Sir Peter MacCallum Department of Oncology - Theses
Now showing items 1-12 of 117
A Genome-wide RNAi screen identifies combinatorial efficacy of CX-5461 with homologous recombination deficiency and Topoisomerase I inhibition in ovarian cancer
High-grade serous ovarian cancer (HGSC) is common, with poor prognosis. Limited therapeutic options are available, and the development of new therapies is of high priority. The RNA Polymerase I (Pol I) transcription inhibitor CX-5461 has shown efficacy in both chemotherapy-sensitive and -resistant ovarian cancer through its ability to activate the DNA damage checkpoint. Here, we combine a genome-wide RNAi screening approach with a focussed drug screen to identify potential targets whose inhibition can enhance the efficacy of CX-5461. We demonstrate that CX-5461 combined with knockdown of homologous recombination DNA repair genes shows cooperative cell proliferation inhibition in several HGSC cell lines. We also demonstrate combinatorial efficacy between CX-5461 and topoisomerase 1 (TOP1) depletion or the TOP1 poison Topotecan. The combination induces cell death, cell cycle arrest and senescence even after drug withdrawal. The mechanism of their cooperativity relies on a cell cycle-independent, nucleolar DNA damage response (DDR) associated with topological stress at the ribosomal DNA and is independent of the ability to inhibit PoI I transcription or induce global replication stress. Despite dose-limiting toxicities hampering the broad use of Topotecan in the clinic, combined treatment with CX-5461 and low-dose Topotecan exhibits striking therapeutic efficacy in vivo, thus providing evidence for a novel strategy to treat HGSC.
A health and economic impact analysis of robotic surgery for the treatment of localised prostate cancer in the Victorian public health system
Background: The rising prevalence of prostate cancer in Australia will increasingly contribute significant morbidity, mortality and economic burden on society. Radical prostatectomy is the mainstay of treatment for localised prostate cancer, and robotic prostatectomy the dominant surgical approach to management in the United States and Europe. Large systematic reviews have demonstrated some perioperative and functional benefits of robotic over open and laparoscopic approaches, however no differences in oncological outcomes have been demonstrated to date. The cost of the robot is undoubtedly greater than open and laparoscopic approaches however studies have shown a significant cost offset due to reduced length of stay and other improved clinical outcomes. We aim to perform a comprehensive health and economic impact analysis of robotic surgery for the treatment of localised prostate cancer in the Victorian public health system since the introduction of the da Vinci surgical robot to Peter MacCallum Cancer Centre (Peter Mac) in July 2010. Methods: To compare patterns of care and perioperative outcomes of robotic prostatectomy to other approaches, we utilised a large dataset from the Victorian Admitted Episodes Dataset (VAED) including all prostatectomy patients performed in the Victorian public sector since the installation of the da Vinci robot. Additionally the RARP series of perioperative, complication, oncological, functional and quality of life (QOL) outcomes at Peter Mac was compared to local, national and international literature. We then created an economic model to evaluate the incremental cost of robotic-assisted radical prostatectomy (RARP) versus open radical prostatectomy (ORP) and laparoscopic radical prostatectomy (LRP), incorporating the cost-offset from differences in length of stay and blood transfusion rate. The economic model constructs estimates of the diagnosis-related group (DRG) costs of ORP and LRP, adds the gross cost of the surgical robot (capital, consumables, maintenance and repairs), and manipulates these DRG costs to obtain a DRG cost per day, which can be used to estimate the cost-offset associated with RARP in comparison with ORP and LRP. Economic modelling was performed around a base-case scenario assuming a 7-year robot lifespan and 124 RARPs performed per financial year. One and two-way sensitivity analyses were performed for the four-arm da Vinci S HD, Si and Si dual console surgical systems. Results: The robotic surgical approach has become the dominant technique to radical prostatectomy for localised prostate cancer in the Victorian health system over ORP and LRP. The introduction of a surgical robot to the Victorian public system has resulted in centralisation of prostatectomy to Peter Mac with huge institutional growth since its instillation. Length of hospital stay and blood transfusion rates are significantly improved with the robotic approach. Positive surgical margin rates with RARP are improved compared to prior Victorian data consisting of primarily an ORP cohort. Complication and oncological outcomes of RARP are comparable between surgical approaches and to large international RARP series. Definitive comparison of RARP functional and QOL outcomes between approaches was difficult without a comparative cohort however compared favourably with previous literature. Improvements in length of stay and blood transfusion rates offset most of the additional cost of the robot in the base case scenario where 124 robotic cases are performed per year. RARP can become cost-equivalent with ORP where ~140 cases are performed in the base-case scenario. Increasing the surgical volume, lifespan of the robot and reducing the cost of the consumables can ameliorate cost. Conclusions: The da Vinci surgical robot has been safely introduced into the Victorian public health system at Peter Mac. The addition of the robot has significantly altered the way we treat patients with localised prostate cancer in Victoria. The robotic approach confers some clinical advantages compared to laparoscopic and open prostatectomy consistent with international literature, and the reduction in length of stay offsets much of the increased cost of the robotic procedure.
