Genetic Epidemiology of Prostate Cancer Risk

Tremendous advances in genomic capabilities, including high-throughput genotyping technology and algorithms, have significantly advanced our understanding of the genetic etiology of complex human traits, including cancer of the prostate gland. Although over 150 genomic loci predictive of prostate cancer susceptibility have been previously reported in the scientific literature, particular questions remain outstanding in our understanding of prostate cancer genetics. These open questions include the extent to which low frequency variants not detectable by genome-wide association studies may appreciably modify risk of prostate cancer, which genes may modify risk of prostate cancer through up- or down-regulation by genetic polymorphisms including prostate cancer risk loci, and the degree to which the normal tissues collected from prostate cancer patients reflect a faithful representation of their baseline germline genetics. The latter is explored in Chapter 2 of this dissertation, using genome-wide genotypes from prostate cancer patients at the University of California, San Francisco medical center. This work reveals significant genetic heterogeneity among diverse sources of DNA deriving from a common patient, and challenges preconceived notions that seminal vesicle tissue DNA from a prostate cancer patient may serve as an accurate representation of germline genetics. In Chapter 3, many diverse biological datasets, including genotypes for over 230,000 UK Biobank and Kaiser Permanente subjects, are integrated to identify genes whose expression levels are associated with prostate cancer risk. Further explored are the mechanisms by which particular associated genes may influence prostate cancer etiology, as well as the mechanisms by which genetic variants may regulate gene expression levels for those genes associated. Finally, Chapter 4 reports the association of several novel prosate cancer risk variants, including two previously unreported rare variants in European-ancestry populations. By meta-analyzing custom microarray genotype data from Kaiser Permanente health plan members along with genetic data from the UK Biobank, this work seeks to clarify the genetic architecture of prostate cancer risk, as well as further characterize the aggregate risk of previously reported loci across multi-ethnic subjects. In conclusion, this dissertation reports novel findings pertaining to rare prostate cancer risk variants, prostatic gene expression in prostate cancer, and genetic mosaicism among urologic tissues