Abstract
Somatic mutation rates in cancer differ across the genome in a cancer cell-type specific manner. Although key factors that contribute to the differences were identified, the major cancer progression stage when these factors associate with the mutation variance remained poorly investigated. Here, we analyzed whole-genome sequencing data of pre-cancerous and matching cancer tissues from 173 individuals and 423 normal tissue chromatin features to determine the critical stage of these features contributing to shaping the somatic mutation landscape. Our data showed that the establishment of somatic mutation landscape inferred by chromatin features occur early in the process of cancer progression, and gastric acid reflux environmental exposure-mediated epigenetic changes, represented as gastric metaplasia, at early stage can dramatically impact the somatic mutation landscape. We suggest a possible crucial role of chromatin features during the mutation landscape establishment at early stage of progression in a cancer-type specific manner.
Highlights
Recent advances in cancer genomics have so far revealed numerous somatic mutation landscapes for various cancer types, leading to a number of key findings
Consistent with the differences in average mutation frequency, both monoclonal B cell lymphocytosis (MBL) samples and chronic lymphocytic leukemia (CLL) samples were indistinguishably located and formed separate clusters based on immunoglobulin heavy chain variable region (IGHV) mutation status, a key marker for distinguishing either naive-B cells or memory B cell origin for both MBL and CLL.[16, 18]
Individual Barrett’s esophagus (BE) tissues formed clusters with the esophageal adenocarcinoma (EAC) tissues separate from the esophageal squamous cell carcinoma (ESCC) tissues, suggesting that the matching of cancer progression history might serve as a stronger factor than the cellof-origin context (Fig. 1b)
Summary
Recent advances in cancer genomics have so far revealed numerous somatic mutation landscapes for various cancer types, leading to a number of key findings. Beyond these gene-focused approaches, systematic analyses of mechanisms that could explain genomic regional variations in mutation rates across various cancer types could significantly extend our understanding about common contributors to the establishment of mutation landscapes before and during cancer progression To this end, a number of studies have examined relationships between regional mutation frequencies across the genome and several types of features, including gene expression level, DNA sequence context, mutation profiles of nucleotide excision and mismatch repair genes, histone post-translational modifications, and open chromatin marks such as DNase1-seq profiles.[8,9,10,11,12,13,14,15] these factors display high correlation with regional mutation rates, somatic mutation profiles used for the studies were limited to fully progressed tumors. Analyzing the mutation landscapes of precancerous, non-neoplastic tissues alongside matching cancer tissues could help to determine the major time points where chromatin marks shape the mutation landscape
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