Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

Ambber Renee Ward

Bachelor of Science (Biomedical) (Honours) Bachelor of Medical Science (Pathology) Bachelor of Psychology (Honours) Bachelor of Behavioural Science

A thesis submitted for the degree of Doctor of Philosophy at The University of Queensland in 2020 School of Medicine and QIMR Berghofer Medical Research Institute

Abstract

Triple negative breast cancer (TNBC) represents 10-20% of all breast cancers and is defined by the absence of estrogen receptors, progesterone receptors and absence of human epidermal growth factor receptor 2 amplification. TNBC is the most aggressive of the subtypes with the poorest prognosis and highest rates of recurrence within 5 years of diagnosis. The standard of care treatment for TNBC is systemic chemotherapy. The development of chemotherapy resistance is a common problem, with relapse rates up to 38% with less than 6 months median survival. Relapse is often associated with aggressive metastatic disease that no longer responds to chemotherapy.

RAD51 recombinase is an evolutionarily conserved protein that plays a critical role the homologous recombination (HR) pathway, which faithfully repairs DNA double-strand breaks and damaged replication forks. In normal cells RAD51 expression is tightly regulated and its activity promotes high fidelity repair and genome integrity. However, dysregulation and overexpression of RAD51 is reported in many human malignancies, including TNBC, and is implicated in resistance to DNA damaging radiotherapy, chemotherapy and PARP inhibition and the promotion of tumour progression and metastasis. Wiegmans et al. (2014) identified that RAD51 is required for spontaneous metastasis in TNBC and that RAD51 expression level differentially regulates the expression of several CEBPβ target genes implicated in tumour progression and metastasis. Furthermore, co-immunoprecipitation identified that RAD51 and CEBPβ interact in situ. To elucidate a possible new non-canonical role for RAD51 in transcriptional regulation we set out to gene edit RAD51 with the aim of generating TNBC model cell lines expressing; (1) HR deficient, RAD51 K133R knock-in mutation, (2) RAD51 knockout and (3) CEBPβ knockout. This was a novel approach as RAD51 is required for CRISPR-Cas9 editing and there are no published studies of RAD51 gene editing. RAD51 knock-out was initially successful in MDA-MB-231 cells but could not be stably maintained by cells in culture, likely due to RAD51 being a core fitness gene in this cell line. CEBPβ was successfully knocked out in MDA-MB-231 cells, however difficulty culturing cells from a single cell or at low density prevented isolation of pure clones with CEBPβ knock-out in other TNBC cell lines. We concluded that as an essential cancer gene RAD51 modulation by small molecule inhibition or transient transfection would be more suitable methods for studying RAD51 function in TNBC.

i Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

To identify a novel small molecule RAD51 inhibitor we evaluated a library of quinazolinone derivatives and analysed structure activity relationships. Among these compounds we identified compound 17, which binds directly to RAD51. We hypothesized that inhibiting RAD51 in TNBC cell lines would block repair by HR, thereby sensitising tumour cells to DNA damaging irradiation and chemotherapy. We found that compound 17 inhibits HR in MDA-MB-231 cells by ~7-fold. Compared to the base compound (B02), compound 17 exhibited up to ~8-fold improved growth inhibition in a panel of TNBC cell lines and 2.5-fold increased inhibition of DNA damage-induced RAD51 foci formation. Additionally, compound 17 significantly enhanced sensitivity to DNA damaging radiotherapy and chemotherapies, suggesting a potentially targeted therapy for TNBC.

A known mechanism by which cancer cells acquire chemoresistance is by deregulation of the DNA damage response, a process that can also create dependencies on specific DNA repair pathways. The clinical success of PARP inhibitors in BRCA mutant TNBC highlights the potential of targeting these dependencies therapeutically to induce synthetic lethality. Understanding DNA repair deficiencies is therefore vital for appropriate therapeutic choices. This is clinically utilised with homologous recombination deficiency (HRD) scoring based on TNBC mutational load, with a positive HRD status predicting PARP inhibition- mediated synthetic lethality. While genetic instability provides a snapshot of deregulated DNA damage response that drives chemotherapy resistance, we have analysed the functional consequences of repair deregulation. Here we show adaption to frontline TNBC chemotherapy combination doxorubicin and docetaxel. We find that chemoresistance results in enhanced genome instability, reliance upon DNA repair mediated by RAD51 and changes in gene expression profile guided by c-ABL and p73 and loss of p53 and BRCA1. Further we find that targeting RAD51 with our small molecule inhibitor can resensitize cells to docetaxel and doxorubicin and overcome DNA damage induced chemoresistance.

ii Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

Declaration by author This thesis is composed of my original work, and contains no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution by others to jointly-authored works that I have included in my thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical assistance, survey design, data analysis, significant technical procedures, professional editorial advice, financial support and any other original research work used or reported in my thesis. The content of my thesis is the result of work I have carried out since the commencement of my higher degree by research candidature and does not include a substantial part of work that has been submitted to qualify for the award of any other degree or diploma in any university or other tertiary institution. I have clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library and, subject to the policy and procedures of The University of Queensland, the thesis be made available for research and study in accordance with the Copyright Act 1968 unless a period of embargo has been approved by the Dean of the Graduate School.

I acknowledge that copyright of all material contained in my thesis resides with the copyright holder(s) of that material. Where appropriate I have obtained copyright permission from the copyright holder to reproduce material in this thesis and have sought permission from co-authors for any jointly authored works included in the thesis.

iii Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

Publications included in this thesis No publications included.

Submitted manuscripts included in this thesis No manuscripts submitted for publication.

Other publications during candidature Ivanova, E., Ward, A., Wiegmans, A. P., & Richard, D. J. (2020). Circulating Tumour Cells in Metastatic Breast Cancer: From genome instability to metastasis. Frontiers in Molecular Biosciences, 7, 134.

Ward, A., Dong, L., Harris, J. M., Khanna, K. K., Al-Ejeh, F., Fairlie, D. P., Liu, L. (2017). Quinazolinone derivatives as inhibitors of homologous recombinase RAD51. Bioorganic and Medicinal Chemistry Letters, 27(14), 3096-3100.

Wiegmans, A. P., Yap, P.-Y., Ward, A., Lim, Y. C., & Khanna, K. K. (2015). Differences in expression of key DNA damage repair genes after epigenetic-induced BRCAness dictate synthetic lethality with PARP1 inhibition. Molecular Cancer Therapeutics, 14(10), 2321-2331.

Manuscripts in preparation Wiegmans, A. P., Ward, A., Ivanova, E., Van Oosetrhout, R., Nones, K., Sadowski, M., Kelly, G., Morrical, S., Lee, J. S., and Richard, D (2020). c-ABL drives frontline chemotherapy chemoresistance via DNA repair crisis and switch to homologous recombination repair in triple negative breast cancer.

Contributions by others to the thesis Dr Ligong Liu and Lilong Dong (Universitiy of Queensland, Institute of Molecular Biosciences) synthesised the quinazolinone compounds described in Chapter 4 Results 4.2.2 and depicted in Figures 4.3 and 4.4..

Dr Johnathan Harris (School of Life Science, Queensland University of Technology) In- silico docking study for RAD51 inhibitor optimisation described in Chapter4 Results 4.2.1 and depicted in Figure 4.2.

Dr Katia Nones (Medical Genomics Laboratory, QIMR Berghofer) conducted SNP array analysis described in chapter 5 Results 5.2 and depicted in Figures 5.5C-D, 5.5D-H.

iv Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

Ekaterina Ivanova and Romy Van Oosetrhout (Tumour Microenvironment Laboratory, QIMR Berghofer) assisted with western blots depicted in Chapter 3 Results, Figures 3.7 and 3.8.

Statement of parts of the thesis submitted to qualify for the award of another degree No works submitted towards another degree have been included in this thesis.

Research Involving Human or Animal Subjects No animal or human subjects were involved in this research.

v Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

Acknowledgements I am grateful to Dr Jason Lee who has provided me with support throughout my PhD and welcomed me into the Epigenetics and Disease Laboratory.

I am thankful to past and present team members and lab buddies Ekaterina, Romy, Jamie, Esdy, Mariska, Jacinta, Fares, YC, Greg and Francesco for their guidance and friendship over the years.

I would especially like to thank my primary supervisor Dr Adrian Wiegmans for his many words of encouragement, support and constructive criticism.

I am also very grateful to my husband Tom and children Joshua and Isabelle, who are interested (or pretend to be interested) in hearing about my successes and failures in the lab.

vi Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

Financial support No financial support was provided to fund this research.

Keywords Triple Negative Breast Cancer, RAD51, DNA repair, DNA damage response, molecular targets, chemoresistance, CRISPR.

Australian and New Zealand Standard Research Classifications (ANZSRC) ANZSRC code: 111201 Cancer Cell Biology, 40% ANZSRC code: 111203 Cancer Genetics, 20% ANZSRC code: 111204 Cancer Therapy, 10% ANZSRC code: 111207 Molecular Targets, 30%

Fields of Research (FoR) Classification FoR code: 1112 Oncology and Carcinogenesis, 100%

vii Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

Table of Contents

Abstract ...... i Table of Contents...... viii List of Figures ...... xii List of Tables ...... xv List of Abbreviations ...... xvi Chapter 1: Literature Review ...... 1 1.1 GENERAL INTRODUCTION ...... 1 1.2 BREAST CANCER CLASSIFICATION ...... 4 1.2.1 Histological Subtypes...... 4 1.2.2 Intrinsic Subtypes ...... 4 1.2.3 Surrogate Intrinsic Subtypes ...... 7 1.3 TRIPLE NEGATIVE BREAST CANCER ...... 9 1.3.1 Heterogeneity of TNBC ...... 9 1.3.2 Current standard of care for TNBC ...... 11 1.3.3 Clinical Outcomes ...... 12 1.4 THE DNA DAMAGE RESPONSE IN TNBC ...... 16 1.5 THE STATUS OF DNA DAMAGE REPAIR PATHWAYS IN TNBC ...... 19 1.5.1 Direct Repair ...... 19 1.5.2 Base Excision Repair and DNA Single-Strand Break Repair...... 19 1.5.3 Nucleotide Excision Repair ...... 22 1.5.4 Mismatch Repair ...... 24 1.5.5 Repair of DSBs by End-Joining Pathways ...... 27 1.5.5.1 Classical NHEJ ...... 27 1.5.5.2 Alternative NHEJ ...... 28 1.5.6 Repair of DSBs by Homologous Recombination ...... 30 1.5.6.1 Canonical HR ...... 31 1.5.6.2 Non-Canonical HR...... 31 1.5.6.3 HR Deficiency ...... 34 1.5.7 DNA Damage Tolerance Mechanisms ...... 34 1.6 THE SIGNIFICANCE OF RAD51 IN CANCER ...... 38 1.6.1 Overview of RAD51 Structure, Function and Activity ...... 38 1.6.2 RAD51 Overexpression in Cancer and Tumour Cell Lines ...... 38 1.6.3 RAD51 Overexpression Associated with Elevated and Aberrant Recombination ...... 39 1.6.4 RAD51 Overexpression associated with Worse Clinical Outcomes...... 42 1.6.5 Targeting RAD51 for Cancer Therapy ...... 45 1.7 CHEMOTHERAPY RESISTANCE IN TNBC ...... 48 1.7.1 Intrinsic versus Acquired Resistance ...... 48 1.7.2 Cancer Stem Cells and EMT...... 49 1.7.3 Upregulation of Drug Efflux Pumps ...... 50 1.7.4 BRCA1 Mutations and Taxane Resistance ...... 50 1.7.5 p53 Mutations ...... 52 1.7.6 Upregulation of Anti-apoptotic BCL-2 Proteins ...... 53 1.7.7 Altered Expression of p53 Homologues; p63 and p73 ...... 53 1.8 HYPOTHESIS AND AIMS OF RESEARCH ...... 57

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Chapter 2: Materials and Methods ...... 58 2.1 CELL LINES ...... 58 2.2 MEDIA AND REAGENTS FOR CELL CULTURE, TRANSFECTION AND TRANSDUCTION ...... 58 2.3 REAGENTS AND MEDIA FOR BACTERIAL GROWTH, TRANSFORMATION AND SELECTION ...... 59 2.4 DRUGS AND INHIBITORS ...... 59 2.5 ANTIBODIES ...... 60 2.6 CHEMICAL REAGENTS ...... 61 2.7 BUFFERS AND SOLUTIONS ...... 62 2.7.1 TAE buffer ...... 62 2.7.2 MTT reagent ...... 62 2.7.3 Propidium iodide (PI) staining solution ...... 62 2.7.4 Cytoskeleton buffer ...... 62 2.7.5 FBT buffer ...... 63 2.7.6 Whole cell lysis buffer ...... 63 2.7.7 Whole cell lysis buffer with protease and phosphatase inhibitor ...... 63 2.7.8 SDS loading buffer (5×) ...... 63 2.7.9 Tris-glycine running buffer (10×) ...... 63 2.7.10 Towbin transfer buffer (1×) ...... 63 2.7.11 TBST (10×) ...... 63 2.8 MOLECULAR BIOLOGY REAGENTS ...... 64 2.9 KITS ...... 64 2.10 OLIGONUCLEOTIDES ...... 65 2.10.1 RAD51 K133R ssODN repair template sequence (5`->3`) ...... 65 2.11 BIOCHEMISTRY METHODS ...... 69 2.11.1 Surface plasmon reasonance ...... 69 2.11.1.1 Immobilization of RAD51 ...... 69 2.11.1.2 Small molecule interactions with RAD51 ...... 69 2.11.2 EMSA assays ...... 70 2.11.2.1 RAD51 binding to ssDNA ...... 70 2.11.2.2 DNA Binding Competition Assay ...... 70 2.12 CELL BIOLOGY METHODS ...... 70 2.12.1 Cell culture ...... 70 2.12.2 Cell seeding, drug, inhibitor and irradiation treatments ...... 71 2.12.3 Determination of drug and inhibitor IC50 concentrations ...... 71 2.12.4 MTT assay ...... 71 2.12.5 MTS assay ...... 72 2.12.6 IncuCyte Zoom imaging ...... 72 2.12.7 Flow cytometry cell cycle analysis ...... 72 2.12.8 Flow cytometry apoptosis analysis ...... 73 2.12.9 Non-homologous end joining assay ...... 73 2.12.10 Homologous recombination assay ...... 73 2.12.11 Immunofluorescence staining and imaging ...... 73 2.12.12 Viability assays involving p73 inhibition and p53 overexpression ...... 74 2.12.13 Metaphase spread analysis ...... 75 2.13 BACTERIAL METHODS ...... 75 2.13.1 Transformation of DNA into competent cells ...... 75

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2.13.2 Large scale plasmid preparation ...... 75 2.13.3 Plasmid DNA purification ...... 75 2.14 MOLECULAR BIOLOGY METHODS ...... 76 2.14.1 Generation Cas9 expressing TNBC cell lines ...... 76 2.14.2 CRISPR target guide sequence cloning protocol ...... 76 2.14.3 Lentivirus production ...... 77 2.14.4 Transduction...... 77 2.14.5 Transfection...... 77 2.14.6 DNA extraction and purification from adherent cells ...... 78 2.14.7 Preparing DNA agarose gels ...... 78 2.14.8 Loading and running agarose gels ...... 78 2.14.9 DNA extraction and purification from agarose gels ...... 79 2.14.10 High fidelity PCR ...... 79 2.14.11 PCR product purification ...... 80 2.14.12 Sanger sequencing ...... 80 2.14.13 RNA extraction ...... 80 2.14.14 cDNA synthesis from RNA ...... 80 2.14.15 Quantitative reverse transcriptase PCR (qRT-PCR) ...... 81 2.14.16 DDR microarray ...... 81 2.15 PROTEIN METHODS ...... 82 2.15.1 Protein extraction ...... 82 2.15.2 Protein estimation ...... 82 2.15.3 Western blotting and wet transfer ...... 82 2.15.4 Immunoblot staining protocol and image acquisition ...... 82 2.15.5 Quantification of western blots ...... 83 2.16 STATISTICAL ANALYSIS ...... 83 Chapter 3: Gene editing RAD51 with CRISPR-Cas9 for novel functional studies84 3.1 INTRODUCTION ...... 84 3.1.1 Aim and rationale ...... 87 3.1.2 Overview of CRISPR-Cas9 ...... 87 3.2 RESULTS ...... 90 3.2.1 Generation Cas9 expressing TNBC cell lines ...... 90 3.2.3 Selection of target sequences for gRNA design ...... 92 3.2.3.1 Target sequences for CEBPβ knockout ...... 92 3.2.3.2 Target sequences for RAD51 knockout ...... 92 3.2.3.3 Target sequence and DNA repair template design for editing RAD51 K133R ...... 92 3.2.4 Sequence validation of gRNAs ...... 97 3.2.5 Validation of RAD51 knockdown in polyclonal cell populations ...... 99 3.2.6 Validation of RAD51 knockout in monoclonal cell populations ...... 99 3.2.7 Validation of CEBPβ knockdown in polyclonal cell populations ...... 102 3.2.8 Validation of CEBPβ knockout in monoclonal cell populations ...... 102 3.2.9 Optimisation PCR conditions for CRISPR gene editing validation ...... 104 3.2.10 Validation of HR-directed modifications by Sanger sequencing ...... 107 3.2.11 Timed delivery of RAD51 R133K gRNA ...... 109 3.2.12 Investigation of an alternative strategy to achieve RAD51 K133R mutation ...... 111 3.3 DISCUSSION ...... 113 3.3.1 Difficulties establishing monoclonal cell populations ...... 113 3.3.2 Low knock-in efficiency ...... 113 3.3.3 Negative selection of gRNAs targeting essential genes ...... 114 3.3.4 Conclusions and future directions ...... 117

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Chapter 4: Identification of a novel small molecule inhibitor of RAD51 ...... 118 4.1 INTRODUCTION ...... 118 4.2 RESULTS ...... 121 4.2.1 In-silico docking study for RAD51 inhibitor optimisation...... 121 4.2.2 Synthesis of B02 analogues ...... 123 4.2.3 Determination of compounds that inhibit growth of Triple Negative Breast Cancer . 128 4.2.4 Analysis of small molecule binding to RAD51 protein ...... 133 4.2.5 Functional characterisation of our lead compound ...... 137 4.2.6 Compound 17 inhibits RAD51 binding to ssDNA ...... 140 4.2.7 Compound 17 selectively inhibits repair of DSBs by HR ...... 142 4.2.8 Compound 17 enhances the anti-proliferative effect of irradiation induced DNA damage in a panel of TNBC cell lines ...... 144 4.2.9 Sensitivity to compound 17 correlates with RAD51 protein expression level in a panel of TNBC cell lines ...... 146 4.2.10 Compound 17 increases TNBC sensitivity to chemotherapy and PARP inhibition 150 4.3 DISCUSSION ...... 152 Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of taxane and anthracycline in TNBC ...... 155 5.1 INTRODUCTION ...... 155 5.2 RESULTS ...... 159 5.2.1 Establishment of resistance to doxorubicin and docetaxel in TNBC cell lines ...... 159 5.2.2 Determination of doxorubicin and docetaxel IC50 in parental and resistant TNBC cell lines ...... 160 5.2.3 P-glycoprotein drug pump is a driver of doxorubicin resistance in MDA-MB-231 Resistant cells only...... 159 5.2.4 Drug adapted cell lines show less G2/M arrest following chemotherapy treatment. 161 5.2.5 Drug adapted cell lines are resistant to chemotherapy induced apoptosis...... 163 5.2.6 Increased genomic instability is associated with chemo-resistance ...... 165 5.2.7 DSB repair is functionally more active in MD-MB-231 Resistant cell line ...... 168 5.2.8 Resistant cell lines show increased dependence on RAD51 mediated HR to survive irradiation and chemotherapy induced DSBs ...... 170 5.2.9 RAD51 inhibition combined with chemotherapy enhances DNA damage induction and DDR activation ...... 174 5.2.10 Chemotherapy induces differential DDR gene expression in sensitive and drug adapted cell lines ...... 179 5.2.11 Chemotherapy induces differential DDR protein expression in sensitive and drug adapted cell lines ...... 182 5.2.12 Depletion of p73 and restoration of WT p53 potentiate drug adapted cell lines to combination chemotherapy...... 185 5.2.13 Small molecule RAD51 inhibition restores sensitivity to chemotherapy ...... 188 5.3 DISCUSSION ...... 190 Chapter 6: General discussion and future directions ...... 194 6.1 CONCLUDING REMARKS ...... 200 References ...... 202 Appendix ...... 247

xi Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

List of Figures

Figure 1-1. Breast Cancer Incidence, Mortality and Survival, Australia. 3 Figure 1-2 Breast cancer classification. 8 Figure 1-3 Patient chemotherapy response relative to PAM50 or refined TNBCtype-4 subtyping. 15 Figure 1-4 DNA damage response pathway. 18 Figure 1-5 Base excision repair. 21 Figure 1-6 Nucleotide excision repair. 23 Figure 1-7 Mismatch repair. 26 Figure 1-8 DSB repair by end joining pathways. 29 Figure 1-9 Models of homologous recombination. 33 Figure 1-10 Homologous recombination mediated DNA Damage Tolerance Mechanisms. 37 Figure 1-11 Role of RAD51 overexpression in cancer development and progression. 41 Figure 3-1 A DNA repair defective dominant negative form of RAD51 enhances cell migration. 86 Figure 3-2 Repair outcomes following a DSB induced by CRISPR-Cas9. 89 Figure 3-3 CRISPR-Cas9 two vector lentiviral GeCKo system. 91 Figure 3-4 Canonical amino acid sequences for CEBPβ and RAD51. 94 Figure 3-5 Schematic representation of RAD51 exon 5, gRNA and ssODN donor repair template. 95 Figure 3-6 Alignment of expected and actual gRNA sequences. 98 Figure 3-7 Western blot validation of RAD51 expression in MDA-MB-231-Cas9 cells transformed with RAD51 gRNAs. 100 Figure 3-8 Western blot validation of RAD51 expression in MDA-MB-436-Cas9 cells transformed with RAD51 gRNAs. 101 Figure 3-9 Western blot validation of CEBPβ expression in MDA-MB-231-Cas9 cells transformed with CEBPβ gRNAs. 103 Figure 3-10 PCR outcomes with CEBPβ primers. 105 Figure 3-11 Optimisation of PCR conditions for RAD51 primers. 106 Figure 3-12 Sanger sequencing of RAD51 expressing cells lines transformed with gRNA KR+K133R repair template. 108 Figure 3-13 Evaluation of timed delivery of gRNA KR+K133R repair template in MDA-MB-231-Cas9 cells. 110 Figure 3-14 RAD51 knockout could not be sutained in MDA-MB-231 cells. 112 Figure 3-15 RAD51 protein-protein interactions with core essential proteins. 116

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Figure 4-1.Structurally different RAD51 inhibitors, including B02. 120 Figure 4-2 Docking of B02 in the ATPase domain of a homology model of human RAD51. 122 Figure 4-3. Structure of quinazolinone derivatives. 125 Figure 4-4 Synthesis of compound library. 126 Figure 4-5. MTT assessment of proliferation inhibition and sensitisation to irradiation. 130 Figure 4-6. Small molecule screening using surface plasmon resonance. 134 Figure 4-7. Favourable 1:1 binding interactions with RAD51 identified by SPR analysis. 136 Figure 4-8. Compound 17 inhibits irradiation induced RAD51 foci. 138 Figure 4-9. Compound 17 inhibits irradiation induced RAD51 foci in a dose- dependent manner. 139 Figure 4-10 Compound 17 inhibits RAD51 binding to ssDNA. 141 Figure 4-11 Compound 17 selectively inhibits repair of DSBs by HR. 143 Figure 4-12. Effect of compound 17 on TNBC cell proliferation in combination with irradiation. 145 Figure 4-13. Sensitivity to compound 17 correlates with RAD51 protein expression in TNBC cell lines. 148 Figure 4-14. Effect of RAD51 inhibition on proliferation of TNBC cell lines. 149 Figure 4-15. Compound 17 combines synergistically with DNA damaging chemotherapies and PARPi. 151 Figure 5-1. Evaluation of chemotherapy resistance in parental and drug adapted cell lines. 162 Figure 5-2 P-glycoprotein contribution to chemoresistance. 160 Figure 5-3 Cell cycle analysis of Sensitive and Resistant MDA-MB-231 and MDA-MB- 468 by flow cytometry. 162 Figure 5-4 Apoptosis induction in untreated and chemotherapy treated Sensitive and Resistant TNBC cell lines. 164 Figure 5-5. Analysis of genome integrity in Sensitive and Resistant TNBC cell lines. 166 Figure 5-6. Evaluation of HR and NHEJ repair efficiency in MDA-MB-231 Sensitive and Resistant cell lines. 169 Figure 5-7. Standardized response of 231 Sen and 231 Res to specific drugs targeting key DDR proteins essential for canonical DDR pathways. 172 Figure 5-8. Standardized response of 468 Sen and 468 Res to specific drugs targeting key DDR proteins essential for canonical DDR pathways. 173 Figure 5-9. Expression changes in DDR genes induced by chemotherapy and chemotherapy combined with RAD51 inhibition for 231 Sen and 231 Res. 176 Figure 5-10 Expression profile highlighting key nodes induced by targeting DDR. 181

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Figure 5-11 Western blot analysis of differential DDR signalling induced by chemotherapy and RAD51 inhibition in sensitive and drug adapted cell lines. 184 Figure 5-12 Depletion of p73 and restoration of p53 sensitise drug-adapted cells to chemotherapy. 187 Figure 5-13. RAD51 inhibition resensitises drug-adapted cell lines to chemotherapy. 189 Figure A1 Inhibition of irradiation induced RAD51 foci formation with compounds 1- 17. 247 Figure A2 Dose response curves for B02 and compounds 1-17 in combination with PARP inhibitor. 248

xiv Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

List of Tables

Table 1-1 Summary of TNBC classification and potential targeted therapies 11 Table 2-1 Medium and Reagents used for Cell Culture 58 Table 2-2 Reagents and Media for Bacterial Growth, Transformation and Selection 59 Table 2-3 Drugs and Inhibitors 59 Table 2-4 Antibodies used for Immunoblotting and Immunofluorescent Staining 60 Table 2-5 Chemical Reagents 61 Table 2-6 Molecular Biology Reagents 64 Table 2-7 Kits 64 Table 2-8 Oligonucleotides for Cloning into lentiGuide-Puro Backbone 65 Table 2-9 Primers for PCR and Sequencing 66 Table 2-10 Primers for qPCR 67 Table 2-11 Thermocycler parameters for high fidelity PCR 79 Table 2-12 Cycling conditions for Roche LightCycler 480* 81 Table 3-1 Summary of guide target sequences 96 Table 4-1 Phyisico-chemical properties of the inhibitors. 127 Table 4-2 TNBC cell survival following treatment with compounds (with and without irradiation). 131

Table 4-3 Comparison of IC50 values for B02 and compound 17 in TNBC cell lines measured by MTS cell viability assay 147 Table 5-1 Characteristics of parental cell lines and final doxorubicin and docetaxel concentrations used to condition the cells 160

Table 5-2 Chemotherapy IC50 values for Sensitive and Resistant cell lines 161 Table 5-3 Copy number variation for genes associated with cell cycle, apoptosis and DNA repair in Sensitive and Resistant TNBC cell lines 167 Table 5-4 Expression changes in DDR genes in MDA-MB-231 Sen and MDA-MB-231 Res cell lines. Data compared to the cell line control (condition treated with DMSO) 177

Table A1 Comparison of IC50 values for B02 and top four compounds (1-17) in TNBC cell lines measured by MTS cell viability assay. 249

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List of Abbreviations

AID Activation induced cytidine deaminase AKT1 Akt serine/threonine kinase 1 Alt-NHEJ Alternative non-homologous recombination ANOVA Analysis of Variance APE1 AP endonuclease 1 ATM Ataxia telangiectasia mutated ATMi Ataxia telangiectasia mutated inhibitor ATR Ataxia telangiectasia and RAD3 related ATRi Ataxia telangiectasia and RAD3 related inhibitor ATRIP ATR interacting protein BAIRD BRCA1 associated RING domain 1 BAX BCL-2-associated X protein BCSC Breast cancer stem cell BER Base excision repair BIR Break induced replication BL1 Basal-like 1 BL2 Basal-like 2 BRCA1 Breast cancer 1 BRCA2 Breast cancer 2 CEBPβ CCAAT/enhancer binding protein beta CHK1 Checkpoint 1 CHK2 Checkpoint 2 c-NHEJ Classical/canonical non-homologous end joining CO Crossing-over CRISPR Clustered regularly interspaced short palindromic repeats CSC Cancer stem cell CtIP C-terminal-binding protein interacting protein DDR DNA damage response DDT DNA damage tolerance dHJ Double Holliday junction DMFS Distant metastasis-free survival DMSO Dimethyl sulfoxide DNA Deoxyribonucleic acid DNA -PKcs DNA -dependent protein kinase, catalytic subunit DNA-PK DNA-dependent protein kinase DNA-Pki DNA -dependent protein kinase inhibitor DSB Double-strand DNA break DSBR Double strand break repair dsDNA Double strand DNA EGFR Epidermal growth factor receptor

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EMSA Electrophoretic mobility shift assay EMT Epithelial–mesenchymal transition ER Oestrogen receptor Excision repair cross-complementing rodent repair deficiency, ERCC1 complementation group 1 EV Empty vector EXO1 Exonuclease 1 FANCD2 Fanconi anemia, complementation group D2 GG-NER Global genome nucleotide excision repair HDAC Histone deacetylase HDACi Histone deacetylase inhibitor HER2 Human epidermal growth factor receptor HR Homologous recombination HRD Homologous recombination deficiency ICLs Interstrand crosslinks IDC Invasive ductal carcinoma IGFR1 Insulin-like growth factor receptor 1 IHC Immunohistochemistry ILC Invasive lobular carcinoma IM Immunomodulatory IRR Irradiation LAR Luminal androgen receptor LOH Loss of heterozygosity LP-BER Long-patch base excision repair LRR Locoregional recurrence M Mesenchymal MDR Multidrug resistance MEF Mouse embryonic fibroblasts MGMT Methylguanine DNA methyltransferase MLH1 Mutl homolog 1 MLH3 Mutl homolog 3 MMR Mismatch repair MRN MRE11, RAD50 and NBS1 MSH2 Muts homolog 2 MSH6 Muts homolog 6 MSI Microsatellite instability MSL Mesenchymal stem-like MTOR Mammalian target of rapamycin NACT Neoadjuvant chemotherapy NCO Non-crossover NER Nucleotide excision repair NF-κB Nuclear factor kappa B NHEJ Non-homologous end-joining OS Overall survival

xvii Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

p53 Tumour protein 53 p63 Tumour protein 63 p73 Tumour protein 73 PARP Poly ADP ribose polymerase PARPi Poly ADP ribose polymerase inhibitor PCNA Proliferating cell nuclear antigen pCR Pathologic complete response PD-L1 Programmed death-ligand 1 P-gp P-glycoprotein PI3K Phosphoinositide 3-kinase PIKK Phosphatidylinositol 3-kinase-related kinases PR Progesterone receptor PTEN Phosphatase and tensin homolog PUMA p53 upregulated modulator of apoptosis qPCR Quantitative reverse transcription-polymerase chain reaction RAD51i RAD51 inhibitor RB1 Retinoblastoma 1 ROS Reactive oxygen species RPA Replication protein a SAR Structure-activity relationship SCE Sister chromatid exchange SDSA Synthesis dependent stand annealing shRNA Short hairpin RNA siRNA Small interfering RNA SP-BER Short-Patch base excision repair SPR Surface plasmon reasonance SSA Single strand annealing SSB Single-strand break SSBR Single-strand break repair ssDNA Single strand DNA TAp63 Transactivation domain containing isoform of tumour protein 63 TAp73 Transactivation domain containing isoform of tumour protein 73 TC-NER Transcription coupled nucleotide excision repair TLS Translesion synthesis TNBC Triple negative breast cancer VEGF Vascular endothelial growth factor XPA Xeroderma pigmentosum, complementation group A XPD Xeroderma pigmentosum, complementation group D XPF Xeroderma pigmentosum, complementation group F XPG Xeroderma pigmentosum, complementation group G ΔNp63 Truncated delta isoform of tumour protein p63 ΔNp73 Truncated delta isoform of tumour protein p73

xviii Investigating Molecular Targets of the DNA Damage Response in Triple Negative Breast Cancer

Chapter 1: Literature Review

1.1 GENERAL INTRODUCTION

Breast cancer predominantly affects women and is the most commonly diagnosed type of cancer in Australia (Australian Institute of Health and Welfare [AIHW], 2020). In 2020, it is estimated that 19,807 Australian women will be diagnosed with breast cancer and 2,997 women will die from the disease making it a national health priority (AIHW, 2020) (Figure 1.1). The risk of developing breast cancer increases with age, with 1 in 7 women likely to be diagnosed in their lifetime (AIHW, 2019). Women over 50 years of age are at greater risk of developing breast cancer and this age group has been targeted to undergo bi-annual mammography since the introduction of national breast screening programs in the late 1980s (Jacklyn et al. 2017). These screening programs have achieved increased detection of early stage breast cancers, which have a 70-80% probability of being curable (Harbeck et al. 2019). Unfortunately, about 5% breast cancers have already spread from the primary tumour to distant organs (metastasized) at the time of diagnosis (AIHW, 2020). While metastatic breast cancer (MBC) can be treated to alleviate symptoms and prolong life it cannot be cured.

In Australia we have seen the 5-year relative survival rate for breast cancer rise from 74.7% in 1987-91 to 91.1% in 2012-16 (AIHW, 2020) (Figure 1.1). This increase in survival is largely due to earlier diagnosis and treatment, as well as the development of better treatments for early stage disease (Jacklyn et al. 2017; Bleyer and Welch 2012). Treatment for early stage breast cancer involves locoregional surgery, radiotherapy and often systemic chemotherapy (Harbeck et al. 2019). The type of systemic therapy recommended and the risk of cancer recurrence following treatment is highly dependent on molecular characteristics of the primary tumour (Ignatov et al. 2018). Patients with tumours that express hormone receptors (oestrogen receptor: ER, progesterone receptor: PR, and/or human epidermal growth factor receptor: HER2) have a decreased risk of cancer recurrence with targeted endocrine therapy or anti-HER2 therapy, which can be combined with conventional cytotoxic chemotherapy (Harbeck et al. 2019; Pan et al. 2017; Burstein et al. 2019). Approximately 15-25% of breast cancers lack expression of ER, PR and HER2 and are referred to as triple negative breast cancer (TNBC) (Rashmi et al. 2018; Boyle 2012; Dent et al. 2007). TNBC is an aggressive type of breast cancer that often develops resistance to conventional chemotherapies and carries a high risk of early recurrence and

Chapter 1: Literature Review 1

distant metastasis (James et al. 2019; Al-Mahmood et al. 2018). Because TNBC lacks expression of hormone receptors it cannot be treated with endocrine therapy or therapies targeted to HER2. Consequently, there is an urgent need to identify clinically actionable molecular targets and develop targeted therapies to improve outcomes for TNBC patients.

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Figure 1-1. Breast Cancer Incidence, Mortality and Survival, Australia.

(A) Age standardised incidence and mortality for breast cancer, 1982 to 2016 (and projections to 2020), by sex. (B) Age specific incidence and mortality for breast cancer, 2016, by sex. (C) 5 year relative survival by stage at diagnosis, 2011 to 2016 (female). This data is from the Australian Institute of Health and Welfare (2020). Cancer data in Australia. Cat. no. CAN 122.

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1.2 BREAST CANCER CLASSIFICATION

For many decades clinicians have noted that breast cancer is not represented by a single phenotype, but rather consists of multiple subtypes that progress and respond to treatment differently (Perou, Sorlie, et al. 2000; Cancer Genome Atlas Network 2012; Sotiriou et al. 2003; Sørlie et al. 2001; Sørlie et al. 2003). Clinicians and researchers rely on various classification schemes to describe tumour features and to guide patient diagnosis, prognosis, and treatment strategy. The classical clinical parameters for describing breast cancers include a description of tumour histology, stage, grade, and receptor status (Harbeck et al. 2019). Commercially available array platforms such as the PAM50 (Parker et al. 2009) are frequently utilised in the research setting to distinguish intrinsic subtypes based on gene expression patterns. Whereas clinicians typically rely on immunohistochemistry (IHC) assessment of hormone receptors and proliferation marker Ki67 as a surrogate for intrinsic subtype to inform prognosis and guide treatment decisions about endocrine therapy and adjuvant chemotherapy (Sønderstrup et al. 2019; Harbeck et al. 2019). An overview of breast cancer classification schemes is depicted in Figure 1.2.

1.2.1 Histological Subtypes While all breast tumours arise from the terminal duct lobular units there is great tumour diversity among breast cancer patients and even within individual tumours. The histopathological type of 70-75% of all breast cancers is Invasive Carcinoma Not Otherwise Specified (Harbeck et al. 2019). These tumours originate from the epithelial cells that line the milk ducts and have proliferated beyond the basement membrane. Whereas Carcinoma In Situ refers to pre-invasive tumours limited to the basement membrane (Harbeck et al. 2019). Histological examination is also used to assess tumour grade and stage. Grading is based on the appearance of tumour cells compared to normal mammary cells and scored from 1 to 3, with 3 being the most abnormal/poorly differentiated with worse prognosis (Wen and Brogi 2019). Staging describes the size of the tumour and if it has spread to the lymph nodes or metastasized to other parts of the body. Stage 0 is pre-invasive cancer, stages 1- 3 are localised to the breast or regional lymph nodes and stage 4 is metastatic disease with poor prognosis (Wen and Brogi 2019).

1.2.2 Intrinsic Subtypes The foundation for the molecular classification of breast cancer was laid by Perou et al. (2000) and Sørlie et al. (2001) who measured the expression of approximately 9000 genes using cDNA micro arrays. They identified approximately 550 genes in the cohort,

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named the intrinsic gene list, which clustered tumours into five subgroups based on expression patterns of the ER gene, amplification and overexpression of the HER2 gene, luminal epithelial genes, basal epithelial genes and proliferation genes (Sørlie et al. 2001). The five intrinsic subtypes identified by hierarchical clustering were luminal A, luminal B, HER2, basal-like and normal breast-like. These five intrinsic subtypes have been validated many times over the years in different cohorts with varying numbers of genes (Sørlie et al. 2001; Sørlie et al. 2003; Langerød et al. 2007; Naume et al. 2007; Calza et al. 2006; Hu et al. 2006). Of note, there are doubts about the existence of the normal breast-like subtype. Some researchers suggest this subtype is derived from contamination of tumour samples with surrounding normal breast tissue during microdissection (Hon et al. 2016; Tang and Tse 2016; Pareja et al. 2019; Prat et al. 2010). In support of this hypothesis Weigelt et al. (2010) identified no cases of normal breast-like subtypes in a series of 64 invasive ductal carcinomas with a tumour-cell content of at least 90%.

Across the intrinsic subtypes the expression of proliferation genes is the main indicator of patient prognosis and this is most apparent in ER positive breast cancers (Reis-Filho and Pusztai 2011). Luminal tumours overexpress the ER gene and are the most common across study cohorts with luminal A representing approximately 50-60% of breast tumours and luminal B about 10-20% (Eroles et al. 2012). ER positive tumours tend to have lower rates of early disease recurrence than ER negative tumours, however recurrence persists even after 10 years (Ignatov et al. 2018). Luminal breast cancers differ mainly in their expression of proliferation genes, HER2 and PR. Luminal A tumours are more likely to express PR than luminal B (Prat et al. 2013), are typically HER2 negative, present with low tumour grade, are slow growing and respond poorly to chemotherapy (Eroles et al. 2012). However luminal A tumours generally respond well to hormone therapy and the mainstay of treatment is with aromatise inhibitors and selective estrogen receptor modulators (Eroles et al. 2012) which is continued for 5 to 10 years prevent recurrence (Prat et al. 2015). The 15 year relapse rate for luminal A cancer is approximately 28% (Kennecke et al. 2010), which is low compared to the other subtypes and they have the best overall survival of all the intrinsic subtypes (Ignatov et al. 2018). In contrast the luminal B subtype has increased expression of proliferation genes and often expresses HER2 (Prat et al. 2015). Luminal B tumours generally present with a higher tumour grade than luminal A (Eroles et al. 2012) and have a worse prognosis with a relapse rate of approximately 45% (HER2 negative: 42.9%, HER2 positive: 47.9%) (Kennecke et al. 2010). Hormone therapy alone is insufficient at treating

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the more proliferative luminal B tumours and benefit is derived from the addition of anthracycline/taxane-based chemotherapy (Prat et al. 2015; Coates et al. 2015).

HER2 enriched and basal-like breast cancers are more aggressive, faster growing and higher grade than the luminal tumours (Eroles et al. 2012) with 15 year relapse rates of about 43% and 51% respectively (Kennecke et al. 2010). In contrast to ER positive tumours, HER2 and basal-like breast cancers carry a high risk of early relapse within 3-5 years of diagnosis however this risk drops dramatically after 5 years (Ignatov et al. 2018; Kennecke et al. 2010). The HER2 enriched subtype is characterised by amplification and overexpression of the gene that encodes HER2 and other genes in the HER2 amplicon, such as GRP7 (Sørlie et al. 2001). HER2 tumours are sensitive to chemotherapy and treatment entails standard chemotherapy combined with one or more anti-HER2 targeting drugs (e.g., trastuzumab) (Llombart-Cussac et al. 2017; Coates et al. 2015). The development of anti-HER2 therapies have significantly improved pathologic complete response rates (Llombart-Cussac et al. 2017) and survival in primary and metastatic HER2+ breast cancer (Piccart-Gebhart et al. 2005; Gianni et al. 2011; Slamon et al. 2001).

There is strong consensus that basal-like tumours are the most aggressive of all the intrinsic subtypes and have the worst outcome despite being sensitive to chemotherapy (Dai et al. 2015). Approximately half of the BRCA1/2 mutated breast tumours are basal-like and these patients have a worse prognosis than those with BRACA1/2 mutated luminal tumours (Sønderstrup et al. 2019). Basal-like tumours are typically grade 3 with high expression of keratins 5, 6, 14, 17, EGFR, proliferation genes and lack expression of ER and PR genes, and have low level or no expression of HER2 genes (Dai et al. 2015). Despite sensitivity to chemotherapy the 10 year patient survival rate for basal breast cancer is only 53% with most deaths occurring within 5 years of diagnosis (Kennecke et al. 2010).

The most recently identified intrinsic subgroup, claudin-low, clusters in close proximity to the basal-like subgroup (Herschkowitz et al. 2007; Parker et al. 2009; Prat et al. 2010). As its name suggests the claudin-low subgroup has low level expression of claudin genes 3, 4, 7 and E-cadherin which are involved in intercellular adhesion and tight junctions (Herschkowitz et al. 2007). Compared to basal-like tumours they have higher activity of ER, PR and HER2 and are enriched for immune response and cancer stem cell-like features (Prat et al. 2010; Sabatier et al. 2014). Claudin-low tumours are less responsive to chemotherapy than basal-like tumours and generally carry a poor prognosis (Prat et al. 2010).

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1.2.3 Surrogate Intrinsic Subtypes The surrogate intrinsic subtypes are based on tumour histology and IHC expression of ER, PR, HER2 and proliferation marker Ki67 (Harbeck et al. 2019). Hormone receptor positive tumours include the surrogate intrinsic subtypes; luminal A-like, luminal B-like (HER2), luminal B-like (HER2 positive) and HER2 enriched (non-luminal) (Harbeck et al. 2019). Tumours that do not express ER, PR and lack HER2 expression/amplification are referred to as ‘triple negative’ and represent the majority of basal-like (~80%) and claudin- low (~65%) tumours (Prat et al. 2010; Sabatier et al. 2014; Jamshidi et al. 2018). Recently Zhu et al. (2020) showed that Ki67 cutoff at 30% can be used to further classify TNBC into two subtypes with distinct responses to chemotherapy and prognoses. Patients with Ki67<30% had a favourable prognosis and did not demonstrate a clear benefit from adjuvant chemotherapy. Whereas TNBC patients with Ki67>30% had a poorer prognosis however adjuvant chemotherapy was associated with significantly improved overall survival for this cohort.

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Figure 1-2 Breast cancer classification.

Overview of breast cancer histological subtypes, intrinsic subtypes and IHC surrogate intrinsic subtypes.

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1.3 TRIPLE NEGATIVE BREAST CANCER

Triple negative breast cancer (TNBC) is characterised by the lack of lack of ER and PR expression and lack of HER2 expression or amplification. TNBC is diagnosed in about 15-25% of breast cancer patients (Rashmi et al. 2018; Boyle 2012; Dent et al. 2007) and disproportionately affects pre-menopausal women under the age of 50 years (46%-60%) (Plasilova et al. 2016; Urru, Gallus, Bosetti, Moi, Medda, Sollai, Murgia, Sanges, Pira, and Manca 2018; Trivers et al. 2009; Santonja et al. 2018). Compared to hormone receptor positive breast cancers TNBC is a more aggressive disease, with an overall survival rate of about 70% and a high risk (~30%) of distant recurrence, particularly in the lungs, brain and soft tissue, within 3-5 years (Dent et al. 2007; Urru, Gallus, Bosetti, Moi, Medda, Sollai, Murgia, Sanges, Pira, Manca, et al. 2018; James et al. 2019; Pogoda et al. 2013). Disease progression following distant recurrence of TNBC is rapid, with a median survival of only 12- 18 months (Kassam et al. 2009; Yao et al. 2019). The vast majority of TNBC tumours harbour somatic mutations in tumour suppressor gene p53 (~93%) (Shah et al. 2012; Koboldt et al. 2012; Niyomnaitham et al. 2019; Wilson et al. 2019) and approximately 20% of TNBC patients have germline mutations in DNA repair genes BRCA1 and BRCA2 (Atchley et al. 2008; Stevens, Vachon, and Couch 2013). The germline BRCA status of a patient has important implications for the selection of platinum compounds and PARP inhibitors in the treatment of TNBC. Treatment of TNBC is a major clinical challenge due to the molecular heterogeneity of TNBC tumours, lack of targetable hormone receptors and its tendency to develop drug resistance to standard chemotherapies. Current treatment strategies for TNBC involve surgery to remove the primary tumour, radiotherapy and cytotoxic chemotherapy (Montero et al. 2014; Liedtke, Mazouni, Hess, André, Tordai, Mejia, Symmans, Gonzalez-Angulo, Hennessy, Green, et al. 2008).

1.3.1 Heterogeneity of TNBC Transcriptome profiling analysis of TNBC tumours has provided insight into the diverse biological behaviour of TNBC. In addition profiling has defined differential molecular responses to chemotherapy and identified potential therapeutic targets in signalling pathways including; proliferation, DNA repair, apoptosis, angiogenesis, immune modulation, and invasion and metastasis (Andreopoulou, Kelly, and McDaid 2017). The first and most extensively used molecular classification of TNBC was proposed by Lehmann et al. (2011) and includes six subtypes: basal-like 1 (BL1), basal-like 2 (BL2), mesenchymal (M), mesenchymal stem-like (MSL), immunomodulatory (IM) and luminal androgen receptor

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(LAR). The BL, M and IM subtypes largely correspond with PAM50 basal-like tumours (Bareche et al. 2018).

