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 ( < 0.0001 and = 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.
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http://dx.doi.org/10.1158/1055-9965.EPI-20-0451 | DOI Listing |
Am J Surg Pathol
December 2024
Department of Pathology, Indiana University School of Medicine, Indianapolis, IN.
Juxtaglomerular cell tumor (JxGCT) is a rare type of renal neoplasm demonstrating morphologic overlap with some mesenchymal tumors such as glomus tumor (GT) and solitary fibrous tumor (SFT). Its oncogenic drivers remain elusive, and only a few cases have been analyzed with modern molecular techniques. In prior studies, loss of chromosomes 9 and 11 appeared to be recurrent.
View Article and Find Full Text PDFTranscription factors (TFs) regulate gene expression despite constraints from chromatin structure and the cell cycle. Here we examine the concentration-dependent regulation of by the Bicoid morphogen through a combination of quantitative imaging, mathematical modeling and epigenomics in embryos. By live imaging of MS2 reporters, we find that, following mitosis, the timing of transcriptional activation driven by the P2 ( P2) enhancer directly reflects Bicoid concentration.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Biomedical Research Foundation, Academy of Athens (BRFAA), 4 Soranou Efesiou St., 11527 Athens, Greece.
Cellular reprogramming of somatic cells towards induced pluripotency is a multistep stochastic process mediated by the transcription factors Oct4, Sox2, Klf4 and c-Myc (OSKM), which orchestrate global epigenetic and transcriptional changes. We performed a large-scale analysis of integrated ChIP-seq, ATAC-seq and RNA-seq data and revealed the spatiotemporal highly dynamic pattern of OSKM DNA binding during reprogramming. We found that OSKM show distinct temporal patterns of binding to different classes of pluripotency-related enhancers.
View Article and Find Full Text PDFBioinform Adv
December 2024
Ray and Stephanie Lane Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, United States.
Motivation: Genomic biotechnology has rapidly advanced, allowing for the inference and modification of genetic and epigenetic information at the single-cell level. While these tools hold enormous potential for basic and clinical research, they also raise difficult issues of how to design studies to deploy them most effectively. In designing a genomic study, a modern researcher might combine many sequencing modalities and sampling protocols, each with different utility, costs, and other tradeoffs.
View Article and Find Full Text PDFAge-dependent changes in DNA methylation allow chronological and biological age inference, but the underlying mechanisms remain unclear. Using ultra-deep sequencing of >300 blood samples from healthy individuals, we show that age-dependent DNA methylation changes are regional and occur at multiple adjacent CpG sites, either stochastically or in a coordinated block-like manner. Deep learning analysis of single-molecule patterns in two genomic loci achieved accurate age prediction with a median error of 1.
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