PDF(Pubmed)
Abstract：
The relationship between tissue-specific DNA methylation and cancer risk remains inadequately elucidated. Leveraging resources from the Genotype-Tissue Expression consortium, here we develop genetic models to predict DNA methylation at CpG sites across the genome for seven tissues and apply these models to genome-wide association study data of corresponding cancers, namely breast, colorectal, renal cell, lung, ovarian, prostate, and testicular germ cell cancers. At Bonferroni-corrected P < 0.05, we identify 4248 CpGs that are significantly associated with cancer risk, of which 95.4% (4052) are specific to a particular cancer type. Notably, 92 CpGs within 55 putative novel loci retain significant associations with cancer risk after conditioning on proximal signals identified by genome-wide association studies. Integrative multi-omics analyses reveal 854 CpG-gene-cancer trios, suggesting that DNA methylation at 309 distinct CpGs might influence cancer risk through regulating the expression of 205 unique cis-genes. These findings substantially advance our understanding of the interplay between genetics, epigenetics, and gene expression in cancer etiology.
摘要：
组织特异性DNA甲基化与癌症风险之间的关系仍未充分阐明。利用来自基因型-组织表达联盟的资源，在这里，我们开发了遗传模型来预测七个组织基因组中CpG位点的DNA甲基化，并将这些模型应用于相应癌症的全基因组关联研究数据，即乳房，结直肠,肾细胞,肺，卵巢,前列腺,睾丸生殖细胞癌.在Bonferroni校正的P<0.05时，我们确定了4248个与癌症风险显着相关的CpG，其中95.4%(4052)是特定癌症类型的特异性。值得注意的是,在通过全基因组关联研究鉴定的近端信号调节后，55个推定的新基因座中的92个CpG与癌症风险保持显著关联。整合的多组学分析揭示了854个CpG基因癌症三重奏，这表明309个不同CpG的DNA甲基化可能通过调节205个独特顺式基因的表达来影响癌症风险。这些发现大大推进了我们对遗传学之间相互作用的理解，表观遗传学,和癌症病因中的基因表达。