The BL subtypes are the most proliferative and genomically unstable subtypes, with the highest frequency of p53 mutations (92%) and copy-number deletions in DNA repair genes (BRCA1/2, MDM2, PTEN, RB1 and p53) (Bareche et al. 2018). BL1 is further characterised by cell-cycle checkpoint loss and elevated DNA damage response pathways (ATR/BRCA) (Lehmann et al. 2011). Candidate therapeutic targets for BL1 include PARP1, RAD51, CHK1 and drugs that target PTEN loss (PI3K/AKT inhibitors) and mutant p53 (Kalimutho et al. 2015). BL2 tumours are enriched in growth factor signalling, myoepithelial markers and activation of metabolic pathways (Lehmann et al. 2011). Potential therapeutic targets for BL2 tumours include EGFR, MET, mTOR and EPHA2 (Kalimutho et al. 2015). The two mesenchymal related subtypes display upregulation of genes associated with cell motility, differentiation and epithelial to mesenchymal transition (Lehmann et al. 2011). The MSL subtype also expresses genes associated with angiogenesis and stemness and has lower expression of proliferation associated genes compared to the M subtype (Bareche et al. 2018). Representative M and MSL cells lines show sensitivity to the PI3K/mTOR inhibitor NVP-BEZ235 (Lehmann et al. 2011). The IM subtype is characterised by upregulation of genes involved in immune signalling and antigen processing and presentation and may have potential to identify patient populations that benefit from immune checkpoint inhibitors, such as PD-L1 inhibitors (Bareche et al. 2018; Lehmann and Pietenpol 2015). LAR is the most frequently identified subtype in older patients (>45 years) and most closely resembles the PAM50 luminal B or HER2-enriched tumours (Bareche et al. 2018).The LAR subtype displays luminal gene expression and high levels of androgen receptor expression (Lehmann et al. 2011) and is enriched in PIK3CA mutations (55%) (Bareche et al. 2018). LAR tumour cell lines are highly sensitive to the androgen receptor antagonist bicalutamide (Lehmann et al. 2011). Lehmann et al. (2016) later refined the TNBC classification to only four subtypes; BL1, BL2, M and LAR (TNBCType-4) on the basis that the IM and MSL subtypes were likely derived from infiltrating lymphocytes and tumour-associated stromal cells respectively and could be associated with any subtype. Subsequent transcriptome profiling studies have proposed similar TNBC classifications with 3 to 4 subtypes, with a high degree of overlap between the classification schemes (Burstein et al. 2015; Jézéquel et al. 2015; Prado-Vázquez et al. 2019). Table 1.1 provides a summary of Lehmann’s TNBC classification and identifies potential targeted therapies.

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Table 1-1 Summary of TNBC classification and potential targeted therapies

TNBC subtype Characteristics Targeted/potential therapies

BL1 Abnormalities in gene genes related to cell cycle, BRCA mutations, HRD score high:

proliferation and DNA repair Platinum compounds

PARP inhibition

HRD score low:

ATM and ATR inhibition

RAD51 inhibition

HDAC inhibitors

BL2 Growth factor signalling, alterations in glycolysis, PI3K/AKT inhibitors glucogenesis, myoepithelial marker expression. Growth factor inhibitors

IM Immunological processes and cascades, TILs PD-1/PD-L1 inhibitors

M Growth factor signaling, EMT, cell differentiation, PI3K/mTOR inhibitors cell motility

MSL Similar to M , angiogenesis genes, low EMT and CSC targeted treatment proliferation, Antiangiogenic therapy

LAR Androgen receptor gene expression Androgen receptor antagonists

1.3.2 Current standard of care for TNBC The current standard of care for TNBC patients relies on neoadjuvant (before surgery) and adjuvant (after surgery) systemic chemotherapy with anthracycline and/or taxane regimens (Bianchini et al. 2016; Peto et al. 2012; Cortazar et al. 2014). Commonly used anthracyclines are the topoisomerase II poisons; doxorubicin and epirubicin (Atwal et al. 2019). Doxorubicin intercalates between DNA base pairs and binds covalently topoisomerase II, generating direct DSBs and bulky topoisomerase II-DNA adducts that block replication and transcription (Nitiss 2009; Marinello, Delcuratolo, and Capranico 2018). Doxorubicin also generates free radicals which in turn can damage DNA. (McGowan et al. 2017). Taxanes used in TNBC therapy include microtubule targeting drugs such as docetaxel and paclitaxel. Taxanes work by binding to a taxoid-binding site on β-tubulin,

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stabilising the mitotic spindle microtubules leading to anaphase arrest, inhibition of cell proliferation, mitotic slippage and apoptosis (Churchill, Klobukowski, and Tuszynski 2015). Standard chemotherapy protocols may also incorporate drugs that block nucleic acid synthesis, such as 5-fluorouracil and capecitabine, or alkylating agents such as cyclophosphamide (Masuda et al. 2014; McAndrew and DeMichele 2018). Optimal protocols of chemotherapy to cover the spectrum of TNBC patients have not yet been established but generally comprise polychemotherapy for early stage TNBC and monotherapy in the metastatic setting (Cortazar et al. 2014; Peto et al. 2012). The goal of treatment in early stage TNBC is curative, whereas in the metastatic setting the goal of chemotherapy is to palliate symptoms and prolong patient survival (Al-Mahmood, Sapiezynski et al. 2018). Selection of therapy is based on risk of toxicity, patient age, comorbidities, prior therapy, tumour burden and degree of symptoms (Al-Mahmood et al. 2018).

1.3.3 Clinical Outcomes Anthracycline and taxane–based neoadjuvant chemotherapy (NACT) results in higher pathologic complete response (pCR) rates in TNBC patients (30-40%) compared to luminal subtypes (<20%) and this outcome is strongly predictive of long term patient survival (Von Minckwitz et al. 2012; Liedtke, Mazouni, Hess, André, Tordai, Mejia, Symmans, Gonzalez- Angulo, Hennessy, and Green 2008; Cortazar et al. 2014; LeVasseur et al. 2020; Haque et al. 2018). TNBC patients who achieve pCR have excellent overall survival (~86% at 10 years) (Symmans et al. 2017). However, if residual disease remains after neoadjuvant chemotherapy TNBC patients are 6 times more likely to experience recurrence and twelve times more likely to die from metastatic disease (Brewster, Chavez-MacGregor, and Brown 2014). Comparative analysis of TNBC subtypes reveals that the BL1 subtype is more responsive in general to anthracycline and/or taxane chemotherapies, pCR 42-52% (Masuda et al. 2013; Lehmann et al. 2016), and has the highest rate of distant relapse free survival (95% at 7 years after treatment). The IM subtype or presence of tumour-infiltrating lymphocytes is also associated with better outcomes (Burstein et al. 2015; Adams et al. 2014; Leon-Ferre et al. 2018; Prado-Vázquez et al. 2019). In contrast BL2, M and LAR subtypes have a lower probability of success with chemotherapy with pCR rates of 0-18%, 31-38% and 10-29% respectively with anthracyclines and taxanes (Masuda et al. 2013; Lehmann et al. 2016). Consistent with low pCR rates the BL2 subtype has the worst distant relapse free survival of the subtypes with a median survival of 2.4 years after treatment (Masuda et al. 2013; Lehmann et al. 2016). Despite having poor response to chemotherapy the LAR subtype has a good long-term outcome, which is attributed to low

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Ki67 expression and slow tumour growth and a tendency toward localised tumour recurrence rather than distant metastasis (Lehmann et al. 2011). Typical chemotherapy response and distant metastasis-free survival (DMFS) rates for TNBC are shown in Figure 1.3.

Although TNBC response rates are higher than other subtypes, overall survival is worse. There is evidence that sequential dose dense anthracycline and taxane based regimens provide greater patient benefit than concurrent lower dose regimens, as does shortening the intervals between cycles (Foukakis et al. 2016; Yoshinami et al. 2020; Gray et al. 2019). A meta-analysis of patient data from 26 trials showed fewer breast cancer recurrences with dose-intense chemotherapy than with standard-schedule chemotherapy (10-year recurrence risk 28·0% vs 31·4%) and reduced mortality (10-year breast cancer mortality 18·9% vs 21·3%). Reductions in recurrence were similar in the seven trials that compared 2-weekly chemotherapy with the same chemotherapy given 3-weekly (24·0% vs 28·3%), in the six trials of sequential versus concurrent anthracycline plus taxane chemotherapy (28·1% vs 31·3%) and in the six trials testing both shorter intervals and sequential administration (30·4% vs 35·0%). Moreover, there are many clinical trials investigating different chemotherapy schedules with the addition of other agents that have been employed to improve the high recurrence rates observed with standard chemotherapy regimens for TNBC.

In the neoadjuvant setting the addition of platinum salts to standard chemotherapy shows promise, particularly with BRCA1/2 mutant/BL1 subtype tumours (Sikov et al. 2015; Sharma et al. 2018; Rugo et al. 2016; von Minckwitz et al. 2014; Loibl et al. 2018). Platinum compounds such as cisplatin and its derivative carboplatin are alkylating agents that covalently bind DNA bases, forming DNA adducts (Rocha et al. 2018). A meta-analysis of nine trials with 2109 TNBC patients showed that NACT with carboplatin was associated with significantly improved pCR, from 37.0% to 52.1%, when compared to platinum-free NACT (Poggio et al. 2018). Of the TNBC subtypes BL1 achieves the highest pCR rates with carboplatin containing NACT; BL1 (53-66%), BL2 (33-47%), M (36-47%), and LAR (21-25%) (Echavarria et al. 2018; Jovanović et al. 2017). In the metastatic setting carboplatin shows efficacy as a monotherapy in BRCA mutant TNBC. In the Phase III Triple Negative Breast Cancer Trial 376 patients with metastatic TNBC were randomly allocated to receive docetaxel or carboplatin treatment (Tutt et al. 2018). In the unselected population carboplatin and docetaxel and were found to be equally effective, with objective response rates of 28% and 35% respectively. In contrast, patients with germline BRCA mutations had double the

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objective response rate with carboplatin compared to docetaxel (68% vs. 33%) and had longer progression free survival with carboplatin (Tutt et al. 2018). The sensitivity of BRCA mutant TNBC to platinum adduct causing agents, such as carboplatin, stems from innate deficiency in the homologous recombination DNA repair pathway which relies on functional BRCA1 and BRCA2. This highlights the importance of the DNA damage response and functional status of DNA repair pathways in the selection of chemotherapies and novel targeted therapies for TNBC patients.

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Figure 1-3 Patient chemotherapy response relative to PAM50 or refined TNBCtype-4 subtyping.

Patient response rates stratified by; (A) TNBC, (B) PAM50 or (C) TNBCtype-4. Distant relapse-free survival from GSE25066 cohort for (D) TNBC patients; (E) TNBC patients stratified by pCR or RD; (F) TNBC patients stratified by PAM50; and (G) TNBC patients stratified by refined by TNBCtype-4.

Reproduced with permission from “Refinement of triple-negative breast cancer molecular subtypes: Implications for neoadjuvant chemotherapy selection”, 2016, by B. D. Lehmann et al, PLOS ONE, 11(6), p. 15. CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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1.4 THE DNA DAMAGE RESPONSE IN TNBC

In response to DNA damage cells activate the DNA damage response (DDR); a complex signalling network to mediate cycle arrest, induce DNA-repair mechanisms, or trigger apoptosis when DNA damage is irreparable (Maréchal and Zou 2013) (Figure 1.4). The anticancer activity of radiotherapy and most chemotherapy drugs used in TNBC relies on induction of the DDR in rapidly dividing cells with inadequate DNA repair (Bouwman and Jonkers 2012). In normal cells DNA damage is quickly recognised by DDR response factors which activate cell cycle checkpoints and initiate DNA repair. Compared to normal cells cancer cells have; increased levels of endogenous DNA damage, replication stress and most have alterations in at least one DDR pathway during tumourigenesis which creates increased dependency on the remaining pathways to deal with DNA damage (Bouwman and Jonkers 2012). The inability of cells to respond and repair DNA damage properly leads to genomic instability (the acquisition of mutations) and drives cancer development and progression (Duijf et al. 2019). However, dysregulation of the DDR can also be exploited with both conventional cytotoxic therapy and DDR inhibitors (Nickoloff et al. 2017).

The DDR signaling pathway (summarised in fig. 1.4) consists of sensors that recognize DNA lesions (RPA, MRN, PARP1, KU70/80), transducer kinases (ATM, ATR, DNA-PK) that convey the signal downstream, and effector proteins (CHK1, CHK2, p53, PCNA etc.) that induce cell cycle arrest allowing initiation of DNA repair pathways (Nandi et al. 2019). Central to the DDR are phosphatidylinositol 3-kinase-related kinases (PIKK); ataxia-telangiectasia mutated (ATM), ataxia telangiectasia and RAD3-related protein (ATR) and DNA-dependent kinase (DNA-PK) (Blackford and Jackson 2017; Sugimoto 2018; Menolfi and Zha 2020). They respond to different types of DNA lesions and phosphorylate a large number partially overlapping substrates to promote DNA repair and checkpoint activation (Butler, Gilad, and Brown 2018). ATM and DNA-PK respond to double strand DNA breaks (DSBs), whereas ATR responds to a wide variety of stimuli that generates RPA coated single stand DNA (ssDNA), including; ssDNA breaks, bulky adducts, end resection during DSB repair, interstrand cross links (ICLs) and stalled or collapsed replication forks (Yazinski and Zou 2016; Saldivar, Cortez, and Cimprich 2017; Lavin 2007; Blackford and Jackson 2017; Menolfi and Zha 2020). Exposed ssDNA is rapidly coated by the nucleoprotein RPA and ATR is recruited to site by its stable binding partner ATRIP (Blackford and Jackson 2017). ATR responds directly to many types of lesions encountered during replication however its involvement in DSB repair is dependent on ATM (Jazayeri et al. 2006). DNA-PK is recruited to DSBs by the heterodimer complex KU70/80 and facilitates repair via nonhomologous end-

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joining (NHEJ) (Singleton et al. 1999; Menolfi and Zha 2020; Lavin 2007). Whereas ATM is recruited to DSBs by the MRN (MRE11/RAD50/NBS1) complex and mediates repair by both non-homologous end joining (NHEJ) and homologous recombination (HR) (Falck, Coates, and Jackson 2005; Lavin 2007; Lee and Paull 2005), however pathway choice dependent on end resection by ATM (Symington 2016). End resection commits a cell to DSB repair by HR and is restricted to S and G2 phases of the cell cycle by the regulatory activity of the cyclin dependent kinases (Mimitou and Symington 2009; Symington 2016).

The primary substrates of ATM and ATR are the checkpoint effector kinases CHK2 and CHK1 respectively (Zannini, Delia, and Buscemi 2014; Helt et al. 2005; Smith et al. 2010). DNA-PK is also involved in the activation of CHK2 (Shang et al. 2014). In response to DSBs, CHK2 phosphorylates CDC25A and CDC25C, which in turn inactivates cyclin- dependent kinases and results in cell cycle arrest at G1/S and to a lesser extent G2/M (Zannini, Delia, and Buscemi 2014). Alternatively, phosphorylation of p53 (directly by ATM or via CHK2) stabilises and activates p53. Activated p53 mediates arrest at G1/S through induction of the cyclin-dependent kinase inhibitor p21 and can also induce apoptosis by transactivating proapoptotic genes such as PUMA, NOXA or BAX (Shiloh and Ziv 2013; Riley et al. 2008). Breast cancer 1 (BRCA1) is another important downstream substrate of ATM (Shiloh and Ziv 2013). BRCA1 facilitates DSB repair by HR and is also a mediator of the intra-S and G2/M checkpoints (Simhadri et al. 2019; Lahusen et al. 2018).

Like ATM, ATR can phosphorylate p53 directly or indirectly (via CHK1) and there can be considerable crosstalk between the two pathways (Anderson and Appella 2010). The ATR/CHK1 pathway initiates the intra-S and G2/M checkpoints via inactivation of CDC25 family members and is crucial to the replication stress response. Arrest at intra-S and G2/M allows time for DNA damage repair, restart of stalled or collapsed replication forks and prevents cells with incompletely-replicated DNA or resected DSBs from entering mitosis (Saldivar, Cortez, and Cimprich 2017). The predominant checkpoint for DNA repair in normal mammalian cells is at the G1/S boundary. However, because p53 mutations are frequent in cancer, particularly TNBC, there is selective loss of the G1 checkpoint. Hence, TNBC tumours are often completely dependent on the S and G2/M checkpoints to arrest cell cycle after genotoxic stress (Morandell and Yaffe 2012). As a consequence, tumour cells have increased reliance on HR as a back-up repair pathway during S and G2.

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Figure 1-4 DNA damage response pathway.

DNA damage detected by sensors (MRN/Ku70/80/RPA) activate the PIKK kinases (ATM/DNA-PK/ATR) which in turn phosphorylate downstream kinases (CHK1/CHK2) which trigger a signalling cascade dependent upon type of DNA damage and stage of the cell cycle to mediate DNA damage repair and tolerance mechanisms and cycle checkpoint activation.

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1.5 THE STATUS OF DNA DAMAGE REPAIR PATHWAYS IN TNBC

Our cells are under constant genotoxic stress from endogenous and exogenous sources. Each cell typically incurs hundreds of thousands of DNA lesions each day (Hoeijmakers 2009). To cope with this constant assault our cells have evolved a number of highly conserved and partially redundant DNA repair pathways to repair single strand DNA (ssDNA) damage, including; direct repair, base excision repair (BER), nucleotide excision repair (NER) and mismatch repair (MMR). In addition there are specialized pathways to repair damage to double strand DNA (dsDNA), including; non-homologous end joining (NHEJ) and homologous recombination (HR). DSBs are the most toxic typic of DNA lesion. Hence most of the agents widely used to treat TNBC are capable of generating DSBs, either directly or indirectly (Goldstein and Kastan 2015). Direct DSBs are repaired by either NHEJ or HR, whereas DSBs that arise indirectly from other lesions that block replication are dependent on HR for repair (Goldstein and Kastan 2015).

1.5.1 Direct Repair Direct repair is the simplest and most frequent repair that occurs cells in response to normal metabolism or exposure to alkylating agents that methylate guanine bases (Kelley and Fishel 2016; Kondo et al. 2010). Cyclophosphamide is an example of this type of this type of alkylating agent that may be used in the treatment of TNBC (McAndrew and DeMichele 2018). Direct repair involves one step; the DNA repair protein O 6 - methylguanine DNA methyltransferase (MGMT) transfers one methyl group (an alkyl adduct) from the O 6 position of guanine, and then MGMT is degraded. Studies suggest that the direct repair pathway is frequently silenced by MGMT promoter methylation in a sub- population of TNBCs with wild-type BRCA1 (58.3 -63.6%) and may serve as a biomarker for sensitivity to alkylating agents (Fumagalli et al. 2012; Fumagalli et al. 2014). If cells do not continually express MGMT then alkyl adducts persist and must be repaired by more complex pathways and may indirectly induce DSBs (Kelley and Fishel 2016).

1.5.2 Base Excision Repair and DNA Single-Strand Break Repair There is considerable overlap between the base excision repair (BER) and single- strand break repair (SSBR) pathways which respond to abasic lesions or small base defects that do not significantly distort the DNA helix, such as oxidised, alkylated and deaminated bases (Figure 1.5)(Krokan and Bjørås 2013). BER involves recognition and removal of inappropriate bases by DNA N-glycosylases, creating an abasic lesion or ssDNA break (SSB) (Prasad et al. 2015). SSBR involves poly ADP-ribose polymerase 1 (PARP1)

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responding directly to abasic lesions that are formed by spontaneous hydrolysis of the N- glycosylic bond (Prasad et al. 2015). Most of the lesions repaired by BER and SSBR are caused by reactive oxygen species (ROS). ROS are normal a by-product of cellular metabolism and are also a generated by therapies used to treat TNBC, including; irradiation and anthracyclines such as doxorubicin (Maynard et al. 2008; McGowan et al. 2017). If BER/SSBR fails to repair damaged bases and SSBs, these lesions indirectly cause cytotoxic DSBs by blocking replication fork progression and are reliant on repair by HR (Harper, Anderson, and O’Neill 2010).

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Figure 1-5 Base excision repair.

Damaged bases are recognised by glycosylases and processed by AP endonuclease (APE1), whereas SSBs are recognised and bound by PARP1 and incised by polynucleotide kinase (PNK). The two pathways then converge and the lesion is repaired by one of two mechanisms, Short-Patch BER (SN-BER) incorporating 1 nucleotide by DNA polymerase β (Polβ) or, or Long-Patch BER (LP-BER) incorporating 2–8 nucleotides by DNA polymerase δ or ε (Polδ/ε) in collaboration with flap endonuclease 1 (FEN1). Throughout the process, x-ray repair cross-complementing protein 1 (XRCC1) stabilizes the damaged area and recruits other proteins required for the repair.

Adapted from “Targeting DNA repair and the cell cycle in glioblastoma” by B. M. Alexander et al, 2012, Journal of Neuro-Oncology, 107(3), p. 465. Copyright 2011 by Springer Nature. Adapted with permission.

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1.5.3 Nucleotide Excision Repair Nucleotide excision repair (NER) repairs helix-distorting, bulky lesions and large adducts that affect only one strand of DNA (Sugasawa 2016) (Figure 1.6). This type of damage most often arises from exogenous sources such as UV radiation, environmental mutagens and bulky chemical compounds (Schärer 2013). NER is important in the response to platinum-based chemotherapies used in TNBC therapy, such as cisplatin and its derivative carboplatin (Rocha et al. 2018). These alkylating agents covalently bind DNA bases, forming DNA adducts, and a double reaction may covalently link two bases together (Rocha et al. 2018). Linked adducts residing on the same DNA strand form intrastrand crosslinks, whereas linked adducts on opposite DNA strands form interstrand crosslinks (ICLs). The bulky adducts and intrastrand crosslinks caused by platinum compounds are repairable by NER however ICLs are preferentially repaired by HR (Rocha et al. 2018).

If NER fails to repair these lesions they are capable of obstructing transcription and replication resulting in DSBs. In TNBC the cytotoxicity of platinum compounds is primarily caused by this indirect induction of DSBs and is commonly used as a second line therapy added to anthracycline and taxane (Rocha et al. 2018). Deficiencies in NER repair occur more frequently in TNBC than other breast cancer subtypes and likely contributes to disease pathogenesis and the increased pCR of TNBC in response DNA damaging chemotherapies (Matta et al. 2017). Ribeiro et al. (2013) reported significant downregulation of 13 DNA repair genes in TNBC, including five genes from the NER pathway: ERCC1, XPA, XPD, XPG and XPF. Decreased NER capacity is a double-edged sword for TNBC. Despite increasing responsiveness to chemotherapy, NER deficiency also increases the genomic instability of the tumour cells, which in turn promotes more mutations to accumulate, which under selection may lead to a more aggressive phenotype (Ribeiro et al. 2013).

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Figure 1-6 Nucleotide excision repair.

In global genome NER (GG-NER), lesions are sensed by the XPC-RAD23 complex. In transcription coupled NER (TC-NER), lesions stalling RNA-polymerase II are sensed by the CSA and CSB proteins, which couple transcription with repair. GG-NER and TC-NER then converge and use common mechanisms to unwind double-stranded DNA in damaged region, excise the damaged nucleotides, and fill the gap by DNA synthesis and ligation.

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1.5.4 Mismatch Repair Mismatch repair (MMR) corrects single base mismatches, and inappropriately inserted or deleted bases (Fishel 2015) (Figure 1.7). These errors may arise during replication and recombination or as a consequence of endogenous ROS or alkylating agents, both of which can cause base modifications (Kelley and Fishel 2016). MMR deficiency occurs frequently in some types of tumours (e.g., endometrial and colorectal tumours) due to somatic or germline mutations and is associated with microsatellite instability (MSI) (Cortes-Ciriano et al. 2017). However TNBC tumours are typically proficient in MMR (Wen et al. 2012; Kurata et al. 2020) and less than 2% of breast cancers harbour high MSI (Cortes-Ciriano et al. 2017).

Upregulation of histone deacetylases (HDACs) are common in TNBC and are implicated in the regulation of MMR and tumour sensitivity chemotherapy (Salgado et al. 2018; Garmpis et al. 2017; Han et al. 2019). HDACs influence protein activity via post translational modifications and affect gene expression via epigenetic modification of histones (Li and Seto 2016). HDAC6 mediates downregulation of the MMR DNA damage sensor MutSα (MSH2-MSH6) by sequential deacetylation and ubiquitination of MSH2. This downregulation of MutSα increases cellular tolerance to DNA damage and decreases mismatch repair activities (Zhang et al. 2014). While HDAC10 promotes DNA mismatch repair through deacetylation of MSH2 (Radhakrishnan et al. 2015). The influence of HDACs on the DDR extends beyond mismatch repair; HDAC1 and HDAC2 facilitate non- homologous end-joining (Miller et al. 2010; Liu et al. 2020), and HDAC9 and HDAC10 facilitate homologous recombination (Kotian et al. 2011). Small molecule HDAC inhibitors show promise in counteracting the effects HDAC upregulation in TNBC. HDACs, such as vorinostat (SAHA), increase oxidative stress and downregulate proteins required for DNA repair and are currently being evaluated as monoagents and in combination with other chemotherapies (Fedele, Orlando, and Cinieri 2017).

In vitro studies with TNBC cell lines have shown that the HDACi vorinostat enhances sensitivity to PARP inhibitor oliparib (Marijon et al. 2018; Min et al. 2015), DNA methyltransferase inhibitor epigallocatechin-3-gallate (Lewis, Jordan, and Tollefsbol 2019; Steed, Jordan, and Tollefsbol 2020), cisplatin (Wawruszak et al. 2019) and doxorubicin (Han et al. 2019). There is currently limited data available on efficacy of HDACis as monoagents or in combination with other therapies in TNBC patients. A phase 1-II trial evaluated pCR as the endpoint for vorinostat in combination with paclitaxel, followed by doxorubicin and cyclophosphamide in 55 patients with advanced breast cancer (Tu et al. 2014). The study

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showed combination of vorinostat with paclitaxel worked well in the 15 TNBC patients, 4 of which reported a complete pathological response (27%). The highest rate of pCR was achieved in patients HER2-positive disease (54%, 13 of 24) and none of 12 patients with ER-positive, HER2 negative disease achieved pCR. A phase I trial with high-dose or low- dose vorinostat with carboplatin or paclitaxel for the treatment of advanced solid tumors is currently ongoing (ClinicalTrial.gov identifier: NCT01281176).

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Figure 1-7 Mismatch repair.

Mismatched bases are recognised by MutSα (MSH2-MSH6 complex), EXO1 excises the mismatched segment of DNA, DNA polymerase fills the gap and the DNA ends are ligated.

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1.5.5 Repair of DSBs by End-Joining Pathways Approximately 10-50 DSBs occur each day in every dividing human cell (Lieber 2010; Vilenchik and Knudson 2003). The majority of DSBs arise from inadvertent events during replication and transcription or as a consequence of endogenous ROS (Bouwman and Crosetto 2018; Lieber 2008). Even one unrepaired DSB can be lethal to cells and if not repaired properly can lead to mutations, deletions, translocations, and genome amplifications (Kelley and Fishel 2016). Upon recognition of a DSB and initiation of the DRR the cell determines the appropriate repair pathway based on the nature of the break, the phase of the cell cycle and the availability of required repair factors (Sullivan and Bernstein 2018). The two major pathways for repairing DSBs are error prone non-homologous recombination (NHEJ) and high-fidelity homologous recombination (HR). Despite being error-prone, NHEJ is the most commonly used pathway to repair DSBs in mammalian cells. This is likely because compared to HR, repair by NHEJ is fast and it can occur throughout the cell cycle (although predominantly during G0 and G1) (Kelley and Fishel 2016; Chang et al. 2017). In contrast HR is limited to S and G2 phases of the cell cycle when the sister chromatid is present to use as a homology template for accurate DNA repair (Helleday et al. 2008). NHEJ consists of two main sub-pathways; classical NHEJ (c-NHEJ) and alternative NHEJ (alt-NHEJ) (Chang et al. 2017). C-NHEJ involves ligation of two ends of DNA and requires minimal end processing. However, if c-NHEJ is unable to repair a DSB, alt-NHEJ becomes the dominant pathway. Alt-NHEJ involves much more extensive resection of the DNA ends and typically results in the loss of larger genomic regions than c- NHEJ (Chang et al. 2017). Anthracyclines and radiotherapy used to treat TNBC are capable of generating direct DSBs that may be repaired by the NHEJ pathway (Curtin 2012; Goldstein and Kastan 2015). DSB repair by end-joining pathways are summarised in Figure 1.8.

1.5.5.1 Classical NHEJ In c-NHEJ the DSB is recognised and bound by the KU70-KU80 heterodimer which blocks extensive end resection and serves as a stabilising scaffold to recruit other canonical NHEJ repair factors to the DNA lesion, including; the catalytic subunit of DNA-dependent protein kinase (DNA-PKcs), DNA ligase IV, XRCC4, XLF and Artemis (Chang et al. 2017; Davis, Chen, and Chen 2014; Sun et al. 2012). Together KU-70-KU80-DNA-PKcs form the DNA-PK complex which has kinase activity (Chang et al. 2017). DSBs with blunt ends can be simply ligated by the XRCC4-LIGIV-XLF complex. If DSB ends are incompatible the

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DNK-PK-Artemis complex carries out minimal end resection and removes 5′ and 3′ DNA overhangs prior to ligation (Chang et al. 2017).

Overexpression of DNA-PK, the core component of c-NHEJ, is common in TNBC and associated with proficient DSB repair by NHEJ (Alluri et al. 2016). Because DNA-PK is crucial to repair by NHEJ its inhibition with small molecule therapy has been proposed as a strategy to sensitise tumours to DSB causing treatments (Damia 2020). Several small molecule inhibitors have been developed that target the kinase activity of DNA-PK (e.g., NU7441, AZD7648, KU-0060648) and have been shown to sensitise TNBC cells to irradiation and topoisomerase II inhibitors; doxorubicin and etoposide (Ciszewski et al. 2014; Fok et al. 2019; Munck et al. 2012; Alluri et al. 2016). The DNA-PK inhibitor M3814 has shown promising results in multiple cancer models in combination with DNA damaging therapies (Damstrup et al. 2016; Wise et al. 2019; Chauhan et al. 2019) and is currently being trialled with radiotherapy in advanced solid tumours (NCT02516813) (Bendell et al. 2019). A disadvantage of DNA-PK inhibitors is that normal replicating cells rely predominantly on DNA-PK mediated NHEJ repair throughout the cell cycle if DSBs are incurred. Hence DNA-PK inhibition has the potential to be very toxic to normal proliferating epithelial cells, particularly when combined with DNA damaging chemotherapies.

1.5.5.2 Alternative NHEJ The alt-NHEJ pathway proceeds independently of the canonical NHEJ repair factors and is not fully understood. PARP1 is involved in sensing DSBs and likely competes directly with the KU proteins for DNA end binding (Wang et al. 2006). PARP1 then recruits CtIP and the MRN complex which resects DNA ends to expose a microhomologous region (<25 bp) (Seol, Shim, and Lee 2018; Chang et al. 2017). The exposed strands of ssDNA are then annealed at the microhomologous sequence, the 3′ ssDNA overhangs are cleaved, DNA polymerase θ fills in the gap and the nick is ligated (Chang et al. 2017; Wang and Xu 2017). Tumours with HR deficiency due to BRCA mutation rely heavily on PARP1 mediated alt- NHEJ during S/G2 to repair DSBs, which makes PARP inhibition an attractive strategy for sensitising these tumours to DSB inducing chemotherapies.

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Figure 1-8 DSB repair by end joining pathways.

Binding of KU during c-NHEJ limits end resection yielding repair products with minimal insertions/deletions. In the absence of KU, repair by alt-NHEJ and SSA involve damage recognition by PARP1 and significant end resection. Alt-NHEJ anneals regions of microhomology flanking the DSB site followed by ligation and deletion of the intervening DNA sequence yielding deletions and insertions at the breakpoint junctions. Single strand annealing is mediated by RAD51 and involves pairing of long stretches of homologous regions flanking the DSB site and induces large deletions but not insertions at repair junctions.

Adapted from “Risky business: Microhomology-mediated end joining” by S. Sinha et al, 2016, Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, 799, p. 18. Copyright 2015 by Elsevier. Adapted with permission.

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1.5.6 Repair of DSBs by Homologous Recombination In normal, non-cancerous cells, repair of DSBs by HR is a complex and tightly regulated process that utilises a homologous sequence located in the sister chromatid to accurately synthesise new DNA to replace the lost DNA. Because a homology template is required for HR it is limited to S and G2 phases of the cell cycle; after DNA has been copied and the two chromatids are still held together by a cohesion complex (Kelley and Fishel 2016). HR is initiated by the MRN complex binding to the DSB site which then recruits other factors required for end resection including; C-terminal-binding protein interacting protein (CtIP) exonuclease 1 (EXO1), Bloom syndrome protein (BLM) and DNA2 nuclease/helicase (Liu and Huang 2016). The decision to initiate extensive DNA end resection and commit to repair by HR is dependent on the activity of 53BP1 and BRCA1, however the exact mechanism is not completely understood. It is likely that 53BP1 is recruited to DSBs that arise throughout the cell cycle and is transiently phosphorylated by ATM (Shibata 2017). 53BP1 in turn recruits and binds RIF1 and together they form a complex that blocks end resection and promotes NHEJ (Bunting et al. 2010; Chapman et al. 2013). During S and G2 phases of the cell cycle BRCA1 acts as an antagonist to this process. BRCA1 promotes 53BP1 dephosphorylation which prompts the release of RIF1 and repositioning of 53BP1, alleviating the barrier to end resection (Isono et al. 2017). Additionally, BRCA1 interacts with CtIP and the MRN complex to promote resection and repair by HR (Yu et al. 2006; Densham et al. 2016). Once HR is initiated it proceeds in three stages: presynaptic, synaptic and post- synaptic.

The presynaptic phase of HR encompasses DNA end resection and formation of the RAD51-ssDNA nucleoprotein filament, also called the presynaptic filament (Gaines et al. 2015). CtIP and the MRN complex digest toward the DSB end using MRE11 3’-5’ exonuclease activity (Cannavo, Reginato, and Cejka 2019). Next EXO1 and/or DNA2 digest DNA in the 5’-3’ direction to produce long 3′-ssDNA tails which are rapidly coated by Replication Protein A (RPA) (Liu and Huang 2016; Mimitou and Symington 2008). Mediators, such as the RAD51 paralogs, RAD52, RAD54, PALB2, the Shu complex, and BRCA2 then assist RAD51 loading onto ssDNA and forming a contiguous helical nucleofilament, displacing RPA in the process (Gaines et al. 2015; Sung et al. 2003).

In the synaptic phase of HR the RAD51 nucleofilament, assisted by RAD54 and SNF2/SWI2, invades duplex DNA where it probes the DNA, 3 base pairs at a time, searching for a homologous stretch of DNA to use as a repair template (Lee et al. 2015; Ceballos and Heyer 2011). Multiple segments of the RAD51 nucleofilament can search different regions

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of duplex DNA at the same time and strand invasion is initiated when a minimum homology sequence of at least 8 base pairs is identified (Qi et al. 2015; Forget and Kowalczykowski 2012). The 3’ end of the pre-synaptic filament then invades the duplex DNA, displacing one strand of the homologous template, yielding a transient structure known as a displacement loop (D-loop) (San Filippo, Sung, and Klein 2008). The displaced strand serves as a template and the invading strand is extended by DNA synthesis (Daley et al. 2014).

1.5.6.1 Canonical HR In the post-synaptic phase the invading strand and D-loop heteroduplex are disassembled by one of three mechanisms which yield gene conversion (GC: non-reciprocal exchange of genetic material) associated or not with crossing-over (CO: reciprocal exchange of the adjacent sequences) (Morrical 2015; Guirouilh-Barbat et al. 2014). As a result of coordinated regulation by many different proteins, including; p53, BCL-2, AKT1, MMR proteins, BRCA1, RTEL, PARI and BLM, normal mitotic cells favour the error-free, synthesis dependent stand annealing (SSDA) pathway which results in GC between two sister chromatids with non-crossover (NCO) (Godin, Sullivan, and Bernstein 2016; Prado 2014b). In SDSA the D-loop dissociates and the extended ssDNA anneals to its complementary ssDNA on the other break end, resulting in second end capture. A second round of DNA synthesis occurs at both DNA ends and ligation resulting in gene conversion (Morrical 2015). When gene conversion occurs between sister chromatids it cannot transfer mutation or result in loss of heterozygosity (LOH) because the DNA sequences in sister chromatids are identical (Prado 2014a). This outcome is also referred to as equal sister- chromatid recombination (León-Ortiz et al. 2018; Bertrand, Saintigny, and Lopez 2004; Plo and Lopez 2009; Guirouilh-Barbat, Wilhelm, and Lopez 2010; Laulier et al. 2011).

1.5.6.2 Non-Canonical HR It is important to recognise that the machinery used in HR is the same as that used during meiosis to ensure allele mixing and genetic diversity (Guirouilh-Barbat et al. 2014) and in CRISPR protocols to introduce mutations (Ran et al. 2013). Hence even as a pathway with high fidelity repair HR has the intrinsic capacity to modify genetic information and promote genomic instability (Guirouilh-Barbat et al. 2014). In cancer cells HR is more likely to have mutagenic outcomes due to regulatory dysfunction and increased use of the double strand break repair pathway (DSBR) and break induced replication (BIR) during post- synapsis. In the DSBR pathway the D-loop remains stable while the invading strand captures its second end by annealing and ligation, forming a double Holliday junction (dHJ) (Morrical 2015). From this point two mechanisms can take place to process; dHJ; dissolution

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or resolution, followed by gap filling and ligation. Dissolution is favoured by normal mitotic cells and generates NCO, whereas resolution produces CO products (Morrical 2015; Sebesta and Krejci 2016). BIR is used in instances where only one broken DNA end can invade into the homologous template, which occurs at collapsed replication forks or eroded telomeres (Elango et al. 2017). During BIR, the invading strand becomes the replication fork and can potentially replicate the template DNA to the end of a chromosome (Godin, Sullivan, and Bernstein 2016). BIR is highly mutagenic compared to normal replication (Godin, Sullivan, and Bernstein 2016; Prado 2014b). Dysregulation of HR can potentially result in recombination between non-allelic repeat sequences of DNA located on a heterologous chromosome, homologous chromosome or even repeat sequences located on the same chromosome or sister chromatid. These aberrant forms of HR promote genome instability and may result in LOH, translocations, deletions, amplifications and inversions (Prado 2014a; León-Ortiz et al. 2018). The various homologous recombination pathways are depicted in Figure 1.9.

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Figure 1-9 Models of homologous recombination.

DSB repair by HR is initiated by 5′–3′ resection of the broken ends creating 3′ ssDNA tails that are rapidly coated by RPA (yellow). With the assistance of mediators, including BRCA2 (blue), RAD51 (green) is loaded onto the ssDNA, displacing RPA, and forms the presynaptic filament. The presynaptic filament initiates pairing and strand invasion with the homologous duplex DNA and is extended by DNA synthesis using the donor duplex as a template leading to the formation of D-loop. In the SDSA model the D loop is displaced, and the DNA is resolved into a non-crossover product (NCO). In the DSBR model second end capture forms a double Holliday junction (dHJ) which can be resolved by dissolution or resolution producing either crossover (CO) or NCO products. BIR occurs when only one end of the DSB is available (e.g., at stalled replication forks) and involves migration of the D-loop replication “bubble” along the chromosome until another replication fork or the end of the chromosome is reached. This form of repair causes both strands of the homologous donor sequence to be copied resulting in loss of heterozygosity (LOH).

Adapted from “Homologous recombination and nonhomologous end-joining repair in yeast” by R. E. Jones and T. C. Humphrey, in I. Kovalchuk and E. Kovalchuk (Eds), Genome Stability (p. 119), 2016, Boston, USA: Academic Press. Copyright 2016 Elsevier. Adapted with permission.

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1.5.6.3 HR Deficiency Germline mutations in tumour suppressor genes BRCA1 or BRCA2 result in HR deficiency (HRD) and are associated with genomic instability and predisposition to breast and ovarian cancer. Mutations in BRCA1 and BRCA2 are found in approximately 20% of TNBC cases (Gonzalez-Angulo et al. 2011; Rodler et al. 2016; Greenup et al. 2013; Brianese et al. 2018; Armstrong et al. 2019; Atchley et al. 2008; Engel et al. 2018). Although an innate deficiency in HR is undesirable from a cancer risk perspective, it can be exploited with DNA damaging chemotherapeutics and targeted therapies.

To maintain DNA integrity, HR-deficient cells rely on PARP-dependent DNA repair pathways such as BER, SSBR, alt-NHEJ and SSA to repair DNA damage, making PARP1 activity essential in BRCA1/2 mutant tumours (López-González, Ibeas Millán, and Provencio 2012). In vitro, PARP inhibition and BRCA1/BRCA2 loss of function mutations are a synthetic lethal combination. This sensitivity is likely caused by both unresolved DNA damage and obstruction of replication forks due to PARP trapping, both of which depend on HR to overcome. These lesions are lethal in BRCA1 and BRCA2 mutant tumours due to loss of a functional HR pathway (Farmer et al. 2005). Currently two PARP1/2 inhibitors, olaparib and talazoparib are approved for clinical use in metastatic TNBC patients with germline BRCA mutations and are associated with significantly longer progression free survival compared with single agent standard chemotherapy (Litton et al. 2018; Robson et al. 2019; Veneris et al. 2020). Several chemotherapy agents (e.g., doxorubicin, carboplatin, paclitaxel) are currently being evaluated in combination with PARP inhibitors to assess if combination therapy can improve chemotherapy responses via increased parp “trapping” or increased formation of double-strand DNA breaks. To date the results from clinical trials show that veliparib (which has less PARP trapping ability and lower haemotoxicity than olaparib and talazoparib) is the best tolerated PARP inhibitor in chemotherapy combination studies (Bayraktar, Glück, and Darling 2019).

1.5.7 DNA Damage Tolerance Mechanisms Stalled replication forks are unstable structures and prolonged arrest increases the risk of fork collapse which generates DSBs (Branzei and Szakal 2016). Consequently cells have evolved DNA damage tolerance (DDT) mechanisms to bypass blockades to replication fork progression, protect the stalled fork and fill in the resulting ssDNA gaps opposite the template strand (Prado 2014b). DDT mechanisms induced by chronic low dose DNA damage prevent the accumulation of unrepaired ssDNA that would trigger cell cycle arrest at G2/M (Prado 2014b). If damage is located on the lagging strand, synthesis of a new

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Okazaki fragment causes the obstructing lesion to be contained in a small ssDNA gap behind the replication fork and these ssDNA gaps are reprimed and filled post-replicatively by either error prone translesion synthesis or HR mediated template switching (Yeeles et al. 2013; Masuda, Hanaoka, and Masutani 2016; Bi 2015; Branzei and Szakal 2016). Whereas, a lesion on the leading strand causes uncoupling of the leading and lagging strand polymerases, generating a stretch of ssDNA close to the fork junction which is bypassed by fork reversal Zellweger (Zellweger et al. 2015). DDT mechanisms both at and behind the replication fork are highly dependent on the regulation of RAD51, the central recombinase in HR (Prado 2018) (Figure 1.10).

Studies in yeast show that RAD51 has essential recombination and non-recombination functions during DDT. Independent of DNA damage Rad52 loads Rad51 onto unperturbed replication forks (González‐Prieto et al. 2013). This recruitment of Rad51 to replication forks is increased in response to genotoxic treatments (Zellweger et al. 2015). When a fork does encounter DNA damage Rad51 acts to slow down replication fork progression and both Rad51 and Rad52 interact with the blocked replication fork helping it to physically bypass the lesion then remain bound to the ssDNA gap left behind the replication fork. González‐ Prieto et al. (2013) observed that this early coupling of Rad52 and Rad51 to the replication fork and ssDNA gap was a pre-requisite for post-replicative gap filling by HR-mediated template switching. DNA lesions that block the replication fork trigger SUMOylation and ubiquitination of the DNA clamp; proliferating cell nuclear antigen (PCNA) via the Atr-Chk1 pathway (Fig. 1.4) (Chang and Cimprich 2009; Hoege et al. 2002). Rad6-Rad18 mediated monoubiqitnation of PCNA promotes the transient switch from DNA polymerase to low fidelity translesion synthesis polymerase to fill in the ssDNA gap post-replicatively using the damaged DNA template (Masuda, Hanaoka, and Masutani 2016). Additional ubiquitination (polyubiquitination) of PCNA by Mms2-Ubc13-Rad5 promotes error-free HR mediated template switching utilising high-fidelity DNA polymerase and the newly synthesised undamaged sister chromatid as a template to fill in the ssDNA gap (Mailand, Gibbs- Seymour, and Bekker-Jensen 2013; Yeeles et al. 2013). During S phase, SUMOylation of PCNA recruits Srs2; a helicase that disrupts RAD51-ssDNA nucleofilament formation (Urulangodi et al. 2015; Pfander et al. 2005; Burkovics et al. 2016) and supresses crossover recombination (Robert et al. 2006; Miura, Shibata, and Kusano 2013). In mammalian cells PARI (Burkovics et al. 2016) and FBH1 (Chiolo et al. 2007; Simandlova et al. 2013) have been suggested as counterparts of yeast Srs2. To balance the anti-recombinase activity of Srs2 the Rad51 paralogues; Rad55 and Rad57 (Liu et al. 2011) and Esc2 (Urulangodi et

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al. 2015; Urulangodi, Szakal, and Branzei 2016) are also recruited to stalled replication forks, permitting stable Rad51-ssDNA filament formation and non-crossover recombination during early S-phase (Alabert, Bianco, and Pasero 2009; González‐Prieto et al. 2013). (Figure 1.10)

When lesions are encountered by the leading stand the preferential DDT mechanism in human cells is characterised by replication fork reversal (Zellweger et al. 2015). Replication fork reversal involves unwinding and annealing of newly synthesized daughter strands and annealing of parental strands to form a four-way junction that is backtracked on the DNA molecule (Neelsen and Lopes 2015). Fork reversal is then followed by either RAD51-mediated strand invasion and HJ formation downstream of the blocking lesion or by DNA synthesis and fork regression (Prado 2014a). Zellweger (2015) has shown in human cells that RAD51 is essential for remodelling forks with extended stretches of ssDNA into reversed forks. RAD51 also plays an important role in protecting and stabilising stalled replication forks that is separate from its HR function. RAD51, in concert with BRCA2 (Hashimoto et al. 2010; Costanzo 2011; Schlacher et al. 2011; Sirbu et al. 2011) and FANCD2 (Schlacher, Wu, and Jasin 2012) prevent fork degradation by forming a stable nucleofilament around vulnerable stretches of ssDNA to limit MRE11 resection (Schlacher et al. 2011; Schlacher, Wu, and Jasin 2012). Thus FANCD2 was found to be synthetic lethal with loss of RAD51 function when treated with HDAC inhibitors (Wiegmans et al, 2015). While DDT mechanisms support genome stability in normal cells they can also facilitate the proliferation and survival of cancer cells with high levels of replication stress (Gaillard, García-Muse, and Aguilera 2015).

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Figure 1-10 Homologous recombination mediated DNA Damage Tolerance Mechanisms.

(A) In response to replication stress (e.g., blocking lesions) displacement and reannealing of the nascent strand of DNA leads to formation of a reversed replication fork through a process that requires RAD51. RAD51 nucleofilament formation at the reversed fork is required to stabilise the structure and to prevent nuclease degradation. Reversed forks may bypass lesions by either DNA synthesis and fork regression, or RAD51 mediated strand invasion ahead of the fork. (B) If lesions bypassed during replication leave ssDNA fragments behind the fork these are filled post-replicatively by either translesion synthesis (TLS) during G2/M phase or homologous recombination (HR) during S or G2/M phase.