Addressing the barriers to translating genetic sequencing into a clinical oncology setting
The molecular diagnostics of cancer are being transformed globally by the adoption of affordable high-throughput sequencing (HTS) to identify a patient’s genetic changes that can be matched to targeted therapies. However, many of the laboratories that have adopted these technologies do not have adequate capabilities in the key dimensions of clinical HTS diagnostics. Laboratories do not have the trained staff with the capabilities for analysis and do not have adequate software to tackle the bioinformatic pipelines, curation, and clinical informatics, which are essential for the maintenance of a robust, clinically defensible HTS assay. The clinicians who rely on results from laboratories that use HTS must be aware of the many limitations of these technologies, which can affect their patients’ outcomes profoundly. The pace of development of software in cancer diagnostics has not matched that of HTS hardware. This research addresses this software gap in the capabilities of HTS diagnostics. This is achieved by designing, developing and deploying a range of software that can be used in a HTS pathology laboratory. Additionally the software can be used by clinical trials and large research projects requiring volume HTS in a clinical setting. The software developed through this translational research covers three broad areas; 1) the bioinformatic pipelines that process the sequencing data, 2) the testing of these pipelines and 3) the analysis and reporting of processed sequencing data. This thesis describes three systems within these areas. Firstly, Canary  is an integrated single command pipeline that performs multiple tasks in a single Java executable file. Secondly, PipeCleaner is a pipeline testing framework incorporating the ability to generate synthetic data and write pipeline tests in a domain specific language. Finally, PathOS is a web based application allowing laboratory scientists to filter, analyse, curate and report on patient variants in high volumes. Both PathOS and Canary have been deployed into a large cancer hospital pathology laboratory and are under active development. Additionally, PathOS, and the associated tools developed with it, are being actively used by the wider research community. The volume of molecular diagnostic testing in cancer has expanded from single exon and single gene assays into progressively larger panels of hundreds of genes and whole exome and genome assays. The introduction of ctDNA assays into clinical use, further allows a patient to be readily tested multiple times during their health care encounter. On the horizon, single cell sequencing may offer deeper diagnostic insights into a patient’s disease. To deal with these increasing volumes of assays and data, robust, high quality software will be needed to scale the laboratory capacity for the future.
Advancing the risk prediction and effective management of infection in patients with myeloma in the era of novel therapies
Infections are a leading cause of morbidity and mortality in patients with myeloma (MM). Increased risk for infections is due to a range of patient-, disease- and treatment-related factors. The major change in the management of MM has been the recent paradigm shift to immunomodulatory drugs (IMiDs) and proteasome inhibitor (PI)-based therapies. In this era, the pattern of infections, risk periods and risk factors for serious infections remains largely undefined. Without this knowledge, effective management of infection and preventative measures that could reduce risk and burden of infections cannot be optimally delivered. Clinical infection risk assessment is becoming unreliable with increasing use of agents with wide-ranging effects on the immune system. This thesis had two primary research aims. The first was to determine the pattern, risk period and clinical determinants for infection in patients managed in the era of novel therapies and to define how these factors vary by treatment period for a range of significant infections. To improve infection management, the second aim of the thesis was to assess the feasibility of immune profiling as a means of predicting future risk for infection. To address the first aim, a longitudinal cohort study was undertaken to establish the epidemiology and risk factors for infection overall and by disease treatment period. Bimodal peaks in incidence of bacterial and viral infections were noted. Treatment with conventional agents and corticosteroids was independently associated with increased risk for infection overall and through key treatment periods, while IMiDs and PIs were not when evaluated against patient and disease factors and conventional agents. This was followed by a series of studies evaluating infections associated with significant burden and mortality, namely varicella zoster, viral respiratory tract infections, bacterial bloodstream infections (BSI) and invasive fungal infections (IFI). Overall, these studies found distinct shifts in patterns of BSI and IFI, identified disease progression to be a high-risk period, multiple lines of therapy (≥ 3) to be an independent risk factor and confirmed the efficacy and duration of antimicrobial prophylaxis. A systematic review and meta-analysis of MM therapy comprehensively established infection rates, contrasted risk for serious infection between the current standard of care (IMiDs and PIs) with the previous standard, and between IMiDs and PIs. In this setting, differential risk for infection by type of IMiD and PI was detected with variation by treatment period. In testing the second research objective, profiling cytokine release in response to mitogen stimulation was feasible and useful for predicting subsequent risk for infection, while numerical evaluation of immune cells was unhelpful. A predominance of T helper-2 cytokine response to mitogen stimulation was associated with future risk for infection. Findings from this body of work have advanced our understanding of infections in this field and enabled the establishment of a future research agenda; studies of preventative measures targeting heavily treated patients with disease progression; evaluation and validation of identified immune profiles in a prospective patient cohort to define its clinical utility; and ultimately, to comprehensively integrate clinical parameters with immunological profiling to advance personalised anti-infective management and prevention in patients with MM.
