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Analysis of primary human cancers : from single genes to whole transcriptomes Pugh, Trevor John

Abstract

Cells in the human body contain DNA genomes that encode instructions regulating their biology. Accumulation of somatic DNA sequence alterations such as point mutations and structural rearrangements can disrupt critical genes resulting in malignant cancer phenotypes. Identification of cancer “drivers” is a central goal of cancer genome analysis due to their causation of oncogenesis and potential as diagnostic and therapeutic targets. Analysis of normal polymorphisms can also impact the treatment of cancer by identifying individuals most likely to benefit from specific therapies. To uncover molecular correlates with treatment outcome, my graduate work has focused on applying DNA sequencing technology to clinical cancer patient samples. In an early example of medical oncogenomics, I evaluated mutations and amplifications of a single gene, EGFR, in patient tumour samples and investigated associations with response to an EGFR inhibitor, gefitinib. This study was challenged by limited nucleic acid quantities available from small or microdissected tissue biopsies. Therefore, I next characterized bias induced by a whole genome amplification technique and demonstrated genotype and copy number analysis using amplified material. To investigate the role that normal polymorphisms play in guiding cancer treatment, my third project sought to correlate DNA repair gene polymorphisms with the development of late side effects following radiation therapy for prostate cancer. Late side effects were associated with variants in three genes, uncovered by sequencing the exons of eight DNA repair genes in patients with varying degrees of radiosensitivity. Advancements in DNA sequencing technologies have enabled a move beyond candidate gene approaches towards gaining sequence and expression information from all expressed genes (i.e. the transcriptome). Utilizing second generation sequencing technology, my final project was a transcriptome analysis of lung tumours prior to treatment with the EGFR inhibitor, erlotinib. I uncovered gene expression profiles specific to clinical subgroups and, in one case, detected expression of the Epstein-Barr virus. The second phase of this project will validate putative somatic mutations identified by transcriptome sequencing and investigate viral involvement in other lung tumours. Genome sequence information is becoming readily extracted from clinical sources and there is great potential to use this information to effectively guide cancer treatment.

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Attribution-NonCommercial-NoDerivatives 4.0 International

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