transductionally and transcriptionally targeted to Her-2/neu overexpressing cells have the potential for application in against cancers that show CAR deficiency and Her-2/neu upregulation.

Compared to Ad.BGH.MUCI.Her-2.Luc, a much higher level of efficiency was observed when survivin regulated Ad.BGH.Survivin.Luc was tested in different cell lines (see Section 6.2.4.3). Comparison with CMV promoter regulated Ad vector

(AD/CMV/LUC) unequivocally demonstrated the specificity of survivin promoter based

Luc expression; Ad.BGH.Survivin.Luc transduction led to highly selective expression in cancer cell lines with survivin overexpression (Figure 6.14). Representation of expression due to Ad.BGH.Survivin.Luc transduction as fold change to that obtained using Ad/CMV/Luc facilitated the comparison without interference from differences between Ad permissiveness of different cell lines. Unlike Her-2 activity, survivin promoter displayed very strong activity as seen from luciferase expression levels in various cell lines.

Chapter 6: Transcriptional and Transductional Targetig 373

Work initiated but not completed in this study

Since the ultimate aim was to direct PNP gene expression specifically to cancr cells, an effort was initiated to arm this virus with a suicide gene, PNP to mediate GDEPT. The successful construction of the plasmid, pAd.BGH.Sur.PNP is reported in this study, however due to a limited time frame virus characterisation could not be performed.

However, based on the strength and selectivity of survivin promoter shown by reporter gene based analyses, it may be expected that after its functional characterization, this virus will restrict the expression of PNP gene in survivin positive cells leading to significant tumour destruction.

Further, to improve the efficiency of gene therapy in situ, the concept of selective Ad replication (virotherapy; CRAds, oncolytic Ads) was also explored. To make these Ad vectors, a number of shuttle vectors that contain expression cassettes containing Ad replication-essential gene E1 under the control of Her-2/neu or survivin promoter were developed (List of plasmids provided in Appendix III; construction methodology is out of the scope of this study (Her-2 neu Oncolytic, Appendix XI and survivin Oncolytic

Appendix XII). In addition to PNP-GDEPT mediated cell killing, localised replication of

Ad vector would lead to selective killing of cancer cells.

Finally, to ensure the safety of these viruses, once the specificity of these transcriptionally targeted vectors is proven, these will then be transductionally targeted to Her-2/neu overexpressing cells by insertion of Her-2 affibody in the viral capsid. The insertion of genetic elemnst that lead to Her-2 affibody insertion in the viral capsid will

Chapter 6: Transcriptional and Transductional Targetig 374 be done in collaboration with Dr Leif Lindholm and Dr Maria Magnusson (from

Sweden). Given that some cancers show a correlation between expression of survivin and Her-2 neu proteins (results from this study and others especially breast cancer

(1014-1016), it may be expected that these viruses, once characterised and proven preclinically will ultimately achieve a greater therapeutic relevance.

Chapter 7: Summary and Perspectives 375

SUMMARY AND PERSPECTIVES

Chapter 7: Summary and Perspectives 376

Summary and Perspectives

The clinical failure of cancer therapy is often related to the heterogeneous and ‘robust’ nature of the disease which cannot be attributed to a single gene, mechanism or pathway. In this study, we especially focussed on Ovarian and Prostate cancer as these represent one of the most common types of cancers in men or women and are currently incurable when in advanced stage or when disease reoccurs after traditional treatments.

While at this stage the understanding of specific gene changes contributing to the continued growth, survival or metastasis of these two types of cancers is limited, the genetic and phenotypic heterogeneity is an established fact. The extent of this heterogeneity is evident from considerable variability in the phenotypes encountered even within one individual. Not surprisingly, single agent therapies have not met our expectations especially, with regards to advanced drug resistant disease and clinical trends from the last 10 years have confirmed this. Not only the efficacy of treatments needs to be improved significantly, but it is now imperative to minimise the side effects for better patient management and improved quality of life. In this context, combining rationale based therapies to treat cancers would be a viable and the most logical approach. Hence, the primary object of this study was to explore novel synergistic combination regimens with the primary aim to target ovarian and prostate cancer heterogeneity.