An investigation of type-1 interferon and the immune response against breast cancer metastasis
Breast cancer is a highly prevalent disease that, like many cancers, lacks effective therapies aimed at treating and preventing metastasis. Harnessing the host immune system to recognise and eliminate malignant cells has recently emerged as an effective therapeutic strategy in many cancers. However, response rates to these approved immunotherapies remain modest in the absence of a more detailed understanding of tumour immunity. The type I interferons are a family of cytokines that have long been understood to enhance the immune response to cancers, though their clinical application has led to underwhelming results in numerous types of cancer. This thesis provides new evidence that proposes the re-visitation of cancer immunotherapies that stimulate the type I interferon pathway. We show that host-derived type interferon is critical for the suppression of breast cancer metastasis through natural- killer cell activation. Induction of a type I IFN response by administering agents that mimic a viral infection (poly(I:C), a double-stranded RNA analog) proved to be powerful anti-metastatic agents in multiple pre-clinical models of triple-negative breast cancer (TNBC). This was linked to widespread immune activation which conferred NK cells with enhanced cytotoxic function to eliminate disseminated tumour cells. The efficacy of this novel immunotherapeutic approach was also found to rely upon the treatment setting in which it was used. Evidence is presented that demonstrates administration prior to primary tumour removal (neo-adjuvant therapy) as the only effective therapeutic regimen. We propose that such immunotherapies are most effective at eliminating circulating and early disseminated cells rather than established metastatic lesions. This provides some explanation to the inefficacy of previous interferon trials that were conducted in patients with late-stage metastatic disease. It also calls into question whether other immunotherapies could be used earlier in cancer treatment to maximise the chances of a clinical response. Finally, we uncover that expression of IRF9, a key transcription factor in the type-I interferon signaling pathway, accurately predicts TNBC patient prognosis. Loss of IRF9 in a patient’s primary tumour predicted significantly poorer overall survival due to metastatic spread. As we show that tumour cells are not directly responsible for the poly(I:C)-induced interferon response, we propose that patients with IRF9-negative TNBC could benefit from neo-adjuvant interferon-based immunotherapy.
