James D. Watson Institute of Genome Sciences, Zhejiang University, Hangzhou, China; T-Life Research Center Fudan University, Shanghai, China.
Prostate. 2011 Jun 15;71(9):955-63. doi: 10.1002/pros.21311. Epub 2010 Dec 6.
The majority of established prostate cancer (PCa) 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 PCa risk remain unclear. Here, we used a series of bioinformatic tools and databases to provide possible molecular insights into the actions of risk SNPs.
METHODOLOGY/PRINCIPAL FINDINGS: 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) (r(2) ≥ 0.5), we first mapped them to genomic functional annotation databases, including the encyclopedia of DNA elements (ENCODE), 11 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 FoxA1-binding sites (P = 0.05). About one-third of the 33 risk SNP blocks are located within AR-binding regions.
CONCLUSIONS/SIGNIFICANCE: The significant enrichment of risk SNPs in AR-binding sites may suggest a potential molecular mechanism for these SNPs in PCa initiation, and provide guidance for future functional studies.
从全基因组关联研究中确定的大多数已建立的前列腺癌 (PCa) 风险相关单核苷酸多态性 (SNP) 并不属于蛋白质编码区域。因此,这些 SNP 影响 PCa 风险的机制仍不清楚。在这里,我们使用了一系列生物信息学工具和数据库,为风险 SNP 的作用提供了可能的分子见解。
方法/主要发现:我们对 33 个已确定并证实与之前研究中的 PCa 风险相关的 SNP 进行了全面评估,以确定其潜在的功能影响。对于这 33 个 SNP 和其他连锁不平衡 (LD) (r²≥0.5) 中的 SNP,我们首先将它们映射到基因组功能注释数据库,包括 DNA 元件百科全书 (ENCODE)、加州大学圣克鲁兹分校 (UCSC) 表浏览器定义的 11 个基因组调控元件数据库,以及通过 ChIP-chip 技术定义的雄激素受体 (AR) 结合位点。然后进行富集分析,以评估风险 SNP 块是否在各种注释集中富集。风险 SNP 块在两个注释集中显著富集,超过了随机预期,包括 AR 结合位点 (P=0.003) 和 FoxA1 结合位点 (P=0.05)。33 个风险 SNP 块中有约三分之一位于 AR 结合区域内。
结论/意义:风险 SNP 在 AR 结合位点的显著富集可能表明这些 SNP 在 PCa 起始中的潜在分子机制,并为未来的功能研究提供指导。