The biggest issue with progress of new therapies to the clinic is that often the patients that enrol are undergoing chemotherapy and are in relatively advanced stages of the disease. Treatments that can synergise with traditional therapies would have the best

Chapter 7: Summary and Perspectives 377 chance of success. Further, disease recurrence often features after treatments such as androgen ablation in PC and chemotherapy in OC and is essentially incurable. Keeping these issues in mind, in this study, synergistic interactions between the traditional chemotherapy (for OC and PC) and a new, as yet clinically unexplored, therapy based on PNP-GDEPT were explored invitro in multi-drug resistant OC cell lines and in vivo in androgen ablation resistant PC represented by human PC-3 and RM1 cells. The idea was to combine potent insitu amplification of cell-killing (shown in this study and previously in our laboratory) engendered by PNP-GDEPT/Fludrabine phosphate

(Fludara is FDA approved for clinical use) with cytotoxicity of Taxotere (only chemotherapeutic with activity against late stage PC) and in case of OC, with Taxotere and carboplatin (standard form employed for chemotherapy of OC patients). Given the different mechanisms of actions by the three modalities, it was anticipated that a larger and more heterogeneous population of cells will be targeted.

With respect to different forms of OC (a chemo-sensitive disease), the fate of most advanced stage patients is decided by taxanes and platinum compounds either alone or in combination, however, with limited success. This is mainly attributed to the emergence drug resistance. In this context, the potential of these combined with molecular therapy engenedered by PNP-GDEPT was extensively explored in cell lines representing multidrug resistant phenotypes (SKOV-3 and OVCAR-3). Evaluations of synergies were based on a widely accepted method developed by Chou and Talalay for both PC and OC studies. The synergies between PNP-GDEPT were significant in PC and OC cell lines and the tri-model synergies were the strongest in OC cells. This

Chapter 7: Summary and Perspectives 378 clearly suggested the possibility of generalised efficacy of the combination regimens. It is plausible to predict that this combination has the potential for efficacy against other types of cancers that display some level of sensitivity to any of the drugs. A significant observation was that the levels of synergies were higher especially, when PNP-GDEPT was part of the combined regimens.

Hence, for the first time, the molecular changes underlying PNP-GDEPT-mediated inhibition of DNA/RNA synthesis were explored by shotgun proteomics based approach, which is a fast but reliable approach. This was also shown by western blot based validation (PARP upregulation) in this particular study. The data clearly suggested a shutdown of most metabolic pathways at 48 h post PNP-GDEPT treated OC cells. Importantly, a downregulation of various proteins that are associated with cancer carcinogenesis and drug detoxification (resistance) was indicated which further gave credence to its selection for this regimen. A clear role of modulated pro and anti- apoptotic proteins, especially involving mitochondrial pathway of apoptosis, was suggested subsequently by our western blotting data and an enhancement of these changes were shown when it was combined with Taxotere and/or carboplatin. Hence, this clear shift towards apoptosis indicated the potential of this combination therapy encouraging our next move to its preclinical evaluation. Given the pan-synergies obtained in all PC and OC lines, it was postulated that similar mechanism may play a role in PC cells. Further, in comparison to OC, immunocomptent models of PC are better characterised. This coupled with our previous expertise in invivo PC models; this evaluation was conducted in subcutaneous immnunodeficient mouse model of human

Chapter 7: Summary and Perspectives 379

PC (PC-3 cells) and orthotopic immunocompetent mouse model of murine PC with lung pseudometastases (RM1). Our ability to generate reliable data using these models was further supported by the fact that preclinical evaluations showing the promise of PNP-

GDEPT done in our laboratory have formed the basis of approval for PNP-GDEPT evaluations in a phase I trial in late stage PC patients. When in vitro synergies were tested between PNP-GDEPT and Taxotere, very high levels of synergies and dose reduction index were achieved in androgen insensitive PC-3 and RM1 cells. This translated very well to evaluations in both, immunocompetent and immnunodefficient models of PC. A suboptimal dose of both together, resulted in reduction of local tumour growth in both mouse models suggesting its potential for efficacy in immunocompromised patients. Improved systemic effects showed that combined use can harness a higher level of apoptosis and increased infiltration of immune cells, signifying its clinical advantage. Most important observation was that while combined efficacy was synergistic, the combined toxicities were not additive. This was shown by a lack of toxicity to kidney/liver and no additional weight loss in combination treated mice (in both models). Finally, involvement of immune system (enhancement of immune infiltration by lymphocytes and macrophages) and long term survival benefit were the final clinchers and suggested the future prospects of this combination regimen to treat local and advanced stage PC in immunocompromised patients.