Adapted with permission from “Homologous recombination: To fork and beyond” by F. Prado, 2018, Genes, 9(12), p. 2, 5. CC BY 4.0 https://creativecommons.org/licenses/by/4.0/

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1.6 THE SIGNIFICANCE OF RAD51 IN CANCER

1.6.1 Overview of RAD51 Structure, Function and Activity Human RAD51 protein (radiation sensitive protein 51) is composed of 339 amino acids and is essential for DNA homology search and strand invasion during homologous recombination (Gonzalez et al. 1999). Homologues of RAD51 are highly conserved among species which reflects the critical role RAD51 plays in HR (Lin et al. 2006). Partial crystalline reproductions of human RAD51 reveal that it contains two domains; a C-terminal capable of binding ATP and an N-terminal that binds both ssDNA and dsDNA (Aihara et al. 1999; Pellegrini et al. 2002). The recombinase function of RAD51 that pairs and exchanges homologous DNA sequences during HR is an ATP dependent reaction (Ogawa et al. 1993; Baumann, Benson, and West 1996). In contrast, the non-enzymatic function of RAD51 binding nascent ssDNA during replication stress to prevent excessive MRE11 mediated degradation is ATP-independent (Mason et al. 2019). Despite the important role RAD51 has in the nucleus during repair and replication it does not contain a nuclear localisation signal, however it does contain a nuclear export signal. Hence, in the absence of genotoxic stress RAD51 is localised to the cellular cytoplasm (Mor, White, and Fontoura 2014). In the event of DNA damage RAD51 localisation to the nucleus and recruitment to chromatin is dependent on protein binding partners that contain a nuclear localisation signal, such as BRCA2 and paralogue RAD51C to transport it into the nucleus (Mor, White, and Fontoura 2014; Gildemeister, Sage, and Knight 2009). The localisation, activity and degradation of RAD51 is largely regulated by post-translational modifications including tyrosine, serine and threonine phosphorylation and ubiquitination (Popova, Henry, and Fleury 2011). RAD51 is a challenging protein to study in mammalian systems because it is considered an “essential” gene with loss of functional RAD51 is embryonic lethal in mouse models, the complete crystal structure of human RAD51 is yet to be solved and the protein monomers cannot be resolved by protein mass spectroscopy (Sonoda et al. 1998; Lim and Hasty 1996; Tsuzuki et al. 1996; Renodon-Cornière et al. 2013).

1.6.2 RAD51 Overexpression in Cancer and Tumour Cell Lines Expression of RAD51 is cell cycle regulated, with its highest expression occurring during S/G2 phase and low levels of expression in non-proliferating cells (Klein 2008). Researchers have observed for many years that RAD51 is overexpressed in a variety of cancers and tumour cell lines, including; breast cancer (Tang et al. 2018), ovarian cancer (Liu et al. 2015), cervical cancer (Paulíková et al. 2013), pancreatic cancer (Maacke, Jost et al. 2000), soft tissue sarcoma (Hannay, Liu et al. 2007), non-small-cell lung cancer

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(Takenaka, Yoshino et al. 2007), prostate cancer (Mitra, Jameson et al. 2009), chronic myeloid leukaemia, melanoma and glioblastoma (Raderschall, Stout et al. 2002). A growing body of evidence supports that RAD51 overexpression in cancer is correlated with higher histological tumour grade (Sarwar et al. 2017; Wiegmans et al. 2014; Maacke, Opitz, et al. 2000; Tang et al. 2018) large tumour size, positive lymph node metastasis and distant metastasis (Sarwar et al. 2017; Wiegmans et al. 2014) chemotherapy resistance (Hansen et al. 2003; Takenaka et al. 2007; Hannay et al. 2007; Yang 2012) and worse overall patient survival (Li, Wang, et al. 2017; Zhang, Ma, et al. 2019; Welsh et al. 2009; Pataer et al. 2018; Tang et al. 2018).

RAD51 overexpression in cancer cells involves changes in transcriptional regulation of the gene promoter rather than gene amplification or increased protein stability (Raderschall, Stout et al. 2002). Hine, Seluanov, and Gorbunova (2008) found that RAD51 mRNA and protein levels were increased around 4–6-fold in cancer cells due to hyperactivation of the RAD51 gene promoter; with activity increased at least 840-fold compared to normal cells. In breast cancer RAD51 is more highly expressed in HER2+ and TNBC tumours, which are considered more aggressive compared to luminal subtypes (Jia et al. 2019). Analysis of mRNA levels in TNBC patient tumours reveals that greater than 70% overexpress RAD51 (Wiegmans et al. 2014). An important regulator of RAD51 expression that is often lost in TNBC is p53. Binding of wild type-p53 to the RAD51 promoter downregulates RAD51 transcription, however mutant p53 has lost this transactivation function (Arias‐Lopez et al. 2006). The hyperactive expression of RAD51 in cancer cells cannot be explained by loss of p53 alone, the promoter is likely activated by several driver oncogenes in a gradual, stepwise manner as cells accumulate mutations and progress towards malignancy (Hine et al. 2014). Additionally, several signalling pathways that are upstream regulators of RAD51 expression or activity are enriched in TNBC tumours, particularly in BL2 and M subtypes, including pathways mediated by; IGFR1 (Venkatachalam et al. 2017), MEK-ERK1/2 and PI3K-AKT (Ko et al. 2009; Lee, Kang, et al. 2019), (Zhong et al. 2016), VEGF (Elaimy et al. 2019), EGFR (Ko et al. 2008) and MET (Chabot et al. 2019).

1.6.3 RAD51 Overexpression Associated with Elevated and Aberrant Recombination Experiments that have manipulated RAD51 expression levels in vitro have shown that overexpression of RAD51 results in increased frequency of repair by HR (Vispe et al. 1998; Bertrand et al. 2003) whereas downregulation of RAD51 decreases HR (Bindra et al. 2004). For instance Vispe et al. (1998) found that a 2-3 fold increase in RAD51 expression increased the rate of HR in p53 deficient Chinese Hamster Ovary cells, as measured by

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recombination between a direct repeat of LacZ genes to give a LacZ+ recombinant, by at least 20-fold and these cells showed increased resistance to ionizing radiation, particularly in G2 of the cell cycle. In addition to increasing the frequency of HR, RAD51 overexpression in cancer cells has been shown to stimulate non-canonical recombination outcomes that promote genome instability. Richardson et al. (2004) found that following induction of DSBs transiently increased levels of RAD51 promoted CO recombination products (which lead to translocation) and aneuploidy (both gain and loss of chromosomes). Consequently, cells overexpressing RAD51 respond with hyperactive and aberrant HR when faced with DNA damage, which in turn might drive normal cells towards neoplastic transformation or contribute to cancer progression, metastasis and chemotherapy and radiotherapy resistance (Nagathihalli and Nagaraju 2011) (Figure 1.11).

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Figure 1-11 Role of RAD51 overexpression in cancer development and progression.

Physiological expression of RAD51 in normal cells leads to the repair of DNA lesions by canonical homologous recombination and suppresses genome instability. In contrast, RAD51 overexpression stimulates illegitimate/hyperrecombination which is associated with outcomes including chromosomal translocations, amplifications, deletions and LOH that might lead to activation of oncogenes, inactivation of tumour suppressor genes and genome instability. These genomic rearrangements could advance normal cell towards neoplastic transformation and facilitate the development and progression of cancer. RAD51 overexpression could also occur as a consequence of tumourigenesis and contribute to cancer progression and metastasis.

Reproduced from “RAD51 as a potential biomarker and therapeutic target for pancreatic cancer” by N. S. Nagathihalli and C. Nagaraju, 2011, Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, 1816(2), p. 211. Copyright 2011 by Elsevier. Reproduced with permission.

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1.6.4 RAD51 Overexpression associated with Worse Clinical Outcomes Several studies have demonstrated a relationship between RAD51 expression and clinical outcomes, disease progression and metastasis. Graeser, McCarthy et al. (2010) studied 68 patients with localized primary breast cancer who received anthracycline‐based neoadjuvant chemotherapy. Core biopsies taken 24 hours after the first administration of chemotherapy were scored for RAD51 positivity based on the presence of RAD51 nuclear foci. The size and number of RAD51 nuclear foci in response to DNA damage is a reliable marker of HR proficiency and characterises the formation of RAD51 filaments at the site of DSBs. Low RAD51 scores were found to predict pCR following treatment, with 33% of low RAD51‐scored tumours achieving a pCR compared to only 3% of high RAD51-scored cancers. Le Scodan et al. (2010) compared tumour samples from 97 breast cancer patients enrolled in a phase III trial (Centre Rene´ Huguenin cohort; CRH cohort) with and without locoregional recurrence (LRR) in order to identify patterns of gene expression associated with clinical outcome. The findings were validated in comparison with those of an independent cohort of 295 breast cancer patients (Netherlands Cancer Institute cohort; NKI cohort). The authors found that RAD51 was the only gene associated with LRR in both cohorts. RAD51 expression was 2.8-fold higher in patients with LRR than in patients without LRR in the CRH and NKI cohorts, respectively. With a median follow-up of 126 months in the CRH cohort, the 5-year LRR-free survival rate was 100% in the 61 patients with low RAD51 expression and 70% in the 36 patients with high RAD51 expression (p< 0.0001). In the NKI cohort RAD51 overexpression was also significantly associated with LRR (97% vs.89%) and overall survival (90% vs. 75%) in patients with low and high RAD51 expression respectively (p< 0.0001).

The development of brain metastases is a devastating consequence of TNBC that occurs in more than a quarter of patients and is associated with a median survival of less than one year (Jin et al. 2018). To identify specific genes associated with brain metastases Woditschka et al. (2014) compared RNA expression in 23 matched sets of resected primary breast tumours and brain metastases. The authors found that RAD51 and BARD1 were significantly elevated in brain metastases samples compared with either matched primary tumours (from the same patient) or unlinked systemic metastases (from GEO GSE14017 microarray set). In vivo, RAD51 overexpression in two models of TNBC (inoculated with brain metastatic MDA-MB-231 BR cells or murine 4T1-BR cells) promoted the formation of brain metastases, but not lung metastases, while shRNA knockdown of RAD51 decreased brain metastases but not lung metastases development. Treatment of cells with Tempol, an

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oxygen radical scavenger inhibited the promotion of brain metastases induced by BARD1 and RAD51 overexpression. The authors posit that the increased HR efficiency observed with RAD51 and BAIRD1 overexpression may constitute a mechanism to overcome the high levels of ROS-mediated genotoxic stress in the brain microenvironment. Supporting these observations, Wiegmans et al. (2014) found that RAD51 depletion inhibited the development of both brain and lung metastases in a syngeneic TNBC mouse model and MDA-MB-231 xenografts. Wiegmans et al. (2014) performed immunohistochemistry analysis on an independent cohort of 235 sporadic breast cancers (invasive ductal carcinoma; IDC=121, invasive lobular carcinoma; ILC=114) and found that RAD51 expression increased during the course of breast cancer progression and metastasis. For ILC cases with lymph node metastases the authors observed significant enrichment of nuclear RAD51 in lymph node metastases (7/28, 25%) compared to the primary tumours (10/114, 8.8%). Comparison of matched primary IDC and brain metastases revealed a higher frequency of nuclear RAD51 positivity in brain metastases (17/39, 43%) compared to primary tumours (8/39, 20%). In vitro, induced overexpression of RAD51 significantly enhanced migration of TNBC HS578T cells and siRNA knockdown of RAD51 significantly inhibited migration of TNBC MDA-MB- 231 cells. Interestingly the authors observed altered morphology in MDA-MB-231 cells after seven days of RAD51 knockdown, from spindle-like to a more epithelial, flattened shape, suggestive of cytoskeletal rearrangement via epithelial–mesenchymal transition (EMT) reversal, however there were no significant changes in expression of EMT markers; CD24/CD44, vimentin or E-cadherin. Because EMT is only partially executed by most tumour cells there may not be a corresponding change in end stage EMT markers, however partial execution of EMT is sufficient to increase cancer cell motility and migration of individual cells or cell clusters thereby promoting invasion, dissemination and metastasis (Brabletz et al. 2018). Similar EMT-like phenotypic changes associated with RAD51 expression levels have been observed in cell lines derived from oesophageal squamous cell carcinoma (Chiu et al. 2020), pancreatic cancer (Nagathihalli and Nagaraju 2011) and fibrosarcoma (Orre, Fält, et al. 2006). Nagathihalli and Nagaraju (2011) observed altered morphology in highly chemoresistant pancreatic cancer cell line, PANC-1 following siRNA RAD51 downregulation which was accompanied by decreased expression of vimentin and N-cadherin expression. In RAD51 silenced oesophageal squamous cell carcinoma cells Chiu et al. (2020) found that the expression of epithelial maker (ZO-1) was increased, while the expression of mesenchymal markers (Slug, Snail, and Vimentin) were decreased compared control cells. In RAD51-overexpressing cells, blocking the p38/Akt pathway decreased expression of Snail and inhibited cell viability and migration, suggesting that

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RAD51 overexpression mediated EMT via p38/Akt/Snail signaling (Chiu et al. 2020). In TNBC Wiegmans et al. (2016) found that p38 inhibition enhanced the cytotoxic effect of RAD51 inhibition alone. Although the mechanism requires elucidation, collectively these results provide evidence of a relationship between RAD51 expression and the acquisition of EMT phenotype in cancer cells, which not only contributes to metastasis but also confers resistance to chemotherapy and radiotherapy (Shibue and Weinberg 2017).

Since EMT is a precursor to metastasis Wiegmans et al. (2014) was motivated to investigate whether RAD51 expression level affects expression of genes known to promote or supress metastasis. Expression levels of 82 metastasis related genes were compared between high RAD51 expressing MDA-MB-231 cells with and without induced knockdown of RAD51 and between low RAD51 expressing Hs578T cells with and without induced overexpression of RAD51 (Wiegmans et al. 2014). The authors identified 25 genes that were significantly induced with RAD51 overexpression and repressed with RAD51 knockdown. Several of these genes (MMP11, MMP13, TGFβ, SMAD2 and p53) were known targets of the transcription factor CCAAT/enhancer binding protein beta (CEBPβ), an important regulator of mammary gland development (Spike and Rosen 2020) that has previously been shown to interact directly with RAD51 (Chipitsyna et al. 2006). In HIV-1 infected astrocytes Chipitsyna et al. (2006) found that RAD51 serves as a co-factor for CEBPβ to modulate transcription of early viral genes (Chipitsyna et al. 2006). Interestingly RAD51 has also been shown to interact with and enhance virus gene transcription mediated by the transcription factor nuclear factor kappa B (NF-κB) during infection with HIV and human polyomavirus JC (Kaminski et al. 2014; White et al. 2014; Rom et al. 2010). Wiegmans et al. (2014) confirmed in TNBC cells that RAD51 and CEBPβ form a complex in situ and that siRNA depletion of RAD51 reduced enrichment of CEBPβ at the promoter of target genes and decreased expression of these genes by up to 80% (Wiegmans et al. 2014). These results provide early evidence of a new function of RAD51 in cancer, as a transcription co-factor, that may facilitate the development of distant metastasis in patients who overexpress RAD51. Further research is needed to identify the full range of gene expression profiles regulated by RAD51 in conjunction with CEBPβ and potentially other transcription factors, such as NF-κB.

In light of the studies discussed in this section it is evident that RAD51 overexpression promotes cancer development, progression, metastasis and resistance to chemotherapy and radiotherapy by at least three mechanisms; by increased and aberrant HR, by promoting acquisition of EMT phenotype and by upregulating pro-metastatic gene expression. Hence inactivation of RAD51 with targeted therapies could be a potential strategy for overcoming

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chemotherapy and radiotherapy resistance and for preventing or treating tumour progression and metastasis.

1.6.5 Targeting RAD51 for Cancer Therapy Several early studies showed that RAD51 depletion sensitised cells to anti-cancer therapies. For example, Ito et al. (2005) showed that cell killing by cisplatin was increased by RAD51 siRNA knockdown in HeLa S-3 (cervical cancer), A549 (lung cancer), PANC-1 and AsPC-1 (pancreatic cancer) cell lines. Similarly, antisense RNA depletion of RAD51 increased sensitivity to ionising radiation in malignant glioma (Short et al., 2011) and osteosarcoma cells (Du et al., 2011). More recently Xu et al. (2019) found that short hairpin RNA silencing of RAD51 increased sensitivity of neuroblastoma cells to doxorubicin and . Choi et al. (2020) observed that RAD51 siRNA knockdown sensitised MDA-MB-231 TNBC cells to proton irradiation and enhanced proton induced apoptosis (Choi et al. 2020). Additionally, Deng et al. (2020) showed that repression of RAD51 transcription and subsequent protein downregulation sensitised MDA‐MB‐231 and MCF‐7 breast cancer cells to cisplatin. These studies validate RAD51 as a clinically relevant target in cancer and provide proof of principle for the development of novel strategies that directly inhibit its recombinase function or interfere with its interaction with other proteins.

To identify leads for drug development researchers have performed high-throughput screening of compound libraries to identify small molecule RAD51 inhibitors. Small molecule inhibitors are a class of low molecular weight, organic compounds that bind to the active site of a target protein to interfere with enzyme activity or protein-protein interactions (Ganten et al. 2006; Arkin and Wells 2004). B02 was the first of these compounds to be well profiled in the literature. B02 was discovered by high-throughput screening of the NIH Small Molecule Repository (>200,00 compounds) using a fluorescence based DNA strand exchange assay (Huang et al. 2011). D-loop assay confirmed that B02 specifically inhibited human RAD51 but not the eukaryotic homologue RecA, with an IC50 of 27.4µM. Order of addition experiments determined that B02 disrupts binding of RAD51 to ssDNA and destabilises the RAD51-ssDNA complex which subsequently inhibits ATP hydrolysis by RAD51 (Huang et al. 2012).

RI-1 is another small molecule RAD51 inhibitor that was identified by high-throughput screening of 10,000 molecules (Chembridge DIVERSetTM). Fluorescent polarization was used to detect molecules that inhibited HsRAD51 binding to ssDNA in human osteosarcoma cells (U2OS) (Budke, Logan, et al. 2012). Subsequent screening with human embryonic kidney cells (HEK293) determined that the inhibitory effect of RI-1 was concentration-

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dependent, with IC50 values in the 5-3 0µM range. RI-1 caused a significant reduction in IR induced RAD51 foci formation and showed some toxicity to commonly used cancer cell lines (HeLa, MCF-7 and U2OS). Preliminary structure activity relationship studies revealed that RI-1 attaches covalently to a pocket on the surface of HsRAD51, inhibiting the ability of RAD51 to bind and form filaments on ssDNA and may interfere with RAD51’s interaction with ATP. The authors noted concerns that RI-1 may have limited therapeutic applications however, because the RI-1-RAD51 bond was irreversible and because Michael acceptors were involved, which are often toxic in drug formulations. In an effort to overcome these issues subsequent structure activity relationship analysis was carried out using derivatives of RI-1 with and without Michael reactivity (Budke, Kalin, et al. 2012). Of these analogues, 7a was identified as the lead compound. 7a and RI-1 were found to compete for the same binding site on RAD51 and binding of 7a to RAD51 was fully reversible and without Michael acceptor activity. However, despite overcoming the issue of Michael acceptor activity and irreversible bindings, the IC50 and LD50 values were significantly higher for 7a, 44.17µM and

70.16µM respectively compared to RI-1 (IC50 = 6.82, LD50=16.62).

IBR2 is a small molecule that mimics the inhibitory effect of BRC repeats binding to RAD51, most commonly associated with BRCA2 binding of RAD51. IBR2 was discovered by screening 24,000 small compounds from the Nanosyn library using a yeast expression construct to identify molecules capable of abolishing interaction between BRC and RAD51- derived probes (Zhu et al. 2013). Surface plasmon reasonance confirmed that IBR2 bound specifically to RAD51 and not to the BRC repeat. Binding of IBR2 to RAD51 inhibited HR by preventing multimerization of RAD51 and filament formation, which are essential early steps in HR (Zhu et al. 2013). Treatment with IBR2 (20µM for 8hrs) significantly inhibited RAD51 foci formation in IR treated MCF7 cells (human breast adenocarcinoma). A longer incubation time of 32hrs with IBR2 (20 µM) was required to inhibit HR in HeLa-DR-GFP cells. qPCR examination of IBR2 treated cells revealed IBR2 does not affect RAD51 at the transcriptional level; rather IBR2 inhibits HR by preventing RAD51 multimerization. RAD51 is unstable as a monomer and is stored in the cytoplasm and nucleus as heptamers. IBR2 disrupts RAD51 heptamers inducing poly-ubiquitination of RAD51; increasing its proteasome-mediated degradation (Zhu et al. 2013). IBR2 was shown to be effective at inhibiting cell growth in a variety of leukemia, cervical and breast cancer cell lines including; K562, HeLa, MDA-MB-

231, MDA-MB-468, MDA-MB-435, MCF7, HBl100 and T47D with an IC50 range of 11.5- 16.0µM. In vivo, IBR2 treatment was tested in a breast cancer xenograft model with nude

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mice. Tumour growth was significantly slowed in mice demonstrating the promising potential of targeting RAD51 as a monotherapy in a pre-clinical model.

To investigate whether IBR2 might be effective in difficult to treat cancers such as imatinib resistant chronic myeloid leukaemia, the authors tested a murine model system consisting of parental and Bcr-abl T3151 mutant expressing cells. IBR2 inhibited proliferation and HR rate in T315I cells and increased apoptosis but did not affect these parameters in parental cells. This finding was consistent with the high levels of RAD51 expression and HR in T315I cells compared to parental cells. In vivo, non-obese diabetic/severe-combined immunodeficient mice injected with T3151 cells and treated with IBR2 (100mg/kg) had a significantly improved survival compared to mice treated with imatinib alone (125mg/kg) (Zhu et al. 2013). These results suggest that inhibitors of RAD51 will be best served as sensitizers to chemotherapies or other agents that induce DNA damage.

The most recent RAD51 small molecule inhibitor reported is CYT-0851 (Cytier) and to date it is the only one to have progressed to clinical trial (ClinicalTrials.gov, NCT03997968). CYT-0851 acts by destabilizing RAD51 foci formation, leading to its premature nuclear export and subsequent degradation. The authors suggest that CYT-0851 is selective for cancers that ectopically express Activation Induced Cytidine Deaminase (AID) (Day, Maclay, and Mills 2019). AID is a DNA-directed cytidine deaminase that is normally expressed transiently in maturing B-lymphocytes and stimulates somatic hypermutation and immunoglobulin class switching (Day, Maclay, and Mills 2019). Ectopic AID expression is reported in multiple solid tumour types, including: breast cancer, sarcoma, melanoma, pancreatic cancer, lung cancer, and head and neck cancers (Day, Maclay, and Mills 2019). The authors suggest that the enzymatic activity of AID leads to the accumulation of point mutations, DNA breaks and replication stress. As a consequence, AID-expressing cells become dependent on RAD51 mediated HR to survive (Day, Maclay, and Mills 2019).

An early version of CYT-0851, named CYT01B, was well tolerated in rats treated with 20, 80, and 240 mg/kg once per day by oral gavage with no changes observed in haematology or clinical chemistry, and no observed histopathological toxicities (Hasham et al. 2018). Further development led to four new compounds; CYT-0851, CYT-0853, CYT- 1027, and CYT-1127 which were assayed for inhibition of RAD51 foci formation and sister chromatid exchange (SCE) in an AID+ (Daudi, Burkitt's Lymphoma) and AID- (WI-38, fibroblast) cell lines (Day, Maclay, et al. 2019). All compounds were more active in AID+ cells with minimal cytotoxicity observed in the AID-negative WI-38 cell line. CYT-0851 and

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CYT-0853 were effective at reducing both SCE and RAD51 foci formation in vitro and both compounds inhibited tumour growth by greater than 50% in xenograft models of AID-high Burkitt's lymphoma (Daudi) and B-cell acute lymphoblastic leukemia (CCRF-SB) (Day, Maclay, et al. 2019). Additional studies found that CYT-0851 produced the most consistent results in CDX models (Day, Maclay, et al. 2019). CYT-0851 was also found to inhibit SCE in human derived HEK293T cells and murine breast cancer 4T1 cells and have a synergistic effect in combinations (0.020-5 µM) with oliparib in TNBC cells lines HCC1937, HCC1143, and BT20 (Guy et al. 2020). In AID+ patient-derived pancreatic cancer xenografts (PDX) models treatment with CYT-0851 inhibited tumour growth by 63% to 104% (Day, Lapierre, et al. 2019). We await the outcome of the CYT-0851 phase1/2 clinical trial which enrolled 165 patients with B-cell malignancies and solid tumours and is due for completion in October 2021(ClinicalTrials.gov, NCT03997968).

1.7 CHEMOTHERAPY RESISTANCE IN TNBC

Resistance to chemotherapy develops when tumours become tolerant to drugs used to treat cancer. More than 90% of mortality in cancer patients is attributed to chemotherapy resistance (Bukowski, Kciuk, and Kontek 2020). A wide variety of mechanisms contribute to chemotherapy resistance and often multiple resistance mechanisms are active. This section will review the common mechanisms of chemotherapy resistance that occur in TNBC, including intrinsic and acquired drug resistance, cancer stem cells and the epithelial- mesenchymal transition (EMT), upregulation of drug efflux pumps, BRCA1 mutations, p53 mutations, upregulation of anti-apoptotic BCL-2 proteins, and altered expression of the p53 homologues; p63 and p73.

1.7.1 Intrinsic versus Acquired Resistance Resistance to chemotherapy is classed as intrinsic or acquired depending on whether it develops prior to chemotherapy exposure or after therapy (Wang, Zhang, and Chen 2019). Intrinsic resistance in TNBC develops during tumourigenesis and progression via genomic instability and the accumulation of mutations (Kim et al. 2018). This genome instability generates intra-tumoral heterogeneity and rare clonal variants that are resistant to chemotherapeutic drugs. Patients may respond well initially to chemotherapy because the majority of cells in the tumour are sensitive to the drug. However, under the selective pressure of chemotherapy the rare chemoresistant cells survive and proliferate after treatment to cause recurrence (Kim et al. 2018). In contrast, acquired resistance relates to the gradual emergence of new mutations or changes in drug target expression levels that

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reduce the efficacy of chemotherapy over time (Wang, Zhang, and Chen 2019). Our current understanding of chemo-resistance in TNBC combines both intrinsic and acquired mechanisms of resistance. Single-cell DNA and RNA sequencing of tumour samples collected from 20 TNBC patients during neoadjuvant chemotherapy showed that clones with pre-existing genomic mutations and copy-number aberrations were initially adaptively selected by chemotherapy (Kim et al. 2018). Following adaptive selection, the surviving cells underwent transcriptional reprogramming as a result of chemotherapy to evolve the resistant phenotypes. Kim et al. (2018) identified that these chemoresistance transcriptional programs converged on few common pathways, EMT, CDH1 targets, AKT1 signaling, hypoxia, angiogenesis, and extracellular matrix degradation.

1.7.2 Cancer Stem Cells and EMT Breast cancer stem cells (BCSCs) are well documented for being a dominant cause of chemoresistance in breast cancer largely due to their inherent upregulation of drug efflux pumps (Dean, Fojo, and Bates 2005) and activation of signalling pathways, such as TGF-β (Bhola et al. 2013), Notch (Al-Hussaini et al. 2011), Wnt (Monteiro et al. 2014) and Hedgehog (Habib and O'Shaughnessy 2016). BCSCs comprise a small sub-population of cells within a tumour that have self-renewal properties and can initiate and re-establish tumour growth (Scioli et al. 2019). IHC markers such as ALDH-1, CD44, and CD24 are used to identify BCSCs in tumour samples and based on screening for these markers. TNBC and HER2+ tumours have been found to harbour the highest proportion of BCSCs compared to luminal breast cancer subtypes (Ma et al. 2017; Wang et al. 2017; Ma et al. 2014; Park et al. 2010). The expression of BCSC markers in primary breast tumours is associated with worse chemotherapy response, metastasis, disease recurrence and worse overall patient survival outcomes (Creighton et al. 2009; Lin et al. 2012). It has been observed that following chemotherapy there is enrichment of cells with BCSC properties in residual tumours compared to tumours pre-treatment (Creighton et al. 2009). This observed enrichment of cells with BCSC markers is likely due to the mechanisms of adaptive selection and transcriptional reprograming proposed by Kim et al. (2018).

TGF-β is a potent inducer of EMT in mammary cells and the TGF-β family of cytokines are regulators of BCSCs (Mani et al. 2008). There is growing evidence that BCSCs and associated signalling pathways may be a dominant factor in TNBC relapse following neoadjuvant chemotherapy. Bhola et al. (2013) found that post chemotherapy TNBC tumour biopsies showed an increase in RNA transcripts of genes associated with BCSCs and TGF- β signalling. Bhola et al. (2013) also reported that using the TGF-β type 1 receptor kinase

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inhibitor LY2157299 in combination with paclitaxel, prevented expansion of BCSCs in both xenografts and TNBC cell lines post-chemotherapy. Increased expression of TGF-β and BCSC markers CD44+CD24- were also reported in an epirubicin resistant MDA-MB-231 TNBC line (Xu et al. 2018). Together, these results suggest that TGF-β signalling is vital in the acquisition of stemness and chemotherapy resistance in TNBC and provide the rationale for strategies targeting TGF- β in combination with chemotherapy.

1.7.3 Upregulation of Drug Efflux Pumps The most well researched mechanism of multidrug resistance in TNBC occurs by upregulation of transmembrane proteins that directly pump drugs out of cells, thereby reducing intracellular accumulation and drug adsorption (Alfarouk et al. 2015; Krishna Vadlapatla et al. 2013). The majority of these transmembrane proteins belong to the ATP- binding cassette (ABC) superfamily which utilise ATP to efflux drugs with many different structures and properties across cellular membranes (Sissung et al. 2010). There are three main groups of ABC transporters implicated in multidrug resistance in breast cancer; P- glycoprotein (P-gp/ ABCB1/MDR1), MDR protein 8 (ABCC11/MRP8) and breast cancer resistance protein (BCRP/ABCG2), all of which have been found to be more highly expressed in TNBC compared to other breast cancer subtypes (Mehrotra et al. 2018; Yamada et al. 2013; Xu et al. 2017). The resistance caused by high rates of drug efflux can be either innate to tumour cells or acquired under the selective pressure of long-term chemotherapy (Wang, Zhang, and Chen 2019; Longley and Johnston 2005). ABCB1, ABCG2 and ABCC11 exhibit very broad and overlapping substrate specificity, interacting with more than 300 identified compounds, including classic anthracycline and taxane based chemotherapies (e.g., doxorubicin, epirubicin, docetaxel, paclitaxel and etoposide) and new generation targeted kinase inhibitors (e.g., GSK-690693; AKT inhibitor, AT9283; Janus kinase 2/3 inhibitor) (Wang et al. 2011; Lee, Lee, et al. 2019; Sissung et al. 2010). Hence, upregulation of ABC transporters present a major challenge to the current backbone of TNBC treatment.

1.7.4 BRCA1 Mutations and Taxane Resistance As with platinum agents and PARP inhibitors, BRCA1- associated TNBC may demonstrate a distinct pattern of response to taxanes compared to sporadic TNBC. During the cell cycle BRCA1 protein mediates activation of the mitotic spindle checkpoint and facilitates triggering of apoptosis in response to microtubule stabilisation caused by taxanes (Sung and Giannakakou 2014). Hence intrinsic or acquired loss of BRCA1 provides a mechanism for cells to potentially evade apoptosis activated by taxane therapies. In vitro

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studies have shown BRAC1-mutant TNBC cell lines are more resistant to taxanes than BRCA1 wild-type cell lines (Chabalier et al. 2006; Sung and Giannakakou 2014; Tassone et al. 2003; Teraoka et al. 2020) and this finding has been largely confirmed by clinical data (Byrski et al. 2008; Akashi-Tanaka, Watanabe, Takamaru, Kuwayama, Ikeda, Ohyama, Mori, Yoshida, Hashimoto, Terumasa, et al. 2015; Kriege et al. 2012; Wysocki et al. 2008; Kurebayashi et al. 2006). Tassone et al. (2003) found that BRCA1-mutant TNBC cell line HCC1937 was greater than 10-fold more resistant to paclitaxel than wild-type counterparts MCF7 and MDA-MB-231. Furthermore, reconstitution of exogenous BRCA1 in the HCC1937 cell line resulted in significantly enhanced sensitivity. Likewise Teraoka et al. (2020) reported increased docetaxel resistance in BRCA1-mutant versus wild-type TNBC cell lines and showed that BRCAness score (determined by multiplex-ligation-dependent probe amplification with P376-B2 BRCA1ness probe mix) positively correlated with IC50 concentration. Acquired BRCA1 loss was observed by Duran et al. (2015) who established taxane resistant MCF7 breast cancer cell lines by long-term selection with cabazitaxel. The authors found that resistant cells downregulated BRCA1 protein early in the selection process. This downregulation of BRCA1 was associated with decreased G2–M arrest and apoptosis induced by taxane treatment (Duran et al. 2015).

In the clinical setting BRCAness is prognostic for poor response to taxane regimens. In a retrospective study of 73 breast cancer patients treated with neoadjuvant taxane regimens Akashi-Tanaka, Watanabe, Takamaru, Kuwayama, Ikeda, Ohyama, Mori, Yoshida, Hashimoto, Terumasa, et al. (2015) found that clinical response rates were significantly lower for patients with BRCAness tumours of all subtypes compared to non- BRCAness tumours (58.8% vs. 89.3%). This was even more evident in patients with triple negative tumours (50% vs. 100%). Pathologic complete response was significantly lower for TNBC patients with BRCAness tumours compared with non-BRCAness cancer (14.3% vs. 77.8%) and all patients with BRCAness tumours had developed recurrence at follow-up (median 26.4 months). In the metastatic setting Kriege et al. (2012) compared outcomes following taxane chemotherapy in BRCA1 and BRCA2‐associated breast cancer patients with outcomes in matched sporadic breast cancer patients. The authors found that BRCA1- associated TNBC patients (n=11) had significantly worse objective response (20% vs 42%) and shorter progression free survival (1.8 vs 3.8 months) compared with sporadic patients (n=19). Together these studies suggest that for TNBC sensitivity to taxanes requires functional BRCA1 protein and that intrinsic or acquired BRCA1 loss promotes a resistance phenotype.

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1.7.5 p53 Mutations Mutations in p53 are present in greater than 90% of TNBC cases (Shah et al. 2012; Koboldt et al. 2012; Niyomnaitham et al. 2019) and contribute to chemotherapy resistance via multiple pathways including; evasion of apoptosis, loss of repression/upregulation of drug efflux pumps and promotion of stem cell-like transcriptional programs. The majority of p53 mutations that occur in cancer are missense mutations clustered in the core domain of p53 and result in loss of DNA binding/transactivation capability (Cho et al. 1994). In cells that express wild type p53 chemotherapy induced DNA damage activates p53 which in turn can trigger the intrinsic mitochondrial/BCL-2 apoptosis pathway. Activated p53 transcriptionally upregulates pro-apoptotic members of the BCL-2 family (BIM, PUMA, NOXA) which in turn bind and inhibit pro-survival BCL-2 proteins (BCL-2, BCL-XL, MCL-1, BCL-W and A1/BFL1), thereby allowing activation of BAX and BAK (Zaman, Wang, and Gandhi 2014; Lopez and Tait 2015; Aubrey et al. 2018). Activation of BAX and BAK cause mitochondrial outer membrane permeabilization and activation of caspases that dismantle the cell (Lopez and Tait 2015; Aubrey et al. 2018). Hence, loss of function mutations in p53 impair its ability to transcriptionally induce pro-apoptotic members of the BCL-2 family and disrupt execution of the intrinsic apoptotic pathway in response to chemotherapy (Aubrey et al. 2018). The apoptotic pathway can also be disrupted by gain of function p53 mutations whereby p53 modulates transcription indirectly via association with transcription factors or cofactors (Zhou, Hao, and Lu 2018). For example, mutant p53 binds the p53 homologues TAp63 and TAp73, thereby preventing them from transactivating target genes shared with wild-type p53 that promote apoptosis (Gaiddon et al. 2001).

High levels of drug efflux pump expression and cancer stem cells are major contributors to chemotherapy resistance in TNBC and are coupled with p53 expression. WT- p53 represses transcription of the P-glycoprotein-encoding MDR1 gene via direct binding of the gene promoter (Chin et al. 1992; Johnson, Shepard, and Scotto 2005). Loss of wild-type p53 is sufficient to upregulate MDR1 transcription and some p53 mutants actually further upregulate P-glycoprotein expression via interaction with the ETS1 transcription factor at the MDR1 promotor (Sampath et al. 2001). Wild-type p53 is also a powerful repressor of cancer stem cell-like transcriptional programs and limits the generation of induced pluripotent stem cells, which are highly resistant to chemotherapy (Santoro et al. 2019). In contrast p53- mutant breast tumours have been found to exhibit transcriptional patterns similar to embryonic stem cells (Mizuno et al. 2010) and show increased expression of stem cell markers, including CD133, CD44 and YAP/TAZ (Escoll et al. 2017). Because of the high

Chapter 1: Literature Review 52

frequency of p53 mutation in cancer and its significant contribution to chemotherapy failure several research groups are investigating small molecules that may restore normal function of mutant p53 and thereby overcome mutant p53 driven resistance (Synnott, Murray, et al. 2017; Walerych et al. 2016; Synnott, Bauer, et al. 2017).

1.7.6 Upregulation of Anti-apoptotic BCL-2 Proteins Apoptosis can be blocked by loss of equilibrium between pro-apoptotic versus anti- apoptotic BCL-2 proteins (Campbell and Tait 2018). Upregulation of pro-survival genes BCL- 2 and MCL-1 have been shown to play a role in the development of chemotherapy resistance in TNBC by inhibiting apoptotic signaling. This upregulation may be intrinsic or acquired following chromosome rearrangements, gene amplification, increased gene expression or enhanced protein stability (Campbell and Tait 2018). In vitro, overexpression of BCL-2 conferred resistance to doxorubicin in MCF7 breast cancer cells (Davis et al. 2003) and in TNBC tumour samples high BCL-2 expression correlated with high histological grade and overexpression was an independent prognostic factor for poorer overall survival (Ozretic et al. 2018). In accordance with BCL-2 overexpression predicting poor response, Yang et al. (2013) showed that decreased BCL-2 expression was predictive for better chemotherapy response in breast cancer patients. Likewise, Campbell et al. (2018) found that MCL-1 overexpression detected by microarray in primary tumour samples was predictive of poor outcome in TNBC patients. Molecular profiling of residual TNBC tumours after neoadjuvant chemotherapy showed that almost 40% had MCL-1 aberrations, making MCL-1 the second most frequently altered gene (after p53) in chemotherapy resistant tumours. The frequency of cells with MCL-1 amplifications was higher in the post-neoadjuvant chemotherapy cohort relative to pre-treatment samples, suggesting adaptive selection of cells with MCL-1 amplification, however MCL-1 copy number was not further amplified in cells upon treatment (Balko et al. 2014). In the same study, Balko et al. (2014) showed that lentiviral-mediated overexpression of MCL-1 in TNBC cell lines increased resistance to doxorubicin and Docetaxel (Balko et al. 2014).

1.7.7 Altered Expression of p53 Homologues; p63 and p73 The p53 family members; p63 and p73 share significant sequence homology with p53 (Rodríguez et al. 2018). Unlike p53, p63 and p73 are rarely mutated in cancers, however their expression levels and protein isoform ratios differ in tumours compared to normal tissues and this can have a profound influence on the sensitivity of tumours to chemotherapy (Müller et al. 2006). The interplay between p53 family members and their role in chemotherapy response is complex, mainly due to the opposing activity of different protein

Chapter 1: Literature Review 53

isoforms of p63 and p73 that result from alternative splicing (Dötsch et al. 2010). Full length protein isoforms; TAp63 and TAp73 transactivate overlapping subsets of known p53 target genes that induce growth arrest, senescence and apoptosis in response to DNA damage (Flores et al. 2002; Vayssade et al. 2005; Dötsch et al. 2010). TAp63 and TAp73 also regulate distinct sets of genes that are not transcriptional targets for p53 (Lin et al. 2009; Fontemaggi et al. 2002). These complementary functions of TAp63 and TAp73 support p53- dependent and p53-independent apoptosis pathways in response to chemotherapy.

In contrast to full length TAp63 and TAp73, the truncated protein isoforms; ΔNp63 and ΔNp73 are dominant negative inhibitors that counteract pro-apoptotic wild-typep53, TAp63 and TAp73 by competing for DNA binding or forming inactive oligomers (Billant et al. 2016). Initially the truncated isoforms were described as lacking transactivation function due to the absence of a canonical TA1 domain (Yang et al. 1998). However, subsequent studies suggest the presence of a second transcription activation domain in the N-terminal truncated region of ΔNp63 and ΔNp73 that enables transactivation of specific target genes (Lena et al. 2015; Lin et al. 2009). The overall effect of p63 and p73 on chemotherapy response seems to be largely dependent on the ratio ΔN/TA of p73 and p63 isoforms, with TA forms promoting chemo-sensitivity and ΔN forms promoting chemo-resistance (Lucena-Araujo et al. 2015; Gonfloni, Caputo, and Iannizzotto 2015; Di et al. 2015). Elevated p73 expression is reported in ~38-70% of breast tumours whereas normal breast tissue has very low levels of p73 expression (Zaika et al. 1999; Gomez et al. 2018; Zaika et al. 2002). Investigation of p73 expression in breast cancer cell lines and patient derived tumours indicate that the predominant type of p73 isoform expressed is associated with chemotherapy response, tumour grade and subtype. Vayssade et al. (2005) observed that in p53 deficient breast cancer cells expressing TAp73, but not ∆Np73 (MDA-MB-157), treatment with doxorubicin induced upregulation of TAp73 and transactivation of p53 target genes, triggering apoptosis, cell cycle arrest and DNA repair. Ectopic overexpression of TAp73 further sensitised cells to doxorubicin. In contrast, ectopic overexpression of ∆Np73 or siRNA depletion of TAp73 conferred resistance in MDA-MB-157. A different response was observed in the T47D cell line which harbours mutant p53 and high endogenous ∆Np73 expression. In these cells doxorubicin induced apoptosis was associated with a reduction in ΔNp73 expression. Interestingly the ratio of ∆Np73/TAp73 expression has been found to differ across breast cancer subtypes and is associated with histological tumour grade. Analysis of 70 IDC breast tumour samples revealed elevated ∆Np73 in 65% of samples, (Gomez et al. 2018). The authors reported that elevated ratio of ∆Np73/TAp73 expression

Chapter 1: Literature Review 54

correlated with methylation of CpG islands located in or close to p73 promoter P1 and was positively associated with the TNBC subtype and high histological tumour grade. In TNBC samples high ∆Np73/TAp73 ratio was observed in 86.7% of high-grade, 77.8% of intermediate grade, and in only 33.3% of low-grade tumours (Gomez et al. 2018). This elevated ratio of ∆Np73/TAp73 in TNBC likely not only impacts tumour grade but also undermines the ability of TAp73 to compensate for the loss of wild-type p53 in triggering apoptosis in response to DNA damaging chemotherapy. Therefore ∆Np73 could be a potential biomarker for TNBC response to chemotherapy but has yet to be fully investigated. In normal breast tissue p63 protein expression is restricted to the nuclei of basal cells (Di Como et al. 2002). In TNBC, p63 is expressed in a small number of tumours and is a characteristic feature of the basal-like 2 subtype (Lehmann and Pietenpol 2014). Microarray analysis of 235 TNBC tumour samples revealed that 7.3% expressed TAp63 and 17% expressed ΔNp63, with most TAp63+ tumours also containing ΔNp63+ cells (Coates et al. 2018). The authors found that ΔNp63 positivity was associated with metaplastic and medullary cancers, and with a basal phenotype, whereas TAp63 positivity was associated with androgen receptor, BRCA1/2 wild-type status and PTEN positivity. TAp63+ patients showed fewer recurrences and improved overall survival compared to TAp63− patients (92.86% vs. 76.02%). This finding is consistent with TAp63 having p53-like tumour suppressor transcriptional activity (Coates et al. 2018). Analysis of p63 and p73 mRNA levels in 23 TNBC tumour samples showed that about one third overexpress both ΔNp63 and TAp73 (Leong et al. 2007; Isakoff 2010). The authors suggest that in a subset of p53 mutant TNBC tumours that overexpress both TAp73 and ΔNp63 that the majority of TAp73 is complexed to ΔNp63, which is sufficient to repress pro-apoptotic TAp73-dependent transcription. Using two TNBC cell lines that co-express ΔNp63 and TAp73; HCC-1937 (mutant-BRCA1) and MDA-MB-468 (wild-type-BRCA1) the authors found that treatment with cisplatin (but not doxorubicin) induced c-ABL–dependent TAp73 phosphorylation and dissociation of the ΔNp63α/TAp73 protein complex. Several hours after cisplatin treatment, despite no overall change in ΔNp63α or TAp73 protein levels the authors observed TAp73- dependent transcription of pro-apoptotic effector genes. In contrast, TAp73 ablation induced marked resistance to cisplatin in both TNBC cell lines, with IC50 increased by more than 10- fold (Leong et al. 2007). This result suggests that co-expression of ΔNp63 and TAp73 in TNBC may represent a shared pathway alternative to HR in BRCA1-mutant and sporadic TNBCs that confers cisplatin sensitivity. This is most likely nucleotide excision repair pathway, based on an ovarian cancer study that showed that alternations in NER genes conferred similar sensitivity to platinum compounds as BRCA1/2 loss (Mouw, D'Andrea, and

Chapter 1: Literature Review 55

Konstantinopoulos 2015). In a study investigating pre-operative cisplatin treatment in 22 TNBC patients Silver et al. (2010) found that ΔNp63/TAp73 ratio > 2 was predictive for good treatment response. Of 9 patients with ΔNp63/TAp73 ratio > 2, 6 (67%) had a good response to cisplatin and 3 (33%) had pathologic complete response. In contrast, of the 13 patients with ΔNp63/TAp73 < 2, five (38%) had good responses to cisplatin and only one (8%) achieved pathologic complete response. However, ΔNp63/TAp73 ratio was not associated with clinical response to platinum salts for previously treated patients with metastatic disease (n = 66) (Isakoff et al. 2015). The authors did however report this ratio was associated with clinical benefit for a subset of patients (n = 7) who presented with de novo metastatic disease and had not received prior chemotherapy. In addition to p63 and p73 isoforms competing for DNA binding at p53 target genes, several studies indicate these isoforms transactivate sets of genes independent of p53 which influences tumourigenesis and chemotherapy response (Fontemaggi et al. 2002; Lin et al. 2009; Holcakova et al. 2017; Sakil et al. 2017; Flores et al. 2005). Flores et al. (2005) observed that p63/p73 mutant mice develop mammary adenocarcinomas at a high frequency. Results from a later study by the same research group indicate that p63 and p73 may suppress tumorigenesis by transcriptionally regulating genes critical to DNA repair (Lin et al. 2009). Using MEFs deficient for each of the p53 family members individually and in combination Lin et al. (2009) conducted genome wide cDNA microarray analysis to determine whether p63 and p73 transcriptionally regulate genes independently of p53 in response to DNA damage. The authors identified by ChIP and luciferase assays that p63 and p73 bind to and transactivate promoters of genes involved in HR, including RAD51, BRCA2, MRE11 and RAD50. Interestingly the ΔN isoforms of p63 and p73 were more potent transactivators of these genes than the TA isoforms. Compared to MEFs expressing wild- type p63 and p73, p63 and p73 knockout MEFs had impaired DNA repair (determined by comet assay) and were significantly more sensitive to irradiation and doxorubicin therapy (Lin et al. 2009). Zaika et al. (2011) showed that p73 downregulation in oesophageal cells also results in increased DNA damage. The authors observed that p73 binds to and regulates transcription of genes involved in BER. Interestingly the authors did not identify RAD51, BRCA2, or MRE11 in their analysis, which this suggests that cell type or tissue differences may be a mediating factor in p73 regulation of DNA repair genes. Overall, the research to date on ΔNp73 indicates that it is a powerful mediator chemotherapy resistance in TNBC.

Chapter 1: Literature Review 56

1.8 HYPOTHESIS AND AIMS OF RESEARCH

TNBC is an aggressive form of breast cancer that carries a high risk of early relapse after completion of neoadjuvant and adjuvant chemotherapy. The lack of targetable receptors, development of chemotherapy resistance and high rate of distant metastasis presents an enormous challenge in the treatment of patients with TNBC. There is an urgent need to identify actionable molecular targets and develop novel therapies to treat patients with these tumours. In planning the research described in this thesis I hypothesized that overexpression of RAD51 in TNBC promotes chemoresistance and metastasis via increased and aberrant homologous recombination and via transcriptional upregulation of pro-metastatic genes (in concert with transcription factor CEBPβ), and that inhibiting RAD51 function would enhance the chemosensitivity of TNBC and decrease metastasis.