Antimicrobials in hospitalised and high-risk children: understanding and improving use
Infection is a near-universal human experience and is responsible for substantial child mortality across the globe, despite impressive reductions in child mortality and morbidity since the twentieth century. Antibiotics and other antimicrobial drugs have transformed our ability to prevent and treat infection. In general, these drugs are so safe, effective and widely available that overuse and inappropriate use are common. This is a cause of real problems in hospitals and the community, with unintended consequences of antimicrobial use including rising antimicrobial resistance. Antimicrobial stewardship (AMS) is aimed at improving the safety and efficacy of prescribing and has received growing attention in recent years. However, evidence to support and improve AMS for Australian children in hospitals is lacking. Australian hospitals are mandated to implement AMS programs and provide access to appropriate national and/or local prescribing guidelines. However, hospitals are under no current obligation to provide appropriately targeted AMS for the children in their care. Prior to mid-2019, national antimicrobial guidelines contained little paediatric and no neonatal advice. Since 2013, the voluntary National Antimicrobial Prescribing Survey (NAPS) has provided national reports on prescribing. However, until now, paediatric-specific data have not been reported. Compared with the literature on adult AMS, research on paediatric AMS is lacking, with few high-quality studies on interventions to improve care. This situation creates challenges for child healthcare providers and paediatric AMS program leaders, and more evidence is required to prioritise and improve care. The overall aims of this thesis are to improve the understanding of current antimicrobial use and stewardship for children in Australian hospitals and determine priorities to improve antimicrobial use now and in the future. This is achieved by analysing antimicrobial prescribing epidemiology and quality using national datasets, including national point prevalence survey and cohort study data. Chapter 1 reviews antimicrobial prescribing to children in hospitals, including in Australia. Chapter 2 presents the first analysis of paediatric antimicrobial prescribing to children in hospitals throughout Australia using NAPS data. Chapter 3 turns to high-risk groups, presenting the first nationwide analysis of prescribing for neonatal sepsis and fungal infections, again using NAPS data. Chapter 4 presents an analysis of antimicrobial prescribing in a contemporary cohort of immunocompromised children with fever and neutropenia, including prescribing quality and outcomes. Chapter 5 presents an interventional study evaluating the implementation of Australian guidelines on antibiotic duration and intravenous-to-oral switch. This is an example of the evidence translation and implementation approach needed for sustainable AMS improvement. Chapter 6 concludes the thesis, discussing the implications of the research and the paediatric AMS horizon in Australia. The analyses reported here reveal unnecessary variations in care and systemic inequities, which have implications for policy and guidelines. Non-metropolitan and non-tertiary hospitals in general provide lower-quality antimicrobial prescribing to children. This is likely to reflect decreased access to high-quality AMS resources, including guidelines and personnel, suggesting the need for systemic improvements. Neonates in Australian hospitals receive highly structured care in terms of antimicrobial choice and indications, but variations in dosing are substantial and undesirable, reflecting the lack of use of national guidelines. Prescribing for febrile neutropenia is highly diverse and often includes empiric aminoglycosides, which this research reveals are associated with real harm, suggesting the need for national guidelines to optimise care. Finally, the standard management of infections in hospitals involves excessive intravenous therapy, which is associated with unnecessarily increased hospital length of stay. As demonstrated, this can be improved with a structured AMS program, which should be available wherever children are treated in hospital. The information generated by this thesis provides new evidence on current antimicrobial prescribing practice and priorities and demonstrates the importance of utilising routinely collected data for the surveillance and improvement of paediatric AMS. Since this body of research began, national guidelines and paediatric-specific resources are now being developed, establishing new benchmarks. Along with continuous surveillance, these must be implemented appropriately to improve care. The research collaborations and networks developed during the production of this thesis will be used to support future surveillance and implementation work, which is needed to address AMS priorities in Australia and support the research and development of paediatric AMS across the globe.
Applications of massively parallel sequencing technology in the evaluation of haematological malignancies
Massively parallel sequencing (MPS) technology has revolutionised the genomic exploration of human disease. This is especially true in the case of cancer, which is primarily driven by the development of acquired genomic aberrations. The body of work described within this thesis represents a broad yet in-depth array of novel applications of MPS technology in the evaluation of haematological malignancies. This field is currently surging in relevance and clinical utility as the ongoing movement of MPS technology from the research to the routine diagnostic setting continues to facilitate the development of increasingly personalised medicine. High impact contributions have been made in a number of areas encompassing myeloid and lymphoid malignancies as well as haematological malignancies as a collective. Key achievements include: quantifying the risk of incidentally detecting germline variants of potential clinical significance during unpaired MPS testing of cancer samples; definitively proving that ASXL1 NM_015338.5:c.1934dup;p.Gly646Trpfs*12 is a true somatic alteration and developing an accurate and sensitive assay for its detection; exploring the pathogenesis of and mechanisms of resistance to histone deacetylase inhibitors in cutaneous T-cell lymphomas as well as defining the clinical features, outcomes and genomic landscape of transformed marginal zone lymphoma. This thesis represents a diverse portfolio of novel research with a strong translational focus. Despite the wide scope of the individual lines of inquiry described herein there is a common thread that binds the narrative together: the pursuit of innovative yet practical ways of utilising the powerful technology now available to improve the genomic characterisation of haematological malignancies and ultimately the lives of the patients and families they affect.