Hence, overall, the synergies between Adenovirally delivered PNP-GDEPT and

Taxotere were definitively shown for the first time in preclinical models of PC. Given that PNP-GDEPT is likely to be locally delivered in the clinic, there is a good

Chapter 7: Summary and Perspectives 380 possibility for these data to be extrapolated to the clinic. With recent concerns with high immunogenecity of Adenoviruses, development of these vectors to safely and effectively target the gene expression only to PC cells (if the vector disseminates out into the system) would be the next logical step.

Hence, the next phase of this study was initiated to improve the therapeutic index by transductionallly and transcriptionally targeting the Ad vector. The two targets chosen for these modifications were Her-2/neu (overexpressed in PC and OC) and survivin,

(overexpressed in OC and PC and is known to be stimulated by hypoxia). The ultimate aim was to make Ad vectors with PNP-gene that are 1. transcriptionally targeted to

Her-2/neu overexpressing cells (MUC1.Her-2/neu promoter) and transductionally targeted to Her-2/neu receptor (Her-2/neu affibody in the viral capsid, Collaboration with Dr Leif Lindholm, Sweden) or 2. transcriptionally targeted to survivin overexpressing cells (survivin promoter) and transductionally targeted to Her-2/neu receptor (Her-2/neu affibody). While the concomitant transductional and transcriptional targeted vectors could not be constructed due to time constraints, vectors with either modification expressing reporter genes were made and characterised. The use of Her-

2/neu (both transcriptional and transductional) and survivin (transcriptional) targeted Ad vectors limited the expression of transgenes to Her-2/neu and survivin expressing cancer cells. This is the first time that Her-2/neu promoter was specific in context of Ad vector, most likely due to effective insulation of the promoter activity from effects of

AdE1A elements. The strength of the promoter was not optimal but the ability of PNP-

GDEPT effects for insitu amplification and synergistic interaction with taxotere may be

Chapter 7: Summary and Perspectives 381 able to overcome this. Further, given the precedence in the literature and success of clinical trials, combining such specificity (Her-2/neu or survivin promoter based) with oncolytic activities of Adenoviral vectors armed with PNP-GDEPT may further improve the efficacy of these vectors. Ultimately, development of transcriptionally and transductionally targeted Oncolytic Adenovirus armed with PNP-GDEPT may be the agent for clinical applications, especially in combination with Taxotere.

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Appendix 458

APPENDIX

Appendix I: List of Antibodies used

Gene Family Antigen Source Class/Reactivity Dilutions used Supplier Bcl -2 (B cell BCL-2 (50E3) Rabbit Monoclonal IgG 1:1000 Cell Signaling Technology, USA leukaemia- 2) (anti-apoptotic) H, M, R, Mk protein family Bax (B-9): sc-7480 Mouse Monoclonal IgG2b 1:100 Cell Signaling Technology, USA (pro-apoptotic) H, M, R Bik Rabbit Monoclonal IgG 1:800 Cell Signaling Technology, USA (pro-apoptotic) H, M, R, Mk Bok (pro-apoptotic) Rabbit Monoclonal IgG 1:800 Cell Signaling Technology, USA H, M, Mk Apoptosis Caspase-3 Rabbit Monoclonal IgG 1:800 Cell Signaling Technology, USA sampler kit H, M, R Cleaved Caspase-3 Rabbit Monoclonal IgG 1:800 Cell Signaling Technology, USA H, M, R, B Caspase-7 Rabbit Monoclonal IgG 1:800 Cell Signaling Technology, USA H, M, R Cleaved Caspase-7 Rabbit Monoclonal IgG 1:800 Cell Signaling Technology, USA H, M, R Caspase-9 Rabbit Monoclonal IgG 1:800 Cell Signaling Technology, USA H only Cleaved Caspase-9 Rabbit Monoclonal IgG 1:800 Cell Signaling Technology, USA H only Apoptosis by M30-CytoDeath Rabbit Monoclonal IgG 1:50 Alexis, Peviva, Sweden Flow H, M, R Cytometry Inhibitors of Surviivn (71G4) Rabbit Monoclonal IgG 1:1000 Cell Signaling Technology, USA Apoptosis H, M, R Growth Factor C-ERBB-2 Mouse Monoclonal IgG1 1:50 Chemicon, Europe Receptor 459