My hypothesis is addressed by three central aims in this thesis.

1. To develop a library of TNBC cell lines expressing DNA repair deficient RAD51 (RAD51-K133R), RAD51 knockout and CEBPβ knockout utilising CRISPR-Cas9 technology and use these cell lines to characterise pro-metastatic gene expression profiles regulated by RAD51 with CEBPβ, regulated by RAD51 independent of CEBPβ and regulated by CEBPβ independent of RAD51.

2. To screen a library of quinazolinone derivative small molecules for specific inhibitory activity against RAD51 recombinase and assess biologic activity of the lead compound in TNBC cell lines.

3. To create a panel of TNBC cell lines that are resistant to standard of care chemotherapy combination doxorubicin/docetaxel and assess the efficacy of small molecule RAD51 inhibition in combination with chemotherapy in these cell lines.

Chapter 1: Literature Review 57

Chapter 2: Materials and Methods

2.1 CELL LINES

The human TNBC cell lines used in this research were obtained from the American Type Culture Collection. TNBC cell lines were; MDA-MB-231, MDA-MB-436, MDA-MB-453, MDA-MB-468, BT549, HS578T and SUM159-PT. For lentiviral production we used HEK293FT cells which were a gift from Glen Boyle (QIMR Berghofer, Brisbane, Australia).

2.2 MEDIA AND REAGENTS FOR CELL CULTURE, TRANSFECTION AND TRANSDUCTION

Table 2-1 Medium and Reagents used for Cell Culture

Reagent Supplier Catalogue Stock Prepared number

Gibco® RPMI-1640 Medium with L- Life Technologies 11875119 Glutamine

Gibco® Dulbecco’s Modified Eagle’s Life Technologies 11995073 Medium (DMEM) - High Glucose with 4.5g/L D-Glucose, L Glutamine, 110 mg/L Sodium Pyruvate

Gibco® Foetal Bovine Serum (FBS), Life Technologies 10437028 certified, USDA approved origin

Gibco® Penicillin-Streptomycin (10,000 Life Technologies 15140122 U/mL)

Gibco® Opti-MEM® I Reduced Serum Life Technologies 31985070 Medium

Gibco® Dulbecco's phosphate-buffered Life Technologies 14190250 saline (DPBS) without Calcium, Magnesium, Phenol red

Gibco® 0.5%Trypsin-EDTA (10x) Life Technologies 15400054 0.25% in DPBS

Lipofectamine® 2000 Transfection Life Technologies 11668-019 Reagent (Invitrogen)

Neomycin Sulfate Life Technologies 21810031 50 mg/mL in dH2O

Blasticidine S hydrochloride Sigma Aldrich 15205 50 mg/mL in dH2O

Puromycin Sigma Aldrich P9620 10 mg/mL in dH2O

Chapter 2: Materials and Methods 58

Dimethyl sulfoxide (DMSO) Sigma Aldrich D8418

2.3 REAGENTS AND MEDIA FOR BACTERIAL GROWTH, TRANSFORMATION AND SELECTION

Table 2-2 Reagents and Media for Bacterial Growth, Transformation and Selection

Reagent Supplier Catalogue Stock Prepared number

Alpha Select Chemically Competent Bioline BIO-85046 Cells (silver efficiency)

One Shot™ Stbl3™ Chemically Life Technologies C737303 Competent E. coli (Invitrogen)

LB broth QIMR Berghofer Media Services

LB agar QIMR Berghofer Media Services

Ampicillin sodium salt Sigma Aldrich P9518 100 mg/mL in dH2O

Kanamycin sulphate Sigma Aldrich K1377 50 mg/mL in dH2O

2.4 DRUGS AND INHIBITORS

Table 2-3 Drugs and Inhibitors

Compound Supplier Catalogue Stock Prepared number

Doxorubicin Hydrochloride Sigma Aldrich 44583 10 mM in DMSO

Docetaxel Sigma Aldrich 01885 10 mM in DMSO

Cisplatin Selleck Chemicals Jomar Life Research S1166 333 mM in DMSO

Veliparib ABT-888 (PARP inhibitor) Jomar Life Research S1004 20 mM in DMSO (Selleck Chemicals)

KU-55933 - ATM inhibitor (Selleck Jomar Life Research S1092 10 mM in DMSO Chemicals)

NU7026 -DNA-PK inhibitor (Selleck Jomar Life Research S2893 10 mM in DMSO Chemicals)

VE-821 - ATR inhibitor (Selleck Jomar Life Research S8007 10 mM in DMSO Chemicals)

NCS59984 – restores p53 pathway Jomar Life Research S8106 10 mM in DMSO signaling (Selleck Chemicals)

Chapter 2: Materials and Methods 59

Tariquidar – Pgp inhibitor (Selleck Jomar Life Research S8028 10 mM in DMSO Chemicals)

B02 - RAD51 inhibitor Sigma Aldrich SML0364 50 mM in DMSO

B02 analogues Institute of Molecular Biosciences, University of Queensland

2.5 ANTIBODIES

Table 2-4 Antibodies used for Immunoblotting and Immunofluorescent Staining

Antibody Supplier Catalogue Application number

53BP1 [N1], N-term (GeneTex) Sapphire Bioscience GTX102595 WB 1:1000

Alexa Fluor 488 goat anti mouse IgG Life Technologies A11001 IF 1:500 (Invitrogen)

Alexa Fluor 594 Donkey anti rabbit IgG Life Technologies A21207 IF 1:500 (Invitrogen)

Alpha-tubulin Sigma Aldrich T9026 WB 1:10,000

ATM (phosphor Ser1981) (GeneTex) Sapphire Bioscience GTX61739 WB 1:1000

ATM [2C1] (GeneTex) Sapphire Bioscience GTX70103 WB 1:1000

ATR (phospho Thr1989) (GeneTex) Sapphire Bioscience GTX128145 WB 1:1000

BRCA1 [8F7] (GeneTex) Sapphire Bioscience GTX70113 WB 1:1000

BRCA2 [5F6] (GeneTex) Sapphire Bioscience GTX70123 WB 1:1000

CEBP Beta [E299] - C-terminal abcam Australia Pty Ltd ab32358 WB 1:1000

DNA-PKcs (phospho Ser2056) Sapphire Bioscience GTX132793 WB 1:1000 (GeneTex)

DNA-PKcs [C3], C-term (GeneTex) Sapphire Bioscience GTX109673 WB 1:1000

Gamma H2AX (phospho S139 abcam ab11174 IF 1:1000

HSP70 (Cell Signaling Technology) Australian Biosearch 4872 WB 1:10,000

p53 (Cell Signaling Technology) Australian Biosearch 9282 WB 1:1000

p53 (phospho Ser46) (GeneTex) Sapphire Bioscience GTX634168 WB 1:1000

p73 alpha+beta antibody [ER-15] abcam ab17320 WB 1:1000

Chapter 2: Materials and Methods 60

PARP1 (F-2) (Santa Cruz) Bio-Strategy Sc-8007 WB 1:500

P-glycoprotein (GeneTex) Sapphire Bioscience GTX108370 WB 1:1000

RAD51 abcam ab88572 WB 1:1000, IF 1:100

2.6 CHEMICAL REAGENTS

Table 2-5 Chemical Reagents

Reagent Supplier Catalogue number

Agarose Sigma Aldrich A9539

ATP disodium salt hydrate Sigma Aldrich A26209

Bovine serum albumin (BSA) Sigma Aldrich A9647

Bradford 1x Dye Reagent Bio-Rad Laboratories 5000205

Sigma Aldrich D0632 DL-Dithiothreitol (DTT)

EDTA disodium salt dihydrate Chem-Supply EA023

Sigma Aldrich E8145 EGTA tetrasodium salt

Ethanol Undenatured 100% Chem-Supply EA043

Glycerol Chem-Supply GA010

Glycine Chem-Supply GA007

Hydrochloric acid (32%) (HCl) Chem-Supply HA020

Iso Propyl Alcohol (Propan-2-ol) Chem-Supply PA013

Magnesium chloride hexahydrate Sigma Aldrich M9272

Methanol Chem-Supply ML004

NucGreen Dead 488 ReadyProbes R37109 Sigma Aldrich Reagent

10×Phosphate Buffered Saline (PBS) QIMR Berghofer Media Services

Phosphatase Inhibitor Cocktail Tablets- Sigma Aldrich 4906837001 PhoSTOP EASYpack (Roche)

PIPES Sigma Aldrich P1851

Chapter 2: Materials and Methods 61

Poly-L-Lysine solution (0.01%) Sigma Aldrich P4832

Prolong Gold Antifade Mountant Life Technologies P10144

Protease Inhibitor Cocktail Tablets- Sigma Aldrich 05892970001 cOmplete Tablets EASYpack (Roche)

Sodium chloride (NaCl) Chem-Supply SA046

Sodium dodecyl sulfate (SDS) Sigma Aldrich L3771

Sodium hydroxide (NaOH) Chem-Supply SA178

Sucrose Chem-Supply SA030

Thiazolyl blue tetrazolium blue (MTT) Sigma Aldrich M2128

Tris base Sigma Aldrich T1378

Triton-X100 Sigma Aldrich X100

TWEEN® 20 Sigma Aldrich P9416

2.7 BUFFERS AND SOLUTIONS

2.7.1 TAE buffer A 50x stock was prepared by dissolving 2M Tris base, 50mM EDTA and 1M glacial acetic acid in dH2O (ph~8.5). The solution was mixed on a magnetic stirrer and stored at room temperature.

2.7.2 MTT reagent A 5 mg/mL stock solution was prepared with Thiazolyl Blue Tetrazolium Blue (MTT) and DPBS. The solution was vortexed, filtered and stored at -20οC protected from light. A working solution was prepared for immediate use with 10% MTT stock diluted in FBS supplemented cell culture media.

2.7.3 Propidium iodide (PI) staining solution A 100 μg/mL PI working solution for immediate use was prepared from 1 mM PI stock with PBS, 20 mg/mL RNase and 0.1% Triton-X.

2.7.4 Cytoskeleton buffer

10 mM PIPES (pH6.8), 100 mM NaCl, 30 mM Sucrose, 3 mM MgCl2, 1 mM EGTA diluted in dH2O, mixed by inversion and stored at 4ºC.

Chapter 2: Materials and Methods 62

2.7.5 FBT buffer 1x FBT buffer was prepared with 10 mM Tris-HCl, 5% FBS, 1% BSA, 0.05% Tween-

20 and 100mM MgCl2 adjusted to final volume in 1x PBS, mixed by inversion and used immediately.

2.7.6 Whole cell lysis buffer 1 x Whole cell lysis buffer was prepared with 50 mM Tris (pH 8.0), 150 mM NaCl, 100 mM EDTA, 100 mM EGTA, 0.5% Triton X-100 and 10% glycerol adjusted to final volume with dH2O, mixed by inversion and stored at room temperature.

2.7.7 Whole cell lysis buffer with protease and phosphatase inhibitor One tablet each of Protease Inhibitor Cocktail and Phosphatase Inhibitor Cocktail were dissolved in 10 mL of Whole Cell Lysis Buffer. 1 mL aliquots were stored at -20oC.

2.7.8 SDS loading buffer (5×) A 5× stock was prepared with 0.25% bromophenol blue, 0.5M DTT, 50% glycerol, 10%

SDS, 0.25M Tris-Cl (pH6.8) and dH2O to final volume. The solution was mixed by vortex and stored in 1 mL aliquots at -20OC.

2.7.9 Tris-glycine running buffer (10×) A 10× stock solution was prepared with 250 mM Tris, 190 mM glycine, 35 mM SDS, pH to 8.3 and adjusted to final volume with dH20. The solution was mixed on a magnetic stirrer and stored at room temperature.

2.7.10 Towbin transfer buffer (1×) A 1x stock was prepared with 25 mM Tris and 192 mM glycine, 20% methanol, adjusted to final volume with dH20. The solution was mixed on a magnetic stirrer and stored at room temperature and stored at 4ºC.

2.7.11 TBST (10×) 10× stock was prepared with 0.2 M Tris base, 1.2 M sodium chloride, 1% w/v tween-

20, pH adjusted to 7.5 with 12N HCl and dH20 added to make final volume. The solution was mixed on a magnetic stirrer and stored at room temperature.

Chapter 2: Materials and Methods 63

2.8 MOLECULAR BIOLOGY REAGENTS

Table 2-6 Molecular Biology Reagents

Reagent Supplier Catalogue number

FastDigest Esp3I (BsmBI) Thermo Fisher Scientific FD0454

supplied with 10x FastDigest Buffer

FastDigest HindIII supplied with 10x Thermo Fisher Scientific FD0504 FastDigest Buffer

T4 polynucleotide kinase New England BioLabs M0201S

T4 DNA ligase reaction buffer, 10× New England BioLabs B0202S

FastAP Thermosensitive Alkaline Thermo Fisher Scientific EF0654 Phosphatase, supplied with 10x FastAP Buffer

Quick Ligation Kit New England BioLabs M2200S

Herculase II fusion polymerase with 5× Agilent Technologies 600679 reaction buffer

ExoSAP-IT (GE) Life Technologies 78201

SYBR Gold nucleic acid gel stain, Life Technologies S-11494 10,000×

6x DNA loading dye Thermo Fisher Scientific R0611

ΦX174 Virion DNA New England BioLabs N3023S

RAD51 siRNA (Santa Cruz) Bio-Strategy sc-36361

2.9 KITS

Table 2-7 Kits

Reagent Supplier Catalogue number

QIAquick gel extraction kit Qiagen 28704

QIAprep spin miniprep kit Qiagen 27106

QIAquick PCR purification Kit Qiagen 28104

PureLink™ HiPure Plasmid Maxiprep Life Technologies K210007 Kit (Invitrogen)

Chapter 2: Materials and Methods 64

PureLink™ HiPure Plasmid Miniiprep Life Technologies K210002 Kit (Invitrogen)

PureLink™ HiPure Plasmid Midiiprep Life Technologies K210005 Kit (Invitrogen)

RNeasy® Plus Mini Kit Qiagen 74134

DNeasy Blood and Tissue Kit Qiagen 69504

FITC Annexin V/Dead Cell Apoptosis Life Technologies V13242 Kit (Invitrogen)

RT2 First Strand Kit (50) Qiagen 330404

RT² Profiler™ PCR Array Human DNA Qiagen PAHS-029ZE-4 Damage Signaling Pathway

RT² SYBR Green ROX qPCR Qiagen 330521 Mastermix

2.10 OLIGONUCLEOTIDES

Oligonucleotides used for cloning, PCR and sequencing were purchased from GeneWorks. Oligonucleotides used for qPCR and the ssODN repair template were purchased from Integrated DNA Technologies.

2.10.1 RAD51 K133R ssODN repair template sequence (5`->3`) ATGTTTGTATTATGCTAAGAGTTATTTCTTATCGCTTTTTTAGGTGGAATTGAGACTGG ATCTATCACAGAAATGTTTGGAGAATTCCGAAAGCTTACTGGACGAACCCAGATCTGT CATACGCTAGCTGTCACCTGCCAGGTGAGCTGTTGGGGCTATAGCTAATCAAATAAG CAAGCATTACTTCATTCCTGC

Table 2-8 Oligonucleotides for Cloning into lentiGuide-Puro Backbone

Name Sequence (5` >3`)

R1 Fwd CACCGTGTTGCCTATGCGCCAAAGA

R1 Rev AAACTCTTTGGCGCATAGGCAACAC

R2 Fwd CACCGTCTCATAGGTATGGTCTCTC

R2 Rev AAACGAGAGACCATACCTATGAGAC

Chapter 2: Materials and Methods 65

R3 Fwd CACCGTACGCTAGCTGTCACCTGCC

R3 Rev AAACGGCAGGTGACAGCTAGCGTAC

R4 Fwd CACCGAGGCAACAGCCTCCACAGTA

R4 Rev AAACTACTGTGGAGGCTGTTGCCTC

KR Fwd CACCGTGTTTGGAGAATTCCGAACT

KR Rev AAACAGTTCGGAATTCTCCAAACAC

C1 Fwd CACCGCGAGTACGGCTACGTGAGCC

C1 Rev AAACGGCTCACGTAGCCGTACTCGC

C2 Fwd CACCGTACGCGCTGCGCGCTTACCT

C2 Rev AAACAGGTAAGCGCGCAGCGCGTAC

C3 Fwd CACCGCGATGTTGTTGCGCTCGCGC

C3 Rev AAACGCGCGAGCGCAACAACATCGC

C4 Fwd CACCGAGGTAAGCGCGCAGCGCGTA

C4 Rev AAACTACGCGCTGCGCGCTTACCTC

Table 2-9 Primers for PCR and Sequencing

Name Sequence (5` >3`)

CEBPB Fwd CAGCACCACGACTTCCTCTC

CEBPB Rev CTCCACCTTCTTCTGCAGCC

RAD51 exon 2 Fwd GCACCTCTGTGAAGTATGTAGGA

RAD51 exon 2 Rev GTACTATTCCCACTAATGCCTCCC

RAD51 exon 5 Fwd TTCTGATGAGCTCCAAGAACATT

RAD51 exon 5 Rev GATTCTTGAGGACAGAGAAAGTACC

RAD51 exon 7 Fwd TGGGTGCTATCATCTCTCTGCT

Chapter 2: Materials and Methods 66

RAD51 exon 7 Rev ATGCTTGATAAAGGAGCTGGGT

U6 Fwd CGTAACTTGAAAGTATTTCGATTTCTTGGC

Table 2-10 Primers for qPCR

Name Sequence (5` >3`)

ATM Fwd TCAGGCCTTGCAGAATTTGG

ATM Rev TTCTTTGCTGACGGAAGTGC

ATR Fwd TAACAGGTCCGAGTGGACAG

ATR Rev CCCAGTCTGACACTCCATGT

DNAPK Fwd GGTGTGTTGCAGAGCCATAG

DNAPK Rev GCACGGTGGTCTTCAGATTC

RAD51 Fwd TGGAGCTAATGGCAATGCAG

RAD51 Rev GCAACAGCCTCCACAGTATG

PARP Fwd AGAGTGCCAACTACTGCCAT

PARP Rev TGCCCAAACCTTTGACACTG

BRCA1 Fwd AAACCACCAAGGTCCAAAGC

BRCA1 Rev TCCAGTTGATCTGTGGGCAT

BRCA2 Fwd AGTCAGTGGTATGTGGGAGT

BRCA2 Rev AGGATCCACCTCAGCTCCTA

p73 Fwd TCAACGAAGGACAGTCTGCT

Chapter 2: Materials and Methods 67

p73 Rev AGGATGGTGGTGAATTCCGT

p53 Fwd CTGTGACTTGCACGTACTCC

p53 Rev TCATGTGCTGTGACTGCTTG

p63 Fwd TCCACCTTCGATGCTCTCTC

p63 Rev CAGTGGAATACGTCCAGGTG

53BP1 Fwd AGTGTGTGAGGAGGATGGTG

53BP1 Rev GCACAGCTGTTTCTCTGGTT

RPA70 Fwd GTCAGCTGAAGCAGTTGGAG

RPA70 Rev TAGAACCCATTCCCGAGCTT

KU70 Fwd CACTCAGTGAAGTGCTGTGG

KU70 Rev GGAAGATGCCTGTATCTCGGA

KU80 Fwd GAGGCACAGTTGAATGCTGT

KU80 Rev CTGTGCAGCAGACACTGAAA

GAPDH Fwd AATTCCATGGCACCGTCAAG

GAPDH Rev ATCTCGCTCCTGGAAGATGG

XPC Fwd CCATCCCGTGACTGATGGAT

XPC Rev CTGATGAGCAGACCTTTGGC

BRIP1 Fwd CCAGGCCCTTGGTAGATGTAT

BRIP1 Rev TGCTGCCGTACCCATTTAGA

cABL1 Fwd GACCTTGAAGGAGGACACCA

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cABL1 Rev GCACCAGGTTAGGGTGTTTG

MRE11 Fwd AAGTCCGTGAGGCTATGACC

MRE11 Rev CTCGGCCTCTTCCTTTGTTG

CEP2 Fwd GTTTGGCGACATCTCCTTCC

CEP2 Rev GATGGCGTTCTTGAGCAGAG

LIG1 Fwd ATGCTTCCCTCTCTGACACC

LIG1 Rev CTCTGTCCTCGTCCTCACTC

PUMA Fwd CGTGAAGAGCAAATGAGCCA

PUMA Rev GATGAAGGTGAGGCAGGCAT

2.11 BIOCHEMISTRY METHODS

2.11.1 Surface plasmon reasonance 2.11.1.1 Immobilization of RAD51 A Biacore T200 SPR biosensor (GE Healthcare Biosciences) was used to evaluate the binding interactions of small molecules with RAD51. Recombinant human RAD51 protein (Sigma-Aldrich, SRP2090) was immobilized to the surface of CM-5 chip by random amine coupling chemistry. The sensor surface was activated by N-ethyl-N′-(3- dimethylaminopropyl)-carbodiimide (EDC) and N-hydroxysuccinimide (NHS) (GE Healthcare Biosciences) followed by injection of RAD51 (61.5ug/ml-abcam) diluted in 10 mM NaOAc (pH 4.5). A 100 μL injection of RAD51 into the flow cell (5 μL/min) resulted in >11 000 response units (RU) of RAD51. Unbound active sites on the chip were blocked with ethanolamine. A control flow cell without bound ligand was created simultaneously. The running buffer used for immobilization contained 1 × HBS-N buffer (GE Healthcare Biosciences) + 1mM DTT.

2.11.1.2 Small molecule interactions with RAD51 Interaction assays were carried out at 25οC in running buffer containing 1 × DPBS buffer + 1mM DTT, 0.05% T20 and 5% DMSO. Small molecules were screened at a

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concentrations 50 μM and 100 μM (diluted in 1 × DPBS buffer + 1mM DTT and 0.05% T20) with a final DMSO concentration of 5%. Sensorgrams were generated by injecting each compound (in duplicate) onto the chip for 30 seconds (10 μL/min) followed by a 60 second dissociation-phase, during which running buffer was flowed across the chip surface. B02 (50 or 100 μM) served as a positive control and was injected every 20 cycles to monitor carry over and binding stability. The actual response for each compound was determined by subtracting the response units (RU) obtained from the control flow cell from RU at the RAD51 bound flow cell. Solvent correction was performed every 30 cycles using an eight-point DMSO solvent correction curve (4.5-5.8% DMSO).

2.11.2 EMSA assays 2.11.2.1 RAD51 binding to ssDNA Electrophoretic mobility shift assay (EMSA) was used to measure RAD51 binding to ssDNA. RAD51 (2, 1, 0.5, 0.25 μM) was incubated with ΦX174 circular ssDNA (40 μM) in 10 μL reaction buffer (24 mM HEPES (pH7.5), 1 mM MgCl2, 30 mM NaCl, 1mM DTT, 0.4 mM 2-mercaptoethanol, 0.02 mM EDTA, 0.1mg/ml BSA, 2% glycerol and 1 mM ATP). Samples were incubated for 15 minutes at 37oC then loaded onto a 0.8% agarose gel in TAE buffer (2.7.1) and electrophoresed at 20V for 16 hrs. The gel was stained with 1 μg/ml SYBR Safe, exposed to UV light and digitally photographed. ssDNA resolution and detection has been further improved by running the gel at 4oC and staining with 1 μg/ml SYBR Gold which should allow use of lower ssDNA and protein concentration in this assay.

2.11.2.2 DNA Binding Competition Assay EMSA was used to measure RAD51 binding to ssDNA in the presence of B02 and the lead compound- 17. RAD51 (2 μM) was incubated with ΦX174 circular ssDNA (40 μM) and compound (100 and 50 μM) in 10 μL reaction buffer. Samples were incubated for 15 minutes at 37oC then loaded onto a 0.8% agarose gel in TAE buffer (2.7.13) and electrophoresed at 20V for 24 hrs at 4oC. The gel was stained with 1 μg/ml SYBR Gold, exposed to UV light and digitally photographed. Further optimisation of the DNA binding completion assay will include pre-incubation of RAD51 with the compound for 15 mins prior to adding ssDNA.

2.12 CELL BIOLOGY METHODS

2.12.1 Cell culture MDA-MB-231, MDA-MB-436, MDA-MB-468, HS578T and HEK293FT cells were cultured in DMEM supplemented with 10% FBS and Penicillin-Streptomycin (100 U/mL). SUM159PT, MDA-MB-453 and BT549 cells were cultured in RPMI supplemented with 10%

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FBS and Penicillin-Streptomycin (100 U/mL). Cells were maintained in a humidified atmosphere at 37oC, 5% CO2. Cells were routinely passaged approximately every 3 days by trypsinisation to detach cells, centrifuged at 1200 rpm for 3 minutes to collect cells and subcultured into new flasks containing fresh media. All cell lines were regularly tested for mycoplasma and authenticated using short tandem repeat profiling (testing performed by QIMR Berghofer in-house media services).

2.12.2 Cell seeding, drug, inhibitor and irradiation treatments For proliferation and viability assays cells were seeded in 96 well plates at a density of 1-5x103 cells/well in culture media and allowed to attach overnight. For flow cytometry experiments cells were seeded in 6 well plates. Seeding was optimised for each cell line so that cells in the vehicle control condition were 85-100% confluent at the experiments endpoint. Cells were treated the day after seeding with chemotherapy, inhibitor, irradiation or a combination of chemotherapy and inhibitor or irradiation and inhibitor. The only exception to this was for IC50 determination of RAD51 inhibitors in Chapter 4 (Table 4.2). In this instance cells were seeded in medium containing RAD51 inhibitor. The vehicle control condition corresponded to a similar volume of DMSO in culture medium. If cells were being irradiated in combination with inhibitor treatment then the inhibitor was added to the cells approximately 1 hour prior to exposure to 5-6 Gy of gamma irradiation. Cells were irradiated using a Gammacell 40 Exactor (MDS Nordian) research irradiator with a 137Cs source at 108 cGy/min.

2.12.3 Determination of drug and inhibitor IC50 concentrations To calculate IC50 concentrations, first we measured cell growth inhibition by MTT (2.12.4) or MTS assay (2.4.5) following 5 days incubation with a 6 point concentration range of the drug or inhibitor of interest. The vehicle control condition represented no inhibitory effect and at the highest concentration assayed growth inhibition achieved 100%. The dose- response data were fit to sigmoidal dose-response curves with nonlinear regression. Data was fit with either a standard slope or variable slope (depending on which model fit best) and IC50 values calculated using GraphPad Prism 7. Drug and inhibitor concentrations assayed were; RAD51 inhibitors (20, 6, 2, 0.6, 0.2, 0 μM), doxorubicin (1000, 300, 100, 30, 10, 0 nM) and docetaxel (10, 3, 1, 0.3, 0.1, 0 nM).

2.12.4 MTT assay End point cell proliferation and viability was determined by MTT or MTS assay. MTT assays were performed using MTT reagent prepared from Thiazolyl Blue Tetrazolium Blue

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(2.7.2). Cells were washed with DPBS and then 50 μL MTT solution (10% MTT reagent diluted in culture medium) was added to each treatment well and also to at least 3 blank o control wells. Cells were incubated for 2 hours at 37 C, 5% CO2 and then the solution was removed and 100 μL propanol was added to each well. Cells were incubated for 1 hour at o 37 C, 5% CO2 and then absorbance was read at wavelength of 590 on a BioTek microplate reader.

2.12.5 MTS assay MTS assays were performed using the CellTiter 96® AQueous One Solution Cell Proliferation Assay Kit. Cells were washed with DPBS and then 100 μL MTS solution (10% CellTiter 96® AQueous One Solution diluted in culture medium) was added to each treatment well and also to at least 3 blank control wells. Cells were incubated for 15-30 o minutes at 37 C, 5% CO2 and then 20 μL of 10% SDS was added to stop the reaction. Absorbance was then read at wavelength of 490 nm on a BioTek microplate reader.

2.12.6 IncuCyte Zoom imaging Cell proliferation and/or cell death over time was evaluated by live cell imaging using the IncuCyte Zoom (Essen BioScience). If cell death was to be measured then Nuc Green Live dead reagent was added to culture medium (1:200) when treatment and vehicle control conditions were added. The Phase channel was used to measure cell proliferation/total cells (measured as % phase confluence) and the Green channel was used to detect cell death (measured as % green confluence). Plates were scanned at 3 hourly intervals to capture images. Data from IncuCyte Zoom was exported into Graphpad Prism to calculate the Area Under the Curve for Phase Confluence and Green Confluence. The percentage of cell death was calculated as:

Area under the curve (green confluence) x 100 Area under the curve (phase confluence) 2.12.7 Flow cytometry cell cycle analysis Cell cycle analysis was performed on fixed, PI stained cells. Approximately 1 × 106 cells were harvested by trypsinisation, washed in DPBS and fixed in cold 70% ethanol overnight at -20oC. Fixed cells were incubated with 500 µL of 100 μg/ml PI staining solution (2.7.3) for 1 hour at room temperature (light protected) and DNA content was determined by collecting 10,000 events using the FACSCanto II flow cytometer (BD Biosciences). Data acquisition and cell cycle analysis was performed using Modfit v4.0 software.

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2.12.8 Flow cytometry apoptosis analysis Apoptotic cells were analysed using the FITC Annexin V/Dead Cell Apoptosis Kit following the manufacturer instructions. Approximately 1×106 cells were harvested by trypsinisation, washed in DPBS and stained with 100 µL of Annexin V and 100 μg/ml PI staining solution for 15 minutes at room temperature (light protected). 400µl of 1 x annexin binding buffer was added to each sample prior to analysis on the FACSCanto II flow cytometer (BD Biosciences). Result analysis was performed using FlowJo (FlowJo LLC).

2.12.9 Non-homologous end joining assay NHEJ repair was investigated using an assay adapted from Lim et al. (2012). The NHEJ reporter plasmid pEGFP-N1 (Clontech) (a gift from Yi Chieh Lim) was digested with HindIII restriction enzyme and purified by gel extraction. Aliquots were analysed by gel electrophoresis to confirm complete digestion. In a 6 well plate adherent cells were transiently transfected using Lipotectamine 2000 with 2µg of linearized NHEJ reporter vector or 2 μg circularized pEGFP-N1 to serve as a control for transfection efficiency. Following transfection, media containing with 10 μM of compound 17 (RAD51 inhibitor) or vehicle was added and GFP expression was measured on the FACSCanto II flow cytometer (BD Biosciences) 72 hours later. Due to the differences in transfection efficiency between individual cell lines, linearized GFP was normalized back to circular GFP.

2.12.10 Homologous recombination assay HR repair was investigated using an assay adapted from Pierce et al. (1999) using plasmids gifted by Maria Jasin; pDRGFP (Addgene plasmid # 26475; http://n2t.net/addgene:26475; RRID:Addgene_26475) and pCBASceI (Addgene plasmid # 26477; http://n2t.net/addgene:26477; RRID:Addgene_26477). Briefly, in a 6 well plate, adherent cells stably transfected with pDR-GFP were transiently transfected using Lipofectamine 2000 with 2 µg pCBASceI or 2 µg of circularized pEGFP-N1 (Clontech) to serve as a control for transfection efficiency. Following transfection, media containing with 10 μM of compound 17 (RAD51 inhibitor) or vehicle was added and GFP expression was measured on the FACSCanto II flow cytometer (BD Biosciences) 72 hours later. Due to the differences in transfection efficiency between individual cell lines, linearized GFP was normalized back to circular GFP.

2.12.11 Immunofluorescence staining and imaging Cells were seeded on Poly-L-lysine (0.01%) coated coverslips or in 96 well plates and allowed to adhere for approximately 6 hours. Cells were then incubated with media

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containing 10 μM of indicated RAD51 inhibitor compound (or vehicle control) for 16 hours, o exposed to 6-Gy γ-irradiation and then incubated for a further 6 hours at 37 C, 5% CO2. Cells were then washed once with PBS, incubated on ice for 5 minutes with cytoskeleton buffer (2.7.4) and washed twice with PBS. Cells were fixed with 4% PFA for 15 minutes at room temperature, washed twice with PBS, permeabilized with 0.5% Triton-X for 15 minutes at room temperature and washed twice with PBS. After blocking with FBT buffer (2.7.5) cells were sequentially stained with primary and secondary antibodies (antibody details provided in Table 2.4). Cells were first stained with 1:1000 γH2AX antibody diluted in FBT buffer for 1 hour and then washed with PBS. Secondary antibody Alexa 488 (1:500) and DAPI (1:1000) were applied for 30 minutes followed by a PBS wash. Cells were then stained overnight staining at 4oC with 1:100 RAD51 antibody and washed with PBS. Cells were stained with secondary antibody Alexa 594 (1:500) for 30 minutes and washed with PBS. At this stage cells stained on coverslips were mounted with Prolong Gold mount media on glass slides and viewed under a Delta Vision Deconvolution microscope (GE Healthcare). Cells stained in a 96-well plate were scanned using the InCell Analyser (GE Healthcare). InCell Developer Toolbox software was used to quantify the number of RAD51 and γ-H2AX foci within each DAPI stained nucleus. Nuclei with 15+ RAD51 foci were scored as RAD51 positive and nuclei with 15+γH2AX foci were scored γH2AX positive. The ratio of RAD51 foci/ɣH2AX foci was calculated as: total RAD51 positive cells divided by total γH2AX positive cells (normalised to the vehicle control condition).

2.12.12 Viability assays involving p73 inhibition and p53 overexpression Cells were seeded the day prior to transfection in 6 well plates at a density of 1 x 105 cells/well. The following day cells were transfected using Lipofectamine 20000 (2.14.5) with plasmids to knockdown p73 (pcDNA3.1 p73shRNA), overexpress p53 (pcDNA.1 p53) or serve as a transection control pEGFP.N1 (Clontech). pcDNA3.1 p73shRNA (shTP73 sequence:CCGGCCAAGGGTTACAGAGCATTTACTCGAGTAAATGCTCTGTAACCCTTG GTTTTTG) was constructed by Greg Kelly, QIMR Berghofer. pcDNA.1 p53, described in Kim et al. (2011) was a gift from Hyunkyung Kim, Seoul National University. The day after transfection, cells were treated with a combination of 200 nM doxorubicin and 2 nM docetaxel, or medium containing DMSO was added to control wells. Culture medium contained 1:200 Nuc Green Live Dead reagent to allow visualisation of dead cells. Culture medium containing DMSO was added to wells serving as a transfection control. Cell proliferation and death was measured over a period of 3 days using IncuCyte Zoom live cell imaging (2.12.6).

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2.12.13 Metaphase spread analysis To prepare metaphase spreads, exponentially growing cells were treated with 1 μg/ml of colcemid for 3 hours. Cells were collected and incubated in hypotonic solution (0.56% KCl) for 6 minutes, fixed in methanol: glacial acetic acid (3:1), spotted onto glass slides and air-dried. To visualize metaphase spreads the chromosomes were stained with DAPI (1:1000 in PBS) and viewed under a Zeiss AxioScop2 fluorescent microscope. Chromosomes were counted for 10 metaphase spreads.

2.13 BACTERIAL METHODS

2.13.1 Transformation of DNA into competent cells 50 µl aliquots of α-Select competent cells (or Stabl3 competent cells used for transforming gRNA plasmids) were thawed on ice. 1-5μL (10pg to 100ng) of plasmid DNA was added to a 50 µl of competent cells in a microcentrifuge tube, gently mixed and then incubated on ice for 30 minutes. The competent cells were then heat shocked at 42ºC for 45 seconds and placed back on ice for a further 2 minutes. 250 µl of pre-warmed S.O.C medium was added to the cells and the tube placed on an orbital shaker at 37 °C, 225 rpm for 1 hour. 25-100 µl of the cell suspension was then spread uniformly across the surface of an LB-agar plate containing the appropriate selection antibiotic and incubated overnight at 37ºC.

2.13.2 Large scale plasmid preparation Single colonies from the agar selection plate were transferred to 5 ml (for Miniprep), 50ml (for Midiprep) or 150-300 ml (for Maxiprep) of LB broth containing the appropriate selection antibiotic and incubated overnight on an orbital shaker at 37ºC, 200 rpm.

2.13.3 Plasmid DNA purification Plasmid DNA was purified using the PureLink® HiPure Plasmid Miniprep, Midiprep or Maxiprep Kit (Invitrogen™). As per the manufacturers’ protocol the transformed bacterial culture was centrifuged at room temperature for 10 minutes at 4000 × g, the supernatant removed and the pellet resuspended in Resuspension Buffer with RNase (0.4, 4 or 10 mL). Lysis Buffer (0.4, 4 or 10 mL) was added to the tube/flask, mixed by inversion and incubated at room temperature for 5 minutes. Precipitation Buffer (0.4, 4 or 10 mL) was added to the lysate, mixed by inversion and centrifuged at 12 000 ×g for 10 minutes at room temperature, the DNA from the lysate was bound to an equilibrated HiPure Maxi Column followed by Wash Buffer (2.5, 10 or 60mL). The DNA was eluted from the column with Elution Buffer (0.9, 5 or 15mL), precipitated in isopropanol (0.63, 3.5 or 10.5 mL) and centrifuged at 12

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000 × g for 30 minutes at 4ºC. The supernatant was discarded and the pellet washed in 70% ethanol (1, 3 or 5mL) and centrifuged at 12 000 × g for 30 minutes at 4ºC. The resulting DNA pellet was air-dried, resuspended in 50-500 µL of TE buffer or deionised water and the DNA concentration of 1 µL of sample was quantified using the NanoDrop Lite (Thermo Scientific).

2.14 MOLECULAR BIOLOGY METHODS

2.14.1 Generation Cas9 expressing TNBC cell lines To create TNBC cell lines containing CEBPB-Lap KO, RAD51-KO and RAD51- K133R substitution mutation we used the CRISPR-Cas9 two vector lentiviral GeCKo system (Sanjana, Shalem, and Zhang 2014). Our first step was to generate TNBC cell lines that stably expressed Cas9. To this end we transfected HEK293FT cells with the lentiCas9-Blast vector. lentiCas9-Blast was a gift from Feng Zang (Addgene plasmid # 52962; http://n2t.net/addgene:52962; RRID:Addgene_52962) and used the lentivirus produced to transduce the TNBC cell lines; MDA-MB-231, MDA-MB-436, MDA-MB-453, MDA-MB-468, MDA-MB-453, HS578T, BT549.

2.14.2 CRISPR target guide sequence cloning protocol Appropriate target sequences were selected from the GeCKo v2 human library (http://genome-engineering.org/gecko/) or identified using the MIT CRISPR Design Tool (http://crispr.mit.edu/). Oligonucleotide pairs designed from target sequences are listed in Table 2.8. The target sequence cloning protocol from the Zhang lab (Sanjana, Shalem, and Zhang 2014) was followed for cloning pairs of target sequence oligonucleotides into the lentiGuide-Puro vector. lentiGuide-Puro was a gift from Feng Zang (Addgene plasmid # 52963; http://n2t.net/addgene:52963; RRID:Addgene_52963). Firstly, the lentiGuide-Puro plasmid was digested with BsmBI restriction enzyme for 30 minutes at 37 °C (5 ug, 3 ul FastDigest BsmBI (Fermentas), 3 µL FastAP, 6 µL 10X FastDigest Buffer, 0.6 ul 100 mM DTT with a final volume made up to 60 µL with dH2O). The digested plasmid was gel purified using the QIAquick Gel Extraction Kit. Next, each pair of oligonucleotides was phosphorylated and annealed (1 µl of each oligonucleotide [100 µM], 1 µl 10x T4 Ligation Buffer with 10 mM ATP, 0.5 µl T4 PNK, total volume made up to 10 µL with dH2O) using a BioRad thermocycler (37°C for 30 min, 95°C for 5 min, ramped-down to 25°C at 5°C/min).

The annealed oligos were then diluted 1:200 in dH2O and inserted into a ligation reaction for 10 minutes at room temperature (50 ng digested plasmid, 1 µL diluted oligo duplex, 5 ul 2X Quick Ligase Buffer, volume to 10 µL with dH2O and then 1 µL 1 ul Quick Ligase).

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To check for correct insertion of sgRNA the vectors were transformed into Stbl3 competent cells and plated overnight on ampicillin LB agar selection plates. 2-3 colonies were picked for each vector and DNA purified by Miniprep (2.14.3). The sequence of each colony was verified by sequencing from the U6 promoter using the U6-Fwd primer (details provided in Table 2.9). Sanger sequencing results for each sample were compared to the LentiGuide-Puro cloning vector sequence (NNNNNNNNNNNNNNNNNNNN GTTTTAGAGCTAGAAAAGAAATAGCTAGCAAGTTAAAATAAGGCTAGTCCGTTATCAA CTTGAAAAAGTGGCACCGAGTCGGTGC) using APE software to check that the 20-nt guide sequence was inserted between the U6 promoter and the remainder of the sgRNA scaffold.

2.14.3 Lentivirus production To make lentivirus, the transfer plasmids were co-transfected with packaging plasmids pLP1, pLP2 and pLP/VSV-G (Invitrogen). Briefly, for each virus, a 10 cm dish of 80 % confluent HEK293FT cells was transfected in 3 mL OptiMEM using 10 ug of the transfer plasmid, and 10 ug of each packaging plasmid (+/- 20uL 10uM ssODN repair template for gRNA KR), and 30 ul of Lipofectamine 2000 (Life Technologies). After 6 hours, media was changed to 10 mL DMEM with 10 % FBS and refreshed again after 12 hours. At 60 hours post transfection viral supernatants were harvested and centrifuged at 1200 rpm at 4 °C for 5 min. The supernatant was filtered through a 0.45 um low protein binding membrane (Millipore) and used immediately. Harvesting of virus was repeated at 84 hours post transfection and used immediately.

2.14.4 Transduction In a 6 well plate, adherent cells at approximately 50% confluence were transduced with 2 mL/well of viral supernatant for 24 hours. Transduction with fresh viral supernatant was repeated the following day. After 24 hours viral supernatant was removed and replaced with fresh culture medium. 24 hours later media was changed and the appropriate selection antibiotic (concentration determined by kill curve) was added for all wells except the uninfected controls. Antibiotic containing media was replaced every 3 days until all uninfected control cells were dead.

2.14.5 Transfection In a 6 well plate, adherent cells at approximately 80% confluence were transfected with 2 µg/well of DNA using Lipofectamine 2000. Plasmid DNA and Lipofectamine 2000 (10 μL/mL final volume) were each mixed separately with OptiMEM and incubated for 5 mins.

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The mixtures were combined, incubated at room temperature for 15 minutes and then 600 μL was transferred to each well. After 6 hours incubation at 37 °C, 5 % CO2 transfection medium was removed and replaced with fresh culture medium. For stable transfections antibiotic selection proceeded 24 hours later (antibiotic concentration determined by kill curve). The appropriate selection antibiotic (concentration determined by kill curve) was added for all wells except the untransfected controls. Antibiotic containing media was replaced every 3 days until all control cells were dead.

2.14.6 DNA extraction and purification from adherent cells DNA extraction and purification was performed using the QIAGEN DNeasy Blood and Tissue Kit following manufacturer’s protocol. Adherent cells were collected by trysinization, washed in DPBS, centrifuged and resuspended in 200 μL DPBS in an Eppendorf tube. 200 µl of Buffer AL was added to the sample, mixed by vortex and incubated at 56°C for 10 min. 200 µl of 100% ethanol was added and mixed by vortex. The sample was then pipetted into a DNeasy Mini spin column with collection tube and centrifuged for 60 seconds at 6000 x g. The flow through was discarded and 500 µl Buffer AW1 was added to the column and centrifuged for 60 seconds at 6000 x g. The flow through was discarded and 500 µl Buffer AW2 was added to the column and centrifuged for 3 min at 20,000 x g. The flow through and collection tube were discarded and, the column was transferred into a 1.5 mL Eppendorf tube. 200 μL of RNase-free water was added to the spin column membrane, incubated for 5 minutes at room temperature and then centrifuged for 1 min at 6000 x g to elute the DNA. 1 µL of sample was quantified using the NanoDrop Lite (Thermo Scientific).

2.14.7 Preparing DNA agarose gels To prepare 1 % agarose gels, 1 g of agarose was mixed with 100 ml of 1xTAE Buffer (2.7.1) in beaker and heated in a microwave until the agarose had completely dissolved. After a brief cooling time, 10 µl of SYBR Safe was added and the agarose was poured into a gel tray and a comb was added to form wells. Once the gel was set and comb removed the tray was placed in an electrophoresis chamber and covered with 1 X TAE buffer.

2.14.8 Loading and running agarose gels Up to 20 µl of DNA combined with 6x DNA loading dye was loaded into wells and the. gel run at 100 V for 1 hour in a Bio-Rad electrophoresis chamber connected to a Bio-Rad PowerPac. Images were acquired under ultraviolet light using the G:BOX Chemi XX6 (Syngene).

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2.14.9 DNA extraction and purification from agarose gels The agarose gel was viewed on top of an ultraviolet transilluminator and the band of interest excised with a scalpel blade and transferred to a 1.5 ml Eppendorf tube. A QIAQuick Gel Extraction Kit was used to isolate the DNA following the manufacturers’ protocol. 300 µl of Buffer QG was added for every 100 µg of gel and the sample heated at 50 °C for 10 minutes. 100 µL of propanol (for every 100 µg of gel) was added and the sample and mixed. The sample was then pipetted into a QIAquick spin column with collection tube and centrifuged for 60 seconds at 10,000 x g for 1 minute. The flow through was discarded and 750 µl Buffer PE was added to the column, incubated for 5 minutes at room temperature and then centrifuged for 1 min at 10,000 x g. The flow through was discarded and tube centrifuged again for 1 min at 10,000 x g to remove any trace material. The column was transferred to a fresh Eppendorf tube and 50 µl of dH2O was added to the fibre matrix and incubated at room temperature for 5 minutes. The DNA solution was collected by centrifugation at 10,000 x g for 1 minute at room temperature.

2.14.10 High fidelity PCR Primers for PCR were designed using Primer Blast (https://www.ncbi.nlm.nih.gov/tools/primer-blast/). PCR using High fidelity PCR was carried out using Herculase II Fusion DNA polymerase. Template DNA (10 ng/μL) was mixed with reaction components (10 µl Herculase II PCR buffer 5×, 1 µl of 100 mM dNTP mix, 2 µl of

50mM MgCl2, 1.25 µl of each 10 μM primer, 1 µl of Herculase II fusion polymerase, 0.5 µl

DMSO and dH2O up to 50 µl) in a PCR tube. Tubes were transferred to a BioRad thermocycler programmed as shown in Table 2.

Table 2-11 Thermocycler parameters for high fidelity PCR

Cycle Number Denature Anneal Extend

1 95 °C, 2 min

2–31 95 °C, 20 s 60 °C, 20 s 72 °C, 30 s

32 72 °C, 3 min

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2.14.11 PCR product purification PCR products were purified using EXOsapIT. 2 µL of EXOsapIT was added to 5 µL of PCR product and incubated for 30 minutes at 37oC (for PCR cleanup) followed by 15 minutes incubation at 56oC to inactivate EXOsapIT.

2.14.12 Sanger sequencing Sanger sequencing was performed by QIMR Berghofer in-house Scientific Services on prepared samples containing purified PCR product (40 ng DNA) and 6 pmol of the appropriate sequencing primer. ApE (A plasmid Editor, v2.0.60) software (https://jorgensen.biology.utah.edu/wayned/ape/) was used to read ABI sequencing trace files and to align sample sequences to the appropriate reference sequence.

