William Isaacs

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Association of prostate cancer risk with SNPs in regions containing androgen receptor binding sites captured by ChIP-On-chip analyses.

Yizhen Lu; Jielin Sun; Andrew K Kader; Seong-Tae Kim; Jin-Woo Kim; Wennuan Liu; Jishan Sun; Daru Lu; Junjie Feng; Yi Zhu; et al. (Profiled Authors: Jeffrey Trent; William Isaacs)

State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China.
The Prostate 2012;72(4):376-85.

BACKGROUND: Genome-wide association studies (GWAS) have identified approximately three dozen single nucleotide polymorphisms (SNPs) consistently associated with prostate cancer (PCa) risk. Despite the reproducibility of these associations, the molecular mechanism for most of these SNPs has not been well elaborated as most lie within non-coding regions of the genome. Androgens play a key role in prostate carcinogenesis. Recently, using ChIP-on-chip technology, 22,447 androgen receptor (AR) binding sites have been mapped throughout the genome, greatly expanding the genomic regions potentially involved in androgen-mediated activity. METHODOLOGY/PRINCIPAL FINDINGS: To test the hypothesis that sequence variants in AR binding sites are associated with PCa risk, we performed a systematic evaluation among two existing PCa GWAS cohorts; the Johns Hopkins Hospital and the Cancer Genetic Markers of Susceptibility (CGEMS) study population. We demonstrate that regions containing AR binding sites are significantly enriched for PCa risk-associated SNPs, that is, more than expected by chance alone. In addition, compared with the entire genome, these newly observed risk-associated SNPs in these regions are significantly more likely to overlap with established PCa risk-associated SNPs from previous GWAS. 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 are located in regions of the genome containing AR binding sites. CONCLUSIONS/SIGNIFICANCE: The results to date 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 ultimately warrant testing through in-depth molecular analyses.

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