Dissecting the sources of gene expression variation in a pan-cancer analysis identifies novel regulatory mutations.

Nucleic Acids Res

Center for Systems and Computational Biology, Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey. New Brunswick, NJ 08901, USA.

Published: May 2018

Although the catalog of cancer-associated mutations in protein-coding regions is nearly complete for all major cancer types, an assessment of regulatory changes in cancer genomes and their clinical significance remain largely preliminary. Adopting bottom-up approach, we quantify the effects of different sources of gene expression variation in a cohort of 3899 samples from 10 cancer types. We find that copy number alterations, epigenetic changes, transcription factors and microRNAs collectively explain, on average, only 31-38% and 18-26% expression variation for cancer-associated and other genes, respectively, and that among these factors copy number alteration has the highest effect. We show that the genes with systematic, large expression variation that could not be attributed to these factors are enriched for pathways related to cancer hallmarks. Integrating whole genome sequencing data and focusing on genes with systematic expression variation we identify novel, recurrent regulatory mutations affecting known cancer genes such as NKX2-1 and GRIN2D in multiple cancer types. Nonetheless, at a genome-wide scale proportions of gene expression variation attributed to recurrent point mutations appear to be modest so far, especially when compared to that attributed to copy number changes - a pattern different from that observed for other complex diseases and traits. We suspect that, owing to plasticity and redundancy in biological pathways, regulatory alterations show complex combinatorial patterns, modulating gene expression in cancer genomes at a finer scale.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5961375PMC
http://dx.doi.org/10.1093/nar/gky271DOI Listing

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