Appendix 460

Appendix II: List of antibodies used for immunohistochemical detection of immune cells infiltrates, microvasculature, proliferating and apoptotic tumour cells in RM1 treated/untreated tumours

Type Detection/Purpose Antigen Specificity/Reactivity Dilutions used Supplier/Catalogue number (c/n) Primary Infiltrating T CD4+ Rat anti-mouse 1:100 BD Bioscience, c/n 550278

antibodies lymphocytes CD8a+ Rat anti-mouse 1:100 BD Bioscience, c/n 550281 Macrophages F4/80+ Rat anti-mouse 1:600 eBioscience, c/n 14-4801 Natural Killer cells AsialoGM1+ Rabbit anti-mouse 1:300 Wako, c/n 986-1000 Endothelial cells CD31+ Rat anti-mouse 1:300 BD Bioscience, c/n 550274 Cell proliferation Ki-67 Rat anti-mouse 1:30 Dako, c/n M7249 Apoptosis M-30 Cytodeath Rabbit anti-mouse 1:50 Alexis Biochemical, c/n (with biotin) ALX 804590B-7200 Secondary Rabbit anti-rat 1:200 Vector Laboratories, CA, antibodies Goat anti-rabbit 1:200 USA Additional requirements Menzel Superfrost UltraPlus slides for immunostaining (Supplier: HD Scientific c/n 41800 72P3) Blocking buffer: PBS containing 2% BSA, 0.2% Tween 20 PBS wash buffer: 0.1% Tween20/PBS

Avidin/Biotin Blocking Kit (Biocare c/nAB972H) 460 Liquid DAB (DAKO), 1:50 in substrate buffer

Appendix 461

Appendix III: List of plasmids used in this study

Name Description/genes Source/Comment pBS-SK/MEEP-tk Her-2 neu promoter with MucI enhancer; Ampicillinr (Ampr) A kind gift from Dr. Ian McNeish, pBS-SK/MucI MucI promoter; Ampr London,UK pTMEEP-CAT Her-2 neu promoter with MucI enhancer; Ampr pSc.CXCR-4.E1 CXCR-4 promoter deriving gene E1; Kanr Prof. David Curiel, University of Alabama, USA (collaborator) pSurvivin-269 Survivin promoter- 269bp; Ampr Purchased from Dr. Feng Zhi Li, Roswell Park Ins., NY, USA pBSK-PNP Suicide gene, PNP; Ampr Dr Khatri (originally from CSIRO, pSV40 Stop signal, BGH; Ampr North Ryde, NSW) pGl3 Basic Multiple cloning site at 5’ end of Luciferase gene; Ampr Promega Corporation, WI, USA pGl3.BGH (Not/SmaI) BGH cloned at 5’ end of Luc gene; Ampr Constructed in this study pGl3.BGH Her-2 Luc Her-2 promoter cloned between BGH and Luc; Ampr pGl3.BGH Survivin Survivin promoter cloned between BGH and Luc; Ampr pShuttle (pSc.) Shuttle vector with multiple cloning site; Kanamycinr (Kanr) Adeasy Kit, Stratagene, TX, USA 461

