Integrating genome and epigenome data to identify tissue-specific DNA methylation biomarkers for cancer risk

Abstract

AbstractThe relationship between tissue-specific DNA methylation and cancer risk remains inadequately elucidated. Leveraging the Genotype-Tissue Expression (GTEx) consortium, we developed genetic models to predict DNA methylation at CpG sites (CpGs) across the genome for seven tissues and applied these models to genome-wide association study (GWAS) data of corresponding cancers, namely breast, colorectal, renal cell, lung, ovarian, prostate, and testicular germ cell cancers. At Bonferroni-correctedP<0.05, we identified 2,776 CpGs significantly associated with cancer risk, of which 92.7% (2,572) were specific to a particular cancer type. Notably, 57 CpGs within 35 putative novel loci retained significant associations with cancer risk after conditioning on proximal GWAS-identified signals. Further integrative multi-omics analyses revealed 791 CpG-gene-cancer trios, suggesting that DNA methylation at 248 distinct CpGs might influence cancer risk through regulating expression of 145 uniquecis-genes. These findings substantially advance our understanding of the interplay between genetics, epigenetics, and gene expression in cancer etiology.