Integrating muti-omics data to identify tissue-specific DNA methylation biomarkers for cancer risk

Nat Commun. 2024 Jul 18;15(1):6071. doi: 10.1038/s41467-024-50404-y.

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.

MeSH terms

  • Biomarkers, Tumor* / genetics
  • CpG Islands* / genetics
  • DNA Methylation*
  • Epigenesis, Genetic
  • Female
  • Gene Expression Regulation, Neoplastic
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study*
  • Humans
  • Male
  • Neoplasms* / genetics
  • Neoplasms, Germ Cell and Embryonal
  • Organ Specificity* / genetics
  • Testicular Neoplasms

Substances

  • Biomarkers, Tumor

Supplementary concepts

  • Testicular Germ Cell Tumor