Functional Annotation And Mechanism Analysis Of Risk Loci Identified Through Genome-wide Association Studies For Prostate Cancer

Prostate cancer (PCa) is one of the most common non-cutaneous cancer affecting men in US and genetic alterations are hypothesized to contribute to the well-characterized familial aggregation of PCa. Androgen receptor (AR) and androgen-response elements (AREs) have long been demonstrated to play a critical role in prostate carcinogenesis. The majority of established prostate cancer risk-associated Single Nucleotide Polymorphisms (SNPs) identified from genome-wide association studies do not fall into protein coding regions. Therefore, the mechanisms by which these SNPs affect prostate cancer risk remain unclear. Here, we used a series of bioinformatic tools and databases to provide possible molecular insights into the actions of risk SNPs. We performed a comprehensive assessment of the potential functional impact of 33 SNPs that were identified and confirmed as associated with PCa risk in previous studies. For these 33 SNPs and additional SNPs in Linkage Disequilibrium (LD)(r2≥ 0.5), we first mapped them to genomic functional annotation databases, including the Encyclopedia of DNA Elements (ENCODE), eleven genomic regulatory elements databases defined by the University of California Santa Cruz (UCSC) table browser, and Androgen Receptor (AR) binding sites defined by a ChIP-chip technique. Enrichment analysis was then carried out to assess whether the risk SNP blocks were enriched in the various annotation sets. Risk SNP blocks were significantly enriched over that expected by chance in two annotation sets, including AR binding sites (p=0.003), and FoxAl binding sites (p=0.05). About one third of the 33 risk SNP blocks are located within AR binding regions. The significant enrichment of risk SNPs in AR binding sites may suggest a potential molecular mechanism for these SNPs in prostate cancer initiation, and provide guidance for future functional studies.To test the hypothesis that sequence variants in AR binding sites are associated with PCa risk, we systematically evaluated the association of PCa risk with SNPs in regions containing AR binding sites in two existing PCa GWAS; the Johns Hopkins Hospital and the Cancer Genetic Markers of Susceptibility (CGEMS) study. We demonstrate that regions containing AR binding sites are significantly enriched for PCa risk-associated SNPs. In addition, compared with the entire genome, risk-associated SNPs in these regions were significantly more likely to overlap with known PCa risk-associated SNPs. These results are consistent with our previous finding from a bioinformatics analysis that one-third of the 33 known PCa risk-associated SNPs discovered by GWAS, including multiple independent SNPs at 8q24, are located in regions of the genome containing AR binding sites. Together, these results provide novel statistical evidence suggesting an androgen-mediated mechanism by which some PCa associated SNPs act to influence PCa risk. However, these results are hypothesis generating and should ultimately be tested through in-depth molecular analyses.In summary, the development of prostate cancer is a slow process and our study suggested that sequence variants in regions containing AR binding sites would alter the AR binding ability and affect the regulation of downstream target gens and fusion gens of androgen and AR, that making prostate cancer difference between individuals. Based on the systematic GWAS analysis of PCa, gene structure information, transcription factor binding sites, epigenomics, post-translational modification, RNA edit information and other SNP related information, we developed FunSNP (Functional Annotation System for SNP) to help biologists to analyze disease data for elucidating biological mechanism.