Systematic integration of protein affecting mutations, gene fusions, and copy number alterations into a comprehensive somatic mutational profile

Abstract

A gene can be mutated across a tumor cohort by protein affecting mutations (PAMs), gene fusions, or copy number alterations (CNAs). These mutations can have a similar phenotypic effect (i.e., allelic heterogeneity) and should be integrated into a unified gene mutation profile. We provide OncoMerge as a somatic mutation integration platform that tames allelic heterogeneity, discovers causal mutations, integrates binary PAM and fusion with quantitative CNA data types, and overcomes known obstacles in cancer genetics. OncoMerge was applied to the 9,584 patient tumors from 32 cancers profiled by the TCGA Pan-Cancer Atlas to validate the novel integration methods. Integration increased the number and frequency of somatically mutated genes and improved the prediction of the somatic mutation role as either activating or loss of function. Using OncoMerge integrated somatic mutations boosts the power to infer active gene regulatory networks that increase the connectedness of the networks and incorporate more somatic mutations and regulators associated with cancer biology. We extracted transcription factor (TF) regulatory networks and found that they were enriched with feedback and feed-forward loop network motifs. Subsequent, signed network motif analysis demonstrated that coherent switch-like feedback motifs and delay-inducing feed-forward loops were the only enriched configurations. This enrichment pattern suggests that evolution in general or in the tumor microenvironment is selecting for these coherent functional configurations. The OncoMerge integrated somatic mutations provide a more comprehensive platform for studies linking somatic mutations to downstream cancer phenotypes and will lead to novel biological insights in clinical samples.