Automated discovery of interacting genomic events that impact cancer survival by using data mining and machine learning techniques
Rapid advancement in genomic technologies has driven down the cost of sequencing significantly. This efficiency has enabled large-scale cancer genomic studies to be conducted, generating a vast amount of data across different levels of omics variables. However, the tasks to extract new knowledge and information from this enormous volume of data present unique challenges. These analyses often require the application of specialised techniques for data mining, integration and interpretation to provide valuable insights. With the rise of machine learning adoption in recent decades, many advanced computational algorithms based on artificial intelligence techniques have also been proposed to analyse these genomics data. Although some of these applications have led to clinically relevant conclusions, many others are still relying on incomplete prior knowledge, or limited to only a selected number of features. These limitations raise the general question about the broader applicability of machine learning in the field of cancer genomics. This research addresses this question by assessing the application of machine learning techniques in the context of breast cancer genomics data. This assessment includes a comprehensive evaluation of computational methods for predicting cancer driver genes and the development of a novel deep learning approach for identifying breast cancer subtypes. The evaluation result of driver gene prediction algorithms suggests that the selection of the best method to be applied to a dataset will primarily be driven by the objectives of the study and the characteristics of the dataset. All of the evaluated approaches could identify well- studied genes, but not all of them performed as well on smaller datasets, subtype-specific cohorts, and in discovering novel genes. To examine the benefit of a more complex machine learning model, this thesis also presents a novel deep learning approach that integrates multi-omics data for predicting various breast cancer’ biomarkers and molecular subtypes. This method combines a semi-supervised autoencoder for dimensionality reduction, and a supervised multitask learning setup for the classifications. Taking an input of gene expression, somatic point mutation and copy number data, the algorithm predicts the ER-Status, HER2-Status and molecular subtypes of breast cancer samples. Further survival analysis of the outputs from this deep learning approach indicates that the predicted subtypes show a stronger correlation with patient prognosis compared to the original PAM50 label. While the outputs from machine learning algorithms still require further validation, the adoption of these complex computational methods in cancer genomics will become increasingly common. Collectively, the results from this thesis suggest that the machine learning analysis of ‘omics data hold great potential in automating the discovery of clinically- relevant molecular features.
BET bromodomain inhibition as combined apoptotic and immunomodulatory therapy for the treatment of MYC-driven lymphoma
Bromodomain and Extra-Terminal (BET) proteins are a conserved family of ‘epigenetic readers’ that bind to acetylated lysine residues on histone and non-histone proteins to modulate transcription. BET proteins are enriched at promoter and enhancer regions and recruit the positive transcription elongation factor b (P-TEFb) complex to activate RNA polymerase II. Anti-tumour responses elicited by BET inhibitors have been associated with the suppression of genes required for cellular proliferation and survival, including oncogenic transcription factors. Suppression of the proto-oncogene MYC was initially reported as a key mechanistic property of BET inhibitors, however more recent evidence suggests that additional target genes are mechanistically implicated. In this thesis, the Eμ-Myc model of aggressive B-cell lymphoma was utilized to investigate the full repertoire of genes modulated by JQ1 and their functional significance in mediating therapeutic responses. JQ1 did not suppress the expression of transgenic Myc in this model, allowing the determinants of apoptosis induction to be assessed, independently of changes in Myc expression. This apoptotic response was p53-independent and associated with modulation in the ratio of pro- and antiapoptotic Bcl-2 family members to favor activation of the intrinsic mitochondrial apoptotic pathway. Therapeutic administration of JQ1 to mice bearing Eμ-Myc lymphomas led to robust clinical responses, however, universal treatment failure was observed despite ongoing therapy. Using RNA-Seq, disease progression and secondary JQ1 resistance was found to be associated with RAS pathway activation and Bcl-2 upregulation. In addition, the efficacy of JQ1 was found to be dependent on an intact host immune system, where a 50% reduction in the survival advantage was observed upon transplantation into immune-deficient mice. Using RNA-Seq, the immune checkpoint ligand Cd274 (Pd-l1) was found to be potently suppressed by JQ1. Mechanistically, BET inhibition decreased Brd4 occupancy at the Cd274 promoter, leading to promoter-proximal pausing of RNA polymerase II, and loss of Cd274 mRNA production. Rapid epigenetic remodeling of the Cd274 locus in response to interferon gamma (IFN-γ) stimulation led to recruitment of Irf1, Brd4, RNA polymerase II, as well as increased local histone acetylation. Accordingly, BET inhibition suppressed constitutive and IFN-γ-induced PD-L1 expression in genetically diverse tumour models. Ectopic expression of PD-L1 in Eμ-Myc lymphomas was sufficient to reduce the efficacy of JQ1, demonstrating the significance of PD-L1 suppression to the observed therapeutic responses associated with BET inhibition. Finally, treatment of mice bearing Eμ-Myc lymphomas with JQ1 in combination with a checkpoint inhibitor (anti-PD-1) or immune stimulating antibody (anti-4-1BB/CD137) led to improved therapeutic responses. The results presented herein demonstrate the importance of MYC-independent apoptotic signaling to therapeutic responses associated with BET inhibition, as well as acquired drug resistance. In addition, these results demonstrated the ability of BET inhibitors to directly engage the host immune response during anti-cancer therapy. Finally, BET inhibitors can suppress oncogenic PD-L1 transcription for therapeutic gain, leading to augmented anti-tumour immunity. These studies establish a strong rationale for clinical investigation of BET inhibitors in combination with immune modulating therapies.