Appendix 462

pSc.MucI/Her- Shuttle plasmid with Her-2 neu promoter deriving Luc gene; BGH Constructed in this study 2.Luc.SV40 insulation on 5’ and SV40 stop signal after Luc gene; Kanr pSc.BGH.Her-2.E1 Shuttle plasmid with Her-2 neu promoter deriving E1 gene; used for construction of Her-2 based oncolytic vector; Kanr pSc.Survivin.Luc.SV40 Shuttle plasmid with Survivin promoter deriving Luc gene; BGH insulation on 5’ and SV40 stop signal after Luc gene; Kanr pSc.BGH.Survivin.E1 Shuttle plasmid with Her-2 neu promoter deriving E1 gene; used for construction of Her-2 based oncolytic vector; Kanr pAdeasy-I Ad5 plasmid backbone used in homologous recombinations; Ampr Stratagene Adeasy Kit, TX, USA pAd.Her-2.Luc Ad plasmid with Her-2 neu promoter deriving the expression of Luc Constructed in this study gene; Kanr pAd.Survivin.Luc Ad plasmid with Survivin promoter deriving the expression of Luc gene; Kanr pAd.Survivin.E1 Ad plasmid with Survivin promoter deriving E1 gene; an oncolytic vector; Kanr pAdDelE1GFP.zz Her-2 neu targeted Ad; GFP driven by CMV promoter; Ampr Dr. Lief Lindholom and Dr Maria pAdDelE1CMV.Luc.zz Her-2 neu targeted Ad; GFP driven by CMV promoter; Ampr Magnusson, University of pAdDelE1Survivin.Luc.zz Her-2 neu targeted Ad; GFP driven by CMV promoter; Ampr Gothenburg, Sweden) (collaborator) 462 * All plasmids were grown at a miniprep level, screened for respective restrictions digestions and positive clones were grown to maxiprep levels

463

Appendix IV: Diagrammatic description of AdEasy System

MCS: NotI, XhoI, Xba, EcoRV, HindIII MCS: KpnI, SalI, NotI, XhoI, HindIII, EcoRV PacI PmeI PacI PmeI

L-lTR ES L-lTR ES CMV pA right arm homology right arm homology r r pShuttle pShuttle.CMV Kana Kana ~6.6kb ~7.4kb left arm homology arm left homology arm left pBR322 ori R-lTR pBR322 ori R-lTR

PacI PacI

PacI ClaI

R-lTR pBR322 ori Ampr left arm homology right arm homology

pAdEasy-I Vector ~33.4kb

Ad5, E1 and E3 deleted

Source - Stratagene

464

r e

I t

d BGH+Her-2+Luc+SV40polyA ~3000

cu in

I C

U d

I H t

N Luc+SV40polyA ~2000

S p

BGH+MucI/Her-2 ~1100

k r

L left arm homology arm left PmeI pA SalI, BamHI R-lTR Luciferase right arm homology right PacI HindIII Her-2 : Restriction digests to confirm integrity of pSc.BGH.MUCI.Her-2.Luc MUCI enhancer XhoI BGH pBR322 ori pBR322 pShuttle.BGH.MucI-Her-2.Luc NotI ES Appendix V

L-lTR

Kana r PacI Appendix VI : Restriction digest to confirm integrity of pSc.BGH.Survivin.Luc

I I II IV dI dI I r n e MCS: KpnI, NheI, SmaI, XhoI, BglII, HindIII n o i i h d dIII H d H X n / NotI XbaI SalI, BamI / / i o a t t l h o o H r / e X f1 ori pA Luciferase pA o p cN cN h c i i u s s X a L a e . rHy l B B t r e

r t 3 k 3 u Su r L L . PGL3 Basic h c

Amp G S G S Ma p p p p

MCS: NotI, XhoI, Xba, EcoRV, HindIII PacI PmeI

L-lTR ES right arm homology r pShuttle Kana left arm homology arm left pBR322 ori R-lTR PacI ~270bp XhoI, BglII NotI HindIII PacI SalI, BamHI ~200bp PmeI L-lTR ES BGH Survivin Luciferase pA right arm homology r

Kana pShuttle.BGH.Survivin.Luc 465 left arm homology arm left pBR322 ori R-lTR

PacI Appendix VII: Confirmation of integrity of pBKS.PNP and pSc.BGH.Sur.Luc (restriction digest)

c V u I r .L e r d u d P .S la H r N I e .P I G I I B I I yp S H . I d c d H K m S in B a r p in e p /B t H /H t I / o k u t h r u e c o a c f n X n M U N M U

PNP gene : ~750bp ~750bp Survivin + BGH : ~600bp ~600bp Survivin: ~270bp ~270bp 466

pBKS.PNP pSc.BGH.SUR.Luc Appendix VIII: Restriction confirmation of pSc.BGH.Sur.PNP (I)

