bioRxivGenomics
Chromatin marks govern mutation landscape of cancer at early stage of progression
Abstract
Accumulation of somatic mutations over time leads to tissue abnormalities, such as cancer. Somatic mutation rates vary across the genome in a cell-type specific manner, depending on the types of mutation processes1-7. Although recent studies have identified several determinants relevant to the establishment of the cancer mutation landscape8-13, these studies have yet to propose the major time point at which these factors come into play during cancer progression. Here, we analyzed whole genome sequencing data from two different types of precancerous tissues, monoclonal B-cell lymphocytosis and Barretts esophagus, and their matching cancer types along with 423 epigenetic features from normal tissues to determine the critical time point when chromatin features contribute to the formation of the somatic mutation landscape. Our analyses revealed that a subset of cell-of-origin associated chromatin features can explain more than 80% of the regional mutation variance for both types of precancerous tissues, comparable to the variance explained level for the genomes of matching cancer types. In particular, major significant chromatin features explaining the mutation landscape of Barretts esophagus and esophageal adenocarcinoma were derived from stomach tissues, indicating that mutation landscape establishment occurs mostly after environment-mediated epigenetic changes during gastric metaplasia. Analyses of the genome of esophageal squamous cell carcinoma tissues demonstrated that the proposed time point for mutation landscape establishment of Barretts esophagus and esophageal adenocarcinoma were specific to the occurrence of cell-type shift. Thus, our data suggest that the major time point for the mutation landscape establishment dictated by chromatin features is early in the process of cancer progression, and epigenetic changes due to environmental conditions at early stages can dramatically impact the somatic mutation landscape of cancer.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
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