Bioimaging in colorectal cancer - prediction of response to neoadjuvant treatment
Over the last decade the management of colorectal cancer has changed significantly with the benefits of neoadjuvant therapies and new adjuvant treatments becoming apparent. Surgical strategies have also evolved with initial evidence that some patients can be successfully managed with local excision or omission of any surgery at all, resulting in a shift towards the individualisation of cancer management. The management of rectal cancer is based on primary staging assessment which relies on imaging techniques such as CT, MRI and ERUS. Recent advances in technology have improved the accuracy and widened the applications of these techniques. With the progress in medical and surgical treatments for rectal cancer, the optimal management of rectal cancer has become more complex. The evolving ability to tailor optimal treatment to the individual has created new roles for imaging such as prediction of response to treatment, restaging with assessment of response to treatment and prediction of prognosis. Consequently, prediction of response will become an important component of modern pre-operative assessment of rectal cancer to optimise individualisation of medical and surgical treatment. Beyond the established role of primary staging of malignancies, the role of conventional imaging techniques in re-staging following neoadjuvant treatment may be of increasing importance. Novel functional imaging techniques such as FDG-PET, DW (diffusion weighted) MRI are also emerging, the roles of which are yet to be determined. This thesis will examine the current status of bio-imaging and explore new imaging techniques in rectal cancer. At the Peter MacCallum Cancer Centre, we have been routinely performing staging and restaging imaging with CT, MRI and PET for the last 5 years which has resulted in a cohort of patients in whom these imaging techniques can be evaluated. This thesis also aims to evaluate a recent and evolving functional imaging technique- DW-MRI, in the prediction of response of rectal cancer to chemo-radiation.
CDK12 and CDK13 cooperatively regulate RNA polymerase II elongation and alternative polyadenylation of mRNA
Transcription driven by RNA Polymerase II (POLII) is a multi-step process that is strictly regulated by Cyclin dependent kinases (CDKs) at multiple checkpoints. Compared to the regulation of transcription initiation and pause release, the roles of CDKs in regulating transcription elongation remain poorly defined. To investigate the individual and shared roles of CDK12 and CDK13 in transcription regulation, a set of cell lines containing analog-sensitive variants of CDK12 and CDK13 were constructed using CRISPR-Cas9 homology-directed repair (HDR) technology. Multiple Next-Generation Sequencing (NGS) based assays including RNA-Seq, ChIP-Seq, PRO-Seq, TT-Seq were utilised to provide a comprehensive characterisation of the consequences of acute inhibition of CDK12, CDK13 or both kinases using these analog sensitive CDK12 and CDK13 cell lines. Selective inhibition of CDK12 or CDK13 led to various molecular responses including selective changes in gene expression, alternations in polyadenylation site usage as well as mild reduction in POLII elongation rate and processivity. In contrast, dual inhibition of CDK12 and CDK13 caused dramatic changes in transcription genome-wide, including the induction of widespread alternative polyadenylation events, reduction in POLII elongation rates and processivity, substantial changes in gene expression, as well as the near complete loss of POLII Ser2 phosphorylation. These observations illustrated that both CDK12 and CDK13 are regulators of POLII transcription elongation. Furthermore, the substantial differences between selective and simultaneous inhibition of CDK12 and CDK13 revealed the redundant and individual roles of CDK12 and CDK13 in maintaining global transcription elongation. To identify substrates of CDK12 and CDK13 that might be responsible for the phenotypes caused by CDK12 and CDK13 inhibition, phospho-proteomic analysis was performed to identify putative CDK12 and CDK13 substrates. The analysis revealed that CDK12 and CDK13 shared multiple substrates and functional redundancy between CDK12 and CDK13 in phosphorylating these substrates was identified. In order to identify the putative substrates that were responsible for the transcriptional changes upon