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ItemUsing transcriptomics to understand cancer progression and predict response to therapyForoutan, Momeneh ( 2018)Transcriptomics data provide useful information to better understand molecular phenotypes in cancer. Epithelial-to-mesenchymal transition (EMT) is one of these molecular phenotypes that is hijacked by cancer cells to obtain mobile mesenchymal characteristics which may assist cells to intravasate into blood stream, generate circulating tumour cells (CTCs) and metastasize to distant organs. CTCs also have heterogeneity in their molecular phenotypes and it is of utmost importance to understand these variations to be able to understand differences in their therapy response and use them to monitor treatment outcome. Using transcriptomics, we can also explore and predict molecular phenotypes associated with sensitivity to different therapeutic regimen. Although EMT is a single molecular phenotype, it can be regulated through different underlying molecular mechanisms, leading to differences in response to therapies. To identify samples with TGFβ-driven EMT, I derive a gene expression signature of EMT induced by TGFβ using metaanalysis and transcriptomics data integration. This signature is able to identify transcriptional profiles arising during TGFβ-driven EMT, and yields highly consistent results in multiple independent pan-cancer cell lines and patients data. Samples fitting this signature show lower number of mutations in elements of TGFβ signalling, poorer overall survival outcome and preferential response to certain drugs. Meta-analysis and data integration such as the above require careful attention to batch effects in datasets. I apply different batch correction methods in order to perform general normalisation or obtain differentially expressed genes (DEGs) in integrated transcriptomics data sets. Further, to classify the fit of individual samples to a gene signature, I apply existing single-sample scoring methods. However, these methods all use information borrowed from the whole set of samples, meaning they are not truly single sample scores. To address this, I developed a rank-based scoring method, called singscore, which generates more stable scores that are independent from sample size and composition in a dataset. CTCs are integral to cancer progression, but while these cells are extremely rare in blood, they have great potential to provide a real-time representation of cancer progression and treatment efficacy. I perform an assessment of current markers for enrichment and/or detection of CTCs, and then, introduce new CTC markers, including general, epithelial and mesenchymal markers obtained by analysing multiple breast cancer and blood data sets. I then assess their expression in publically available CTC data and a number of in-house patient samples. Finally, I use pharmacogenomics data in breast cancer cell lines and the singscore method to predict drug response outcome for 90 drugs based on gene expression data, which have been shown to be the most predictive molecular feature in breast cancer. I derive drug sensitivity signatures by quantifying associations between gene expression and drug response and evaluate the utility of these gene signatures using cell lines, PDX models and patient data and show consistent pattern of response across independent data sets. Further associations between drug sensitivity scores and EMT phenotype are assessed.
ItemThe contribution of genetic variations in the region of the parathyroid hormone-like hormone, PTHLH, gene to breast cancer susceptibilityFreeman, Adam Noel ( 2016)Aims: • Analyse the evidence for PTHLH and PTHrP, its protein product, playing a role in breast cancer and update the empirical definition of the gene. • Describe the 3-Dimensional structure of the PTHLH region and determine its system of regulatory interactions, including remote regulatory elements affecting PTHLH. • Integrate existing tools in addition to the novel perspectives generated above to enable a comprehensive annotation and analysis of genetic variants identified through molecular epidemiological techniques including Genome-Wide Association Studies (GWAS) and somatic DNA sequencing of tumour tissue to derive putative molecular mechanisms for the region’s involvement in breast cancer susceptibility. Methodology: • Review published studies and databases, integrating findings from diverse sources. • Acquire and analyse DNA and RNA sequencing, regulatory, expression, algorithm-inferred, and proximity-ligation data from multiple public data sources including ENCODE, ROADMAP, dbGAP, COSMIC and other to update the definition of PTHLH, and advance concepts of structure and regulatory function in the region. • Acquire and analyse primary GWAS data, performing imputation with multiple algorithms and references, and annotating associated variants with a suite of tools. • Use genome browsers including UCSC, WUSTL, and Golden Helix SVS, and their associated databases and tools, to analyse and visually integrate findings. Results: • PTHrP has multiple discretely functional segments active throughout the cell. It likely plays a bivalent and context-dependent role in cancer biology. Analysis of somatic variation in cancer suggests PTHrP may have a tumourigenic role within the nucleus. • PTHLH sits within a 1.3Mb TAD featuring multiple sub-structures that are integrated with the region’s regulatory function. There are activated chromatin hubs (ACHs) at protein-coding genes with evidence of extensive interaction between them. This is facilitated by the TAD’s structure, collocating them at the neck of the TAD. • The ACHs at MRPS35, KLHL42, and CCDC91 each monopolise a subordinate regulatory sub-net with a hierarchical structure. They each appear to act as important remote regulatory elements that integrate regulatory signals generated within their respective sub-nets, transferring them to PTHLH, and other genes, via ACH-ACH interactions. • There appear to be multiple discrete GWAS breast cancer association signals in the PTHLH region. Annotation of the associated variants suggests three particular regulatory elements may be its key drivers. In the context of the regulatory concepts developed in this thesis, the variants may affect a particular regulatory signal at multiple points in its assembly. PTHLH is the likely downstream target of this signal. • There are multiple poorly-describe coding, and non-coding, genes in the region that are also potential actors in breast cancer and should be investigated. Conclusion: • The PTHLH region is likely involved in the pathogenesis of breast cancer through the modification of PTHLH expression. There are likely to be other mechanisms in parallel that are yet to be fully described.
ItemRole of Epithelial Mesenchymal Plasticity associated cancer subpopulations in mammary tumourigenisis and chemoresistancePinto, Cletus Anthony ( 2014)Tumour heterogeneity is a key characteristic of cancer and has significant implications relating to tumour response to chemotherapy as well as patient prognosis and potential relapse. It is increasingly accepted that tumours are clonal in origin, suggestive of a tumour arising from a deregulated or mutated cell. Cancer stem cells (CSC) possess/propagate these capabilities, and with appropriate intracellular triggers and/or signalling from extracellular environments, can ‘differentiate’ to initiate tumour formation. Additionally through epithelial mesenchymal plasticity (EMP), where cells gain and maintain characteristics of both epithelial and mesenchymal cell types, epithelial-derived tumour cells have been shown to ‘de-differentiate’ to acquire cancer stem attributes, which also imparts chemotherapy resistance. This new paradigm places EMP centrally in the process of tumour formation, propagation, progression and metastasis, as well as modulating drug response to current forms of chemotherapy. Furthermore, EMP and CSCs have been identified in cancers arising from different tissue types making them a possible generic therapeutic target in cancer biology. In this study, we expand on the relationship between tumour heterogeneity, EMP and CSC in BrCa through the identification and characterisation of epithelial and mesenchymal subpopulations within two BrCa cell lines. In addition, we demonstrate the plasticity that allows these cell populations to effectively regenerate the other cell populations with a particular emphasis on the CSC phenotype. Through a functional genomics screen, the importance of the mesenchymal phenotype in tumour initiation is demonstrated. Taken together, this study demonstrates that heterogeneity exists at a cell line level and this heterogeneity differs in different cellular systems. We also find evidence to suggest that BrCa cell lines can use multiple mechanisms to achieve an outcome such as tumour initiation or mammosphere formation, and subsequently emphasize the importance of phenotype specific drugs. This ideology of drug repurposing to identify phenotype specific drugs is explored through the use of the connectivity map database to identify new uses for previously established drugs to target these subpopulations find preliminary evidence for the role of HDACi to affect these EMP associated subpopulations in BrCa cell lines.