XhoI, BglII PacI NotI SalI, BamHI PmeI pSc.BGH.Sur.LUC.SVpolyA pSc.BGH.Sur.PNP.SVpolyA L-lTR ES BGH Survivin PNP pA right arm homology (XhoI/SalI) (XhoI/SalI)

r Survivin+Luc+polyA Survivin+PNP+polyA

Kana pShuttle.BGH.Survivin.PNP 270+1750+250 = ~2300bp 270+750+250 = ~1300bp left arm homology arm left pBR322 ori R-lTR pSc.Sur.Luc 1 2 3 4 5 6 7 8 9 10 11 12

PacI

~2300bp

~1300bp ~1300bp

Hyperladder III

Clone # 7 and 11 were confirmed as pSc.BGH.Sur.PNP.SVpolyA. 467 Further analysis was required to check the exact orientation of PNP gene (see appendix IX) Appendix IX: Restriction digest to confirm integrity of pSc.BGH.Sur.PNP (II) XhoI/SpeI

1) 3) 4) (#7) (#1 (#1 (#1 pSc.BGH.Sur.Luc.SVpolyA I uc I L pSc.BGH.Sur.PNP.SVpolyA I . .PNP .PNP .PNP .PNP (XhoI/SpeI) r ur ur ur ur ur (XhoI/SpeI) de .S S S S S Shouldn’t cut d . . . . H Survivin + fragment of PNP la H H H H No SpeI site in pSc vector r G G G G G Right orientation: 270 +10bp ~ 280bp e B p . .B .B .B .B y c c c c c Wrong orientation: 270 +740bp ~ 1000bp S S S S S H p p p p p PNP

MfeI Blunt BamHI Blunt

X SpeI ~1000bp ~280bp ~280bp

Clone # 7, 11 and 14 were chosen: A 280bp fragment upon XhoI/SpeI 468 suggests that survivin promoter and PNP gene are in right orientation. c u L . P c 2 u N - r P L . . n Appendix X: Restriction digests to confirm integrity n He i i . v v I i I i I r v C v I of pAd.BGH.MUCI.Her-2.Luc, pAd.BGH.Sur.Luc ke U r r Sur a Sur M de I d m y a s l SphI digest and pAd.BGH.Sur.PNP a GH. a GH. GH. r B B B bd E pe d. d. d- d. based screening m a Hy pA pA L pA pA A B

Predicted gel images for SphI restriction pattern of recombinant Ad plasmids

pAd-EasyI pAd.BGH.MUCI.Her-2.Luc

Panel A: Predicted gel images for SphI restriction pattern of recombinant pAd.BGH.MUCI.Her-2.Luc (generated by NEB cutter).

Similar profiles were generated for the other plasmids (not shown) Panel B: Gel image showing Sph1 restriction profiles of 469 different recombinant Ad plasmids, for comparison , parent Ad plasmid pAd-EasyI is included. 0.7% Agarose gel was used. 470

Appendix XI: A schematic representation for the development of Ad.BGH.Muc1.Her-2.E1 (Oncolytic)

PacI

L-lTR ES BGH MUCI Her-2 AdE1 Enhancer Promoter Kana pShuttle.BGH.MUCI-Her-2.E1

pBR322 PacI left arm homology right arm homology R-lTR

ClaI

R-lTR pBR322 ori Amp left arm homology right arm homology PacI Regions of homologous recombinations

pAdEasy-I Electroporation in BJ5183 cells

E1 and E3 deleted

PacI digestion

PacI PacI

L-lTR ES BGH MUCI Her-2 AdE1 Adenoviral DNA R-lTR Enhancer Promoter

Transfect AD-293 cells with Lipofectamine

Virus production

Ad.BGH.Muc1.Her-2.E1

Oncolytic 471

Appendix XII: A schematic representation for the development of Ad.Survivin.E1 (Oncolytic)

PacI

L-lTR ES BGH Survivin AdE1 Promoter Kana pShuttle.BGH.MUCI-Her-2.E1

pBR322 PacI left arm homology right arm homology R-lTR

ClaI

R-lTR pBR322 ori Amp left arm homology right arm homology PacI Regions of homologous recombinations

pAdEasy-I Electroporation in BJ5183 cells

E1 and E3 deleted

PacI digestion

PacI PacI

L-lTR ES BGH Survivin AdE1 Adenoviral DNA R-lTR Promoter

Transfect AD-293 cells with Lipofectamine

Virus production

Ad.BGH.Survivin.E1 Oncolytic