2.14.13 RNA extraction RNA extraction was performed using the QIAGEN RNeasy® Plus Mini Kit following manufacturer’s protocol. Adherent cells were collected by trysinization, washed in DPBS and centrifuged. 350 μL Buffer RLT was added to the cell pellet and vortexed. An equal volume of 70% ethanol was then added and the mixture vortexed. The sample was transferred to an RNeasy Mini spin column with collection tube and centrifuged for 15 seconds at 8000 x g. The flow through was discarded and 700 μL of Buffer RW1 added to the column and centrifuged for 15 seconds at 8000 x g. The flow through was discarded and the RNA was washed twice with RPE buffer. The first spin at for 15 seconds at 8000 x g and second spin at for 2 min at 8000 x g. Finally, the column was transferred into a 1.5 mL Eppendorf tube and 30 μL of RNase-free water was added to the spin column membrane. The column was centrifuged for 1 min at 8000 x g to elute the RNA. 1 µL of sample was quantified using the NanoDrop Lite (Thermo Scientific).

2.14.14 cDNA synthesis from RNA cDNA was synthesised using the R2 profiler first strand kit following the manufactures’ protocol. Firstly, genomic DNA elimination mix was prepared for each RNA sample consisting of; 1μg RNA, 2 μL Buffer GE and RNase free water to make a total volume of 10 μL. The sample was mixed, briefly centrifuged, incubated for 5 minutes at 42oC and then placed on ice for at least 1 minute. Secondly, reverse transcription mix was prepared with each reaction containing 4 μL of 5× Buffer BC3, 1 μL of Control P2, 2 μL of RE3 Reverse Transcriptase Mix and 3 μL of RNase free water. Next, 10 μL of reverse-transcription mix was added to each tube containing 10 μL genomic DNA elimination mix and gently mixed. The samples were incubated at 42oC for 15 minutes and then the reaction was stopped by

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incubating at 95oC for 5 minutes. Finally, 91 μL RNase-free water was added to each reaction, mixed and samples kept on ice or stored at -20ºC.

2.14.15 Quantitative reverse transcriptase PCR (qRT-PCR) Quantitative Reverse-Transcriptase PCR (qRT-PCR) was performed in a 384-well plate array format using RT2 SYBR Green Mastermix qPCR reagent. Each reaction contained 5 μL SYBR green mastermix, 0.8 L diluted cDNA, 2.5 μM each primer and RNase-free water up to 10 μL. Reactions were cycled on a Roche® Light Cycler 480 using parameters described in Table 2.11. Ct values were calculated using the accompanying Light Cycler 480 software, version 1.5.0.39. Calculations were performed using the ∆∆Ct method, with values normalised to ß-actin as a housekeeping gene. Ct values more than 35 were considered failed reactions, and were not used for analysis.

Table 2-12 Cycling conditions for Roche LightCycler 480*

Cycles Duration Temperature

1 10 min 95oC

45 15 s 95oC

1 min 60oC

* ramp rate adjusted to 1.5oC/sec

2.14.16 DDR microarray The QIAGEN Human DNA Damage Signaling Pathway array (RT2 Profiler PCR Array, PAHS-029Z) was used to obtain the relative expression of 84 genes involved in DNA damage signalling pathways, following the manufacturer instructions. Briefly, RNA was reverse-transcribed into cDNA (2.15.11). The cDNA was used on the real-time RT² Profiler PCR Array in combination with RT² SYBR® Green qPCR Mastermix. Each reaction contained 5 μL SYBR green mastermix, 0.8 μL diluted cDNA and RNase-free water up to 10 μL and was cycled a Roche® Light Cycler 480 using parameters described in Table 2.11.

CT values were exported to an Excel file to create a table of CT values. This table was then uploaded on to the data analysis web portal at http://www.qiagen.com/geneglobe. Samples were assigned to controls and test groups. CT values were normalized to GADPH.

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2.15 PROTEIN METHODS

2.15.1 Protein extraction Adherent cells were trypsinized and centrifuged for 5 minutes at 1400 rpm. The supernatant was removed, the cell pellet resuspended in 1mL PBS and transferred to an Eppendorf tube. Cells were pelleted, resuspended in 50-100 µL of Whole Cell Lysis Buffer containing protease and phosphatase inhibitor (2.7.7) and incubated on ice for 1-2 hours. The samples were then and centrifuged at 15,000 rpm for 10 minutes at 4ºC and the supernatant collected and stored at -20C.

2.15.2 Protein estimation Protein concentration was determined by Bradford assay with protein standards prepared with BSA diluted in dH2O (0.25-2mg/mL). In a 96 well plate, 1μl of sample or protein standard was added to each well followed by 100 μL of Bradford reagent. Samples were incubated for 5min at room temperature (light protected) and absorbance at 595nm with a Bio-Rad microplate reader. Concentration of samples was determined by standard curve.

2.15.3 Western blotting and wet transfer Protein samples were prepared in 5x SDS loading buffer (5.7.8) followed by boiling at 95°C for 5 min. Samples were separated on 4-20% Mini-PROTEAN® TGX™ Precast Gels (Bio-Rad) using Mini-PROTEAN Tetra Cell system (Bio-Rad) in Tris-glycine running buffer (5.7.9). Protein bands on gel were transferred onto PVDF membrane (Bio-Rad) using the Mini Trans-Blot® Electrophoretic Transfer Cell (Bio-Rad) in Towbin buffer (2.7.10).

2.15.4 Immunoblot staining protocol and image acquisition Following completion of transfer of proteins onto PVDF membrane, the membrane was blocked with 5% skim milk powder in TBST (2.7.11) at 4°C for 1 hour. Following this, primary antibody diluted in 5% milk in TBST (primary antibody dilutions provided in Table 2.4) was applied to membrane blots over night at 4°C. The following morning blots were washed three times for 5 mins each with TBST and blots were incubated with the secondary antibody in 5% milk in TBST (secondary antibody dilutions provided in Table 2.4) for 1 hr at room temperature. Blots were washed three times for 5 mins each with TBS-T. Clarity™ Western ECL Substrate (Bio-Rad) was used according to the manufacturer’s instructions. For image acquisition, the blot was exposed to an x-ray film and the film was developed.

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2.15.5 Quantification of western blots Image J software was used to measure the intensity of each protein band detected by Western Blotting. The result for each protein band was normalised by dividing its intensity value by that of the loading control in the same lane. This normalised value was then divided by the normalised value of the control band to give a final value expressed as a ratio of the control band.

2.16 STATISTICAL ANALYSIS

GraphPad Prism 7 was used to perform statistical analysis with a p value ≤ 0.05 considered statistically significant. Throughout this thesis significance is denoted with asterisks, where * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, **** p ≤ 0.0001. Data is expressed as mean ± standard error of the mean (SEM). Students’ t-test (two-tailed) was used to detect statistically significant differences between two means. One-way analysis of variance (ANOVA) was used to detect statistically significant differences between three or more means influenced by one independent variable. A two–way ANOVA was used to detect significant differences between means influenced by two independent variables. Tukey’s, Dunnet’s or Sidak’s tests were used (as indicated for each experiment) for post hoc analysis to correct for multiple comparisons and identify where the significant differences occurred. Pearson product-moment correlation coefficient was used to assess the relationship between two variables.

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Chapter 3: Gene editing RAD51 with CRISPR- Cas9 for novel functional studies

3.1 INTRODUCTION

The canonical role of RAD51 in HR repair and replication maintenance is well established in the literature (Wright, Shah, and Heyer 2018; Kolinjivadi et al. 2017). In BRCA1 deficient tumours overexpression of RAD51 provides a powerful mechanism by which these tumours re-establish a functional HR pathway and develop resistance to PARP inhibition (Martin et al. 2007). In TNBC, RAD51 overexpression was observed at twice the rate in BRCA1 mutant tumours compared to non-BRCA1 tumours (Wiegmans et al. 2014). However, a variety of wild-type BRCA1 tumours also display high levels of nuclear RAD51 without induced DNA damage (Mitra et al. 2009; Raderschall et al. 2002) which suggests that the role of RAD51 overexpression in tumorigenesis is not limited to compensating for BRCA1 deficiency and DDR (Martin et al. 2007).

There is emerging evidence that RAD51 overexpression plays a role in tumour metastasis. In human TNBC cell lines Wiegmans et al. (2014) found that manipulating the expression levels of RAD51 altered the potential for cells to metastasize in orthotopic animal models. Knockdown of RAD51 in both syngeneic and xenograft TNBC tumour models resulted in reduced migration and enhanced animal survival. In contrast, overexpression of RAD51 enhanced spontaneous TNBC metastasis. Utilizing an in vitro metastatic gene array of 82 candidate genes Wiegmans et al. (2014) compared gene expression profiles of MDA- MB-231 TNBC cells depleted of RAD51 with HS578T TNBC cells engineered to overexpress of RAD51. They found that RAD51 expression differentially regulated 25 genes. Four of the 25 identified genes, namely MMP2, MET, NF2 and p53, are expressed in aggressive lung metastases from breast cancer (Minn et al. 2005) and five of the 25 genes (MMP11, MMP13, SMAD2 TGF, p53) are known targets of the transcription factor CCAAT/enhancer binding protein beta (CEBP). In support of a possible role of a pro-metastatic RAD51 transcriptional complex, CEBP regulates metastatic gene expression in prostate (Kim and Field 2008), pancreatic (Shimizu et al. 2007) and mammary cancer cells (Gomis et al. 2006). Additionally RAD51 has been shown to co-operate with CEBP in astrocytes affecting gene expression (Chipitsyna et al. 2006) and recent studies have reported that RAD51 is preferentially recruited to transcriptionally active sites (Aymard et al. 2014). Wiegmans et al. (2014)

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reported that RAD51 co-localised with CEBP in situ (<40nm) independent of DNA damage, at similar levels as its cognate binding partner BRCA2, and the complex could be precipitated under physiological conditions. The significant loss of CEBP transcriptional activity after RAD51 depletion provides strong support for the functional interaction between the two proteins. These findings suggest that RAD51-mediated binding with CEBP to promoters of pro-metastatic genes may be a mechanism for a DDR-independent role that supports metastasis.

In unpublished preliminary work we have ectopically overexpressed the dominant negative RAD51 K133R mutant in low RAD51 expressing TNBC cell line BT549 to investigate the possible pro-metastatic role of RAD51 in the absence of its DNA repair function. The RAD51 K133R mutant contains an altered walker motif, disrupting ATP- hydrolysis and rendering the recombinase 100-fold less effective for DNA repair (Costantino et al. 2014; Skourti-Stathaki and Proudfoot 2014). Our preliminary data showed that BT549- K133R was unable to repair DNA damage in response to gamma irradiation but displayed enhanced migration potential compared to the parental cell line (Fig. 3.1).

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Figure 3-1 A DNA repair defective dominant negative form of RAD51 enhances cell migration.

(A) The TNBC cell line BT549 and wild type RAD51 overexpression clone display normal repair of H2Ax marked double strand breaks while the K133R mutant RAD51 clone is defective for DNA repair, ( B) The K133R mutant RAD51 clone displays enhanced migratory potential in a scratch wound repair assay. Data generated for grant application.

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3.1.1 Aim and rationale To enable further investigation of the possible DNA repair independent, pro-metastatic role of RAD51 the aim of this chapter was to use CRISPR-Cas9 technology to generate a library of TNBC cell lines expressing RAD51 knockout, RAD51 K133R mutation and CEBPβ knockout. These cell lines could then be utilised in functional studies to examine gene expression profiles regulated by; wild-type RAD51, mutant RAD51 K133R that retains DNA repair-independent functions of RAD51 and CEBPβ. To date there are no known published reports of CRISPR-Cas9 editing of RAD51. In this chapter we describe the experiments performed to establish CRISPR-Cas9 gene editing of CEBPβ and RAD51 in TNBC cell lines.

3.1.2 Overview of CRISPR-Cas9 Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR associated protein (Cas9) is a popular gene editing tool. Engineered CRISPR-Cas9 systems are adapted from an immune defense mechanism that exists in prokaryotes against invading viruses (Wiedenheft, Sternberg, and Doudna 2012; Barrangou et al. 2007). When bacteria are invaded by a virus, they collect short repeats of the viral DNA and incorporate it into their own genome. If the same virus invades again, transcripts of these repeats direct Cas9 nuclease to the complementary viral DNA, causing DNA cleavage which destroys the virus (Wiedenheft, Sternberg, and Doudna 2012; Barrangou 2013; Garneau et al. 2010)

Engineered CRISPR systems contain two main components; Cas9 protein and single guide RNA (gRNA). The gRNA is made up of specificity-determining CRISPR RNA (crRNA) fused with an auxiliary trans-activating RNA (tracrRNA) (Jinek et al. 2012). In the type II CRISPR system derived from Streptococcus pyogenes (which is used in this chapter) the first 20 nucleotides of the gRNA are complementary to the target DNA sequence (as defined by the researcher) followed by a 5′-NGG protospacer adjacent motif (PAM) motif (Jinek et al. 2012). Co-expression of Cas9 and gRNA in mammalian cells results in a DSB in the target DNA approximately 3-4 nucleotides upstream of the PAM sequence (Ran et al. 2013).

DNA editing with CRISPR can be achieved via two main DSB repair pathways following DNA cleavage by Cas9: high efficiency, error-prone NHEJ or low efficiency, high fidelity HR (if a repair template is present) (depicted in Fig 3.2) (Ran et al. 2013). Repair via NHEJ gives rise to small insertions and deletions (indels) in the target DNA which ideally results in a loss of function mutation in the targeted gene (gene knockout) (Ran et al. 2013). Gene knockouts are far easier to achieve with CRISPR-Cas9 than precise gene editing due to the high

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frequency of NHEJ repair in mammalian cells compared to the very low frequency of HR repair (Rozov, Permyakova, and Deineko 2019; Song et al. 2016; Li, Zhang, et al. 2017).

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Figure 3-2 Repair outcomes following a DSB induced by CRISPR-Cas9.

DSBs induced by Cas9 (yellow) can be repaired by the error prone NHEJ pathway or high-fidelity HR pathway. Repair by NHEJ can result in random indel mutations and potential gene knockout. If homologous donor DNA is present repair can proceed through the HR pathway using the donor DNA as a repair template (Ran et al. 2013).

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3.2 RESULTS

3.2.1 Generation Cas9 expressing TNBC cell lines To create TNBC cell lines containing CEBPβ-Lap knockout, RAD51 knockout and RAD51 K133R substitution mutation we used the CRISPR-Cas9 two vector lentiviral GeCKo system (Fig. 3.3). We first transduced TNBC cell lines MDA-MB-231, MDA-MB-436, MDA- MB-453, MDA-MB-468, MDA-MB-453, HS578T and BT549 with lentiCas9-Blast to integrate Cas9 into the cell lines. Following this, Cas9 expressing cells were transduced with lentiGuide-Puro which expressed the chimeric guide RNA.

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Figure 3-3 CRISPR-Cas9 two vector lentiviral GeCKo system.

The lentiGuide-Puro vector was used to express chimeric guide RNA in cell lines already integrated with Cas9, via stable transfection with the lentiCas9-Blast plasmid. The lentiGuide-Puro vector was digested using BsmBI, and a pair of annealed oligos (based on the 20 bp target site sequence) were cloned into the single guide RNA scaffold.

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3.2.3 Selection of target sequences for gRNA design 3.2.3.1 Target sequences for CEBPβ knockout CEBPβ is an intronless gene located on chromosome 20 that is expressed as three distinct isoforms; Lap 1, Lap 2 and Lip (Cunningham et al. 2018; TheUniProt Consortium, 2018) (Fig 3.4A). Lap 1 and Lap 2 are transcriptional activators associated with oncogenic signalling in breast cancer and are 345 and 322 amino acids in length respectively. Lip is 147 amino acids in length and lacks a transcriptional domain. In our unpublished preliminary work we found that RAD51 can bind CEBPβ-Lap1 to induce expression of pro-metastatic genes. We selected four validated CEBPβ target sequences (20 base pairs in length) from the GeCKo v2 human library (http://genome-engineering.org/gecko/) to design our CEBPβ gRNAs; HGLibA_08959, HGLibA_08960, HGLibB_08951, HGLibB_08953 (from this point referred to as C1, C2, C3 and C4 respectively). The location and quality of each target sequence (based on number of off-target sites) was verified using both the MIT CRISPR design tool (http://crispr.mit.edu/) and CHOP CHOP (https://chopchop.cbu.uib.no/).

3.2.3.2 Target sequences for RAD51 knockout The RAD51 gene is located on chromosome 15 and contains 10 exons which code a canonical sequence of 339 amino acids (Cunningham et al. 2018; The UniProt Consortium, 2018) (Fig. 3.4B). gRNAs to induce RAD51 knockout were designed using four validated RAD51 target sequences (20 base pairs in length) from the GeCKo v2 human library; HGLibA_48366, HGLibA_48367, HGLibB_41026, HGLibB_41027 (from this point referred to as R1, R2, R3 and R4 respectively).

3.2.3.3 Target sequence and DNA repair template design for editing RAD51 K133R When using CRISPR-Cas9 to induce HR directed gene editing it is recommended that the sequence to be edited be located within 10 base pairs of the DSB induced by Cas9 (Ran et al. 2013). Our goal was to introduce a mutation at amino acid 133 that replaces Lysine (K) with Arginine (R) (K133R). This target amino acid is coded by RAD51 exon 5 located at ch15:40,709,025- 40,709,116. To identify appropriate target sequences for gRNA design we inserted the 92-nucleotide sequence of RAD51 exon 5 into the MIT CRISPR design tool and further verified our results using CHOP CHOP (Table 3.1). We selected a high-quality guide predicted to generate a Cas9 mediated DSB 6 base pairs upstream of the K133 coding sequence (AAG).

We next designed a 195 bp single-stranded oligonucleotide (ssODN) repair template (depicted in Fig. 3.5) that contained the sequence for Arginine (CGA) instead of Lysine

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(AAG) at amino acid position 133 (RAD51 exon 5). To ensure that our repair template was not targeted by gRNA-Cas9 a silent mutation was introduced at the PAM sequence (GGG- >GGA; glycine). A HindIII (AAGCTT) restriction site was also added to the repair template and primers designed flanking the modified region so that restriction-fragment length polymorphism analysis could be used downstream to identify clones containing repair template.

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Figure 3-4 Canonical amino acid sequences for CEBPβ and RAD51.

(A) Amino acid sequence for CEBPβ (UniProt ID: P17676). CEBPβ Lap1 isoform contains 345 amino acids, Lap2 isoform is missing amino acids 1-23 (highlighted in blue), Lip isoform is missing amino acids 1-198 (outlined in black). (B) Amino acid sequence for RAD51 (UniProt ID: Q06609). K133 highlighted in blue.

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Figure 3-5 Schematic representation of RAD51 exon 5, gRNA and ssODN donor repair template.

The nucleotide sequence for RAD51 exon 5 is shown (top) with the target sequence (blue), K133 codon (green) and PAM site (red) shown. The ssODN repair donor template (middle) with the inserted R133 mutation (green) silent PAM mutation (red) and HindIII restriction site (grey) shown. At the bottom primers (blue) are shown flanking the region of interest on RAD51 exon 5.

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Table 3-1 Summary of guide target sequences

Off-targets Genomic GC Self- Guide Gene Target sequence Exon Strand Efficiency location (%) complementarity MM0 MM1 MM2 MM3

KR RAD51 TGTTTGGAGAATTCCGAACTGGG chr15:40709055 5 + 40 0 0 0 0 5 58.12

R1 RAD51 TGTTGCCTATGCGCCAAAGAAGG chr15:40701129 2 + 50 1 0 0 0 5 53.76

R2 RAD51 TCTCATAGGTATGGTCTCTCTGG chr15:40728703 7 + 45 0 0 0 1 4 45.41

R3 RAD51 TACGCTAGCTGTCACCTGCCAGG chr15:40709095 5 + 60 2 0 0 1 3 50.74

R4 RAD51 AGGCAACAGCCTCCACAGTATGG chr15:40701114 2 - 55 0 0 0 0 9 45.83

C1 CEBPβ CGAGTACGGCTACGTGAGCCTGG chr20:50191437 1 + 65 1 0 0 0 0 44.49

C2 CEBPβ TACGCGCTGCGCGCTTACCTCGG chr20:50191646 1 + 65 2 0 0 0 0 41.82

C3 CEBPβ CGATGTTGTTGCGCTCGCGCCGG chr20:50191861 1 - 65 1 0 0 0 0 49.22

C4 CEBPβ AGGTAAGCGCGCAGCGCGTACGG chr20:50191643 1 - 65 2 0 0 0 0 36.87

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3.2.4 Sequence validation of gRNAs To create the gRNAs the target sequence oligos were cloned into the lentiGuide-Puro plasmid (Fig. 3.3). After transforming a sample of each gRNA plasmid into Stbl3 competent E. coli and allowing colonies to grow, the DNA from individual colonies was isolated and sequenced from the U6 promoter. The sequence for each constructed gRNA was compared to the expected sequence for the gRNA (20bp target sequence + 85 chRNA sequence for gRNA):

NNNNNNNNNNNNNNNNNNNNGTTTTAGAGCTAGAAATAGCAAGTTAAAATAAGGCTA GTCCGTTATCAACTTGAAAAAGTGGCACCGAGTCGGTGC

We confirmed that all the constructed gRNAs contained the correct DNA sequence. Alignment of sequences from constructed gRNAs with expected results are shown in Figure 3.6.

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Figure 3-6 Alignment of expected and actual gRNA sequences.

Following Sanger sequencing sample gRNA sequences were to aligned the appropriate reference sequence using ApE software. Correct alignment to the reference is shown for gRNAs; KR, R1, R2, R3, R4, C1, C2, C3, and C4.

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3.2.5 Validation of RAD51 knockdown in polyclonal cell populations Western blotting of polyclonal cell populations of MDA-MB-231-Cas9 cells stably transformed with RAD51 gRNAs showed knockdown of RAD51 protein expression. Cells transformed with gRNAs KR (+ssODN), R1, R2, R3 and R4 displayed RAD51 knockdown of ~70%, ~10%, ~60%, ~70% and ~90% respectively (Fig. 3.7A). For MDA-MB-436-Cas9 the polyclonal cell population transformed with gRNA R4 showed no detectable RAD51 expression and the polyclonal cell population transformed with gRNA KR+ssODN showed ~70% knockdown (Fig. 3.8A). Based on this result we decided to transform our other 5 TNBC-Cas9 cell lines with gRNA KR - ssODN repair template combination with the goal of achieving cell populations with both RAD51 knock out and K133R editing.

3.2.6 Validation of RAD51 knockout in monoclonal cell populations Since polyclonal cell populations transformed with gRNA KR + ssODN likely contained cells with a variety of mutations in RAD51 exon 5 we needed to isolate single cell clones to achieve complete RAD51 knockout and K133R editing. The first method we tried for isolating single cells was by serial dilution. This method was successful for MDA-MD-231 and MDA- MB-436 cell lines however the TNBC-Cas9 cell lines; HS578T, MDA-MB-468, MDA-MB453 and BT549 did not survive low density seeding. We next tested if supplementing the growth medium with 20% FBS and/or supernatant from the parental cell line grown at high density could improve cell survival, as cells deprived of signalling cues from other cells usually undergo cell death. Unfortunately, these attempts were also unsuccessful. Hence, we decided to move forward with only the MDA-MB-231 and MD-MBA-436 cell lines.

MDA-MB-231-Cas9-KR + ssODN and MDA-MB-436-Cas9-KR + ssODN single cells were expanded in culture media for approximately two weeks and then processed for western blotting. We identified three MDA-MB-231-Cas9 KR+ssODN monoclonal populations with no detectable expression of RAD51; clones 20, 23 and 24 (Fig 3.7C). For MDA-MB-436-Cas9 KR+ssODN we identified 13 clones with no detectable RAD51 expression; 1, 6, 7, 9, 12, 13, 30, 37, 38, 40, 41, 42 and 43 (Fig. 3.8A-B).

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Figure 3-7 Western blot validation of RAD51 expression in MDA-MB-231-Cas9 cells transformed with RAD51 gRNAs

(A) Western blot analysis of whole cell lysates extracted from polyclonal populations of MDA-MB-231-Cas9 cells transformed with empty vector gRNA (EV) and RAD51 gRNAs; KR + ssODN, R1, R2, R3 and R4. (B) - (C) Monoclonal populations of MDA-MB-231-Cas9 cells transformed with empty vector gRNA (EV) and RAD51 gRNA KR + ssODN. Clones identified by number. Bands shown represent expression of RAD51 with α tubulin serving as the loading control.

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Figure 3-8 Western blot validation of RAD51 expression in MDA-MB-436-Cas9 cells transformed with RAD51 gRNAs

Western blot analysis of whole cell lysates extracted from MDA-MB-436-Cas9 cells. (A) Lane 1; monoclonal population transformed with empty vector gRNA (EV), lane 2; polyclonal population transformed with gRNA R4, lane 3; polyclonal population transformed with gRNA KR + ssODN repair template, lanes 4-13; monoclonal populations transformed with gRNA KR + ssODN repair template, clones identified by number (B) Lane 1; monoclonal population transformed with empty vector gRNA (EV), lanes 2-13 monoclonal populations transformed with gRNA KR + ssODN repair template, clones identified by number. Bands shown represent expression of RAD51 with α tubulin serving as the loading control.

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3.2.7 Validation of CEBPβ knockdown in polyclonal cell populations Western blotting of polyclonal cell populations of MDA-MB-231-Cas9 cells stably transformed with CEBPβ gRNAs showed good knockdown of CEBPβ Lap and Lip with gRNAs C1 and C2 (Fig 3.9A). Since we had cells stably transfected with gRNA C2 currently growing in cell culture we decided to isolate monoclonal cell populations from MDA-MB-231- Cas9-C2 for further validation.

3.2.8 Validation of CEBPβ knockout in monoclonal cell populations Single cells of MDA-MB-23-Cas9-C2 were isolated by serial dilution and then expanded in culture media for approximately two weeks. Approximately 50 monoclonal populations were isolated and a selection of these were processed for western blotting. We identified 15 monoclonal populations with no detectable expression of CEBPβ Lap 1 or Lap 2, clones; 14,18 29, 21, 22, 23, 24, 26, 27, 28, 32, 33, 34, 41, and 46 (Fig 3.9B).

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Figure 3-9 Western blot validation of CEBPβ expression in MDA-MB-231-Cas9 cells transformed with CEBPβ gRNAs

(A) Western blot analysis of whole cell lysates extracted from polyclonal populations of MDA-MB-231-Cas9 cells transformed with empty vector gRNA (EV) and CEBPβ gRNAs; C1, C2, C3 and C4. Bands shown represent expression of CEBPβ Lap and CEBPβ Lip with α tubulin serving as the loading control. (B) Western blot analysis of whole cell lysates extracted from monoclonal populations of MDA-MB-231-Cas9 cells transformed with empty vector gRNA (EV) and CEBPβ gRNA C2. Monoclonal CEBPβ gRNA C2 populations are identified by number. Bands shown represent expression of CEBPβ Lap and CEBPβ Lip with HSP70 serving as the loading control.

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3.2.9 Optimisation PCR conditions for CRISPR gene editing validation In order to validate CRISPR-Cas9 gene editing of targeted regions with Sanger sequencing we first needed to optimise PCR conditions for primers. Several attempts to optimise conditions for the CEBPβ primers were unsuccessful, resulting in either no bands of the desired size or multiple unintended bands (Fig 3.10A-B). Hence validation for CEBPβ knockout was limited to western blotting of expressed protein. Optimal PCR conditions were established for RAD51 primers amplifying targeted regions in exons 2, 5 and 7 (Fig. 3.11A- B).

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Figure 3-10 PCR outcomes with CEBPβ primers.

PCR products of MDA-MB-231 (parental) DNA. Intended fragment length 618 base pairs. (A) Annealing temperature 55-57οC with indicated MgCl2 concentration (mM). (B) Annealing temperature 57-60οC with indicated MgCl2 concentration (mM).

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Figure 3-11 Optimisation of PCR conditions for RAD51 primers.

PCR products of MDA-MB-231 (parental) DNA with RAD51 primers. (A) Lane 1: exon 7 primers showing intended fragment size of ~284 base pairs, lane 2: exon 5 primers no band present, lane 3: exon 2 primers showing intended fragment size of ~275 base pairs. (B) Exon 5 primers; annealing temperature 56-60οC with indicated MgCl2 concentration (mM). Optimal conditions for PCR achieved at 59οC and 2 mM MgCl2 (lane 8). Intended band size ~305 base pairs.

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3.2.10 Validation of HR-directed modifications by Sanger sequencing Genomic DNA was isolated from MDA-MB-231-Cas9 KR+ssODN clones and polyclonal MDA-MB-231-Cas9 KR+ssODN identified by western blotting as expressing RAD51. The target region in exon 5 was amplified by PCR and subjected to Sanger sequencing. DNA sequences returned for each sample were aligned with the ssODN repair template DNA sequence to determine if the RAD51 K133R repair template had been incorporated (Fig 3.12A-C). Several of the samples exhibited mutations in RAD51 exon 5 (mismatches, insertions and deletions) however none had incorporated the K133R repair template.

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Figure 3-12 Sanger sequencing of RAD51 expressing cells lines transformed with gRNA KR+K133R repair template.

(A)-(B) Sequence alignment of RAD51 K133R ssODN repair template with matched region of MDA-MB-231- Cas9 KR clones. (C) Sequence alignment of RAD51 K133R ssODN repair template with matched region of polyclonal MDA-MB-436-Cas9 KR.

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3.2.11 Timed delivery of RAD51 R133K gRNA A major obstacle with CRISPR-Cas9 HR directed gene editing is the very low frequency of DSB repair by HR compared to NHEJ. NHEJ operates predominantly in G1, although it can occur throughout the cell cycle, while HR is restricted to late S-phase and G2 (Zhao et al. 2017). To improve the likelihood of HR repair and successful incorporation of the K133R repair template we decided to synchronize the cell cycle of MDA-MB-231- Cas9 cells and deliver the gRNA KR+ssODN while cells were in late S and G2 phase.

To determine the optimal timing for gRNA KR+ssODN delivery cells were treated with thymidine to induce arrest at the boundary of G1/S and harvested following release at 2 hourly time points for propidium iodide staining and flow cytometry cell cycle analysis (Fig. 3.13A). Cells were predominantly in late S-G2 phase at 6 to 8 hours following release. Hence, we chose this time period for lentiviral delivery of gRNA KR+ssODN to MDA-MB- 231-Cas9 cells. Following puromycin selection and recovery, single cells were isolated by serial dilution and expanded for 2 weeks in media. Only 6 out of approximately 30 isolated monoclonal cell populations survived. These 6 samples were probed for RAD51 by western blotting (Fig. 3.13B) and the two clones that showed strong RAD51 expression (31 and 33) underwent Sanger sequencing to determine if the K133R ssODN had been incorporated. Unfortunately, both samples were found to contain the wild-type RAD51 exon 5 sequence (Fig. 3.13C).

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Figure 3-13 Evaluation of timed delivery of gRNA KR+K133R repair template in MDA-MB-231-Cas9 cells.

(A) Analysis of the cell-cycle progression of MDA-MB-231 Cas9 cells released after thymidine block. Cells were fixed at the indicated timepoints, stained with propidium iodide and DNA content analysed by flow cytometry. (B) Western blot analysis of whole cell lysates extracted from monoclonal populations of MDA-MB- 231-Cas9 cells transformed with empty vector gRNA (EV) and RAD51 gRNAs KR + ssODN at 6-8 hours after release from thymidine block. Bands shown represent expression of RAD51 with α tubulin serving as the loading control. (C) Sequence alignment of RAD51 K133R ssODN repair template with matched region of MDA-MB-231-Cas9 KR clones; 31 and 33.

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3.2.12 Investigation of an alternative strategy to achieve RAD51 K133R mutation Due to the difficulty we had experienced with CRISPR HR mediated gene editing we decided to instead utilise our RAD51 knockout clones and transfect these with a RAD51 expression vector following site directed mutagenesis to introduce the K133R mutation. We planned to use the GFP-RAD51SM vector described by Forget et al. (2007). To this end we retrieved KR clones previously identified as having RAD51 knockout from -80oC storage (MDA-MB-231 KR clones; 20, 23 and 24, depicted in Fig. 3.14A), expanded these in culture media for approximately one week and repeated western blotting to confirm RAD51 knockout. The western blot showed that these KR clones were re-expressing RAD51, with clone KR 23 having the lowest level of expression (Fig. 3.14B). At this point we thought that our initial isolation of single cell clones may have contained another clonal population that expressed RAD51. Hence, we repeated serial dilutions on KR23 to re-isolate single cells and expanded these monoclonal populations in culture for approximately 2 weeks. During the same period we also retrieved clone KR 32 (previously identified as RAD51 knockout) from -80ºC storage and expanded these cells in culture. We then assessed our new KR 23 sub-clones and KR 32 for RAD51 expression. Western blotting identified that KR 23.2 and KR 32 had no detectable RAD51 expression (Fig. 3.14C).

To investigate if re-expression of RAD51 during culturing was also due to loss of gRNA expression we compared RAD51 expression in KR 23.2 and KR 32 cells grown in normal culture media for seven days to cells grown in media containing puromycin (gRNA selection antibiotic) for seven days, and cells grown in puromycin for 7 days followed by normal culture media for seven days. Western blotting identified that RAD51 was re-expressed under all conditions (Fig. 3.14D). Culturing cells in puromycin resulted in a lower level of RAD51 re- expression for KR 23.2 however it did not lessen RAD51 re-expression for KR 32. Based on these results we determined that stable CRISPR-Cas9 mediated RAD51 knockout was not tolerated in MDA-MB-231 cells and re-focused our research efforts on developing a small molecule inhibitor of RAD51 (described in chapter 4).

Chapter 3: Gene editing RAD51 with CRISPR-Cas9 for novel functional studies 111

Figure 3-14 RAD51 knockout could not be sutained in MDA-MB-231 cells.

(A) Western blot showing RAD51 knockout was initially achieved in MDA-MB-231 KR clones 20, 23 and 24. (B) RAD51 protein expression in KR clones 20, 23, and 24 increased following an additional ~7 days growth in culture medium. (C) Serial dilution clone KR23 identified subsequent RAD51 knockout clone KR 23.2. KR clone 32 with initial RAD51 knockout shown. (D) After growth in culture medium for 7-14 days RAD51 expression increased in clones KR23.2 and KR32. Addition of puromycin to culture medium decreased RAD51 expression for KR clone 23.2 but increased expression for clone 32.

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3.3 DISCUSSION

In this chapter we described the experiments undertaken using CRISPR-Cas9 technology with the aim of creating model TNBC cell lines with stable knockout of CEBPβ, stable knockout of RAD51 and stable expression of the RAD51 K133R mutation. Further, we planned to use these model cell lines to study the possible DNA repair independent, pro- metastatic role of RAD51, in concert with and independent of CEBPβ transcriptional regulation of metastatic genes. Our rationale for using CRISPR-Cas9 gene editing was based on the reported simplicity and specificity with which CRISPR-Cas9 can edit DNA and its widespread use and success in biological research to create model cell lines. While we had some initial success creating CEBPβ and RAD51 knockout cell lines we were unable to knock-in the specific RAD51 K133R mutation. Furthermore, we identified that RAD51 knockout was only transient in TNBC cell line MDA-MB-231. While the CRISPR-Cas9 system has demonstrated great promise for cancer research we encountered several obstacles that impede its efficacy which we will discuss here.

3.3.1 Difficulties establishing monoclonal cell populations Culturing of CRISPR-Cas9 edited cells results in a heterogeneous polyclonal population of cells. A critical step in the functional and genetic characterisation of mutations achieved with CRISPR-Cas9 is pure clonal isolation from a single cell (Ran et al. 2013). A major obstacle we experienced was that several of our TNBC cell lines (MDA-MB-453, MDA- MB-468, BT549 and HS578T) could not be cultured from a single cell or at densities low enough to enable manual picking of colonies, likely due the absence of essential growth factors and survival signals provided by neighbouring cells (Kim, Turnbull, and Guimond 2011). Supplementing culture medium with additional FBS and conditioned media from the parental cell lines was not successful. In hindsight, early efforts should be made to determine if a cell line can be successfully cultured from a single cell or low density seeding before proceeding with CRISPR-Cas9 gene editing. Improvements in cell survival following single cell isolation have been reported with culturing cells in semi-sold media, for example Matrigel, which also aids in manual colony picking (Chen and Pruett-Miller 2018) and supplementing culture medium with ROCK inhibitor, which prevents dissociation-induced apoptosis (anoikis) (Watanabe et al. 2007).

3.3.2 Low knock-in efficiency To achieve knock-in mutations and precise gene editing with CRISPR-Cas9 systems the induced DSB must be repaired by HR using an inserted DNA repair template. However,

Chapter 3: Gene editing RAD51 with CRISPR-Cas9 for novel functional studies 113 in mammalian cells DSBs occurring throughout the cell cycle are primarily repaired using the NHEJ pathway. The vast majority of studies using CRISPR-Cas9 gene editing have reported gene knockouts via indels resulting from NHEJ repair of Cas9 induced DSBs. However, successful knock-ins are observed at a significantly lower rate of 0.5-20% (Wang et al. 2015). To put this in perspective, at 0.5% HR efficiency one would need to successfully isolate, culture and characterise at least 200 pure clones to achieve one clone with the desired knock-in. The low frequency of HR combined with the challenge of isolating pure clones makes this a difficult and extremely laborious feat to achieve practically.

In an effort to improve knock-in efficiency with CRISPR-Cas9 several approaches have emerged, including; cell cycle synchronization and timed delivery of the gRNA and DNA repair template (Lin et al., 2014), suppression of key NHEJ molecules by gene silencing (Weber et al. 2015), the use of small molecule NHEJ inhibitors (Srivastava et al. 2012; Tomkinson, Howes, and Wiest 2013; Robert et al. 2015; Vartak and Raghavan 2015; Yu et al. 2015) and the use of small molecules to enhance HR (Song et al. 2016). In the present study we attempted to improve HR efficiency with cell synchronisation and timed delivery the gRNA and DNA repair template during late S-G2 phase. Unfortunately, our gRNA plasmid was designed for lentiviral delivery and the limited delivery timeframe (between 6-8 hours after release from blockade) significantly decreased the number of target cells transduced. The timed delivery approach is likely better suited to gRNA plasmids that are designed for direct delivery with nucleofection. However since DSB repair still predominantly occurs by NHEJ during G2 phase (~80%) (Beucher et al. 2009), success achieving knock- in will remain limited. With the use of DNA Ligase IV inhibitor; Scr7, HR efficiency with CRISPR-Cas9 has been reported to increase 2 to19-fold (Srivastava et al. 2012; Chu et al. 2015; Maruyama et al. 2015) and up to 5-fold with RAD51 enhancer, RS-1(Song et al. 2016). However, consideration should be given to the potential toxic effects of small molecule compounds on target cells and optimal concentrations and treatments timeframes determined for individual cell lines. In the context of RAD51 gene editing with CRISPR-Cas9 it is likely that inhibition of NHEJ combined with RAD51-K133R mutation is a potentially synthetic lethal combination.

3.3.3 Negative selection of gRNAs targeting essential genes To the best of our knowledge there are no published reports of successfully editing RAD51 using CRISPR-Cas9 systems. CRISPR-Cas9 studies involving RAD51 have been limited to its inclusion in pooled gRNA screening libraries in a variety of mammalian cancer cell lines (Blomen et al. 2015; Wang et al. 2014; Koike-Yusa et al. 2014). In pooled CRISPR

Chapter 3: Gene editing RAD51 with CRISPR-Cas9 for novel functional studies 114 screening experiments target cells are transduced with multiple gRNAs targeting thousands of genes to create a population of cells with diverse gene mutations (Shalem et al. 2014). Depletion or enrichment of particular gRNAs in a cell population enables identification of which genes are essential or non-essential, since cells are unable to proliferate if an essential gene is knocked out (Bertomeu et al. 2018). Prior to the recent development of pooled CRISPR screens, pooled library shRNA screens were the gold standard for identifying core fitness genes (Hart et al. 2014). Direct comparison of the two approaches has demonstrated that CRISPR screens are substantially more sensitive (Hart et al. 2014) and have identified many additional genes as essential in cancer cell lines, including RAD51 (Hart et al. 2014; Bertomeu et al. 2018; Blomen et al. 2015).

To date pooled CRISPR gRNA screens have identified RAD51 as a core fitness gene in 301 cancer cell lines (of 325 screened) across 13 types of cancer (Behan et al. 2019). Specifically Behan et al. (2019) identified RAD51 as a being a core fitness gene for TNBC cell line MDA-MB-231 which is consistent with our observations that RAD51 knockout could not be stably maintained under experimental culture conditions for this cell line. RAD51 is also identified as a core fitness gene for other TNBC cell lines included in our study; MDA- MB-453, MDA-MB-468, HS578T and BT549 (Behan et al. 2019), and on this basis these cell lines are not considered suitable for generating stable RAD51 knockout model cell lines. Since amino acid K133 is critical for proper RAD51 function during homologous recombination it is also very likely that the aforementioned TNBC cell lines would not be able to stably maintain the RAD51 K133R mutation. Interestingly Behan et al. (2019) reports that RAD51 is not a core fitness gene for TNBC cell line MDA-MB-436, which is likely due to compensation for its BRCA1 mutation and associated disrupted HR pathway. Hence, it may be possible to move forward with the MDA-MB-436 RAD51 knockout clones we identified in the present study. Despite our lack of success inserting the RAD51 K133R mutation using CRISPR-Cas9 it is at least theoretically possible this could be stably achieved in MDA-MB- 436 since the mutation does not affect RAD51-protein interactions and has little effect on binding affinity of RAD51 to ssDNA (Kim et al. 2012). This is an important distinction to make since RAD51 interacts directly with at least 22 other core essential proteins (STRINGdb; Szklarczyk et al., 2019), the overwhelming majority of which are required for DNA repair and replication protein-protein (Fig. 3.15)

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Figure 3-15 RAD51 protein-protein interactions with core essential proteins.

Shown are proteins encoded by essential genes that directly interact with RAD51 identified by STRINGdb analysis.

Chapter 3: Gene editing RAD51 with CRISPR-Cas9 for novel functional studies 116

3.3.4 Conclusions and future directions Despite the excitement surrounding CRISPR-Cas9 technology and its increasing application in cancer research, our study highlights that CRISPR is associated with challenges and limitations in its application to particular cell lines and genes. Our future research involving RAD51 gene manipulation will likely utilise transient and inducible expression constructs to generate the desired phenotype in TNBC cell lines and small molecule RAD51 inhibition. The CEBPβ knockout clones we have generated with CRISPR could be applied in this context. Given the fundamental role played by RAD51 in TNBC it represents a key potential target for drug development. Like many essential genes, RAD51 is highly expressed in multiple types of tumours whereas nonessential genes exhibit similar transcription activity in both cancer and normal cells (Chen et al. 2019). This distinction suggests that essential genes are more sensitive to tumorigenesis and may be superior targets for drug screening and development (Chen et al. 2019). Our future work will focus on the development and screening of small molecule inhibitors of RAD51 (Chapter 4) and their application in chemotherapy resistant TNBC (Chapter 5).

Chapter 3: Gene editing RAD51 with CRISPR-Cas9 for novel functional studies 117

Chapter 4: Identification of a novel small molecule inhibitor of RAD51

4.1 INTRODUCTION

Triple Negative Breast Cancer (TNBC) is an aggressive and heterogeneous subgroup of breast cancers that lack expression of hormone receptors or HER2 overexpression (Zaharia and Gómez 2013). Extensive research efforts have been made to identify therapeutic targets based on the molecular landscape of TNBC, however this has generated little clinical success (Collignon et al. 2016). Consequently treatment for TNBC patients is largely dependent on surgery, radiotherapy and conventional chemotherapy (Wahba and El-Hadaad 2015). The goal of radiotherapy and most chemotherapies is to cause DNA damage that is lethal to rapidly dividing cancer cells. Unfortunately the DNA damage caused by these treatments can be counteracted by cellular DNA repair activity (Helleday et al. 2008). The genomic instability of TNBC tumours is frequently associated with deregulated DNA repair activity and represents an important mechanism of resistance (Tubbs and Nussenzweig 2017; Wein and Loi 2017; Curtin 2012).

Homologous recombination (HR) is an evolutionarily conserved DNA repair pathway that repairs potentially lethal DSBs during S and G2 phases of the cell cycle using the undamaged sister chromatid as a template to ensure error-free repair (San Filippo, Sung, and Klein 2008). RAD51 recombinase is essential for HR (Tsuzuki et al. 1996) and provides protection against genotoxic stress by efficient repair and preventing degradation of nascent DNA strands during stalled replication (Mason et al. 2019). In normal, non-cancerous cells HR and RAD51 activity are tightly regulated (Nagathihalli and Nagaraju 2011). Upregulation of RAD51 is reported in several cancers, including TNBC (Wiegmans et al. 2014), glioblastoma (King et al. 2015), prostate cancer (Mitra et al. 2009), pancreatic cancer (Maacke, Jost, et al. 2000) soft tissue sarcoma (Hannay, Liu et al. 2007), non-small-cell lung cancer (Takenaka, Yoshino et al. 2007), chronic myeloid leukaemia and melanoma and (Raderschall, Stout et al. 2002). RAD51 overexpression is associated with hyperactive and aberrant HR that supports cancer progression (Nagathihalli and Nagaraju 2011). It is suggested that resistance to radiotherapy and chemotherapeutic agents is due to this hyperactive HR capacity in tumours that overexpress RAD51 (Schild and Wiese 2010). In contrast, HR deficient (HRD) tumours are significantly more sensitive to ionizing irradiation and DNA damaging chemotherapeutics (Helleday 2010). Hence, being able to disrupt

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 118

RAD51 recombinase activity may sensitise resistant tumours to DNA damaging treatments. On this basis RAD51 is increasingly recognised as a potential therapeutic target.

Several small molecule RAD51 inhibitors have been discovered by high-throughput screening of compound libraries, notably B02 (Huang and Mazin 2014; Huang et al. 2013; Huang et al. 2012), the RI series (Budke, Logan, et al. 2012; Budke, Kalin, et al. 2012; Lv et al. 2016) and the IBR2 series (Zhu et al. 2015; Zhu et al. 2013) (Fig. 4.1). Alternatively, a fragment-based screening approach at Cambridge identified another series of compounds (Scott et al. 2015; Scott et al. 2016) (Fig. 4.1). Mechanistically, B02 disrupts RAD51 binding to ssDNA, RI-2 interferes with RAD51 binding to dsDNA, and IBR2 and the Cambridge series inhibit RAD51-BRCA2 interaction. These compounds have cytotoxic activity at micromolar concentrations. Since the HR pathway is predominantly utilized by actively replicating cells (Helleday 2010), short-term disruption of HR via RAD51 inhibition is expected to have little impact on quiescent cells of normal tissue, whilst being detrimental to rapidly proliferating cancer cells.

The first of the small molecule RAD51 inhibitors to be well profiled was B02 (Huang et al. 2012). DNA binding assays revealed that B02 disrupted initial RAD51 binding to ssDNA, and later dsDNA binding to the RAD51-ssDNA filament (Huang et al. 2012). D-loop assays confirmed B02 specificity for human RAD51 over its bacterial homologue RecA and other human HR proteins (Huang et al. 2011). In vitro, B02 inhibited irradiation-induced RAD51 foci formation, HR repair of DSBs (Huang et al. 2012) and sensitized cells to a panel of chemotherapy drugs including cisplatin, mitomycin C, doxorubicin, etoposide, and topotecan (Huang et al. 2012; Huang and Mazin 2014). In vivo B02 significantly enhanced the therapeutic effect of cisplatin in a TNBC xenograft model (Huang and Mazin 2014).

The structure of B02 has three motifs, which could be manipulated and chemically modified to optimise efficacy of RAD51 binding. In this chapter we report structure-activity relationships for a library of quinazolinone derivative analogues of B02 based on manipulation of the three motifs. This medicinal chemistry elucidated an inhibitor selective for high RAD51 expressing TNBC cell lines. A novel RAD51 inhibitor (compound 17-Fig 4.3) displays up to ~8-fold enhanced inhibition of cell growth in a panel of TNBC cell lines compared to B02, and approximately 2.5-fold increased inhibition of irradiation-induced RAD51 foci formation. Additionally, compound 17 significantly enhances TNBC cell sensitivity to DNA damaging radiotherapy and chemotherapies, implying a potentially targeted therapy for TNBC.