CDK12 and CDK13 inhibition, a novel siRNA screen method “mini-bulk” CEL-Seq2 siRNA screen was developed and utilised. The screen revealed that SF3B1 and SRRM2 could be the potential substrates of CDK12 and CDK13 that were partially responsible for the transcriptional phenotype caused by the dual inhibition of CDK12 and CDK13, as depletion of SF3B1 and SRRM2 led to similar differential gene expression and alternative polyadenylation profiles as CDK12 and CDK13 inhibition. Finally, as the phospho-proteomic analysis also revealed that CDK12 and CDK13 might regulate phosphorylation of multiple translation regulators, the effect of CDK12 and CDK13 inhibition on protein translation was also investigated. Both nascent protein labelling as well as polysome profiling revealed that CDK12 and CDK13 function was required to maintain global translation. In conclusion, this thesis explored the role of CDK12 and CDK13 in POLII driven transcription and protein translation. CDK12 and CDK13 were shown to cooperatively regulate POLII transcription elongation processivity and alternative polyadenylation, potentially through regulating POLII Ser2 phosphorylation and the phosphorylation of other CDK12 and CDK13 substrates.
Circulating tumour DNA analysis for personalised care in breast cancer
Phenotypic diversity of breast cancers poses insurmountable challenges in the treatment of this lethal disease. Recent advances in next generation sequencing have led to unprecedented insight into the genomic landscape underlying breast tumours. This has resulted in burgeoning development of targeted treatments and predictive biomarkers, several of which have recently demonstrated clinical activity. However, key challenges hinder optimal application. On the background of extensive molecular heterogeneity, most biomarkers represent minority patient subpopulations, hampering clinical development. Furthermore, considerable genomic evolution of breast tumours impacts accuracy of genomic characterisation that is thus far heavily reliant on the sequencing of non-contemporaneous and invasive tumour tissue biopsies. Finally, stratification to genomically-matched targeted therapies also fails to fulfil the extent of its promise. In many cases relentless tumour growth remains unperturbed, while in others resistance ultimately develops. Crucially, molecular mechanisms underlying resistance remain poorly understood, while follow-on treatment options are often poorly defined. Central to the promise of personalised medicine is the robust and accurate characterisation of the tumour genome. Minimal invasiveness and convenience of circulating tumour DNA (ctDNA) analysis, with ability to detect tumour genomic aberrations from a blood draw, highly recommends this approach. Recent technological advances have paved the way to a range of clinical applications, with evolving potential for ctDNA analysis to address the continuum of challenges posed to precision medicine throughout patient management. Toward this end, extensive clinical development is required, while prevailing technological hurdles need to be addressed. This thesis explores a multi-faceted and rigorous approach towards the integration of ctDNA analysis in the management of breast cancer patients. Firstly, the development and validation of multiple assays (allele-specific and NGS-based) tailored to breast cancers, enabled comprehensive genomic analysis with in-built flexibility to be readily applicable to a variety of clinical scenarios. Subsequent establishment of a prospective ctDNA-based molecular profiling program across a large cohort of metastatic breast cancer (mBC) patients demonstrated feasibility of real-time analysis in the clinical setting across a range of genomic targets of variable abundance. Importantly, integration of longitudinal testing in this program throughout patient management demonstrated capacity for ctDNA analysis to reflect genomic evolution in real-time to optimise precision-guided patient management. Finally, exploratory longitudinal ctDNA analysis for the study of resistance mechanisms to CDK4/6i, constituting a novel class of targeted compounds for breast cancer, highlights established and novel resistance markers. Indeed, this study also serves to demonstrate a workable framework for ctDNA analysis as a highly effective approach for the de novo elucidation of resistance mechanisms to novel targeted agents that is relevant across cancer types.