| Genome-wide association studies (GWAS) have identified numerous prostate cancer (PrCa) associated risk loci. The overwhelming majority of these loci have not been functionally characterized and candidate genes have not been identified. We hypothesize that some of these risk variants may be regulatory and influence expression of nearby genes.;We studied one locus in depth; the prostate risk single nucleotide polymorphism (SNP), rs10993994, is in the promoter of the gene encoding microseminoprotein-beta (beta-MSP), a prostate secretion. We explored rs10993994's regulation of gene expression and beta-MSP's role in prostate cancer. The risk allele for prostate cancer at rs10993994 causes lower levels of transcription activity, but we could not identify the specific transcription factor involved. Excess beta-MSP reduces prostate cell viability, but this decrease is cell line specific and is not due to apoptosis.;Most PrCa risk variants do not have obvious functional effects. We used cis-expression quantitative trait loci (cis-eQTL) analysis to develop candidate gene targets for PrCa risk loci. In our first study, we investigated 50 PrCa samples for 59 PrCa risk variants and performed cis-eQTL analysis. We found 27 significant associations. The top ranked cis-eQTL involved IRX4 and rs12653946, tagged by rs10866528 in our study. Replication studies, linkage disequilibrium, and imputation analyses highlight population specificity at this locus.;Next, we interrogated prostate tissue from 45 benign samples and 47 tumor samples from Finnish prostate cancer patients for cis-eQTL in 107 PrCa risk or secretion associated SNPs. We found two strong cis-eQTLs in benign prostate tissue and two in tumor. We validated previously identified cis-eQTL and detected a novel cis-eQTL at 6q25, rs1933488 with RGS17. The protective allele for prostate cancer is correlated with lower levels of RGS17 , a plausible candidate prostate cancer gene. We conclude that cis-eQTL analysis in relevant tissues, even with a small sample size, can be a powerful method to expedite functional follow-up of GWAS.;Genetic epidemiology studies have been outstripping the pace of functional genetics. Our studies have shown that integration of genomic analyses and targeted functional studies are invaluable assets in keeping up with the rate of discovery. |