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 119

Figure 4-1.Structurally different RAD51 inhibitors, including B02.

Components of B02 to be varied in this study are separately coloured.

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 120

4.2 RESULTS

4.2.1 In-silico docking study for RAD51 inhibitor optimisation. To optimize compound design we initially performed an in silico docking study of B02 using the crystal structure of the full-length RAD51 homolog from Pyrococcus furiosus (PDB code: 1PZN (Shin et al. 2003) (Fig 4.2A). B02 was docked into the model in several different putative binding sites and based on mapping of high energy electrostatic potential. These included the ATPase domain known to bind small fragments like tetrapeptide and bicyclic aromatics (Scott, Ehebauer, Pukala, Marsh, Blundell, Venkitaraman, Abell, and Hyvonen 2013) (Fig. 4.2A). One preferred conformation of B02 showed motif 2 (3-pyridyl) occupying the same cleft that accommodates aromatic groups, like the phenylalanine side chain of Phe-His-Thr-Ala (Fig. 4.2B). Motifs 1 and 3 instead spread-eagled across the shallow hydrophobic entrance to the cleft with the charged residue D187 nearby. The cleft was surrounded by hydrophobic residues (L104, M158, I160, A190, A192, L203, A207, L219). A second shallow indentation close to motif 3, accommodating the threonine side chain of the tetrapeptide in the crystal structure with a truncated RAD51 (Scott, Ehebauer, Pukala, Marsh, Blundell, Venkitaraman, Abell, and Hyvönen 2013; Scott, Ehebauer, Pukala, Marsh, Blundell, Venkitaraman, Abell, and Hyvonen 2013), is formed by hydrophobic residues (F166, P168, L171, V185, L186, V189). These features were used to design small molecules with high avidity.

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 121

Figure 4-2 Docking of B02 in the ATPase domain of a homology model of human RAD51.

(A) Representation of Pyrococcus furiosus RAD51 showing putative B02 binding sites. ATPase domain and N-terminal domain indicated. (B) Highlight showing B02 at the surface pocket of the RAD51 ATPase domain- BRCA2 BRC interface.

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4.2.2 Synthesis of B02 analogues With the aim of improving ligand interaction with RAD51 we conducted structure activity relationship (SAR) analysis using the quinazolinone scaffold of B02 as our base compound and modifying motifs 1 (R1), 2 (R2) and 3 (R3) (Fig. 4.3). The rationale behind SAR analysis is that the chemical formula and 3D structure of a compound determines it physical properties, biological activity and toxicological profile (Hughes, Rees et al. 2011). In collaboration with medicinal chemists (University of Queensland) we initially synthesized derivatives (1–27) containing modification at motif R1 (Fig. 4.3A). Preliminary data for MTS growth inhibition assays and immunofluorescent detection of RAD51 foci formation inhibition identified modification at motif 1 4-chlorobenzyl (compound 17) as showing the most promising biological activity (Fig. A1, Fig. A2 and Table A1). Keeping motif R1 as 4- chlorobenzyl we then synthesised compounds 28–39 by making modifications to motif R2 (Fig. 4.3B) and compounds 40–52 by modifying motif R3 (Fig. 4.3C).

Ligands were synthesized, as shown in Figure 4.4A–J, to allow for independent optimisation of the three motifs. Two general strategies were used to synthesize ligands both of which introduced motif R1 onto initial motif 3. The first strategy involved early incorporation of motif R2 and the second strategy involved synthesis of motif R3 and late incorporation of motif R2. In the first strategy motif R2 was synthesised by coupling ethyl anthranilate (Fig. 4.4A) with the corresponding acyl chloride, followed by ester hydrolysis (Fig. 4.4 A to B). Depending on the availability of the building blocks, the cinnamide analogues (Fig. 4.4B) were also constructed by Heck coupling of the corresponding aromatic bromide with acrylamide (Fig. 4.4 A to C to B). Motif R1 was then introduced as amine onto initial motif 3 via amide coupling (Fig. 4.4 D to E), followed by cyclisation under mild dehydration conditions with iodine and hexamethyldisilazine to give the desired quinazolinone products (Fig. 4.4F). In this way, one series of compounds incorporated alkyl and cycloalkyl substituents (Fig. 4.3A 1–8), and another series contained substituted aromatics with a variable spacer –(CH2)n– (n =0-2) (Fig. 4.3A 9–27). The latter series was designed to optimally target residues F195 and Y191 through pi-interactions. Various substituents, such as halogen, hydroxy, amino and its precursor nitro, carboxylate and acetamide were incorporated to improve properties or polar interactions.

The second strategy utilised a one-pot synthesis from anthranilic acid (Fig. 4.4G) to 2- methylquinazolinone (Fig. 4.4I) through the mixed anhydride 2-methyloxazinone (Fig. 4.4H) to prepare variations in motif 3 (R3) (Fig. 4.4 G to H to I). To probe the shallow hydrophobic cleft where threonine of Phe-His-Thr-Ala bound (Figure 4.2B), one amino group was

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 123 introduced at position 6 of the quinazolinone core (compound 44), which was further derivatized by either acylation (compounds 45–51) or guanidinylation (compound 52). Motif R1 was then introduced onto initial motif 3 (Fig. 4.4 H to I) and motif R2 was assembled using either a similar linear process as the first synthetic strategy (Fig. 4.4 A to E to F), or more efficiently from common intermediate 2-methylquinazolinone (Fig. 4.4I) through one- step divergent enamine-aldehyde coupling (Fig. 4.4 I to J to F).

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 124

Figure 4-3. Structure of quinazolinone derivatives.

(A) Compounds 1–27 (B02 = 9) derived from modifications to motif R1. (B) Compounds 28–39 have R1 = 4- chlorobenzyl and modifications to motif R2. (C) Compounds 40–52 have R1 = 4-chlorobenzyl and modifications to motif R3.

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 125

Figure 4-4 Synthesis of compound library.

(A–F) Representative procedures of synthetic strategy 1 with early incorporation of motif R2. A = ethyl anthranilate, B = cinnamide analogues, C = acrylamide D = common intermediate acid, F = quinazolinone products (G̶–F) Representative procedures of synthetic strategy 2 with modification of motif R3 and late incorporation of motif R2. G = anthranilic acid, H = anhydride 2-methyloxazinone, I = 2-methylquinazolinone, J = enamine-aldehyde.

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 126

The physico-chemical properties of our compound library are summarised in Table 4.1 and satisfy Lipinski’s’ parameters for predicting ‘drug-like’ physico-chemical properties necessary for a compound to be membrane permeable and easily absorbed by the body (Lipinski, Lombardo et al. 1997). After analysing more than 2000 drugs and candidate drugs Lipinski and his colleagues concluded that the following properties were predictive of orally active drugs: a molecular weight less than 500 Daltons, no more than 5 hydrogen bond donors, no more than 10 hydrogen bond acceptors and an octanol-water partition coefficient log P (lipophilicity) not greater than 5 (Lipinski, Lombardo et al. 1997). Extensions to Lipinski’s’ parameters includes; no more than 10 rotatable bonds and a polar surface area less than 140 Å (Veber, Johnson et al. 2002).

Table 4-1 Phyisico-chemical properties of the inhibitors.

Property Value

Molecular weight (Da) 350–410 (<500)

Hydrogen bond donors 0–2 (<5)

Hydrogen bond acceptors 4–7 (<10)

Lipophilicity, (logP) 3.0–5.5 (<5)

Number of rotatable bonds 4–5 (<10)

Polar surface area (Å) 45–97 (<140)

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 127

4.2.3 Determination of compounds that inhibit growth of Triple Negative Breast Cancer The genomic instability of TNBC predisposes tumour cells to high levels of replication stress even in the absence of chemotherapy and radiation induced DNA damage (Zhang, Dai, et al. 2016). In addition to mediating repair of direct DSBs via HR, RAD51 plays a pivotal role in overcoming replication stress by protecting stalled replication forks against degradation (Mason et al. 2019; Bhat and Cortez 2018), enabling break induced replication and facilitating fork reversal and restart (Zellweger et al. 2015). On this basis we used compound inhibition of proliferation in TNBC MDA-MB-231 cells, as determined by MTT assay, as a surrogate measurement for RAD51 inhibition. To evaluate compound-induced sensitisation to DNA damage we compared survival of irradiated untreated cells to irradiated cells treated with 10 µM of each compound. The dosage of 10 µM was chosen based on results of preliminary experiments (Fig. A-2 and Table A-1) which determined the IC50 of B02 (after 5 days incubation in combination with 2.5 µM PARP inhibitor ABT-888) to be ~10 µM.

To determine if the compounds sensitised TNBC cells to DNA damaging irradiation we compared mean cell survival following 120 hours incubation with each compound (plus irradiation) to mean cell survival following incubation with the vehicle control (plus irradiation). The data obtained from these experiments was analysed using a two way ANOVA with Sidak’s post hoc comparison. For B02 and compounds with modifications to motif R1 (1– 27) mean cell survival was significantly decreased compared to the vehicle control with the following compounds: B02 (p<0.05), 5 (p<0.01), 16 (p<0.01), 17 (p<0.0001), 18 (p<0.01), 19 (p<0.0001), 20 (p<0.0001) and 23 (p<0.01) (Fig. 4.5A). For compounds with the same R1 motif as compound 17 (4-chlorobenzyl) and modifications to motif R2 (28–39) mean cell survival was significantly decreased compared to the vehicle control with the following compounds: 28 (p<0.001) , 29 (p<0.05), 31 (p<0.0001), 32 (p<0.0001), 34 (p<0.01) and 39 (p<0.001) (Fig. 4.5B). For compounds with the same R1 motif as compound 17 (4- chlorobenzyl) and modifications to motif R3 (40–52) mean cell survival was significantly decreased compared to the vehicle control with the following compounds: 40 (p<0.05), 41 (p<0.01), 42, 43, 44 (p<0.0001), 46 (p<0.0001), 47 (p<0.05), 48 (p<0.001) and 51 (p<0.0001) (Fig. 4.5C)

To take into account the toxicity of each compound in the absence of irradiation we compared % survival for each compound (plus and minus irradiation) by two way ANOVA with Sidak’s post hoc comparison (e.g., % survival compound 17 versus % survival

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 128 compound 17 + irradiation) (Table 4.2). With the exception of compounds 43, 45, and 51 all compounds showed significantly greater inhibition of cell survival when combined with irradiation than used alone (p<0.0001). In combination with irradiation cell survival decreased most with compound 17 (6.7-fold) compared to vehicle control (2.0-fold), B02 (2.5-fold), 5 (3.2-fold), 16 (2.7-fold), 18 (3.6-fold), 19 (3.2-fold), 20 (3.7-fold), 23 (3.0-fold), 28 (2.2-fold), 29 (2.8-fold), 31 (3.2-fold), 32 (4.2-fold), 34 (3.4-fold), 39 (3.1-fold), 40 (2.2- fold), 41 (2.8-fold), 42 (4.3-fold), 44 (2.8-fold), 46 (2.2-fold), 47 (2.6-fold), and 48 (2.2-fold) (Table 4.2).

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 129

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Figure 4-5. MTT assessment of proliferation inhibition and sensitisation to irradiation.

Viability of MDA-MB-231 cells was determined by MTT assay following 120 hours treatment with 10 µM of each compound +/-6 Gy gamma irradiation (IRR) (black = non-irradiated, grey = irradiated). (A) % cell survival (normalized to the non-irradiated vehicle control) following treatment with compounds 1–27 (modifications at the R1 motif). (B) % cell survival following treatment with compounds 28–39 (R1=4-chlorobenzyl and modifications at motif R2. (C) % cell survival following treatment with compounds 40–52 (R1=4-chlorobenzyl and modifications at motif R3). Results represent the mean ± SEM for 3 independent experiments. Comparison of % mean survival vehicle treated + irradiation versus % mean survival compound treated + irradiation analysed by two-way ANOVA with Sidak’s post hoc comparison. *p<0.05, **p<0.01, ***p<0.001 ****p<0.0001.

Chapter 4: Identification of a novel small molecule inhibitor of RAD51 130

Table 4-2 TNBC cell survival following treatment with compounds (with and without irradiation).

% Survival % Survival Mean survival Compound (10 µM compound) (10 µM compound + IRR) -IRR vs + IRR Fold change survival

Mean SEM Mean SEM Significance (-IRR/+IRR) Vehicle 100.0 1.6 50.7 1.4 **** 2.0 B02 80.8 3.3 32.3 2.8 **** 2.5 1 87.9 6.8 39.9 2.3 **** 2.2 2 98.6 5.2 35.8 1.4 **** 2.8 3 101.7 7.9 38.8 2.2 **** 2.6 4 97.8 6.9 35.9 0.6 **** 2.7 5 90.2 6.9 28.6 0.9 **** 3.2 6 83.5 3.7 40.3 2.5 **** 2.1 8 99.3 7.2 39.2 1.0 **** 2.5 10 102.0 3.9 42.4 0.7 **** 2.4 11 104.0 1.5 35.0 1.6 **** 3.0 12 91.5 7.1 37.7 1.5 **** 2.4 13 88.9 4.3 39.3 2.0 **** 2.3 14 77.3 4.3 36.0 2.9 **** 2.1 16 80.9 4.9 30.4 1.2 **** 2.7 17 32.0 2.9 5.0 2.4 **** 6.4 18 99.3 2.8 27.7 3.7 **** 3.6 19 75.0 3.6 23.7 2.2 **** 3.2 20 79.7 4.1 21.7 3.1 **** 3.7 21 93.5 4.7 35.2 4.5 **** 2.7 22 93.6 3.6 43.8 5.2 **** 2.1 23 90.9 2.1 30.5 2.6 **** 3.0 24 84.7 1.4 39.7 3.3 **** 2.1 25 95.5 2.2 43.4 1.1 **** 2.2 26 95.4 6.0 43.6 4.5 **** 2.2 27 96.9 0.1 39.1 3.3 **** 2.5 28 63.6 2.6 28.5 4.0 **** 2.2 29 93.4 2.7 33.3 6.9 **** 2.8 30 119.5 7.1 37.1 2.8 **** 3.2 31 107.1 2.5 25.8 1.5 **** 4.2 32 83.3 3.2 26.0 2.1 **** 3.2 33 97.2 3.6 42.4 3.5 **** 2.3 34 108.6 3.7 31.6 3.1 **** 3.4 35 92.9 1.3 36.6 2.2 **** 2.5 36 102.6 3.2 45.0 4.2 **** 2.3 37 88.5 5.1 41.8 5.7 **** 2.1 38 95.7 1.8 43.3 2.5 **** 2.2 39 93.9 0.2 30.1 1.1 **** 3.1 40 84.8 1.1 38.1 1.1 **** 2.2 41 96.1 2.2 34.0 3.0 **** 2.8

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42 99.6 3.0 23.2 8.1 **** 4.3 43 1.8 1.5 1.0 0.9 ns 1.8 44 66.2 0.6 23.7 2.6 **** 2.8 45 42.6 3.5 40.6 3.4 ns 1.0 46 46.2 6.6 20.9 2.5 **** 2.2 47 96.5 0.0 37.3 0.9 **** 2.6 48 70.8 3.8 32.2 1.9 **** 2.2 50 73.5 0.2 42.6 2.5 **** 1.7 51 4.7 2.0 2.8 1.2 ns 1.7 52 100.1 2.3 56.5 2.8 **** 1.8

Results represent the mean (normalised to vehicle control) ± SEM for 3 independent experiments. Statistical analysis by two-way ANOVA with Sidak’s post hoc comparison. ****p<0.0001, ns = not significant.

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4.2.4 Analysis of small molecule binding to RAD51 protein To evaluate compound binding interaction with RAD51 we performed surface plasmon resonance (SPR) analysis. An example setup for an SPR experiment is depicted in Figure 4.6A. hsRAD51 was bound to the sensor chip surface by amine coupling (shown in Fig. 4.6B) and compounds were sequentially passed over the RAD51 conjugated surface and a blank control surface. The compound-RAD51 interactions were plotted over time generating sensorgrams and binding response was measured in response units (RU) when all RAD51 binding sites were saturated by compound. Based on our initial in silico docking study we determined that the ideal compound-RAD51 interaction would be represented by rapid (high affinity) binding at one site on the RAD51 protein (thought to be at the ATPase domain). For small molecules, this ideal type of binding interaction generates a square pulse shaped sensorgram (Fig. 4.6C, sensorgram score = 1-2) with an RU value less than the theoretical maximum (Rmax) for one-to-one binding stoichiometry. An additional requirement for good binding response was that the compound achieves an RU approximately equivalent to B02 or higher. Rmax was calculated using the following formula:

Rmax = analyte MW x immobilised amount x stoichiometric ratio ligand MW

Where analyte MW = compound molecular weight (277.32−545.18 Da), ligand MW = hsRAD51 molecular weight (36,971 Da), immobilised amount = amount of RAD51 bound to sensor chip (6632.5−19090.9 RU), stoichiometric ratio = 1:1.

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Figure 4-6. Small molecule screening using surface plasmon resonance.

(A) The SPR biosensor detects changes in refractive index caused by analyte-ligand binding interactions. Molecules binding to the sensor surface generates a response proportional to the mass bound shifting the angle from A to B. The sensorgram is a plot of resonance angle versus time for association/dissociation. (B) Sensorgram generated from the immobilisation of ~15000 RU of RAD51 to CM5 sensor chip via amine coupling at pH 4.5. (C) Representative sensorgrams displaying scores from 1 to 4. Scores of 1-2 represent small molecules that associate quickly with RAD51 suggestive of a single binding site. Scores of 3-4 indicate slower association of the small molecule with RAD51 and increasing complexity of binding.

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To assess non-specific binding activity, each compound (50 µM) was initially injected across the blank control surface and RU was measured (Fig. 4.7A). This identified compound 51 as having strong non-specific binding activity; hence it was not subjected to further evaluation. Screening at 50 µM identified 7 compounds with good binding response profiles: 6, 17, 34, 35, 38, 50 and 52 (Fig. 4.7B). Increasing the screening concentration to 100 µM also identified compounds 6, 17, 34, 35, 38 as hits (Fig. 4.7C). At 100 µM multiple additional compounds were identified as positive hits (18, 19, 22, 24, 25, 26, 30, 42, 44, 45 and 47), however these responses were disproportionately high compared to screening at 50 µM, which is indicative of non-stoichiometric binding and/or compound aggregation. Aggregation with increased compound concentration was confirmed by measuring RU of compound serial dilutions (400-3.12 µM) (sensorgrams for compound 38 shown in Fig. 4.7D). Hence the screening result at 50 µM was less likely to generate false-positive hits and better represents compound interaction with RAD51.

An initial modification at motif 1 (1–17) resulted in promising compounds, with both saturated cyclohexylmethyl (6) and 4-chlorobenzyl (17) analogues displaying fast 1:1 binding with RAD51. One methylene spacer shorter (5 versus 6) or longer (10 versus B02) markedly reduced binding affinity. Restricting rotation (indane 11) or introducing potential charged isosteres, such as morpholine (7–8) or pyridine to replace benzene (12–14), all reduced affinity. Smaller alkanes (1–4) also displayed reduced affinity. Varying spacer length in compound 17, with one methylene unit shorter (15) or longer (16) resulted in slow and complex binding to RAD51 and indicated optimal positioning of the aromatic ring in 17. Of the substituted benzyl series, 18 and 19 (fluoro) had reduced RAD51 binding affinity and the response for 20 exceeded Rmax. Compounds 21-22 (nitro) had reduced affinity and p- hydroxy (23) showed complex binding with RAD51 and exceeded Rmax. A polar substrate, such as p-acetamidomethyl (24) and carboxylic acid (25–26), were detrimental, while 3,4- dichloro (27) showed improved affinity (based on 100 µM screening). This demonstrated that a hydrophobic interaction was important at this site.

Keeping motif 1 as 4-chlorobenzyl, any modifications at motif 2 apart from 3-pyridyl were detrimental, including its regioisomer 4-pyridyl (36), mono-amino substituted 3-pyridyl (37–39), and a series of mono-substituted (hydoxy, nitro or amino) phenyl (28–33). This suggested that there were limits to both the substituent size and the polar interaction, with only the 3-pyridyl moiety being effective at this site. In motif 3, incorporating an extended pi- system (40) or a nitrogen isostere (41–43) were detrimental.

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Figure 4-7. Favourable 1:1 binding interactions with RAD51 identified by SPR analysis.

(A) Assessment of compound binding (measured in RU) to blank control surface of the CM5 chip. (B) Screening of compound binding to hsRAD51 at 50 µM. (C) Screening of compound binding to hsRAD51 at 100 µM. Response (RU) is adjusted for compound molecular weight and normalized to B02 (B02 = 100). Positive hits are indicated with red dots and represent RU ≥ 90% B02 < Rmax (1:1) accompanied by sensorgram score < 4. (D) Sensorgrams generated from serial dilutions of compound 38 with calculated theoretical Rmax and aggregation indicated.

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4.2.5 Functional characterisation of our lead compound After a DSB is formed RAD51 must be assembled onto the RPA coated and resected ssDNA to initiate repair by HR. A marker of this critical step is the visualization of nuclear RAD51 foci with immunofluorescent staining. A selection of compounds were assessed for their ability to inhibit nuclear RAD51 foci formation in MDA-MB-231 cells following irradiation induced DNA DSBs (Fig. 4.8A). Compounds 6, 17, 22, 34, 35, 38 and 52 were chosen based on their promising SPR result and compounds 10 and 47 were included to represent poor compound-RAD51 interaction. Compounds 6 and 17 significantly inhibited RAD51 foci formation compared to the vehicle control, p<0.01 and p<0.001 respectively. Compound 17 also significantly inhibited RAD51 foci formation compared to B02 (p<0.05). Compounds 22, 34, 35, 38 and 52 which were identified as positive hits via SPR did not inhibit RAD51 foci formation.

We focused our next experiments on compound 17 since it had now given favourable results for 3 screening experiments. The inhibitory effect of compound 17 was dose dependent with reductions in RAD51 foci formation of 67.1%, 34.5%, 13.5%, and 7.2% at 10, 5, 2.5 and 1.25 µM respectively compared to the vehicle control (Fig. 4.9A-B).

A reduction in RAD51 foci formation could be caused by reduced levels of cellular RAD51 protein or if progression to S/G2 of the cell cycle (where HR occurs) was prevented. Western blotting of MDA-MB-231 cell lysates that had been incubated with 10 µM B02 or compound 17 for 48 hours confirmed that neither compound depleted cellular RAD51 at this time point (Fig. 4.8B). Flow cytometry cell cycle analysis using propidium iodide DNA staining confirmed that 48 hours incubation with compound 17 did not prevent progression of cells into S/G2 (Fig. 4.8C).

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Figure 4-8. Compound 17 inhibits irradiation induced RAD51 foci.

(A) Cells were incubated with 10 µM of compound for 2 hours, irradiated with 6 Gy gamma irradiation and harvested 6 hrs post irradiation. DAPI stained cells and RAD51 and gamma-H2AX foci were quantified following immunofluorescent staining using the GE InCell Investigator software. The ratio of RAD51 foci /gamma-H2AX foci for each compound was normalized to the vehicle control with RAD51 siRNA treated cells serving as a negative control. Results represent the mean ± SEM for 3 independent experiments. Statistical analysis by one-way ANOVA with Dunnett’s post hoc analysis. **p<0.01, ***p<0.001. (B) Western blotting of MDA-MB-231 cell extracts following incubation with 10 µM of B02 or compound 17 for 48 hours shows no reduction in RAD51 protein level. HSP70 used as a loading control. (C) Flow cytometry analysis of propidium iodide stained MDA-MB-231 cells following 48 hrs incubation with 10 µM compound 17 shows that progression to G2 was not disrupted by compound 17.

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Figure 4-9. Compound 17 inhibits irradiation induced RAD51 foci in a dose-dependent manner.

(A) Quantification of RAD51 and gamma-H2AX foci with InCell Investigator software shows that RAD51 foci inhibition increases with increasing concentrations of compound17. Results represent the mean ± SEM for 3 independent experiments. (B) Representative images of DAPI, gamma-H2AX and RAD51 stained cells at 40X magnification following treatment with 1.25, 2.5, 5 and 10 µM compound 17.

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4.2.6 Compound 17 inhibits RAD51 binding to ssDNA We next assessed the effect of B02 and compound 17 on RAD51-ssDNA binding by electrophoretic mobility-shift assay using circular phi-X174 ssDNA as substrate. In the absence of compound we observed increased RAD51-ssDNA complex formation (and reduced free ssDNA) proportional to RAD51 concentration (Fig. 4.10A). In the presence of B02 and compound 17 RAD51-ssDNA complex formation was reduced and free ssDNA increased (Fig 4.10B-D). Inclusion of 50 µM and 100 µM compound 17 reduced RAD51- ssDNA complex formation by 2.6-fold and 3-fold respectively. While both 50 µM and 100 µM B02 decreased RAD51-ssDNA complex formation by approximately 1.5-fold. The result for 100 µM B02 likely represents a loading error or sample retention in the well. This preliminary electrophoretic mobility-shift assay result is consistent with our immunofluorescent imaging results since RAD51 binding to ssDNA is a necessary precursor step for RAD51 foci formation at DSBs.

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Figure 4-10 Compound 17 inhibits RAD51 binding to ssDNA.

Electrophoretic mobility shift assay for the binding of phi-fX174 circular ssDNA to recombinant hsRAD51 protein in the presence of ATP. (A) 40 µM ssDNA was incubated with 0.25 - 2 µM RAD51 for 15 minutes at 37oC. The samples were analysed by 0.8% agarose gel electrophoresis in TAE buffer and bands were visualized by Sybr Safe staining. Lane 1 indicates a negative control without RAD51. The size of RAD51- ssDNA complexes decreases from top to bottom as indicated. (B) 40 µM ssDNA binding to 2 µM RAD51. Lanes 3 and 4 indicate experiments in the presence of 50 µM and 100 µM B02 respectively. Lanes 5 and 6 indicate experiments in the presence of 50 µM and 100 µM compound 17 respectively. (C) Quantification of RAD51-ssDNA complexes (inside blue box) by densitometry normalised to vehicle plus RAD51 (lane 2). (D) Quantification of free ssDNA by densitometry normalised to vehicle plus RAD51 (lane 2). One experiment only conducted under these conditions.

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4.2.7 Compound 17 selectively inhibits repair of DSBs by HR To demonstrate that compound 17 selectively inhibits RAD51 mediated HR repair we measured DSB repair events in MDA-MB-231 cells transfected with reporter plasmids for HR and NHEJ, representing the two major DSB repair pathways. We assessed HR events using cells stably transfected with the DR-GFP construct which contains two non-functional copies of the GFP gene, one of which is interrupted by an I-Scel endonuclease site (Fig. 4.11A). Transient transfection with I-SceI can induce a DSB that when repaired by HR generates a functional GFP gene and subsequent fluorescent green cell. To assess NHEJ events a linearized pEGFP-N3 construct was transfected into MDA-MB-231 cells. The linearized plasmid contains a DSB between the promoter and GFP gene, preventing GFP expression unless the DNA ends are ligated by NHEJ repair (4.11D).

We found that cells incubated compound 17 had a 6.75-fold reduction in HR frequency (p<0.001) (Fig. 4.11B-C) and a 1.41-fold increase in NHEJ frequency (p<0.01) (Fig. 4.11E- F). This result indicates that compound 17 selectively inhibits RAD51 mediated repair by HR, and that cells attempt to compensate for this by upregulating DSB repair by NHEJ.

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Figure 4-11 Compound 17 selectively inhibits repair of DSBs by HR.

(A) Schematic diagram of the DR-GFP reporter used to measure DSB-induced HR. (B) Fold change in HR frequency for MDA-MB-231-DR-GFP cells after 72 hours incubation with 10 µM 17 compared to vehicle. (C) GFP events representing HR repair were detected by flow cytometry in samples of 30, 000 cells. Transfection efficiency was estimated by transfection with circularised pEGFP.N3. Cells untransformed by I-SceI were used as a negative control (mock). (D) Schematic diagram of the linearized pEGFP-N3 reporter used to measure DSB repair by NHEJ. (E) Fold change in NHEJ frequency for MDA-MB-231 cells transfected with linearized pEGFP.N3 after 72 hours incubation with 10 µM 17 compared to vehicle. (F) GFP events representing NHEJ repair were detected by flow cytometry for samples of 30, 000 cells. Transfection efficiency was estimated by transfection with circularised pEGFP.N3. Cells untransformed by linearized pEGFP were used as a negative control (mock). Results represent the mean ± SEM for 3 biological replicates. Statistical analysis by student’s t-test. **p<0.01, ****p<0.0001.

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4.2.8 Compound 17 enhances the anti-proliferative effect of irradiation induced DNA damage in a panel of TNBC cell lines Radiation therapy is commonly used in the neoadjuvant and adjuvant treatment settings of TNBC with the goal of shrinking tumours, preventing further tumour growth and killing cancer cells. Ionising radiation causes multiple types of DNA lesions, with DSBs being the most lethal, and consequently has an anti-proliferative effect on cells in culture (Goldstein and Kastan 2015). We sought to determine if compound 17 (compared to B02) could enhance the anti-proliferative effect of irradiation in TNBC cell line MDA-MB-231. Based on our findings that compound 17 significantly decreased irradiation induced RAD51 foci and DSB repair by HR in MBA-MD-231 cells we hypothesised that compound 17 would enhance the anti-proliferative effect of irradiation. We found that compound 17 significantly reduced proliferation of irradiated cells by 1.6-fold, 2.4-fold, and 14-fold at concentrations of 5 µM, 10 µM, and 20 µM respectively compared to the vehicle control (p<0.0001) (Fig. 4.12A-B). B02 sensitised cells to irradiation compared to the vehicle control at concentrations of 10 µM (p<0.001) and 20 µM (p<0.0001) but not 5 µM. (Fig. 4.12C-B). The inhibitory effect of 17 on cell proliferation was significantly greater than B02 at all concentrations tested (p<0.0001) (Fig. 4.12E-F). At 20 µM (in combination with irradiation) cells reached maximum confluence at 72 hours with B02 (11.2%) and at 52 hours with compound 17 (2.2%). Between the timepoints 72 to 120 hours cell confluence decreased by ~1.6% with both compounds. This result suggests that compound 17 is faster acting than B02 and this may confer a treatment advantage with very fast growing TNBC cell lines and tumours. The dose dependent effect of compound 17 on cellular proliferation following irradiation is consistent with our previous finding that compound 17 inhibits irradiation induced RAD51 foci formation in a dose dependent manner.

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Figure 4-12. Effect of compound 17 on TNBC cell proliferation in combination with irradiation.

MDA-MB-231 cells were treated with 5, 10 and 20 µM of compound 17 or B02 +/- 6 Gy gamma irradiation (IRR) and proliferation was measured for 120 hours using the IncuCyte (Essen Bioscience) live-imaging system. Proliferation was measured as % confluence and normalised to the non-irradiated vehicle control. Proliferation was quantified by measuring the Area Under the Curve (AUC) for each condition and normalised to the non-irradiated vehicle condition. (A) Graph shows proliferation for cells incubated with compound 17 and vehicle. (B) Quantification of compound 17 treated cells compared to vehicle control (C) Graph shows proliferation for cells incubated with B02 and vehicle. (D) Quantification of B02 treated cells compared to vehicle control. (E) Graph shows proliferation for irradiated cells treated with compound 17 and B02. (F) Quantification of irradiated compound 17 treated cells compared to irradiated B02 treated cells. Results represent the mean ± SEM for 3 independent experiments. Statistical analysis by two-way ANOVA with Tukey’s post hoc analysis, ns = non-significant, ***p<0.001, ****p<0.0001.

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4.2.9 Sensitivity to compound 17 correlates with RAD51 protein expression level in a panel of TNBC cell lines We next compared compound 17 with B02 for growth inhibition in a panel of TNBC cell lines with varying levels of RAD51 protein expression; MDA-MB-231, MDA-MB-436, MDA- MB-468, BT549 and HS578T. We found that compound 17 had a significantly greater inhibitory effect on cell survival in all 5 TNBC cell lines compared to B02 (IC50 ≤ 5.5 µM vs.

IC50 ≤ 44.8 µM). IC50 concentrations are summarised in Table 4.2.

We hypothesised that if compound 17 was exerting its inhibitory effect via RAD51 then cell lines with higher levels of RAD51 protein expression would be more sensitive than those with lower expression. Western blotting identified MDA-MB-231 cells with the highest level of RAD51 and SUM159T cells with the lowest level of RAD51 (Fig. 4.13A) and this result corresponded with the highest and lowest IC50 concentrations for both B02 and compound

17, however a significant correlation was not evident with IC50 concentrations (Table 4.2).

To further investigate the relationship between RAD51 expression and compound sensitivity we measured growth of each cell line in the presence of 3 µM B02 or compound

17. We selected a concentration of 3 µM because this was approximately the lowest IC50 concentration for compound 17 in the cell lines. Consistent with our IC50 results we found that incubation with 3 µM compound 17 resulted in less cell proliferation in all TNBC cell lines compared to B02 (Fig. 4.13B and Fig. 4.14). A significant negative correlation between RAD51 protein expression level and cell growth was observed for both compounds, with a stronger correlation achieved with 3 µM compound 17 (r = 0.94, p<0.01) than 3 µM B02 (r = 0.84, p<0.05) (Fig. 4.13C). This result supports our hypothesis that cells with higher levels of RAD51 expression are more sensitive to compound 17 than cells with lower RAD51 expression. However, the differing sensitivity of cell lines to RAD51 inhibition is also likely influenced by specific mutations contained by each cell line and compensatory activity of alternate DNA repair pathways in response to RAD51 inhibition.

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Table 4-3 Comparison of IC50 values for B02 and compound 17 in TNBC cell lines measured by MTS cell viability assay

Cell line B02 17

IC50 µM IC50 µM

BT549 c 19.7 ± 0.8 4.6 ± 0.3****

SUM159Te 44.8 ± 9.9 5.5 ± 0.9*

MDA-MB-468 a 7.5 ± 0.5 4.1 ± 0.2***

HS578Tb 9.0 ± 0.7 4.5 ± 0.4**

MDA-MB-231 a 5.0 ± 0.4 3.2 ± 0.2*

MDA-MB-436 a 6.3 ± 0.3 3.8 ± 0.1**

IC50 concentrations determined from dose-response curves following 5 days incubation with B02 or compound 17 (0.2-20 µM). Results represent the mean ± SEM for 3 independent experiments. Statistical significance of B02 IC50 compared to compound 17 IC50 determined by Student’s t-test. *p<0.05, **p<0.01, ***p<0.001. aAdenocarcinoma, bCarcinoma, cDuctal carcinoma, dInfiltrating ductal carcinoma.

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Figure 4-13. Sensitivity to compound 17 correlates with RAD51 protein expression in TNBC cell lines.

(A) Western blot analysis of RAD51 expression in whole cell extracts from TNBC cell lines used in proliferation assay. Semi-quantification of RAD51 expression (normalised to BT549 and α tubulin) is depicted under each band. (B) The indicated cell lines were incubated with 3 µM B02, 3 µM compound 17 or vehicle and cell proliferation (confluence) was measured over 120 hours using the IncuCyte (Essen Bioscience) live-imaging system. Bar graph shows quantification of proliferation (confluence AUC) normalised to the vehicle control for each cell line and indicated treatment. (C) Dot plots representing the correlation between relative RAD51 protein expression and relative confluence of TNBC cell lines with 3 µM B02 and 3 µM compound 17. Correlation coefficients indicated. Results represent the mean ± SEM for 3 biological replicates. *p<0.05, **p<0.01.

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Figure 4-14. Effect of RAD51 inhibition on proliferation of TNBC cell lines.

Representative images of indicated cell lines following 120 hours incubation with vehicle (DMSO), 3 µM B02 or 3 µM compound 17.

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4.2.10 Compound 17 increases TNBC sensitivity to chemotherapy and PARP inhibition We next examined whether compound 17 could enhance sensitivity of MDA-MB-231 cells to anticancer drugs; doxorubicin, cisplatin and veliparib (inducers of DNA damage) and docetaxel (microtubule stabiliser). DSBs caused by doxorubicin can be repaired by NHEJ and HR, while cisplatin induced DNA interstrand crosslinks (ICLs) rely predominantly on repair by RAD51 mediated HR. Veliparib inhibits PARP1 (an enzyme involved in repairing ssDNA breaks) and generates DSBs during replication that are reliant on HR for repair. Based on the mechanism of action of these drugs we hypothesised that compound 17 would have a greater sensitising effect when combined with DSB and ICL inducing drugs (doxorubicin, cisplatin, veliparib) than with docetaxel.

MDA-MB-231 cell survival following 120 hours single agent treatment with 10 µM compound 17, 250 µM cisplatin, 20 nM doxorubicin, 20 µM PARPi (ABT-888) and 0.5 nM docetaxel was 60.2%, 97.2%, 50.7%, 68.7% and 91.2%, respectively (Fig. 4.15A). Combination treatments of 10 µM compound 17 with: 250 µM cisplatin, 20 nM doxorubicin, 20 µM PARPi (ABT-888) and 0.5 nM docetaxel yielded cell survival of 40.7%, 11.8%, 31.2%, and 54.0%, respectively (Fig. 4.15A). To evaluate whether the drug combination effects were additive, synergistic or antagonistic we applied the BLISS Independence model (Foucquier and Guedj 2015). Using this model the observed drug combination effect was compared to the expected additive effect using the formula for probabilistic independence EA + EB(1 − EA) = EA + EB − EAEB, where 0 ≤ EA ≤ 1 and 0 ≤ EB ≤ 1. The resulting Combination Index (CI) was calculated as:

CI = EA + EB − EAEB EAB In this formula EA is the inhibitory effect of drug A, EB is the inhibitory effect of drug B and EAB is the inhibitory effect of the drug combination. CI<1 indicates a greater than expected additive effect (synergistic), CI > 1 indicates a lesser than expected effect (antagonistic) and CI = 1 is the expected additive effect. Applying the BLISS independence model we found that compound 17 (10 µM) interacted synergistically (CI<1) with; 250 µM cisplatin (CI = 0.71) (Fig. 4.15B), 20 nM doxorubicin (CI = 0.77) (Fig. 4.15C) and 20 µM veliparib (CI = 0.86) (Fig, 4.15D). While the combination of compound 17 with 0.5 nM docetaxel produced the expected additive effect (CI = 0.99) (Fig. 4.15E).

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Figure 4-15. Compound 17 combines synergistically with DNA damaging chemotherapies and PARPi.

(A) Cell viability was determined by MTT assay following 5 days of treatment with each drug alone (at sub-IC50 concentration indicated) and in combination with 10 µM of compound 17. The graph depicts % survival for each treatment condition normalised to the vehicle control. Application of the BLISS independence model with dotted line representing the expected additive effect (EA + EB − EAEB) and calculated CI indicated. (B) Inhibitory effect of single agent and combination cisplatin and compound 17. (C) Inhibitory effect of single agent and combination doxorubicin and compound 17. (D) Inhibitory effect of single agent and combination PARPi and compound 17. (E) Inhibitory effect of single agent and combination docetaxel and compound 17. Results represent the mean ± SEM for 3 independent experiments. Statistical analysis by two-way ANOVA with Sidak’s post hoc analysis. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

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4.3 DISCUSSION

DNA damage inducing radiation therapy and chemotherapy are used extensively in the treatment of TNBC due to the lack of clinically relevant targets, although EGFR, CDK4/6, MTOR, PI3K have been suggested (Mayer et al. 2017). To date the most promising strategy targeting the DNA damage response in TNBC is the use of PARP inhibitors in patients with BRCA1/2 mutations. PARP inhibition induces synthetic lethality in BRCA1/2 mutant tumours due to an accumulation of DSBs in cells that lack functional homologous recombination (HR) repair (Bryant et al. 2005; Farmer et al. 2005; Turner et al. 2008). In sporadic TNBC with proficient HR repair we suggest small molecule RAD51 inhibition as a strategy for sensitising resistant tumours to DNA damaging treatments and PARP inhibition.

Cancer cells, unlike the vast majority of normal cells in the body are highly proliferative and experience increased levels of replication stress associated with genomic instability. These biological conditions foster increased reliance on RAD51 mediated HR and RAD51 facilitated replication for survival. Additionally, upregulation of RAD51 and HR activity is reported for multiple types of cancers and contributes to the development chemotherapy and radiotherapy resistance. Hence RAD51 inhibition also represents a strategy for sensitising resistant tumours to DNA damaging treatments. The most extensively researched small molecule inhibitor of RAD51 is B02. Biochemistry studies have determined that B02 disrupts binding of RAD51 to ssDNA during nucleofilament formation, destabilises the RAD51-ssDNA complex, and inhibits ATP hydrolysis by RAD51. In the present study we conducted SAR analysis using B02 as the base compound to identify a novel small molecule inhibitor with increased RAD51 specific biological activity in TNBC. By altering B02 with the addition of 4-chlorobenzyl to the R1 motif we have identified a new cinnamylquinazoline, compound 17, that shows enhanced cytotoxicity to TNBC cells via RAD51. We have shown that compound 17 binds directly to RAD51 and inhibits RAD51 binding to ssDNA at the site of DSBs and decreases RAD51 mediated repair of DSBs via HR. Importantly compound 17 sensitizes aggressive metastatic TNBC to DNA damage induced by irradiation and synergises with anti-cancer therapeutics doxorubicin, cisplatin and PARPi to improve cell killing. Our data supports the principle of targeting the HR pathway, specifically RAD51, as a mechanism to sensitize aggressive TNBC to DNA damaging treatments.

There is increasing evidence that TNBC patients with homologous recombination repair deficiency (HRD) achieve better clinical outcomes with DNA damaging chemotherapies than those who are HR proficient (Akashi-Tanaka, Watanabe, Takamaru,

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Kuwayama, Ikeda, Ohyama, Mori, Yoshida, Hashimoto, and Terumasa 2015; Sharma et al. 2018; Telli et al. 2018). This has led to the clinical development of several PARP inhibitors as anti-cancer therapies. It is estimated that up to 55% of wild-type BRCA TNBCs also display a "BRCAness" phenotype due to mutations or epigenetic modifications of genes involved in the HR pathway and these patients may also derive benefit from PARP inhibition (Sharma et al. 2018; Mori et al. 2016). Regardless of the underlying mechanism for HRD, the detection of RAD51 foci in tumour samples serves as a functional indicator of HR- proficiency and predictor of patient response to DNA damaging chemotherapy and PARP inhibition (Cruz, Castroviejo-Bermejo, Gutiérrez-Enríquez, Llop-Guevara, Ibrahim, Gris- Oliver, Bonache, Morancho, Bruna, and Rueda 2018; Graeser et al. 2010; Shah et al. 2014; Liu, Burness, et al. 2017). This observation has led us and several other researchers to hypothesise that RAD51 inhibition could be used in HR-proficient tumours to therapeutically induce a “BRCAness” phenotype, expanding the population of TNBC patients who will benefit from PARP inhibition and DNA damaging radio- and chemotherapies. Our results with compound 17 demonstrate that small molecule RAD51 inhibition can indeed enhance the therapeutic power of DNA damaging irradiation, chemotherapies (doxorubicin and cisplatin) and PARP inhibitor (veliparib) in HR-proficient TNBC. Since upregulation of RAD51 is a mechanism by which BRCA1 mutated TNBC acquires resistance to PARP inhibition (Liu, Burness, et al. 2017), small molecule RAD51 inhibition could be applied in this setting to resensitise these tumours to PARP inhibition without the selective pressure that causes secondary mutations.

Immune checkpoint blockade has shown great promise across a range of different cancers, particularly melanoma and lung carcinoma, and is emerging as the standard-of- care therapy for these patients (Hodi et al. 2010; Reck et al. 2016). Recent clinical trials have demonstrated that treatment with immune checkpoint inhibitors (PD-L1 inhibitors) is enhanced in patients with high tumour mutation burden (Goodman et al. 2017). Clinical responses with checkpoint blockade in advanced breast cancer have been modest, partly due to the low number of tumour-infiltrating lymphocytes in most breast cancers (Nanda et al. 2016; Dirix et al. 2018). An exception to this is BRCA mutant breast cancers. In a clinical trial with 54 TNBC patients evaluating the combination of PARP inhibitor (niraparib) and programmed death ligand 1 (PD-L1) inhibitor (pembrolizumab) patients with germline BRCA mutations had higher objective responses (8 of 12, 67%) than the rest of the cohort (Vinayak et al. 2018). BRCA mutant cancers have increased tumour mutation burden due to HRD and consequently increased neoantigen expression and tumour immunogenicity

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(Nolan et al. 2017; Strickland et al. 2016; Kraya et al. 2019). The relationship between HRD and tumour immunogenicity supports the rational combination of small molecule RAD51 inhibition and PD-L1 inhibition for HR-proficient TNBC. Our data supports that small molecule RAD51 inhibition in combination with chemotherapy and PARP inhibition enhances killing of tumour cells, and potentially this could be combined with PD-L1 inhibition to stimulate the immune response and keep residual tumour cells in check.

Currently, small molecule RAD51 inhibitor CYT-0851(Cytier) is the most clinically advanced with 165 patients with B-cell malignancies and solid tumours enrolled in Phase 1 and Phase 2 clinical trials that commenced in October 2019 (ClinicalTrials.gov, NCT03997968). Clearly recognising the therapeutic potential of RAD51 inhibition in the cancer setting Cytier has invested over $US72 million to date into the development of CYT- 0851 (Vinluan 2019). Maclay, Day, and Mills (2019) report that CYT-0851 is selectively active in cells that express Activation Induced Cytidine Deaminase (AID). In cancer cells, AID causes high rates of DSBs which creates a dependency on RAD51 mediated repair activity for survival. CYT-0851 acts by destabilizing RAD51 focus formation and promoting its degradation. Cancers that over express AID and might benefit from CYT-0851 include; B-cell malignancies and a subset of patients with solid tumours, such as non-small cell lung cancer (NSCLC), sarcoma, breast cancer, ovarian cancer, and squamous cell carcinoma of the head and neck. We intently watch the development of CYT-0851 and other promising small molecule RAD51 inhibitors in the drug development pipeline (Ward, Khanna, and Wiegmans 2015; Pastushok et al. 2019). In conclusion, our data provides further support to the clinical relevance of targeting RAD51 in TNBC. Future research should include studying the effect of compound 17 in cell lines derived from non-tumorigenic breast tissue, for example MCF10A and BRE80. Our future studies will also include determining the maximum tolerated dose of compound 17 in TNBC xenograft mouse models and in combination with standard chemotherapy and with PARP inhibition. We expect that compound 17 will be well tolerated as a single agent however it is more likely to be useful in combination therapy to sensitize to induced DNA damage. Compound 17 will be a valuable research tool for studying combination therapies to overcome RAD51 driven resistance in TNBC and may be applied to other cancer models. As such, this work represents an important advance in oncology drug development.

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Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of taxane and anthracycline in TNBC

5.1 INTRODUCTION

The development of drug resistance is a major challenge in the treatment of triple negative breast cancer (TNBC) and is responsible for more than 90% of treatment failures in patients with metastatic disease (Longley and Johnston 2005). Often early stage TNBC is sensitive to chemotherapy, however upon relapse these tumours are no longer to responsive to the initial drug treatment (Longley and Johnston 2005). The cellular mechanisms that underlie chemotherapy resistance in TNBC are many and may co-exist, including upregulation of drug efflux transporters, alteration of target proteins, mutations in key cell cycle proteins and deregulated DNA repair pathways (Nedeljković and Damjanović 2019). These resistance mechanisms can be present in tumour cells prior to drug treatment (innate resistance) or may develop following prolonged exposure to chemotherapy (acquired resistance) (Pan et al. 2016). Patients who present with chemotherapy resistant TNBC and metastatic disease have limited options for additional chemotherapy treatment (Rivera and Gomez 2010). Consequently there is a strong need to understand the mechanisms driving chemotherapy resistance and to identify novel molecular targets to overcome resistance.

