The existence of a sex gap in human health and longevity has been widely documented. Autosomal DNA methylation differences between males and females have been reported, but so far, few studies have investigated if DNA methylation is differently affected by aging in males and females. We performed a metaanalysis of 4 large whole blood datasets, comparing 4 aspects of epigenetic age-dependent remodeling www.aging-us.com AGING between the two sexes: differential methylation, variability, epimutations and entropy. We reported that a large fraction (43%) of sex-associated probes undergoes age-associated DNA methylation changes, and that a limited number of probes show age-by-sex interaction. We experimentally validated 2 regions mapping in FIGN and PRR4 genes and showed sex-specific deviations of their methylation patterns in models of decelerated (centenarians) and accelerated (Down syndrome) aging. While we did not find sex differences in the ageassociated increase in epimutations and entropy, we showed that the number of probes having an age-related increase in methylation variability is 15 times higher in males compared to females. Our results can offer new epigenetic tools to study the interaction between aging and sex and can pave the way to the identification of molecular triggers of sex differences in longevity and age-related diseases prevalence.

Background: Age-related epigenetic dysregulations were associated with several diseases, including cancer. The individual number of stochastic epigenetic mutations (SEMs) 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 blood 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. Further, 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 odds ratios (ORs) per one-unit increase in log(SEM) from logistic regression models adjusted for age and cancer risk factors were 1.25; 95% CI 1.11-1.41 for breast cancer, and 1.23; 95% CI 1.07-1.42 for lung cancer. In MCCS, the OR for mature B-cell neoplasm was 1.46; 95% CI 1.25-1.71. Enrichment analyses indicated that SEMs more likely occur in silenced genomic regions and in transcription factor binding sites regulated by EZH2 and SUZ12 (p<0.0001 and p=0.0005 respectively): two components of the Polycomb-Repressive-Complex-2 (PCR2). Finally, using longitudinal DNA methylation data, we showed that PCR2-specific SEMs are generally more stable in 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. Enrichment analyses indicate key enzymatic pathways possibly involved in carcinogenesis mechanisms. Impact:We provide the first evidence of the prospective association between epimutations and a higher risk of different cancers. We hypothesized a possible mechanism of carcinogenesis involving PCR2 complex proteins worthy of further investigation.

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Background The “HER2-low” nomenclature identifies breast carcinomas (BCs) displaying a HER2 score of 1+/2+ in immunohistochemistry and lacking ERBB2 amplification. Whether HER2-low BCs (HLBCs) constitute a distinct entity is debated. Methods We performed DNA and RNA high-throughput analysis on 99 HLBC samples (n = 34 cases with HER2 score 1+/HLBC-1, n = 15 cases with HER2 score 2+ and ERBB2 not amplified/HLBC-2N, and n = 50 cases with score 2+ and ERBB2 copy number in the equivocal range/HLBC-2E). We compared the mutation rates with data from 1317 samples in the Memorial Sloan-Kettering Cancer Center (MSKCC) BC cohort and gene expression data with those from an internal cohort of HER2-negative and HER2-positive BCs. Results The most represented mutations affected PIK3CA (31/99, 31%), GATA3 (18/99, 18%), TP53 (17/99, 17%), and ERBB2 (8/99, 8%, private to HLBC-2E). Tumor mutational burden was significantly higher in HLBC-1 compared to HLBC-2E/N (P = 0.04). Comparison of mutation spectra revealed that HLBCs were different from both HER2-negative and HER2-positive BCs, with HLBC-1 resembling more HER2-negative tumors and HLBC-2 mutationally related to HER2-addicted tumors. Potentially actionable alterations (annotated by using OncoKB/ESCAT classes) affected 52 patients. Intra-group gene expression revealed overlapping features between HLBC-1 and control HER2-negative BCs, whereas the HLBC-2E tumors showed the highest diversity overall. The RNA-based class discovery analysis unveiled four subsets of tumors with (i) lymphocyte activation, (ii) unique enrichment in HER2-related features, (iii) stromal remodeling alterations, and (iv) actionability of PIK3CA mutations (LAURA classification). Conclusions HLBCs harbor distinct genomic features when compared with HER2-positive and HER2-negative BCs; however, differences across IHC classes were also unveiled thus dissecting the full picture of heterogeneity across HER2-low disease. The HLBC-2E category harbors most distinctive features, whereas HLBC-1 seems superimposable to HER2-negative disease. Further studies are needed to ascertain whether the four genomic-driver classes of the LAURA classification hold prognostic and/or predictive implications.