Pathology - Theses
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ItemMolecular profiling of ovarian cancer to guide targeted treatment( 2015)Ovarian cancer is a complex disease composed of multiple distinct molecular and clinical subtypes. The survival rate for ovarian cancer has remained largely unchanged over the past three decades, despite the rapid advancement of the knowledge of the molecular and genetic mechanisms underlying most of the subtypes of ovarian cancer. There is, therefore, an urgent need to rapidly translate this knowledge into improved clinical outcomes for patients with ovarian cancer. There have been significant clinical responses of certain types of cancer to targeted therapies that are designed to inhibit specific molecular defects that some tumours appear to be dependent upon. To assist in allocating patients with ovarian cancer to targeted therapies, two customised assays for mutation and copy number alteration detection were developed for molecular profiling. A panel of 29 genes, which are commonly mutated in ovarian cancer, and are potentially therapeutically targeted, was selected to be screened using an amplicon-based assay, designed for next generation sequencing. Seventy six ovarian cancer cases with matched formalin-fixed paraffin- embedded tumour tissue, snap-frozen tumour tissue and blood samples were used for the assay validation and estimation of the diagnostic yield. A panel of 11 commonly copy number altered genes in ovarian cancer was also selected for screening with a herein developed method for multiplex low-level copy number detection. Furthermore, a thorough assessment and optimisation of the available and developed analysis methods was performed to ensure accurate analysis and reporting of mutations and copy number alterations. Thirty five patients with advanced ovarian cancer were tested using the developed assays as part of the ALLOCATE study, with genetic changes detected in 90.9%, demonstrating a high diagnostic yield. Molecular profiling of these cases was not only useful in identification of possible targeted treatment strategies with the aim of improving clinical outcomes, but also assisted in determining the correct diagnosis. Moreover, a novel algorithm was proposed for the prediction of individual tumour response to PARP inhibitors, a promising targeted treatment in high-grade serous ovarian cancer.
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ItemFunctional analysis of genes in regions commonly amplified in high-grade serous and endometrioid ovarian cancer( 2013)Genomic copy number amplification is a hallmark of oncogene-associated tumour development and progression. The targeted increase in copy number of such chromosomal regions has a significant impact upon gene expression that imparts selective advantages on cancer cells. This may result in aberrant expression of the amplified target gene. These genes are attractive therapeutic targets; particularly as increased gene expression within the cancer genome is often associated with ‘oncogene addiction’. Moreover, copy number amplification provides a striking genetic characteristic that allows for the stratification of patients into the appropriate therapeutic streams. To identify amplicon targets we have adopted a methodology that combines genomic copy number with RNA interference to identify genes that drive amplification events in ovarian cancer. According to our analysis of SNP array data for a cohort of ~400 high-grade serous and endometrioid tumours, over 46Mb of the genome was amplified at a high level in 10% or more tumours, encompassing ~300 genes. This set of candidate genes has been functionally assessed in vitro using a boutique siRNA library to interrogate phenotypic alterations in cellular viability. We utilized SNP array data from a panel of 39 ovarian tumour cell lines to identify 18 cell lines that recapitulate the gene amplifications observed in the clinical specimens and which formed the basis of this study. This screen identified a number of genes that may be specifically targeted for the treatment of high-grade serous and endometrioid tumours. Importantly, known mediators of ovarian tumourigenesis, such as URI1, were detected using this methodology, providing a robust proof-of-principle for the experimental and analysis approach applied in this study. In addition to URI1, 7 genes located in 4 amplicons were also identified as strong candidates for therapeutic targeting including BMP8B, CACNA1C, DYRK1B, GAB2, PAK4, SAMD4B and ZFP36. Genes identified in the screen have been correlated with clinical outcome in three independent patient cohorts, including The Cancer Genome Atlas (TCGA), Australian Ovarian Cancer Study (AOCS) and the Ovarian Cancer Association Consortium (OCAC)/Ovarian Tumor Tissue Array (OTTA) consortium. This analysis provided further evidence to support the oncogenic role of CACNA1C, GAB2, URI1 and ZFP36 in ovarian tumourigenesis. In addition, the therapeutic utility of DYRK1B and PAK4 was investigated in more detail using targeted therapeutics against their gene products in both amplified and non-amplified cell lines. The inconsistent results obtained in this preliminary analysis highlight the difficulties associated in the selective targeting of genes in tumour cells using small molecules. The results from this study provide strong evidence for the value of focused functional genomic screening. We demonstrated that combining high-throughput technologies on this scale has the potential to rapidly identify candidate driver genes that may then be streamlined into the validation and translational phase of clinical development.
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ItemIdentification of novel growth promoters of ovarian cancer( 2011)Ovarian cancer is a heterogeneous, genomically unstable and highly lethal disease in women. Despite nearly half a century of research in ovarian cancer, few early detection markers, disease drivers or chemoresistance conferring genes have been discovered. The recent and rapid advances in microarray and sequencing technologies have provided new tools with which a thorough search can be performed to discover novel ovarian cancer associated genes. This thesis describes the use of two high resolution microarray platforms to identify novel growth promoters of ovarian cancer. This study investigated a cohort of 72 ovarian tumours using the Affymetrix Genome-Wide Human SNP Array 6.0 (SNP6) to assess copy number, and the Affymetrix GeneChip® Whole Transcript (WT) Sense Target Array 1.0 to study gene expression. The high quality copy number data generated using the SNP6 platform was used to define frequently gained regions of the ovarian cancer genome. Gene expression data was integrated with the copy number data using novel informatics approaches to identify genes whose expression was directly affected by copy number gain. Further integrative analyses and a search of current literature yielded seven candidate drivers of ovarian cancer - PRKCI, RAB2A, PUF60 (SIAHBP1), MYNN, PTK2, PLEC1 and TPX2. These seven candidate ovarian cancer driver genes were tested for functional effects using immortalised ovarian cancer cell lines. Nine cell lines were chosen in such a way that each of the seven candidate genes were represented by at least two cell lines that showed copy number gain and two cell lines that were copy number neutral at the candidate gene locus. Small-interfering RNAs were used to knockdown the expression of candidate genes in the selected ovarian cancer cell lines. Changes in cell proliferation upon gene knockdown were recorded for all cell lines and all genes. TPX2 and RAB2A, showed a significant decrease in proliferation following siRNA knockdown in some cell lines. The changes in proliferation for TPX2 were copy number independent while for RAB2A, changes were strongly driven by copy number. The functional assays validated the power of the analysis methods in identifying novel ovarian cancer drivers.