Due to the absence of druggable receptors in TNBC tumours the primary form of drug treatment is cytotoxic chemotherapy (Chalakur-Ramireddy and Pakala 2018). Taxanes (e.g., docetaxel, paclitaxel) and anthracyclines (e.g., doxorubicin, epirubicin) are the most common first-line chemotherapies for both early stage TNBC and metastatic disease and may be administered sequentially or in combination (Zaheed et al. 2019). Taxanes are microtubule stabilising agents that block normal microtubule spindle assembly and cell division (McGrogan et al. 2008), while anthracyclines exert their effect via three main mechanisms; intercalating between nucleotide base pairs to inhibit DNA and RNA synthesis, forming complexes with topoisomerase II to generate DNA double strand breaks, and generating iron-mediated free oxygen radicals that damage cell membranes (McGowan et al. 2017). Unfortunately the therapeutic efficacy of anthracyclines is limited by the development of systemic toxicity, especially cardiotoxicity at high doses (McGowan et al.

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2017). Patients who are treated with sequential or combined anthracycline and taxane regimens often develop resistance to one or both of the drugs (Rivera and Gomez 2010). Therefore, understanding and overcoming resistance to the commonly used agents doxorubicin and docetaxel would represent a significant advance in the effective management of TNBC.

The primary goal of chemotherapeutic treatment is to irreparably damage cells and cause cell death. Therefore dysregulation of DNA repair pathways and apoptosis plays a major role in chemoresistance (Curtin 2012). The tumour suppressor protein p53 is a key mediator of DNA repair and apoptosis and is induced by a variety of anticancer drugs, including doxorubicin and docetaxel (Chuang et al. 2012). Activated p53 in turn regulates downstream genes that are involved in cell cycle arrest (e.g., p21CIP), DNA repair (e.g., ATM, ATR, DNA-PK) and apoptosis (e.g., BAX, FAS, PUMA) (Fridman and Lowe 2003). Ninety- three percent of TNBCs express mutant p53 (Wilson et al. 2019) and consequently these cells may fail to arrest at cell cycle checkpoints following DNA damage and be less likely to die by apoptosis. The relationship between p53 status and chemotherapy response was confirmed by a large study conducted by the National Cancer Institute, USA (investigating 60 cell lines and 123 anticancer drugs) who determined that mutant p53 status was positively correlated with drug resistance (O'Connor et al. 1997). In support of this finding, a meta- analysis of 356 independent studies comparing drug sensitivity of cell lines after manipulating p53 status revealed that p53 knockout cells were more resistant than their wild- type p53 counterparts and that mutant p53 cells transfected with wild-type p53 were sensitized to cytotoxic drugs (Cimoli et al. 2004). Clinical studies evaluating adjuvant and neoadjuvant response to chemotherapy in TNBC patients have reported that high p53 expression level detected by IHC (due to accumulation of stabilised mutant p53 protein) predicts poor response to anthracycline based regimens (Chrisanthar et al. 2011; Rahko et al. 2003; Coradini et al. 2015; Maeda et al. 2016). Pre-clinical studies have reported on several small molecules that are capable of restoring wild type p53 function in p53 mutant TNBC cells, thereby reactivating apoptosis and enhancing chemosensitivity (Synnott, Murray, et al. 2017; Walerych et al. 2016; Synnott, Bauer, et al. 2017). Restoration of p53 activity has strong therapeutic potential, however it remains to be seen if any of these compounds show efficacy for the treatment of cancer in human studies.

There is increasing recognition that the p53 family member p73 also modulates the cytotoxicity of chemotherapeutic drugs. p73 shares significant sequence homology with p53 and due to alternate splicing gives rise to full-length p73 containing an N-terminal

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 156 taxane and anthracycline in TNBC transactivation domain (TAp73) and truncated isoforms lacking the N-terminal domain (∆Np73). TAp73 transactivates an overlapping set of p53 target genes that drive cell cycle arrest and apoptosis. Whereas ∆Np73 lacks the N-terminal required to transactivate p53 target genes and inhibits p53 and TAp73 mediated apoptosis by hetero-oligomerization and competing for the same promoter binding sites (Ishimoto et al. 2002). Both TAp73 and ∆Np73 are upregulated in cancer cells in response to a variety of chemotherapeutics including; doxorubicin, bleomycin, mitoxantrone (Müller et al. 2005), docetaxel (Alsafadi et al. 2016), paclitaxel (Sánchez-Carrera et al. 2015) and cisplatin (Sánchez-Carrera et al. 2015) and are implicated as determinants of chemotherapy response in cancer treatment. In vitro studies show that TAp73 knockout increases resistance to doxorubicin in mouse embryonic fibroblasts (Flores et al. 2002) and increases resistance to cisplatin in TNBC cell lines (Isakoff et al. 2007). While upregulation of anti-apoptotic ∆Np73 increases resistance to camptothecin (topoisomerase II inhibitor) (Zaika et al. 2002), bleomycin, and cisplatin in human colon cancer cells, hepatocellular carcinoma cells and ovarian cells respectively (Müller et al. 2005; Leung et al. 2013). In support of these findings Zaika et al. (2002) showed that downregulation of ∆Np73 increases chemosensitivity by restoring p53 and TAp73 mediated apoptosis. Furthermore, destabilisation of mutant p53 with small molecule NSC59984 has been shown to restore TAp73 pro-apoptotic signalling and sensitise colorectal cancer cells to camptothecin (Zhang et al. 2015). Very few clinical studies have examined role of TAp73 and ∆Np73 in chemotherapy responsiveness, however one of these studies found high ∆Np73 expression to be associated with platinum resistance in p53 mutated ovarian cancers (Concin et al. 2005). Importantly overexpression of ∆Np73 has been observed in approximately 30% of breast cancers, including TNBC (Domínguez et al. 2006; Zaika et al. 2002) and clearly has a potential role in chemoresistance that warrants investigation.

The most potent type of DNA damage caused by cytotoxic chemotherapy are DNA double strand breaks (DSBs) (Dunkern et al. 2003). Therefore upregulation of DSB repair pathways such as non-homologous end joining (NHEJ) and homologous recombination (HR) represent an important mechanism of chemotherapy resistance in TNBC. NHEJ is the default DSB repair pathway throughout the cell cycle and is mediated by DNA-PK (Goodwin and Knudsen 2014). Repair by NHEJ is an error-prone repair process that re-ligates DNA broken ends (Chang et al. 2017). For NHEJ to proceed the catalytic subunit of DNA-PK (DNA-PKcs) must phosphorylate downstream proteins, including KU70 and KU80, and importantly must undergo autophosphorylation (Goodwin and Knudsen 2014). RAD51-

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 157 taxane and anthracycline in TNBC mediated HR occurs predominantly in late S and G2 phase of the cell cycle and uses the homologous sequence in the sister chromatid as a template to accurately to accurately repair DSBs (Kelley and Fishel 2016). In addition to mediating apoptotic response p53 regulates DNA repair in response to chemotherapy induced DNA damage. p53 preferentially promotes repair via NHEJ by recruiting NHEJ mediator 53BP1 to the site of DSBs and restraining recruitment of HR mediator BRCA1 (Moureau et al. 2016). Additionally, HR is inhibited by wild-type p53 largely via its interactions with RAD51, the recombinase responsible for DNA strand invasion and exchange in HR. p53 represses RAD51 gene expression by binding to the RAD51 promoter (Arias‐Lopez et al. 2006) and forms complexes with RAD51 that inhibit strand exchange between sister chromatids (Stürzbecher et al. 1996; Yoon et al. 2004) and also acts to promote clearance of RAD51 foci from the site of DSBs (Orre, Stenerlöw, et al. 2006). In contrast, mutant p53 fails to repress RAD51 gene expression or RAD51 foci formation following chemotherapy induced DNA damage (Arias‐Lopez et al. 2006) and is associated with elevated levels of HR (Lu, Lozano, and Donehower 2003; Bertrand et al. 1997) that potentially confers resistance to DNA damaging chemotherapies (Klein 2008). Hence in tumours that express defective or mutant p53, RAD51 mediated HR may become the preferential pathway by which cells repair chemotherapy induced DSBs (Moureau et al. 2016).

Interrogation of histopathological parameters in the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) dataset confirmed that mutant p53 correlates with high RAD51 mRNA expression in breast tumours and that 73% of TNBCs overexpress RAD51 (Wiegmans et al. 2014). Importantly high RAD51 expression and the presence of RAD51 nuclear foci are surrogate markers for HR efficiency (Meijer et al. 2019; Adam-Zahir et al. 2014) and are predicative of poor response to chemotherapies including; docetaxel (Asakawa et al. 2010), anthracyclines (Graeser et al. 2010; Asakawa et al. 2010; Rodriguez et al. 2010), cisplatin (Sakai et al. 2008) and PARP inhibition (Cruz, Castroviejo-Bermejo, Gutiérrez-Enríquez, Llop-Guevara, Ibrahim, Gris-Oliver, Bonache, Morancho, Bruna, Rueda, et al. 2018; Liu, Burness, et al. 2017). Absence of nuclear RAD51 foci is a strong indicator of HR deficiency (HRD) and has been shown to outperform HRD genomic testing in predicting sensitivity to PARP inhibition (Castroviejo‐Bermejo et al. 2018). We and several other research groups have developed small molecule RAD51 inhibitors (Ward et al, 2017) and have demonstrated that these compounds inhibit DNA damage induced RAD51 foci formation and repair by HR and increase cytotoxicity of several anticancer drugs including; doxorubicin (Alagpulinsa, Ayyadevara, and Shmookler Reis 2014; Huang and Mazin 2014),

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 158 taxane and anthracycline in TNBC etoposide, topotecan, and cisplatin (Huang and Mazin 2014). Hence small RAD51 inhibition represents a targeted strategy to resensitise a cohort of chemotherapy resistant TNBCs.

In this chapter we characterise a panel of doxorubicin and docetaxel adapted TNBC cell lines that we have developed and investigate the contribution of DNA damage response (DDR) dysregulation to resistance. We show that targeting RAD51 with the small molecule inhibitor, compound 17 (characterised in chapter 4) effectively resensitises chemoresistant TNBC.

5.2 RESULTS

5.2.1 Establishment of resistance to doxorubicin and docetaxel in TNBC cell lines The development of drug resistant cancer cell lines is a useful approach for studying the mechanisms of drug cytotoxicity and resistance. For this study we selected the parental TNBC cell lines; MDA-MB-231, MDA-MB-468, MDA-MB-453, HS578T and BT549 to develop resistant variants. These five cell lines were selected on the basis that they are frequently utilised in research settings to model TNBC, are well characterised in the literature and represent a variety of TNBC subtypes (characteristics of TNBC cell lines are summarised in Table 5.1). The two main strategies employed to develop drug resistance were initial low dose, pulsed drug treatment followed by stepwise continuous exposure. Cells were initially treated with a low dose combination of doxorubicin and docetaxel added to culture media for three days on and three days off to allow for cell recovery. Once cells were showing good recovery from pulsed drug exposure the treatment strategy switched to stepwise drug escalation. The overall treatment period was approximately six months. Suitable commencing drug dosages (10 nM doxorubicin, 0.1 nM docetaxel) were determined by cytotoxicity assays of the parental cell lines with single drug exposure. The final drug concentrations used to condition the cells is shown in Table 5.1. To ensure that resistance was stable over the long term cell stocks used for experiments were frozen following at least 4 weeks withdrawal from drug exposure. After thawing, resistant cell lines were maintained in culture media without drug.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 159 taxane and anthracycline in TNBC

Table 5-1 Characteristics of parental cell lines and final doxorubicin and docetaxel concentrations used to condition the cells

Cell line TNBC Cell line origin Tumour Mutations Final subtype source concentration (nM)

Dox a Doc b

MDA-MB-231 Mesenchymal- Adenocarcinoma Metastasis, CDKN2A, KRAS, 200 1.5 like like pleural NF2, TP53 effusion

HS 578T Mesenchymal- Carcinoma Primary CDKN2A, HRAS, 50 1 like PIK35RI, TP53

MDA-MB-468 Basal-like Adenocarcinoma Metastasis, PTEN, RB1, 50 1 pleural SMAD4, TP53 effusion

MDA-MB-453 Luminal Carcinoma Metastasis, PIK3CA, CDH1, 100 1 androgen pleural PTEN receptor effusion

BT549 Mesenchymal Ductal Primary PTEN, RB1, TP53 100 1 carcinoma a Dox (Doxorubicin), b Doc (Docetaxel)

5.2.2 Determination of doxorubicin and docetaxel IC50 in parental and resistant TNBC cell lines To determine the level of drug adaption achieved in the resistant variants we assessed single drug and combined drug dose-responses following 5 days treatment by

MTT assay and calculated IC50 concentrations. The drug concentrations assayed were: 10– 1000 nM doxorubicin, 0.1–10 nM docetaxel and a 100:1 fixed ratio combination of doxorubicin and docetaxel to mimic the clinical scenario (10/0.1–1000/10 nM).

The IC50 concentrations calculated for each of the six cell lines are provided in Figure 5.2 and demonstrate that stable resistance was achieved with the MDA-MB-231, MDA-MB- 468, BT549 and HS578T resistant variants. The MDA-MB-231 resistant variant (from this point forward abbreviated to 231 Res) was 48.2-fold, 3.4-fold and 20.8-fold more resistant

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 160 taxane and anthracycline in TNBC to doxorubicin, docetaxel and combined drug respectively than sensitive parental MDA-MB- 231 (from this point forward abbreviated to 231 Sen). While the MDA-MB-468 resistant variant (from this point forward abbreviated to 468 Res) was 3.1-fold, 4.0-fold and 3.4-fold more resistant to doxorubicin, docetaxel and combined drug respectively than sensitive parental MDA-MB-468 (from this point forward abbreviated to 468 Sen). The IC50 concentrations obtained for the MDA-MB-453 cell lines revealed that meaningful stable resistance had not been established in the MDA-MB-453 resistant variant (from this point forward abbreviated to 453 Res). Of note parental MDA-MB-453 displayed significantly higher IC50 concentrations for doxorubicin and docetaxel compared to the other parental TNBC cell lines used in this study which suggests it might already have acquired a resistant phenotype. Additionally, unlike the other TNBC cell lines MDA-MB-453 does not express mutated p53. The fold resistance for 453 Res was 1.23, 1.08 and 1.19 for doxorubicin, docetaxel and combined chemotherapy respectively. On the basis of this result the MDA- MB-453 cell lines were not further investigated in this study. The resistant BT549 and HS578T cell lines were recently established and our future work will include examination of the resistance mechanism utilised.

Table 5-2 Chemotherapy IC50 values for Sensitive and Resistant cell lines

Cell line IC50 ± SEM (nM)

Doxorubicin Docetaxel Combined doxorubicin/docetaxel (100:1)

231 Sen 29.05 ± 6.05 0.84 ± 0.18 27.07 ± 3.47/ 0.27 ± 0.04

231 Res 1400.34 ± 185.12 **** 2.89 ± 0.44 *** 563.99 ± 84.60/ 5.64 ± 0.84 ****

468 Sen 15.47 ± 1.22 0.16 ± 0.03 14.14 ± 2.05/ 0.14 ± 0.02

468 Res 48.64 ± 7.24 **** 0.65 ± 0.09 **** 48.42 ± 8.24/ 0.48 ± 0.08 ****

453 Sen 116.00 ± 5.67 1.01 ± 0.06 79.12 ± 5.57/ 0.79 ± 0.06

453 Res 142.00 ± 11.03 * 1.09 ± 0.15 93.53 ± 11.03/ 0.94 ± 0.11

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 161 taxane and anthracycline in TNBC

Figure 5-1. Evaluation of chemotherapy resistance in parental and drug adapted cell lines.

Dose response curves comparing survival of Sensitive and Resistant TNBC cell lines following 5 days treatment with single agent and combined doxorubicin-docetaxel. 231 Sen and 231 Res survival with: (A) single agent doxorubicin, (B) single agent docetaxel and, (C) combined doxorubicin-docetaxel. 468 Sen and 468 Res survival with: (D) single agent doxorubicin, (E) single agent docetaxel and, (F) combined doxorubicin- docetaxel. 453 Sen and 453 Res survival with: (G) single agent doxorubicin, (H) single agent docetaxel and, (I) combined doxorubicin-docetaxel. 100:1 ratio of doxorubicin to docetaxel used in combined chemotherapy. Results represent the mean ± SEM for 3 independent experiments. Statistical analysis by student’s t-test.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 162 taxane and anthracycline in TNBC

5.2.3 P-glycoprotein drug pump is a driver of doxorubicin resistance in MDA-MB-231 Resistant cells only. A common mechanism for chemotherapy resistance is upregulation of drug efflux proteins, most commonly P-glycoprotein 1 (P-gp), that is encoded by ATP-binding cassette sub-family B member 1 (ABCB1) (Zelnak 2010). To examine the contribution of P-gp upregulation to resistance in 231 Res and 468 Res cell lines we measured protein levels of P-gp by immunoblotting and repeated dose curves for combined chemotherapy with the addition of a third generation P-gp inhibitor, Tariquidar (Roe et al. 1999). Results for this section are depicted in figure 5.2. Western blotting showed that 231 Sen and 231 Res expressed P-gp at similar levels while 468 Sen and 468 Res did not express P-gp at detectable levels (Fig. 5.2A). Based on the western blotting result we hypothesised that Tariquidar would increase sensitivity of the MDA-MB-231 cell lines to doxorubicin and docetaxel treatment but have little effect on the MDA-MB-468 cells lines. To rule out intrinsic toxicity of Tariquidar we first assessed dose-response in the MDA-MB-231 cell lines following 120 hours incubation with concentrations ranging from 0.01 – 1 µM (recommended working concentration range). Tariquidar was relatively non-toxic to cells at 1 µM (Fig. 5.2B) and so we chose this concentration to combine with doxorubicin and docetaxel treatment.

The addition of 1 µM P-gp inhibitor had no significant effect on IC50 for combined chemotherapy 231 Sen (Fig. 5.2C), 468 Sen (Fig. 5.2H) or 468 Res (Fig. 5.2I). In contrast, the IC50 for combined doxorubicin and docetaxel for 231 Res was decreased by almost 3- fold with the addition of P-gp inhibitor (Fig. 5.2D). To evaluate if 231 Res utilised P-gp upregulation as a resistance mechanism against both drugs equally or differentially we repeated single drug (doxorubicin, docetaxel) dose curves plus 1 µM Tariquidar. The addition of P-gp inhibitor had no significant effect on docetaxel IC50 for 231 Res. In contrast,

P-gp inhibition significantly decreased doxorubicin IC50 from 1400 to 270 nM. These results indicate that increased drug efflux is partially responsible for resistance in 231 Res however other resistance mechanisms are active in both resistant cell lines.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 159 taxane and anthracycline in TNBC

Figure 5-2 P-glycoprotein contribution to chemoresistance.

(A) Western blot showing P-gp expression in MDA-MB-231 and MDA-MB-468 Sensitive and Resistant cell lines. 20 µg of protein extracted from whole cell lysates loaded per well. Dose response curves determined by MTT after 5 days treatment with the indicated drugs. (B) 231 Sen and 231 Res treated with P-gp inhibitor (P- gpi) Tariquidar (0.01-1µM). (C) 231 Sen treated with combined doxorubicin-docetaxel ± 1 µM P-gpi. (D) 231 Res treated with combined doxorubicin-docetaxel ± 1 µM P-gpi. (E) 231 Res treated with single agent doxorubicin ± P-gpi. (F) 231 Res treated with single agent docetaxel ± P-gpi. (G) 231 Sen and 231 Res treated with combined doxorubicin-docetaxel + P-gpi. (H) 468 Sen treated with combined doxorubicin-docetaxel ± P- gpi. (I) 468 Res treated with combined doxorubicin-docetaxel ± P-gpi. (J) 468 Sen and 468 Res treated with combined doxorubicin-docetaxel + P-gpi. 100:1 ratio of doxorubicin to docetaxel used in combined chemotherapy. Results represent the mean ± SEM for 3 independent experiments. Statistical analysis by student’s t-test. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 160 taxane and anthracycline in TNBC

5.2.4 Drug adapted cell lines show less G2/M arrest following chemotherapy treatment. Based on the anti-proliferative and DNA damaging properties of doxorubicin and docetaxel an expected consequence of treatment is altered cell cycle distribution, in particular increased cell cycle arrest even with mutant p53 present. To characterise the normal cell cycle distribution of Sensitive and Resistant cell lines and evaluate the effect of combined chemotherapy on cell cycle progression we conducted flow cytometric analyses on untreated and chemotherapy treated propidium iodide stained cells. Based on our previous dose curve results, we chose to treat cells with a 100:1 ratio of doxorubicin:docetaxel that gave maximal heterogeneity between Resistant and Sensitive cell lines. Results for this section are depicted in figure 5.3.

The baseline untreated cell cycle distribution for 231 Res showed a decreased proportion of cells in S phase compared to 231 Sen and greater proportion of cells in G2/M arrest (26.3% vs. 7.6%, p<0.0001). For 231 Sen, chemotherapy treatment significantly increased the percentage of cells in G2/M arrest (65.9% vs 7.6%, p<0.0001) and sub-G1 (8.9% vs 0.1%, p<0.0001), indicative of cell death, but had no effect on cell cycle distribution for 231 Res (Fig. 5.3A-C).

In the absence of drug there was no significant difference between 468 Sen and 468 Res cell cycle distribution. Both cell lines displayed increased G2/M arrest following treatment (p<0.0001) with 468 Sen displaying greater G2/M arrest than 468 Res (39.1% vs. 24.9%, p<0.0001). 468 Sen also displayed significantly increased sub-G1 population with chemotherapy (8.6% vs. 0.7%, p<0.05) (Fig. 5.3D-F).

In cell culture we observed that 231 Res cells grew markedly slower than 231 Sen (~2- fold increased doubling time) and this is consistent with the decreased S-phase and increased G2/M arrest observed for 231 Res at baseline. Future experiments utilising Edu incorporation may be useful in characterising differences in DNA synthesis during S-phase. The lower levels of G2/M arrest observed in the Resistant compared to Sensitive cell lines following chemotherapy suggest dysregulated checkpoint activation.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 161 taxane and anthracycline in TNBC

Figure 5-3 Cell cycle analysis of Sensitive and Resistant MDA-MB-231 and MDA-MB-468 by flow cytometry.

(A) Representative DNA content histograms generated following propidium iodide staining and flow cytometric analysis for 231 Sen and 231 Res cells incubated for 72 hours with vehicle (DMSO) or chemotherapy (30 nM doxorubicin + 0.3 nM docetaxel (sub-G1, G1, S,G2/M indicated). (B) Quantification of cell cycle distribution for 231 Sen and 231 Res with vehicle (C) Quantification of cell cycle distribution for 231 Sen and 231 Res with chemotherapy. (D) Representative DNA content histograms for 468 Sen and 468 Res cells incubated for 72 hours with vehicle (DMSO) or chemotherapy (20 nM doxorubicin + 0.2 nM docetaxel (sub-G1, G1, S,G2/M is indicated). (E) Quantification of cell cycle distribution for 468 Sen and 468 Res with vehicle. (F) Quantification of cell cycle distribution for 468 Sen and 468 Res with chemotherapy. Results represent the mean + SEM for 3 independent experiments. Statistical analysis by two way ANOVA followed by Tukey’s post hoc analysis. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 162 taxane and anthracycline in TNBC

5.2.5 Drug adapted cell lines are resistant to chemotherapy induced apoptosis. We next wanted to evaluate the apoptotic response of the Sensitive and Resistant cell lines to chemotherapy on the basis that evasion of apoptosis is a common mechanism of chemotherapy resistance, particularly in tumours that harbour p53 mutations. To this end we conducted flow cytometry on Annexin V-FITC/PI double stained cells following 120 hours incubation with either vehicle or combined doxorubicin and docetaxel. Results for this section are shown in figure 5.4.

In the absence of treatment both 231 Res and 468 Res had a decreased live cell population and increased apoptotic cell population compared to their Sensitive counterparts. With chemotherapy the percentage of cells that underwent apoptosis only increased ~1.2- fold for 231 Res compared to ~13-fold for 231 Sen (Fig. 5.4A-C). Chemotherapy treatment also induced significantly less apoptosis for 468 Res compared to 468 Sen, with the percentage of apoptotic cells increased by ~2.4-fold and ~17.2-fold respectively compared to the vehicle condition (Fig. 5.4D-F). These results indicate that chemotherapy was less effective at inducing apoptosis in the Resistant cell lines.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 163 taxane and anthracycline in TNBC

Figure 5-4 Apoptosis induction in untreated and chemotherapy treated Sensitive and Resistant TNBC cell lines.

(A) Representative scatter plots for apoptotic cell analyses for 231 Sen and 231 Res following 120 hours incubation with either the vehicle control or chemotherapy (30 nM doxorubicin +0.3 nM docetaxel). Quadrants representing Live cells (Annexin V-, PI-), Early apoptosis (Annexin V+, PI-) and Late apoptosis (Annexin V+, PI+) are indicated. (B) Quantification of % live and apoptotic cells for 231 Sen and 231 Res with vehicle. (C) Quantification of % live and apoptotic cells for 231 Sen and 231 Res with chemotherapy. (D) Representative scatter plots for 468 Sen and 468 Res following 120 hours incubation with either the vehicle control or chemotherapy (20 nM doxorubicin +0.20 nM docetaxel). (E) Quantification of % live and apoptotic cells for 468 Sen and 468 Res with vehicle. (F) Quantification of % live and apoptotic cells for 468 Sen and 468 Res with chemotherapy. Results represent the mean + SEM for 3 biological replicates. Statistical analysis by two way ANOVA followed by Tukey’s post hoc analysis. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 164 taxane and anthracycline in TNBC

5.2.6 Increased genomic instability is associated with chemo-resistance Genomic instability refers to an increased rate of genetic alteration and is a hallmark of cancer. Increased genomic instability provides a mechanism for cancer cells to accumulate mutations that that might confer chemotherapy resistance (Wein and Loi 2017). Common characteristics of genomic instability include aneuploidy, amplifications, deletions, loss of heterozygosity (LOH), chromosome rearrangements and altered DNA sequences. Chemotherapy resistance has been shown to correlate with acquisition of new genomic aberrations and adaptive copy-number evolution (C. Kim et al. 2018). To investigate this, we performed metaphase spread counts comparing chromosome numbers between sensitive and resistant paired lines and isolated DNA for SNP array analysis of each cell line.

The normal number of chromosomes in human cells is 46 (2n). Analysis of metaphase spreads revealed aneuploidy in all MDA-MB-231 and MDA-MB-468 cell lines and reduced chromosome numbers in the Resistant cell lines compared to their Sensitive counterparts (Fig. 5.5) The mean chromosome count was significantly reduced for 231 Res compared to 231 Sen (46.2 ± 0.7 vs. 52.1 ± 0.8, p<0.0001) but did not reach significance for 468 Res compared to 468 Sen (45.9 ± 0.5 vs. 47.2 ± 0.5) (Fig 5.5A vs E).

SNP array analysis revealed complex genomic profiles for all MDA-MB-231 and MDA- MB-468 cell lines characterised by multiple low amplitude losses and gains, scarce homozygous deletions and infrequent high level amplifications. Overall the Resistant cell lines had increased genomic losses (LOH) and decreased duplications (copy number ≥ 3, CN3+) compared to their Sensitive counterparts (Fig. 5.5). Losses were most frequent for 231 Sen in 9p and 23q and for 231 Res in 3pq, 4q, 8p, 9p, 16q, 17p, 21q and 23q. For 468 Sen losses were most frequent in 13q, 16p, 22p and for 468 Res in 4q, 13q, 16p, 19p, 22p and 23p. Closer inspection of genomic regions revealed copy number differences for Sensitive and Resistant cell lines for multiple genes associated with cell cycle regulation, apoptosis and DNA repair (Table 5.3). Interestingly 231 Res had fewer copies compared to 231 Sen of p53 (2 vs. 3), p63 (2 vs. 3), 53BP1 (2 vs. 3), BRCA1 (2 vs. 3) and DNA-PK (1 vs. 2) and 468 Res had fewer copy numbers of KU70 (2 vs.3) compared to 468 Sen. Overall the data suggests that adaptation to DNA damaging agents requires or results in loss of genetic material.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 165 taxane and anthracycline in TNBC

Figure 5-5. Analysis of genome integrity in Sensitive and Resistant TNBC cell lines.

(A) Metaphase chromosome counts for 231 Sen and 231 Res showing mean + SEM. (B) Comparison of copy number losses and gains for 231 Sen and 231 Res. Results represent mean + SEM for 3 replicates. (C) Genomic profile of 231 Sen and 231 Res. (D) Zoomed in image of p53 and BRCA1 gene location on chromosome 17 for 231 Sen and 231 Res. (E) Metaphase chromosome counts for 468 Sen and 468 Res showing mean + SEM. (F) Comparison of copy number losses and gains 468 Sen and 468 Res. Results represent mean + SEM for 3 replicates. (G) Genomic profile of 468 Sen and 468 Res. (H) Zoomed in image of p53 and BRCA1 gene location on chromosome 17 for 468 Sen and 468 Res. Statistical analysis by Student’s t-test. ****p<0.0001.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 166 taxane and anthracycline in TNBC

Table 5-3 Copy number variation for genes associated with cell cycle, apoptosis and DNA repair in Sensitive and Resistant TNBC cell lines

Copy number Gene Pathway Genomic location 231 231 468 468 Sen Res Sen Res p53 p53 family chr17: 7,661,779 -7,687,550 3 2 2 2 p63 p53 family chr3: 189,631,389-189,897,276 3 2 2 2 p73 p53 family chr1: 3,652,516-3,736,20 2 2 - - MDM2 p53 regulator chr12: 68,808,177-68,850,686 2 2 2 2 ATR ATR-CHK1 pathway chr3: 142,449,007-142,578,733 2 2 3 3 CHK1 ATR-CHK1 pathway chr11: 125,625,665-125,676,255 4 3 4 3 ATM ATM-CHK2 pathway chr11: 108,222,484-108,369,102 4 4 4 4 CHK2 ATM-CHK2 pathway chr22: 28,687,743 -28,742,422 2 2 3 3 CDC25A Checkpoint chr3: 48,157,146-48,188,402 3 2 2 2 WEE1 Checkpoint chr11: 9,595,228-9,615,004 3 3 2 2 p16 Senescence chr9: 21,967,753-21,995,301 0 0 2 2 p19 Senescence chr19: 10,566,462-10,569,059 2 2 5 3 FAS Apoptosis chr10: 88,990,531-89,017,059 3 3 3 3 NOXA Apoptosis chr18: 59,899,948-59,904,306 2 3 2 2 PUMA Apoptosis chr19: 47,220,822-47,232,766 3 2 3 3 BAX Apoptosis chr19: 48,954,815-48,961,798 3 2 3 3 BIK Apoptosis chr22: 43,110,750-43,129,712 2 2 3 2 BCL2 Apoptosis chr18: 63,123,346-63,320,128 2 3 2 2 MLH2 MMR chr2: 47,402,969-47,663,146 3 2 4 4 MLH1 MMR chr3: 36,993,350-37,050,846 3 2 2 2 XPC NER chr3: 14,145,145-14,178,672 3 3 2 2 XPG NER chr13: 102,807,146-102,876,001 2 2 4 5 XPF NER chr19: 45,407,333-45,478,828 3 2 4 4 XRCC1 BER chr19: 43,543,040-43,580,473 3 2 4 3 PARP1 BER, alt-NHEJ chr1: 226,360,691-226,408,093 3 3 4 3 DNA-PK NHEJ chr8: 47,773,108-47,960,183 2 1 2 2 KU70 NHEJ chr22: 41,621,119-41,664,048 2 2 3 2 KU80 NHEJ chr2: 216,107,464-216,206,303 3 3 3 3 53BP1 NHEJ chr5: 43,403,061-43,510,728 3 2 3 3 MRE11 HR chr11:94,415,578-94,493,908 4 4 2 4 BRCA2 HR chr13: 32,315,086-32,400,266 2 2 2 2 RAD51 HR chr15: 40,694,774-40,732,340 2 2 2 2 RPA1 HR chr17: 1,829,702-43,170,245 3 2 2 2 BRCA1 HR chr17: 43,044,295-43,170,245 3 2 2 2

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 167 taxane and anthracycline in TNBC

5.2.7 DSB repair is functionally more active in MD-MB-231 Resistant cell line Upregulated DNA repair activity can provide a survival advantage to cancer cells and make them resistant to DNA damaging treatments. Since DNA DSBs are the most lethal type of DNA lesion caused by commonly used TNBC treatments such as radiation therapy and cytotoxic chemotherapy we have focused our investigations on DSB repair activity. Here we assess DSB repair efficiency in the 231 Sen and 231 Res cell lines using DNA reporter plasmids for HR and NHEJ, representing the two main DSB repair pathways. Results are shown in figure 5.6.

For the HR assay we first generated stable transfections of the DR-GFP reporter in the 231 Sen and 231 Res cell lines. The DR-GFP reporter contains two defective GFP genes: iGFP and SceGFP, with SceGFP containing an I-SceI restriction site. Transient transfection with the cutting endonuclease I-SceI produces a single DSB in the SceGFP gene that when repaired by HR gives rise to GFP expression (Pierce et al. 1999). We measured the frequency of HR events (GFP+ cells) in 231 Sen and 231 Res cells 72 hours after transfection with I-Scel. In the absence of I-SceI it is possible for spontaneous recombination to occur, however this was negligible in both cell lines. Transfection with an intact GFP expression vector (pEGFP n.3) was used to determine transfection efficiency for both cell lines in each experiment and used to normalise the % HR events score. The average frequency of HR events was increased almost 7-fold for 231 Res compared to 231 Sen (p<0.01)(Fig. 5.6A-C).

To investigate NHEJ activity in the 231 Sen and 231 Res cell lines they were transiently transfected with linearized pEGFP N.3 plasmid and NHEJ events determined by flow cytometry . The linearized plasmid contains a DSB between the promoter and GFP gene, preventing GFP expression unless the DNA ends are ligated by NHEJ after transfection. The frequency of NHEJ events (GFP+ cells) was measured by flow cytometry 3 days after transfection. Circular pEGFP N.3 was used as a transfection control for each cell line and to normalise the % NHEJ events score. The average frequency of NHEJ repair events was increased almost 3-fold for 231 Res compared to 231 Sens(p<0.001)(Fig. 5.6D-F).

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 168 taxane and anthracycline in TNBC

Figure 5-6. Evaluation of HR and NHEJ repair efficiency in MDA-MB-231 Sensitive and Resistant cell lines.

(A) Schematic diagram of the DR-GFP reporter used to measure DSB-induced HR. The reporter consists of two non-functional GFP genes, one of which contains an I-SceI endonuclease site. Expression of I-Scel produces a DSB that when repaired by HR using the downstream GFP sequence template gives rise to a functional GFP gene. (B) Total GFP events within the gated region were determined by flow cytometry and scored against pEGFP-N3 transfected cells for the same cell line to account for transfection efficiency. (C) Graph quantifies the fold change in HR frequency for 231 Res (red) compared to 231 Sen (grey). Results represent the mean ± SEM for 3 independent experiments. (D) Schematic diagram of the linearised pEGFP- N3 reporter used to measure DSB repair by NHEJ. The NHEJ plasmid contains a CMV promoter and eGFP coding sequence separated by a multiple cloning site (MCS) that contains a HindIII restriction site. Repair of the DSB by NHEJ a produces a functional GFP transcript. (E) Total GFP events for linearized DNA transfected cells was normalised to circular pEGFP-N3 transfected cells for the same cell line to account for transfection efficiency. (F) Graph quantifies the fold change in NHEJ frequency for 231 Res (red) compared to 231 Sen Sensitive cells (grey). Results represent the mean ± SEM for 3 biological; replicates. Statistical analysis by student’s t-test. **p<0.01, ***p<0.001.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 169 taxane and anthracycline in TNBC

5.2.8 Resistant cell lines show increased dependence on RAD51 mediated HR to survive irradiation and chemotherapy induced DSBs From our genomic profiling (5.2.6) we know that the Resistant cell lines have an overall loss of genetic material correlating with reduced copy numbers in key mediators of the DDR. These alterations have the potential to perturb function of the specific DNA repair pathways that are triggered by DNA damaging chemotherapy. The most toxic type of lesion caused by doxorubicin is DSBs, which can be repaired by three main pathways; DNA-PK mediated NHEJ, PARP1 mediated alt-NHEJ and RAD51 mediated HR. We have observed in section 5.2.7 that in response to simple DSBs generated directly by the cutting enzyme I-Scel 231 Res utilises enhanced DNA repair functions of both NHEJ and HR to survive. However the DSBs generated by doxorubicin and by radiation therapy used to treat cancer can be more complex, involving bulky adducts, breaks generated during replication and stalled replication forks. To assess the contribution of specific DSB repair pathways to cell survival following irradiation and chemotherapy induced DNA damage we combined these treatments with commercially available drugs to inhibit key proteins in canonical DSB repair pathways. DNA- dependent protein kinase inhibitor (DNA-PKi), Ataxia telangiectasia mutated inhibitor (ATMi) and ATM- and RAD3-related inhibitor (ATRi) were used to disrupt the most upstream DDR kinases. DNA-PK is required for c-NHEJ, ATM predominantly supports HR but also c-NHEJ and alt-NHEJ to a lesser extent, while ATR responds to replication stress and phosphorylates many of the same substrates as ATM. To directly target HR and alt-NHEJ we employed RAD51 inhibitor (RAD51i) (compound 17, lead compound characterised in chapter 4) (Ward et al. 2017) and poly-ADP ribose polymerase inhibitor (PARPi) respectively. Of note, PARP1 has been implicated in the modulation of the c-NHEJ pathway, however its importance to this pathway and the effect of PARP inhibition on c-NHEJ is not completely clear (Curtin and Szabo 2020).

In brief, cells were pre-treated with 10 µM DDR inhibitor and then subjected to 5 Gy gamma-irradiation or incubated with chemotherapy. Cell death was then measured over a period of 96 hours by live imaging, generating cell death curves. For 231 Sen and 231 Res chemotherapy consisted of 30 nM doxorubicin plus 0.3 nM docetaxel. 468 Sen and 468 Res were treated with 20 nM doxorubicin plus 0.2 nM docetaxel. The area under the curve was calculated for each DDR inhibitor treatment condition and normalised to the vehicle control for each cell line.

The combination of RAD51 inhibition with irradiation was more detrimental to 231 Res than 231 Sen, increasing cell death by 7.9-fold and 1.9-fold respectively (p<0.0001) (Fig.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 170 taxane and anthracycline in TNBC

5.7A). While irradiation combined with inhibition of ATM, ATR and DNA-PK was more lethal to 231 Sen than 231 Res, with cell death increased by 4.3-fold vs. 2.3-fold (p<0.01), 8.5-fold vs. 6.2-fold (p<0.01) and 3.6-fold vs. 1.1-fold (p<0.001) respectively. In response to irradiation, direct inhibition of kinases required for HR, NHEJ and alt-NHEJ yielded similar levels of cell death for 231 Sen, suggesting approximately equal reliance on the three DSB repair pathways to repair irradiation induced DSBs (Fig. 5.7B). While direct inhibition of RAD51 mediated HR was significantly more lethal than inhibition of NHEJ (p<0.0001) or alt- NHEJ (p<0.0001) for 231 Res, suggesting preferential reliance on HR to repair irradiation induced DSBs (Fig. 5.7C).

In combination with chemotherapy inhibition of ATM, ATR and RAD51 was more lethal to 231 Res than 231 Sen, with cell death increased by 6.9-fold vs. 0.9-fold, 7.4-fold vs. 3.5- fold and 7.8-fold vs. 1.3-fold (p<0.0001) respectively (Fig. 5.7D). Consistent with the result for irradiation, direct inhibition of NHEJ, alt-NHEJ and HR combined with chemotherapy produced similar levels of cell death for 231 Sen (Fig. 5.7E), while inhibition of RAD51 mediated HR was most lethal for 231 Res (p<0.0001), suggesting preferential reliance on HR to repair chemotherapy induced DSBs (Fig. 5.7F).

For MDA-MB-468 cell lines, the combination of irradiation and RAD51 inhibition was more lethal for 468 Res than 468 Sen, with cell death increased by 8.4-fold vs. 4.7-fold (p<0.001) compared to irradiation alone (Fig. 5.8A). Inhibition of HR produced greater cell death than NHEJ and alt-NHEJ inhibition for both 468 Sen and 468 Res, p<0.01 and p<0.001 respectively (Fig. 5.8B-C). Combined with chemotherapy RAD51 inhibition increased cell death by 6.1-fold for 231 Res and 3.0-fold for 231 Sen (p<0.01) compared to chemotherapy alone (Fig. 5.8D). For 468 Sen the preference for HR repair over NHEJ and alt-NHEJ not significant (Fig. 5.8E) while 468 Res displayed a strong preference for HR over NHEJ or alt- NHEJ (p<0.0001) with significantly greater cell death resulting from chemotherapy combined with HR inhibition (Fig. 5.8F).

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 171 taxane and anthracycline in TNBC

Figure 5-7. Standardized response of 231 Sen and 231 Res to specific drugs targeting key DDR proteins essential for canonical DDR pathways.

(A) 231 Sen and 231 Res cells were treated with vehicle (DMSO) or 10 µM of the indicated DDR inhibitors and irradiated with 5 Gy gamma radiation. Cell death was measured 96 hours later and normalised to the vehicle condition. (B) Proportion of irradiation induced cell death caused by inhibiting indicated DSB repair pathway (NHEJ, alt-NHEJ, HR) with specific inhibitor (DNA-PKi, PARPi, RAD51i) respectively for (B) 231 Sen and, (C) 231 Res. (D) 231 Sen and 231 Res cells were treated with vehicle (DMSO) or 10 µM of the indicated DDR inhibitors combined with 30 nM doxorubicin + 0.3 nM docetaxel. Cell death was measured 96 hours later and normalised to the vehicle condition. (E) Proportion of chemotherapy induced cell death caused by inhibiting indicated DSB repair pathway (NHEJ, alt-NHEJ, HR) with specific inhibitor (DNA-PKi, PARPi, RAD51i) respectively for (E) 231 Sen and, (F) 231 Res. Results represent the mean ± SEM for 3 independent experiments. Statistical analysis used was ANOVA followed by Tukey’s post hoc analysis. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 172 taxane and anthracycline in TNBC

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Figure 5-8. Standardized response of 468 Sen and 468 Res to specific drugs targeting key DDR proteins essential for canonical DDR pathways.

(A) 468 Sen and 468 Res cells were treated with vehicle (DMSO) or 10 µM of the indicated DDR inhibitors and irradiated with 5 Gy gamma radiation. Cell death was measured 96 hours later and normalised to the vehicle condition. (B) Proportion of irradiation induced cell death caused by inhibiting indicated DSB repair pathway (NHEJ, alt-NHEJ, HR) with specific inhibitor (DNA-PKi, PARPi, RAD51i) respectively for (B) 468 Sen and, (C) 468 Res. (D) 468 Sen and 468 Res cells were treated with vehicle (DMSO) or 10 µM of the indicated DDR inhibitors combined with 20 nM doxorubicin + 0.2 nM docetaxel. Cell death was measured 96 hours later and normalised to the vehicle condition. (E) Proportion of chemotherapy induced cell death caused by inhibiting indicated DSB repair pathway (NHEJ, alt-NHEJ, HR) with specific inhibitor (DNA-PKi, PARPi, RAD51i) respectively for (E) 468 Sen and, (F) 468 Sen. Results represent the mean ± SEM for 3 independent experiments. Statistical analysis used was ANOVA followed by Tukey’s post hoc analysis. *p<0.05,**p<0.01 ***p<0.001, ****p<0.0001.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 173 taxane and anthracycline in TNBC

5.2.9 RAD51 inhibition combined with chemotherapy enhances DNA damage induction and DDR activation In response to DNA damage, cells respond by activating DDR gene expression to sustain integrity of the genome. We next investigated the DDR gene expression profile in the MDA-MB-231 cell lines in response to chemotherapy alone and in combination with RAD51 inhibition. To this end, we used low-density arrays (DDR PCR Array; PAHS-042Z, Qiagen). Following 72 hours incubation with vehicle (DMSO), chemotherapy (30 nM doxorubicin + 0.3 nM docetaxel), or chemotherapy combined with 5 µM RAD51i (compound 17, characterised in chapter 4), RNA was extracted and the changes in the mRNA levels regarding DNA damage induction and DDR gene expression were analysed.

Fold expression changes for all 84 genes assayed for 231 Sen and 231 Res are depicted in Figure 5.9 and the gene list and numerical values for gene fold expression change are provided in Table 5.4. In summary, the 231 Res cells showed very little DDR gene induction in response to chemotherapy. In contrast, the 231 Res cells showed a very significant induction of DDR genes with the RAD51 inhibitor chemotherapy combination. The 231 Sen cells showed moderate induction of DDR genes in response to both chemotherapy and the RAD51 inhibitor chemotherapy combination.

In response to chemotherapy 231 Sen significantly upregulated ATM and DNA-PK which transcribe upstream DDR kinases. ATM is the main responder to DSBs and activates downstream targets CHK2 and p53 that initiate cell cycle arrest, DNA repair and apoptosis, while DNA-PK regulates DSB repair by NHEJ. Chemotherapy induced upregulation of CHK2 and p21 (a cyclin dependent kinase inhibitor) and downregulation of CDC25A (a promotor of cell cycle progression) and REV1 (involved in translesion synthesis), providing support for p53 mediated cell cycle arrest. Chemotherapy also induced upregulation of SMC1A, which transcribes a protein that interacts with BRCA1 to support repair by HR. Additionally, DDIT3 which transcribes a pro-apoptotic transcription factor was upregulated. Chemotherapy combined with RAD51 induced additional upregulation of genes that transcribe proteins involved checkpoint activation and DNA repair. HUS1 was upregulated and transcribes a component of the RAD9A-RAD1-HUS1 (9-1-1) checkpoint complex which responds to genotoxic stress (Balmus et al. 2015). Genes that transcribe proteins involved in HR were upregulated, including BLM, FANCG, BRCA1 (D'Andrea 2003), MLH3 (Ranjha, Howard, and Cejka 2018), XRCC2 and XRCC3 (Thacker and Zdzienicka 2003). KU70, a component of NHEJ (Thacker and Zdzienicka 2003) and PMS2 which is involved in mismatch repair (Zubani et al. 2017) were also upregulated.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 174 taxane and anthracycline in TNBC

For 231 Res chemotherapy induced upregulation of DNA-PK, HUS1 and XRCC2. In contrast, RAD51 inhibition combined with chemotherapy induced upregulation of 81 out of 84 DDR genes, suggesting a gene expression-mediated response in an attempt to evade cell death. The most marked increase was observed for p73, which shares significant sequence homology with p53 and is known to transcribe variants that have tumour suppressor and oncogene function. Three genes were downregulated; BARD1, CHK1 and CRY1. BARD1 transcribes a BRCA1 interacting protein required for BRCA1 stability and tumour suppressor function (Weber-Lassalle et al. 2019). CHK1 acts via both ATR dependent and independent pathways to induce cell cycle arrest and activate RAD51 mediated HR (Narayanaswamy et al. 2016) and CRY1 is a modulator in the ATR mediated DNA damage checkpoint response (Kang and Leem 2014).

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 175 taxane and anthracycline in TNBC

Figure 5-9. Expression changes in DDR genes induced by chemotherapy and chemotherapy combined with RAD51 inhibition for 231 Sen and 231 Res.

The scatter plots compare the normalised gene expression for the treatment condition against the cell line control for all the genes on the DDR array for 231 Sen and 231 Res. The central dotted line indicates unchanged gene expression (fold expression = 1). Data points above the top dotted line have increased gene expression (fold expression > 2). Data points below the bottom dotted line have decreased gene expression (fold expression < 0.5). Genes validated by qPCR are depicted for 231 Res (Chemo + RAD51i).

