A computational framework for detecting signatures of accelerated somatic evolution in cancer genomes

Smith, K. S.; Ghosh, D.; Pollard, K. S.; De, S.

doi:10.1101/177261

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bioRxiv · 10.1101/177261

A computational framework for detecting signatures of accelerated somatic evolution in cancer genomes

Smith, K. S.·Ghosh, D.·Pollard, K. S.·De, S.

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Abstract

By accumulation of somatic mutations, cancer genomes evolve, diverging away from the genome of the host. It remains unclear to what extent somatic evolutionary divergence is comparable across different regions of the cancer genome versus concentrated in specific genomic elements. We present a novel computational framework, SASE-mapper, to identify genomic regions that show signatures of accelerated somatic evolution (SASE) in a subset of samples in a cohort, marked by accumulation of an excess of somatic mutations compared to that expected based on local, context-aware background mutation rates in the cancer genomes. Analyzing tumor whole genome sequencing data for 365 samples from 5 cohorts we detect recurrent SASE at a genome-wide scale. The SASEs were enriched for genomic elements associated with active chromatin, and regulatory regions of several known cancer genes had SASE in multiple cohorts. Regions with SASE carried specific mutagenic signatures and often co-localized within the 3D nuclear space suggesting their common basis. A subset of SASEs was frequently associated with regulatory changes in key cancer pathways and also poor clinical outcome. While the SASE-associated mutations were not necessarily recurrent at base-pair resolution, the SASEs recurrently targeted same functional regions, with similar consequences. It is likely that regulatory redundancy and plasticity promote prevalence of SASE-like patterns in the cancer genomes.

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Smith, K. S., Ghosh, D., Pollard, K. S., De, S.. 2017-08-16. A computational framework for detecting signatures of accelerated somatic evolution in cancer genomes. https://doi.org/10.1101/177261

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