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Epigenomic and genomic analysis of familial prostate cancer

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Cazaly, E 2017 , 'Epigenomic and genomic analysis of familial prostate cancer', PhD thesis, University of Tasmania.

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Abstract

Over a million men world-wide are affected by prostate cancer, with the disease particularly prevalent in Australia, with more than 20,000 men diagnosed annually across the country. There remain significant clinical challenges in diagnosis and treatment. A family history is a major risk factor, indicating an underlying genetic component, yet the majority of inherited factors contributing to disease remain to be elucidated. Identifying this unaccounted heritable contribution will extend our understanding of prostate cancer development and progression, and has the potential to improve diagnosis and treatment.

It is becoming evident that high-risk genetic variants often occur in regulatory regions of genes, the primary sites of epigenetic regulation, therefore mapping epigenetic changes may shed some light on missing heritiability. Epigenetic marks are chemical modifications to DNA or it’s associated proteins, that do not alter the genomic sequence, yet play a key role in regulating gene expression. DNA methylation, the most frequently studied epigenetic mark, is influenced by a range of intrinsic and external factors including diet, lifestyle and age. However, it is becoming increasingly apparent that genetic drivers may have the greatest influence on epigenetic patterns. While genetically driven epigenetic profiles contribute to natural phenotypic variation, such alterations may also underpin part of the unexplained inherited contribution to complex disease risk.

Large pedigrees with clusters of affected individuals can provide invaluable insight into complex diseases, affording reduced genetic complexity. As such, this study utilises the unique Tasmanian Familial Prostate Cancer Resource to further understand the inherited drivers of epigenetic change that can predispose men to prostate cancer. Particularly, this study focuses on identifying genetic variants that may trigger DNA methylation changes in regulatory regions of the genome. Such variants have been termed methylation quantitative trait loci, or meQTLs, and can be examined in a similar manner to expression quantitative trait loci.

Clusters of affected men, representing dense aggregates of prostate cancer incidence often spanning up to five generation, were selected from four large families in the Tasmanian Familial Prostate Cancer Study. Samples were analysed for genotype and methylation profiles, initially using array based techniques which were then validated and extended with bisulphite sequencing.

Fundamental to analyses of methylome data is normalization and batch correction, to ensure unwanted technical bias is removed while maintaining the biological information of interest. While pre-processing methodologies were available for analysis of matched disease and control samples, the development of an optomised pre-processing pipeline for the analysis of famililal data was required. Specifically, this included testing a range of normalisation methods with qualitative and quantitative performance metrics to determine which method was the most appropriate and effective on familial data.

Potential meQTLs of interest were then identified through two distinct approaches. The first approach prioritised the most variable methylation sites between individuals, while the second approach examined methylation surrounding previously identified prostate cancer risk loci. To test the selected meQTLs, methylation data was combined with genotype using a generalized linear model accounting for kinship. After adjusting for multiple testing error, significant associations were prioritised using the following criteria; proximity to prostate cancer relevant genes and the presence of key regulatory elements. Through bisulphite sequencing, prioritised meQTLs were initially validated, followed by finer mapping of the influence of meQTLs on surrounding methylation profiles. Additionally, unaffected controls were drawn from the Tasmanian Prostate Cancer Case Control Study to examine differential methylation patterns between affected and unaffected individuals, with the aim of identifying predisposing variants.

Using this approach an meQTL associated with the tumour suppressor gene CASZ1 was identified. This meQTL, located at 1p36.22, showed genetically driven methylation patterns at the SNP, which extended approximately 150bp either side, to two additional CpGs. Distinct differential methylation profiles were also observed between cancer and control groups for the CASZ1 region. This meQTL provides an intriguing basis for further investigation as dysregulation of the gene has been associated with an aggressive prostate cancer phenotype.

Item Type: Thesis - PhD
Authors/Creators:Cazaly, E
Keywords: Epigenetics, epigenomics, meQTL, prostate cancer, familial, bioinformatics
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Copyright 2016 the author

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