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 176 taxane and anthracycline in TNBC

Table 5-4 Expression changes in DDR genes in MDA-MB-231 Sen and MDA-MB-231 Res cell lines. Data compared to the cell line control (condition treated with DMSO)

Fold Change (comparing to 231 Sen Fold Change (comparing to 231 Res Vehicle Vehicle) Gene Sen Chemo + Symbol Sen Chemo RAD51i Res Chemo Res Chemo + RAD51i APEX1 0.9473 1.6406 1.0944 126.2317 ATM 2.3357 1.8148 1.048 2818.7862 ATR 1.2992 1.291 1.0449 822.2529 ATRIP 0.9859 0.9997 0.9898 3032.4256 ATRX 1.8421 1.332 1.2687 1622.7903 BARD1 1.5623 1.904 1.3765 0.0851 BAX 1.0772 0.4866 1.0043 3740.9804 BLM 1.5101 2.3909 1.4104 5290.1151 BRCA1 1.6091 2.4128 1.8705 6438.529 BRIP1 1.5745 1.2645 1.6887 14095.8683 c-ABL 0.7827 0.7756 0.6062 89.3512 CDC25A 0.3772 1.3128 1.0371 457.6722 CDC25C 1.223 1.0764 1.0691 5.5245 CDK7 1.0792 1.1716 0.9902 17.2064 CHEK1 1.6595 1.7051 1.0545 0.0969 CHEK2 2.1497 2.4474 1.2768 61.0178 CIB1 1.109 1.2615 1.1716 37.7854 CRY1 1.4276 1.6602 1.3325 0.0287 CSNK2A2 1.6332 1.6597 1.0624 419.4607 DDB1 1.2762 1.6055 1.1652 31.9558 DDB2 1.6146 1.2575 1.7447 56.8373 DDIT3 2.0609 3.4518 1.4623 220.7113 DNA-PK 2.4165 1.6006 2.207 80.6953 ERCC1 0.9329 0.9297 0.9239 303.047 ERCC2 0.9248 0.969 0.8588 79.1817 EXO1 0.9484 1.6143 1.1677 246.3575 FANCA 1.0649 1.7021 0.9585 57.47 FANCD2 1.6346 1.456 1.0781 23.2913 FANCG 0.9538 2.1145 1.0054 43.0338 FEN1 1.2013 1.3084 1.2378 13.6364 GADD45A 2.1806 1.7559 0.8357 63.4366 GADD45G 0.7513 1.8482 1.315 1364.6536 H2AX 0.8141 1.5424 1.1471 3.4099 HUS1 1.3314 2.4114 2.0073 287.9017 KU70 1.9778 2.6321 1.6462 8.7324 LIG1 0.8472 0.8192 0.893 736.335 MAPK12 0.8737 1.1656 0.8803 170.5986 MBD4 1.3086 1.6292 0.806 44.8858 MCPH1 1.1079 1.4091 0.9911 311.9718

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 177 taxane and anthracycline in TNBC

MDC1 1.2009 1.7613 0.8908 48.516 MLH1 1.1738 1.7017 0.9275 185.7411 MLH3 1.603 2.9086 1.0249 58.9174 MPG 1.1843 0.7114 1.1433 11.0996 MRE11 1.3846 1.5927 1.063 24.1324 MSH2 1.0964 1.2683 1.5392 46.3076 MSH3 1.3248 1.1666 1.4038 2416.1621 NBN 1.0001 1.0693 1.3492 95.7447 NTHL1 1.1317 0.944 1.2362 103.8481 OGG1 0.8554 1.0022 1.3316 45.1479 p21 2.9465 4.0677 0.9415 19.9453 p53 1.4861 2.3618 0.9783 167.0975 p73 0.9829 1.9611 0.6062 291113.5021 PARP1 0.6991 1.0627 0.9784 52.6454 PCNA 0.6701 0.9052 0.9601 2.1125 PMS1 1.218 1.7975 1.0267 151.9286 PMS2 1.394 2.4402 1.0328 184.2035 PNKP 0.6361 1.1679 0.8721 259.2979 PPM1D 0.9828 1.0355 1.0092 115.3903 PPP1R15A 1.3136 2.5081 1.4194 40.181 PUMA 1.028 1.8584 0.7249 3799.8142 RAD1 1.237 1.0969 1.2646 21.2612 RAD17 1.2682 1.5524 1.3942 128.6552 RAD18 1.3641 1.6796 1.5264 74.1742 RAD21 0.8891 1.1485 0.8164 2.8841 RAD50 1.1459 1.5127 0.978 43.2935 RAD51 1.5412 1.1885 1.2041 926.4522 RAD51B 1.3927 1.8854 1.1376 13.3917 RAD9A 0.8199 1.3797 1.0231 127.2612 RBBP8 0.8991 1.0335 1.0268 542.7011 REV1 0.029 0.5269 0.8402 130.4851 RNF168 1.089 1.9605 1.0035 144.6702 RNF8 1.2287 1.3161 1.4452 95.036 RPA70 1.1724 1.621 1.3492 18.6883 SIRT1 1.3249 1.3971 1.3809 54.0619 SMC1A 2.172 2.9717 1.184 16.9438 SUMO1 0.9426 1.0798 0.8503 65.4575 TOPBP1 0.9755 1.214 0.8414 73.7061 UNG 0.8543 0.6714 0.9386 115.7129 XPA 1.1068 1.0905 1.1625 105.7097 XPC 0.7777 1.389 1.0376 26562.0996 XRCC1 1.1908 1.1267 1.2174 367.6084 XRCC2 1.6022 3.796 2.0721 429.0783 XRCC3 1.0089 3.3466 0.9036 538.0346 53BP1 1.3361 1.3665 1.1952 25.2175

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 178 taxane and anthracycline in TNBC

Comments for Table 5.2: Fold-change values less than 1 indicate gene down-regulation and values greater than 1 indicate gene upregulation. Fold-change values greater than 2 are indicated in red; fold-change values less than 0.5 indicated in blue. 5.2.10 Chemotherapy induces differential DDR gene expression in sensitive and drug adapted cell lines To validate the gene array results we performed qPCR to assess expression of 18 genes included on the gene array (gamma-H2AX, RAD51, ATM, ATR, DNA-PK, PARP1, BRCA1, p73, p53, 53BP, RPA70, KU70, BRIP1 XPC, LIG1, PUMA, c-ABL) and additionally BRCA2, which transcribes a central component of the HR pathway and CEP2, a transcriptional target of p73. MDA-MB-231 and MDA-MB-468 cell lines were harvested for qPCR following 72 hours incubation with vehicle, chemotherapy, RAD51 inhibition and chemotherapy plus RAD51 inhibition ct values of experimental samples were normalised to the cell line vehicle control to determine the relative expression of genes in each sample. Fold expression changes for the genes assayed are depicted in figure 5.10.

In response to chemotherapy we observed four different gene expression profiles induced by drug treatment conditions; genes induced in both the Res and Sens lines, genes induced in only one cell line each and genes not induced in either cell line. Correlating with the array data we observed significantly upregulated p73 and DNA-PK in 231 Res compared to 231 Sen, and these genes were further upregulated with the addition of RAD51 inhibitor. This is an interesting finding since our results from section 5.8.2 show that DNA-PK inhibition has no effect on 231 Res survival with chemotherapy. In contrast to 231 Sen, 231 Res did not upregulate ATM, BRCA1, BRCA2 or BRIP1 in response to chemotherapy or RAD51 inhibition. Again this is an interesting finding since our results from section 5.8.2 show that the HR repair pathway (involving BRCA1 and BRCA2) plays a significant role in 231 Res survival with chemotherapy.

Of note, the p73 probes used for qRCR were not designed to distinguish between the different isoforms of p73. However we observed that chemotherapy induced upregulation of p73 in 231 Res was not accompanied by upregulation of TAp73 target genes PUMA, LIG1 or CEP2. This finding suggests that the p73 isoform expressed by 231 Res in response to chemotherapy might not possess the transactivation function of full length TAp73 and represents the truncated ∆Np73 isoform.

Chemotherapy induced upregulation of HR genes RAD51 and BRCA1 for 468 Res, and when RAD51 was inhibited, 468 Res responded by upregulating XPC. In contrast, 468 Sen responded with significant upregulation in genes that encode proteins required for

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 179 taxane and anthracycline in TNBC

NHEJ and alt-NHEJ, including DNA-PK, KU70, KU80 and PARP1 when RAD51 was inhibited.

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Figure 5-10 Expression profile highlighting key nodes induced by targeting DDR.

Expression of selected DDR genes was evaluated by qPCR following 72 hours incubation of with vehicle control (DMSO), chemotherapy (MDA-MB-231: 30 nM doxorubicin + 0.3 nM docetaxel, MDA-MB-468: 20 nM doxorubicin + 0.2 nM docetaxel), 5 µM RAD51 inhibitor, and chemotherapy plus RAD51 inhibitor. (A) Heat map depicting fold change in gene expression for 231 Sen and 231 Res for the listed treatment conditions and genes. (B) Heat map depicting fold change in gene expression for 468 Sen and 468 Res for the listed treatment conditions and genes. Fold change was calculated by comparing ct values to housekeeping genes and standardized to DMSO controls. Results represent the mean of 3 independent experiments with triplicate samples.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 181 taxane and anthracycline in TNBC

5.2.11 Chemotherapy induces differential DDR protein expression in sensitive and drug adapted cell lines Protein analysis of 231 Res revealed that DNA-PK did not display the classical phosphorylation in response to chemotherapy as seen in 231 Sen, although total DNA-PK protein expression was sustained (Fig. 5.11A). This suggested non-functional or ablated non-homologous end joining activity. We also observed associated increases in 53BP1 protein expression in 231 Res across all treatment conditions supporting activation of DNA- PK and non-homologous end joining activity (Fig. 5.11A). RAD51 protein expression was not enhanced and there was an associated loss of BRCA1 expression, suggesting suppression of homologous recombination. BRACA1 however is not essential for HR (Yazinski et al. 2017) and is likely compensated for by the observed upregulation of BRCA2.

Our DDR microarray and qPCR results showed that p73 was responsive to chemotherapy induced DNA damage particularly for 231 Res and western blotting showed an induction of p73 with associated repression of p53 activation, suggesting a switch in DNA damage sensing to p73. Importantly, we observed that p73 was expressed in the Sensitive and Resistant MDA-MB-231 (Fig. 5.11A) and MDA-MB-468 cell lines (Fig. 5.11B) with a band size of approximately 37 KD, which is consistent with the truncated anti-apoptotic ∆Np73 isoform. The predicted band size for full length TAp73 is 70 KD and none of the TNBC cell lines had detectable p73 at this size.

Neither of the MDA-MB-468 cell lines activated DNA-PK following chemotherapy suggesting that NHEJ was not the preferable DSB repair pathway (Fig. 5.11B). However it should be taken into consideration that DNA-PK phosphorylation can occur rapidly after DNA damage and is followed by dephosphorylation, hence although DNA-PK phosphorylation is not evident at 72 hours it may have occurred at an earlier timepoint. With RAD51 single agent inhibition the cells switched to activating DNA-PK thereby demonstrating that the NHEJ pathway could be utilised, however this did not occur with combined RAD51 inhibition and chemotherapy. This result suggests that 468 Sen and 468 Res are unlikely to use NHEJ as a backup repair pathway to combat chemotherapy induced damage if HR is blocked. Collectively the western blot results and survival outcomes with specific DSB repair pathway inhibitors (5.2.8) indicate that both 468 Sen and 468 Res engage RAD51 mediated HR in response to chemotherapy, however 468 Res show greater reliance on HR for survival.

In regard to variations in DDR protein expression compared to mRNA expression it should be noted that a correlation of ~0.40 is typical owing to factors that include post

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 182 taxane and anthracycline in TNBC transcriptional, translational and degradation regulation of protein concentration (Vogel and Marcotte 2012).

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Figure 5-11 Western blot analysis of differential DDR signalling induced by chemotherapy and RAD51 inhibition in sensitive and drug adapted cell lines.

(A) 231 Sen and 231 Res cells were treated with DMSO vehicle, chemotherapy (30 nM doxorubicin + 0.3 nM docetaxel), 5 µM RAD51i or chemotherapy + RAD51i for 72 hours. Cells were then harvested and 20 µg of protein was analysed by western blotting. α tubulin was used a loading control. (B) 468 Sen and 468 Res cells were treated with DMSO vehicle, chemotherapy (20 nM doxorubicin + 0.2 nM docetaxel), 5 µM RAD51i or chemotherapy + RAD51i for 72 hours. Cells were then harvested and 20 µg of protein was analysed by western blotting. α tubulin was used a loading control. The blots shown are representative of 3 independent repeats. .

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 184 taxane and anthracycline in TNBC

5.2.12 Depletion of p73 and restoration of WT p53 potentiate drug adapted cell lines to combination chemotherapy. We next explored the response of 231 Res cells to changes in expression of p53 and p73 under the pressure of chemotherapy treatment. We have shown that 231 Res cells induce p73 in response to combined chemotherapy treatment and do not significantly upregulate or activate mutant p53. Based on our gene expression and western blot results we hypothesise that the p73 isoform expressed by 231 Res is the truncated anti-apoptotic D∆Np73 isoform and that it promotes chemoresistance. Zhang, Sun, et al. (2019) showed that mutant p53 represses pro-apoptotic TAp73 signalling whereas wild type p53 lacks this function. Therefore we expected that knockdown of p73 by shRNA or transient overexpression of wild-type p53 to increase sensitivity to chemotherapy. To this end cells were transfected with control pcDNA, p73shRNA to knockdown p73 or p53pcDNA to overexpress wild-type p53. In support of our hypothesis knockdown of p73 resulted in significantly decreased cell proliferation (Fig. 5.12A) and increased cell death in the presence of chemotherapy (p<0.05) compared to the control (Fig. 5.12B). The extent to which overexpression of wild-type p53 diminished cell growth and enhanced cell death with chemotherapy approached significance (p<0.10). The results represent the mean ± SEM for two independent experiments with a transfection efficiency of ~30%. It is expected that higher transfection efficiency would enhance the detrimental effects seen with p73 knockdown and wild-type p53 overexpression.

After completion of imaging we harvested adherent (live) and non-adherent (dead) cells from each experimental condition for gene expression of p73, p53, DNA-PK, RAD51 and BRCA2. Further supporting our hypothesis we found cells (pcDNA transfected) that had survived chemotherapy had significantly upregulated p73 (>2-fold increase) while cells that did not survive had significantly decreased p73 (Fig. 5.12C). A trend was observed whereby induction of DNA-PK with chemotherapy was associated with cell death and p73 downregulation whereas induction of RAD51 and BRCA2 (in the absence of DNA-PK induction) was associated with cell survival (Fig. 5.12C). In p73 knockdown cells p53 induction following chemotherapy treatment was strongly associated with cell death (~32- fold increase) rather than cell survival (<2-fold increase). In cells expressing wild-type p53 we observed induction of p73 in cells that survived chemotherapy and loss of p73 in cells that died. In these cells p53 induction was more strongly related to death (>100-fold increase) than survival (19-fold increase).

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Taken together the results indicate that upregulation anti-apoptotic DNp73 and HR mediators RAD51 and BRCA2 facilitates survival following chemotherapy in the 231 Res cell line. Whereas in the presence of high D∆Np73 expression induction of DNA-PK does not result in successful NHEJ and these cells die. This is likely because , ΔNp73 binds 53BP1 inhibiting function, therefore depleting 53BP1 foci recruitment at DSBs and repressing non-homologous end joining (Wilhelm et al. 2010). Wild-type p53 restrains RAD51 induction in response to DNA damage while mutant p53 does not, further contributing to reliance on HR in 231 Res cells. The data also provides further support for reliance on RAD51 mediated HR for survival following chemotherapy.

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Figure 5-12 Depletion of p73 and restoration of p53 sensitise drug-adapted cells to chemotherapy.

231 Res cells were transiently transfected with pcDNA (control), p73shRNA (p73sh) and wild-type p53pcDNA (p53oe). 18 Hours after transfection media was replaced with media containing DMSO (vehicle) or chemotherapy (200 nM doxorubicin and 2 nM docetaxel). Nuc green dead 488 reagent was added to visualise dead cells. Live images were captured 3 hourly for a period of 72 hours. (A) Quantification of cell proliferation (% confluence) in control, p73 knockdown and p53 overexpressing 231 Res cells. (B) Quantification of cell death in control, p73 knockdown and p53 overexpressing 231 Res cells. The results represent mean ± SEM for two independent experiments with triplicate samples. Statistical analysis used was one way ANOVA followed by Tukey’s post hoc analysis, *p<0.05. (C) Heat map depicting fold change in gene expression following chemotherapy for listed genes in control, p73 knockdown and p53 overexpressing 231 Res cells. Fold change was calculated by comparing ct values from experimental samples to the value obtained for the matched pcDNA control. Results represent the mean for three biological replicates.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 187 taxane and anthracycline in TNBC

5.2.13 Small molecule RAD51 inhibition restores sensitivity to chemotherapy Having established an enhanced homologous recombination repair phenotype in chemoresistant cell lines, we wondered if targeting of the key repair protein RAD51 could sensitize these cells. Utilizing a validated small molecule inhibitor of RAD51 (compound 17, characterised in chapter 4) (Ward et al. 2017) 231 Res were significantly re-sensitized to the combination of docetaxel and doxorubicin and were also more sensitive to RAD51 inhibitor alone than 231 Sen, confirming a survival phenotype underpinned by homologous recombination.

The results depicted in Figure 5.13A-B showed that 231 Sen, 231 Res, 468 Sen and 468 Res cell survival was decreased by 1.9-fold (p<0.001), 6.8-fold (p<0.0001), 3.4-fold (ns) and 8.5-fold (p<0.001) when chemotherapy was combined with RAD51 inhibition compared to chemotherapy alone. When small molecule RAD51 inhibition was added to the treatment the Resistant cell lines became as sensitive or more sensitive to chemotherapy as the Sensitive cell lines.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 188 taxane and anthracycline in TNBC

Figure 5-13. RAD51 inhibition resensitises drug-adapted cell lines to chemotherapy.

Bar graph shows percentage cell survival for (A) 231 Sen and 231 Res following 120 hours days incubation with DMSO (vehicle), chemotherapy (30 nM doxorubicin + 0.3 nM docetaxel), 10 µM small molecule RAD51i and chemotherapy plus small molecule RAD51i. (B) 468 Sen and 468 Res following 120 hours incubation with DMSO (vehicle), chemotherapy (20 nM doxorubicin + 0.2 nM docetaxel), 10 µM small molecule RAD51i and chemotherapy plus small molecule RAD51i. Results represent the mean ± SEM for 3 independent experiments. Statistical analysis used was two way ANOVA followed by Tukey’s post hoc analysis. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 189 taxane and anthracycline in TNBC

5.3 DISCUSSION

Despite many advancements having been made in the treatment of breast cancer, recurrent, resistant TNBC and metastatic disease remains a major clinical challenge and cause of mortality (Bianchini et al. 2016). Consequently there is a strong need to identify resistance mechanisms and importantly how to bypass the resistance. To this end, resistant TNBC cell line models provide a valuable research tool for investigating the mechanisms that drive chemoresistance, evaluating molecular targets and testing new drug combinations and novel therapies. In this study we developed and characterised two drug adapted TNBC cell lines derived from the parental cell lines MDA-MB-231 and MDA-MB-468 by stepwise continuous exposure to both doxorubicin and docetaxel. The fold resistance of both cell lines was clinically relevant (greater than 3) and stably maintained after drug withdrawal.

The genomic instability of TNBC is often associated with dysregulation of DNA repair pathways, with some being upregulated, down-regulated or lost completely. Due to the redundancy of many components of DNA repair cells may compensate for defects in a particular pathway by utilising the remaining functional pathways (Curtin 2012). This presents both challenges and opportunities for treating TNBC. Tumours with upregulated DNA repair pathways may acquire resistance to DNA damaging chemotherapies. However reliance on a specific repair pathway or component for survival also exposes their Achilles heel and this weakness can be exploited therapeutically to induce synthetic lethality (Curtin 2012). By applying this we show a shift in reliance on NHEJ to HR and significantly increased dependency on RAD51 mediated repair for survival following chemotherapy. Considering HR was the preferred DNA repair pathway it is interesting that the Resistant cell lines were observed to downregulate HR mediator protein BRCA1 following treatment with chemotherapy. One would expect that loss of BRCA1 would be counterproductive to HR and chemoresistance. However studies utilising BRCA1 deficient tumour cells have shown that HR can occur independently of BRCA1 (Yazinski et al. 2017). Furthermore, BRCA1 deficiency is correlated with primary resistance to docetaxel-based chemotherapy in metastatic breast cancer patients (Wysocki et al. 2008; Isakoff 2010). In addition to its role in DNA repair BRCA1 is involved in cell cycle regulation and checkpoint activation. Chabalier et al. (2006) demonstrated that paclitaxel treatment activates the G2 and spindle checkpoints in MCF7 cells and knockdown of BRCA1 conferred paclitaxel resistance by prematurely inactivating the spindle checkpoint. Hence downregulation

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 190 taxane and anthracycline in TNBC of BRCA1 with chemotherapy treatment may confer resistance against to the docetaxel component while still allowing for efficient repair via HR.

It is likely that RAD51 mediated HR is essential to the survival of chemoresistant TNBC due to the complexity of DNA damage caused by combined doxorubicin and docetaxel chemotherapy (e.g., bulky DNA adducts, oxidative damage, SSBs, DSBs, microtubule stabilisation) coupled with underlying defects in DNA repair pathways which culminates in an extremely high level of replication stress. Defects in DSB repair pathways (NHEJ, alt- NHEJ) and SSB repair pathways (NER, BER, MMR) lead to an accumulation of damage at the replication fork. To overcome this blockade cells rely on RAD51 mediated DNA damage tolerance (DDT) mechanisms. Crucial RAD51 mediated DDT functions include; prevention of ssDNA degradation at stalled replication forks (Schlacher et al. 2011), remodelling replication forks that become uncoupled (Zellweger et al. 2015), filling in gaps in ssDNA (Adar et al. 2009) and repairing DNA damage that has been bypassed (Prado 2014b). Unlike cells with wild-type p53 these RAD51 mediated processes are uninhibited in mutant p53 tumours and provide a final opportunity for cells to replicate and repair DNA damage in the presence multiple DNA repair defects. Hence RAD51 inhibition effectively blocks the DDT pathways that the Resistant cell lines likely depend on for survival.

Genomic profiling of the TNBC cell lines used in the present study demonstrated a high level of genomic instability in all cell lines, evidenced by aneuploidy and gene copy number variations. The high level of genomic instability in TNBC drives both inter-tumour and intra- tumour heterogeneity (Wein and Loi 2017) which in turn increases the probability of resistant sub-clones arising prior to drug treatment commencement or developing under selective pressure during chemotherapy treatment (Gerlinger et al. 2012). Our genomic data shows that under the selective pressure of long term chemotherapy that additional mutations were acquired in the Resistant cell lines, with an overall decrease in chromosome number and altered copy number variations (predominantly losses) in key cell cycle, DNA repair and apoptotic genes. The reduced chromosome number in the Resistant cell lines represents a mechanism to lessen potential DNA damage and sensitivity to replication stress by decreasing the total amount of DNA that must be replicated each cycle (Passerini et al. 2016). Additionally the overall loss of genomic material likely provides a survival advantage to the Resistant cell lines via functional loss of tumour suppressor genes (Komarova and Wodarz 2004).

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Almost all TNBC harbor p53 mutations, with 93% of patients displaying somatic alterations (Wilson et al. 2019). Most p53 mutations confer resistance to drugs that directly target DNA or DNA synthesis (Liu, Banister, and Buckhaults 2019). In our study, the lines MDA-MB-231 and MDA-MB-468, have R280K and R273H p53 gain-of-function missense mutations, respectively. These mutations reduce DNA binding and infer reduced activation of cell death pathways (Leroy et al. 2014; Gomes et al. 2018). Cancer cells that harbor mutation of p53 modulate induction of apoptosis through p73 (Bergamaschi et al. 2003). p73 is most commonly thought to act as a tumour suppressor via induction of cell death pathways under oncogenic stress. We observed a loss of function in mutant p53 after drug adaptation, however with no associated induction of apoptosis via p73 (Bae et al. 2013). This is likely due to the exclusive expression of the ∆Np73 isoform that acts as a dominant-negative inhibitor. ∆Np73 competes with p53, TAp63 and TAp73 for promoter binding and inhibits the activation of target genes, thereby blocking apoptosis (Oswald and Stiewe 2008). Indeed, we did not see induction of the classical apoptosis target gene PUMA in 231 Res. However, apoptosis was achieved when exogenous functional p53 was expressed or restored by p73 depletion. In addition to evading apoptosis, we suggest that ∆Np73 contributed to the switch to dependence on homologous recombination. In contrast to TAp73, ∆Np73 binds 53BP1 inhibiting function, therefore depleting 53BP1 foci recruitment at DSBs and repressing non- homologous end joining (Di et al. 2013). Furthermore, ∆Np73 is a potent transactivator of homologous recombination genes; RAD51 and BRCA2 (Lin et al. 2009). Therefore, in contrast to serving as a tumour suppressor, we and others suggest that ∆Np73 acts as an oncogene (Stiewe and Pützer 2002b). Increased drug efflux resulting from upregulation of the ATP dependent efflux pump P- glycoprotein is a frequently identified resistance mechanism in TNBC (Liu, Chen, et al. 2017; Guestini et al. 2019; Zhang, Yang, et al. 2016). P-glycoprotein has multiple drug binding sites which are capable of binding and pumping a wide variety of drugs used in chemotherapy, including doxorubicin and docetaxel (Chen et al. 2016). In the present study we found that blocking P-glycoprotein partially restored doxorubicin sensitivity and that these mechanisms play at most a minor role in the chemoresistance observed. Additionally P- glycoprotein inhibition did not enhance sensitivity to docetaxel for 231 Res or to either drug for 468 Res. This result suggests that mechanisms other than P-glycoprotein are driving this resistance and prompted us to further explore the underlying mechanisms of resistance. Given the dominant role of P-glycoprotein upregulation in chemotherapy resistance there is a lot of interest in developing P-glycoprotein inhibitors. Four generations of P-glycoprotein

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 192 taxane and anthracycline in TNBC inhibitors have been developed to date and have shown promising results in in vitro however clinical trials with P-glycoprotein inhibitors have had limited success (Dong et al. 2020). For example early P-glycoprotein inhibitors, verapamil and cyclosporine, demonstrated issues with toxicity and high doses needed to achieve P-glycoprotein inhibition (Höll et al. 1992; List et al. 2001). Newer P-glycoprotein inhibitors such as tariquidar and zosuquidar, have increased potency and improved specificity for P-glycoprotein but their in vivo efficacy and safety are yet to be determined (Jackson et al., 2020).

While I was preparing this thesis our group established two additional chemotherapy resistant cell lines derived from parental TNBC cell lines BT549 and HS578T and repeated experiments described in this chapter. Both resistant cell lines showed loss of genetic material, a switch from NHEJ to HR repair and upregulation of p73. Significant chemotherapy resistance and p73/RAD51/c-ABL induction was recapitulated in the sensitive MDA-MB-231 cell line with a combination of targeting p53 and 53BP1 or p53 and DNA-PK. These results suggested that p53 destabilization is an early event followed by the loss of efficient non-homologous end joining either via 53BP1 switch or reduced DNA-PK expression/function resulting in chemoresistance and reliance on homologous end joining. Analysis of gene expression data from the phase 2 study (PROMIX trial) (GSE87455) revealed that high c-ABL1 expression (but not DNA-PK or RAD51) significantly stratified for poor outcome for TNBC patients who received chemotherapy. c-ABL induction with combined chemotherapy and RAD51 inhibition validated from our array and qPCR data. However, neither c-ABL knockdown or c-ABL inhibition with a current clinical trial drug, asciminib enhanced sensitivity to chemotherapy in our chemotherapy resistant MDA-MB- 231 TNBC cell line. This suggests that c-ABL1 is potential biomarker for chemoresistance in TNBC but not a good target to overcome it. In conclusion, loss of integrity of the DDR is crucial to chemotherapy responsiveness and development of chemoresistance in TNBC. Our findings suggest that in the landscape of p53 mutations that chemotherapy responsiveness in TNBC is influenced by upregulated expression of ∆Np73 and loss of genetic material via low fidelity NHEJ. We suggest the pressure on DNA damage sensor p53 and NHEJ mediator DNA-PK cause enhanced genetic loss and acquisition of mutations. This in turn results in a reliance upon HR and RAD51 function. Based on our results we suggest RAD51 as a rational clinical target to resensitize resistant tumours to chemotherapy.

Chapter 5: RAD51 inhibition overcomes dysregulated DDR mediated resistance to the combination of 193 taxane and anthracycline in TNBC

Chapter 6: General discussion and future directions

The lack of targetable receptors, development of chemotherapy resistance and high rate of distant metastasis presents an enormous challenge in the treatment of patients with TNBC. In the era of personalised medicine, cancer drug discovery efforts have transitioned from cytotoxic chemotherapies to molecularly targeted therapies to bypass serious side effects due to a lack of selectivity (Chen and Jin 2017). Compounds designed to target proteins or signalling pathways that are cancer-specific or upregulated in tumour cells are typically less toxic and better tolerated than conventional chemotherapy (Chen and Jin 2017). Currently there are no targeted therapies approved to treat sporadic TNBC. The identification of molecular targets in TNBC that are clinically actionable will help to improve treatment outcomes for these patients (Liu, Saber, and Haisma 2019).

Cancer genetic dependencies are referred to by various terms in the literature, including ‘addictions’, vulnerabilities’ and ‘cancer essential genes’ (Lin and Sheltzer 2020). These genetic dependencies may be acquired during tumourigenesis and be specific to a particular type of tumour, for example the BCR-ABL translocation that is a hallmark of CML (Lin and Sheltzer 2020). Alternatively, the gene or protein product may have a function in non-cancerous cells but is upregulated and/or particularly important for tumour growth and survival (Lin and Sheltzer 2020). RAD51 recombinase, the central protein in homologous recombination repair represents a genetic dependency in TNBC that when knocked out or inhibited impairs replication and triggers cell death (Behan et al. 2019). Overexpression of RAD51 and upregulation of RAD51-mediated HR provides a rescue mechanism for tumour cells with high levels of replication stress and abnormal DNA damage checkpoints, which are characteristic of TNBC. This addiction to RAD51 makes it a promising therapeutic target (Ward, Khanna, and Wiegmans 2015). Since RAD51 mediated HR repair is predominantly active in replicating cells and non-cancerous cells have access to multiple redundant DNA repair pathways, disruption of HR has little impact on cells of normal tissue, while being detrimental to rapidly proliferating cancer cells (Laurini et al. 2020; Helleday 2018). Additionally, compared to normal cells RAD51 is often significantly upregulated in TNBC (Wiegmans et al. 2014). These observations suggest that targeted small molecule inhibition of RAD51 may enhance TNBC sensitivity to conventional chemotherapy and irradiation by reducing HR. Our results from chapter 4 provide strong support for RAD51 as a molecular

Chapter 6: General discussion and future directions 194 target in TNBC and confirm that small molecule inhibition of RAD51 does indeed enhance response to chemotherapy (doxorubicin and cisplatin) and irradiation induced DNA damage. Furthermore, sensitivity to small RAD51 inhibition positively correlated with RAD51 expression in TNBC cell lines, which confers selectivity for high RAD51 expressing cancerous cells compared to low RAD51 expressing normal cells.

Discovery of the synthetic lethal interaction between PARP inhibitors and mutations in BRCA1 and BRCA2 by two research groups in 2005 (Bryant et al. 2005; Farmer et al. 2005) paved the way for the first semi-targeted treatment of TNBC. Currently PARP inhibitors are approved for a small sub-population of TNBC patients with BRCA1/2-associated metastatic disease, however PARP inhibitors have little impact on tumour growth and apoptosis for patients with HR-proficient sporadic TNBC or PARP inhibitor resistant BRCA1/2 associated cancers (Veneris et al. 2020). Expanding the population of patients who might derive benefit from PARP inhibitors is a worthy goal and one that might be achieved with small molecule RAD51 inhibition. Small molecule targeting of RAD51 in HR-proficient TNBC is a rational approach to induce synthetic lethality with PARP inhibitors. This targeting would create an HR deficient setting and transform current non-responders to PARP inhibitors into responders and transform responders into super-responders. We showed a synergistic interaction between the PARP inhibitor veliparib and our lead small molecule RAD51 inhibitor compound. The therapeutic power of veliparib was significantly increased when combined with RAD51 inhibition in HR-proficient TNBC compared to veliparib alone. Further exploration of dosage and scheduling of each drug to maximize cancer cell killing and minimize adverse events is needed to optimize outcomes.

Whether RAD51 inhibitor-PARP inhibitor combination outcomes translate from the laboratory bench to the clinic is dependent on the success of small molecule RAD51 inhibitors progressing through the necessary stages of the drug development pipeline to clinical trials. Despite several research groups having developed small molecule RAD51 inhibitors in the past decade that show promise in in vitro and in vivo studies, for example B02 (Huang and Mazin 2014; Huang et al. 2012; Huang et al. 2011), RI series (Budke, Kalin, et al. 2012; Budke, Logan, et al. 2012), IBR series (Zhu et al. 2015; Zhu et al. 2013), Cambridge series (Scott et al. 2015; Scott, Ehebauer, Pukala, Marsh, Blundell, Venkitaraman, Abell, and Hyvönen 2013; Scott et al. 2016) only one, CYT-0851 (Day, Maclay, and Mills 2019) has advanced to clinical trial (phase I-II) (ClinicalTrials.gov, NCT03997968), which highlights the frustratingly slow pace and high failure rates associated with drug development, in particular the targeting of RAD51.

Chapter 6: General discussion and future directions 195

In the discovery and development of small molecule RAD51 inhibitors, our group and several other research groups have identified multiple promising ‘hit’ compounds that bind RAD51 and inhibit HR repair with in vitro IC50 concentrations in the micromolar range. By introducing a 1 4-chlorobenzyl to the R1 motif of our base quinazolinone compound (B02) we enhanced binding to RAD51 and showed increased biological inhibition of RAD51 and HR in TNBC cell lines. We anticipated further improvements in compound binding and biological activity following specific modifications to motifs R2 and R3, however these modifications did not produce the desired outcome. Like other researchers in this field we struggled to generate a strong ‘lead’ compound with nanomolar range activity that was a suitable candidate for clinical trials. Similar issues were encountered with the RI series of small molecule RAD51 inhibitors. The initial lead compound RI-1 incorporated a toxic Michael acceptor (Budke, Logan, et al. 2012) and further SAR study was conducted to identify analogues that retained RAD51 inhibitory activity without requiring Michael acceptor activity, yielding RI-2. RI-2 inhibited RAD51-ssDNA activity but had an up to 6-fold increased IC50 concentration compared to RI-1 in cell based assays (Budke, Kalin, et al. 2012). Further rounds of SAR analysis identified RI-2h which inhibits RAD51-dsDNA activity but does not inhibit RAD51-ssDNA activity (Budke et al. 2019). This was undesirable, as RAD51 binding to ssDNA at stalled replication forks is a mechanism that tumour cells use to withstand replication stress and avoid apoptosis. Thus we found a common divide between the expected medicinal chemistry principles and the observed biological results (Hoelder, Clarke, and Workman 2012). The process of lead optimisation in drug development is further complicated by the fact that multiple research groups are often working competitively on the same molecular target. Negative results are often not published, which can potentially lead other research groups to waste time and resources pursuing redundant experiments (Mlinarić, Horvat, and Šupak Smolčić 2017). Alternatively, the chemical structures of promising compounds, the reagents and methods used to derive compounds and detailed experimental methods may not be published due to intellectual property hoarding. This is the case with RAD51 inhibitor CYT-0851 which has progressed to clinical trials. The decision not to publish chemical structures of drugs and methods with sufficient detail to be reproducible is likely motivated by a fear of being scooped by competing research groups or companies, which is undeniably a realistic concern. It has a detrimental effect on the collaborative nature of science and may ultimately impede the discovery of life saving drugs (Schapira, Open Lab Notebook, and Harding 2019).

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In addition to its well described recombinase function during HR, RAD51 is a multitasking protein that performs other biological functions, referred to as protein moonlighting (Jeffery 2019). These moonlighting functions include; RAD51 interaction with transcription factor CEBPβ to regulate pro-metastatic gene expression (Wiegmans et al. 2014), RAD51 binding to unwound ssDNA providing stalled replication fork stabilisation (Kolinjivadi et al. 2017; Mason et al. 2019), and RAD51 binding to short DNA fragments in the nucleus preventing their release into the cytosol, thereby suppressing activation of innate immune signaling (Bhattacharya et al. 2017; Wolf et al. 2016; Pépin and Gantier 2017). Our understanding of the moonlighting functions of RAD51 and their contribution to cancer development, progression, metastasis and treatment resistance is very limited. Further investigation of these functions, how they influence each other, how they are regulated and how they respond to small molecule RAD51 inhibition could provide clues to new ways to treat TNBC. Wiegmans et al. (2014) identified 84 pro-metastatic genes regulated by RAD51 in concert with CEBPβ, which potentially may represent only a small fraction of pro-cancer gene profiles modulated by RAD51. We have shown in Chapter 3 that CRISPR gene editing is not a viable technique for studying RAD51 multi-functionality due to it being a cancer essential gene, however small molecule inhibitors that disrupt unique RAD51 binding interactions could be useful tools in RAD51 functionality studies. Disruption of RAD51- ssDNA with our compound would inhibit replication fork stalling, small peptide transport such as that observed in loading exosomes and non-coding strand transcription. We estimate this would equate to enhanced genome instability, reduced signalling to distant sites and reduction in pro-metastatic gene expression, all contributing to inhibition of primary and secondary tumour growth. In contrast disruption of RAD51-dsDNA with compound RI-2h, is likely to inhibit strand exchange resulting in inhibition of DNA repair function and enhanced genome instability. With the addition of RAD51 silencing and CEBPβ silencing as controls for loss of DNA repair and transcription would help to delineate the relative importance of RAD51 binding interactions in transcriptional regulation.

The involvement of RAD51 in both the DNA damage response and immune signalling raises interesting possibilities for combinational strategies targeting these pathways to improve immune mediated clearance of tumours. Genomic instability, replication stress and genotoxic treatments associated with cancer cause the release of fragmented DNA from the nucleus into the cytoplasm, triggering immune signalling (Li and Chen 2018; Bhattacharya et al. 2017). Cytosolic self-DNA is recognised by cyclic GMP-AMP synthase (cGAS) which recruits and activates the STimulator of INterferon Genes (STING) protein. Activated STING

Chapter 6: General discussion and future directions 197 promotes pro-inflammatory signalling pathways, such as those regulated by NF-KB, and the subsequent production of interferons and chemokines that attract and activate immune cells in the tumour microenvironment (Klarquist et al. 2014; Woo, Corrales, and Gajewski 2015; Bakhoum et al. 2018). In BRCA-mutant tumour cells, PARP inhibition has been shown to increase cytosolic DNA accumulation and STING activation and lead to increased Type 1 interferon production, but not in HR-proficient cells (Shen et al. 2018; Pantelidou et al. 2019). In vivo, CRISPR-mediated knockout of STING significantly impaired T-cell infiltration and PARP inhibitor shrinking of tumours, demonstrating that both HR-deficiency and STING activation are required for optimal PARP inhibitor efficacy (Pantelidou et al. 2019). However, in addition to its immune priming effect PARP inhibition can have an immune suppressive effect by promoting adaptive overexpression of cell surface programmed death ligand 1 (PD- L1) (Jiao et al. 2017; Sen et al. 2019). In HR-proficient tumour cells it has been shown that downregulation of RAD51 increases accumulation of self-DNA in the cytoplasm, triggering a STING-mediated innate immune response after replication stress and DNA damage (Bhattacharya et al. 2017). It is likely that RAD51 inactivation or depletion, and activation of the STING pathway also has both immune priming and immune suppressive effects although this is yet to be tested.

HR-deficient tumours with BRCA1/2 mutations are associated with a higher mutational load resulting in generation of neoantigens (Lin 2018; Wen and Leong 2019). Neoantigens are capable of activating cytotoxic T cells and increasing tumour cell immunogenicity and responsiveness to immune checkpoint blockade (Wen and Leong 2019). Hence our lead RAD51 inhibitor compound which disrupts RAD51-ssDNA activity and HR may serve as an immune primer in HR proficient TNBC. Small molecule inhibition of RAD51-ssDNA activity would be expected to induce accumulation of cytoplasmic DNA and activation of the STING pathway. The induction of HR-deficiency would be expected to enhance generation of neoantigens via increased mutational burden. Further work to test these hypotheses is warranted. Taken together these findings raise the prospect of using small molecule RAD51 inhibition as an adjuvant in combination with PARP inhibitors and anti-PD-1 or anti-PD-L1 antibodies in HR-proficient TNBC.

Tumour resistance to frontline chemotherapy is the main cause of breast cancer related deaths. In order to spare patients from aggressive therapies that are ineffective and toxic we need to identify biomarkers that accurately predict tumour response to chemotherapy and develop effective targeted strategies to overcome resistance. Whole exome sequencing of drug adapted cell lines has revealed a wide variety of genomic

Chapter 6: General discussion and future directions 198 variations that predict for resistance, even within clones of a single cell line. Nonetheless, not a single genomic marker adequately predicts resistance (Hansen et al. 2016). Understanding the stresses on the DNA damage repair pathways in adaptive response to chemotherapy is crucial for monitoring the emergence of chemoresistance. In our investigation of chemotherapy resistant TNBC cell lines we observed a switch from DSB repair by non-homologous end joining to reliance upon high fidelity homologous recombination after drug adaption. In contrast to our expectation, upregulation of homologous recombination repair in drug adapted cell lines was not accompanied by increased expression of RAD51. Chemo-resistant cell lines were exquisitely sensitive to small molecule RAD51 inhibition with our lead compound, showing that dependence on the homologous recombination repair pathway rather than RAD51 upregulation is the key determinant of sensitivity to small molecule RAD51 inhibition. We observed that chemotherapy resistance was also accompanied by significant upregulation of ΔNp73. We suggest that ΔNp73 contributed to the switch to dependence to homologous recombination in drug adapted cell lines. In contrast to WTp73, ΔNp73 binds 53BP1 inhibiting function, therefore depleting 53BP1 foci recruitment at DSBs and repressing non-homologous end joining (Wilhelm et al. 2010). Therefore in contrast to serving as a tumour suppressor we and others suggest a ΔNp73 acts as an oncogene (Stiewe and Pützer 2002a).

To identify a potential biomarker for patient response to chemotherapy our group conducted follow up studies focused on DNA damage response genes that were upregulated in response to chemotherapy in drug adapted cells (identified from array and qPCR data in chapter 5). Interrogation of gene expression data from the phase 2 study (PROMIX trial) (GSE87455) revealed that high c-ABL1 expression significantly stratified for poor outcome for TNBC patients who received chemotherapy (unpublished data). Recapitulation of the DDR adaptions leading to homologous recombination dependency and c-ABL activation promoted resistance to chemotherapy in drug sensitive TNBC cells. However, neither p73 knockdown or p73 inhibition with a current clinical trial drug, Asciminib enhanced sensitivity to chemotherapy in our drug adapted MDA-MB-231 TNBC cell line. This suggests that c-ABL1 is an excellent biomarker for chemoresistance but not necessarily a biological target to overcome it. We suggest the downstream homologous recombination effector, RAD51 as a rational clinical target to resensitize resistant tumours to chemotherapy. To move forward from basic to translational research, future work could expand to in vivo patient derived xenograft models of chemotherapy resistant TNBC to examine remission of tumour growth with our lead small molecule RAD51 inhibitor in

Chapter 6: General discussion and future directions 199 combination with chemotherapy or alternative combinations with PARP inhibition and anti- PD-L1 antibodies.

6.1 CONCLUDING REMARKS

The activity of RAD51 makes a significant contribution to the development, progression, metastasis and treatment outcomes of TNBC. This thesis is the first study to evaluate the utility of CRISPR-Cas9 mediated gene editing of RAD51 to achieve stable knockout or specific knock-in mutations in TNBC tumour cell lines. CRISPR-Cas9 gene editing is frequently described as an easy and effective method for achieving stable gene knockout and specific gene knock in mutations to examine phenotypic consequences, such as chemotherapy resistance and metastatic potential. The only comments about RAD51 in published studies utilising CRISPR relate to its role in achieving gene editing via homologous recombination mediated integration of a DNA repair template or the absence of enrichment of clones transfected with RAD51 guide RNA in pooled screening studies. Based on our results in chapter 3 it is very clear that CRISPR-Cas9 is not a suitable technique for the manipulation of RAD51 expression in TNBC, and most likely the majority of cancers. The reason for this is that RAD51 is a cancer essential gene, hence stable disruption of its essential function, homologous recombination, via specific mutation or total protein loss is not compatible with cancer cell survival. The induction of transient alterations to RAD51 expression or reversible small molecule inhibition represent suitable alternatives for studying RAD51 in TNBC.

In chapter 4 we identified a novel small molecule inhibitor of RAD51 inhibitor that acts by disrupting RAD51-ssDNA activity, thereby inhibiting RAD51 foci formation in response to DSBs and subsequent repair by homologous recombination. We showed that small molecule RAD51 inhibition enhances sensitivity to DNA damaging chemotherapy, irradiation and synergises with PARP inhibition in HR-proficient TNBC. The chemical structures of all compounds screened, the reagents and methods used to derive compounds and detailed experimental methods have been published and can thereby be utilised by other researchers to further our understanding of RAD51. In chapter 5 we developed chemotherapy resistant models of TNBC to study the DDR mechanisms that contribute to chemotherapy resistance. We identified alterations to the DDR acquired during long term chemotherapy lead to a switch from non-homologous end joining to upregulation and reliance upon RAD51 mediated homologous recombination. Small molecule targeting of RAD51 with our lead compound resensitised resistant TNBC to chemotherapy. The results presented in chapter 5 led to follow up studies that identified c-ABL as a potential predictive

Chapter 6: General discussion and future directions 200 biomarker of TNBC patient response to conventional chemotherapy. The ability to predict tumour response at the time of diagnosis would facilitate the personalisation of TNBC treatment and ensure that chemotherapy is given only patients who are mostly likely to benefit.

Chapter 6: General discussion and future directions 201

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Appendix

Figure A1 Inhibition of irradiation induced RAD51 foci formation with compounds 1-17. (A) TNBC MDA-MB-231 cells were incubated with 5 µM or (B) 10 µM of compound for 2 hours, irradiated with 6 Gy gamma irradiation and harvested 6 hrs post irradiation. DAPI stained cells and RAD51 and gamma-H2AX foci were quantified following immunofluorescent staining using the GE InCell Investigator software. The data represents the ratio of RAD51 foci (nuclear intensity) / gamma-H2AX foci (nuclear intensity), with lower ratios indicating greater RAD51 foci inhibition.

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Figure A2 Dose response curves for B02 and compounds 1-17 in combination with PARP inhibitor. Dose response curves for TNBC MDA-MB-231 cells was determined by MTS assay following 5 days incubation with B02 and compounds 1-17 (0, 0.625, 1.25, 2.5, 5, 10 uM) + 2.5 uM PARP inhibitor (ABT-888)

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Table A1 Comparison of IC50 values for B02 and top four compounds (1-17) in TNBC cell lines measured by MTS cell viability assay.

Compound IC50 (µM) B02 23.78 B02 + 2.5 µM PARPi 10.94 15 + 2.5 µM PARPi 9.24 10 + 2.5 µM PARPi 8.79 17 + 2.5 µM PARPi 5.48 6 + 2.5 µM PARPi 4.96

IC50 concentrations determined from dose-response curves shown in Figure A2.

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