Stochastic epigenetic mutations are associated with risk of breast cancer, lung cancer, and mature b-cell neoplasms

Background: Age-related epigenetic dysregulations are associated with several diseases, including cancer. The number of stochastic epigenetic mutations (SEM) has been suggested as a biomarker of life-course accumulation of exposure-related DNA damage; however, the predictive role of SEMs in cancer has seldom been investigated. Methods: A SEM, at a given CpG site, was defined as an extreme outlier of DNA methylation value distribution across individuals. We investigated the association of the total number of SEMs with the risk of eight cancers in 4,497 case-control pairs nested in three prospective cohorts. Furthermore, we investigated whether SEMs were randomly distributed across the genome or enriched in functional genomic regions. Results: In the three-study meta-analysis, the estimated ORs per one-unit increase in log(SEM) from logistic regression models adjusted for age and cancer risk factors were 1.25; 95% confidence interval (CI), 1.11-1.41 for breast cancer, and 1.23; 95% CI, 1.07-1.42 for lung cancer. In the Melbourne Collaborative Cohort Study, the OR for mature B-cell neoplasm was 1.46; 95% CI, 1.25-1.71. Enrichment analyses indicated that SEMs frequently occur in silenced genomic regions and in transcription factor binding sites regulated by EZH2 and SUZ12 (P < 0.0001 and P ¼ 0.0005, respectively): two components of the polycomb repressive complex 2 (PCR2). Finally, we showed that PCR2-specific SEMs are generally more stable over time compared with SEMs occurring in the whole genome. Conclusions: The number of SEMs is associated with a higher risk of different cancers in prediagnostic blood samples. Impact: We identified a candidate biomarker for cancer early detection, and we described a carcinogenesis mechanism involving PCR2 complex proteins worthy of further investigations.The authors are very thankful to Dr. Akram Ghantous (IARC, Lyon, France) for the methylation analyses of PEM-Turin study, produced within the Exposomics EC FP7 grant (grant agreement no. 308610, to P. Vineis). The results here are, in part, based upon data generated by TCGA research network: https://www.cancer.gov/tcga. The EPIC Italy component of this research was supported by European Commission grant no. 633666, awarded to P. Vineis, and by the AIRC grant (Progetto IG 2013 N.14410, to C. Sacerdote) for part of the DNA methylation experiments. The Melbourne Collaborative Cohort Study (MCCS) cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS component of the work was funded by the Australian National Health and Medical Research Council, including grants 1106016 (to G.G. Giles); 1011618 (to L. Baglietto); 1026892 (to M.C. Southey); 1027505 (to D.R. English); 1050198 and 1087683 (to A.M. Hodge); 1088405 (to R.L. Milne); and 1043616, 209057, 396414, and 1074383 (to G.G. Giles). Cases and their vital status were ascertained through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database. The NOWAC component of the work was supported by the European Research Council Advanced Researcher grant, 2008: Transcriptomics in cancer research (grant no. ERC-2008-AdG, to E. Lund).