Chromatin accessibility of primary human cancers ties regional mutational processes and signatures with tissues of origin.

ABSTRACT: Somatic mutations in cancer genomes are associated with DNA replication timing (RT) and chromatin accessibility (CA), however these observations are based on normal tissues and cell lines while primary cancer epigenomes remain uncharacterised. Here we use machine learning to model megabase-scale mutation burden in 2,500 whole cancer genomes and 17 cancer types via a compendium of 900 CA and RT profiles covering primary cancers, normal tissues, and cell lines. CA profiles of primary cancers, rather than those of normal tissues, are most predictive of regional mutagenesis in most cancer types. Feature prioritisation shows that the epigenomes of matching cancer types and organ systems are often the strongest predictors of regional mutation burden, highlighting disease-specific associations of

SUBMITTER: Ocsenas O 

PROVIDER: S-EPMC9365152 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature