Evolutionary Analysis of TCGA Data Using Over- and Under- Mutated Genes Identify Key Molecular Pathways and Cellular Functions in Lung Cancer Subtypes

SIMPLE SUMMARY: Evolution drives the initiation and progression of cancer. This is apparent in the concept of “driver mutations” that initiate cancer and observed in cells of the lineage. Less appreciated is natural selection’s role in conserving genes that are necessary for optimal cancer cell fitness. We identified highly mutated and highly conserved (under-mutated) genes across subtypes of lung adenocarcinoma distinguished by their driver mutations. The subtypes often shared highly mutated genes suggesting common utility in adapting to similar tissue environments. Conversely, conserved genes were subtype specific indicating tight co-adaptation with the initiating driver mutation. Conserved genes were highly expressed compared to those selected for mutations consistent with our hypothesis that they are critical for optimal fitness. Thus, subtype-specific conserved genes reveal variations critical molecular pathways and cellular functions within each tumor subtype. Computer simulations suggest targeting tumor-specific conserved genes may represent a highly effective treatment strategy. More generally, we present an investigative approach that uses evolutionary selection for hypotheses building and to identify genes in which further investigation should yield maximal clinical benefit. ABSTRACT: We identify critical conserved and mutated genes through a theoretical model linking a gene’s fitness contribution to its observed mutational frequency in a clinical cohort. “Passenger” gene mutations do not alter fitness and have mutational frequencies determined by gene size and the mutation rate. Driver mutations, which increase fitness (and proliferation), are observed more frequently than expected. Non-synonymous mutations in essential genes reduce fitness and are eliminated by natural selection resulting in lower prevalence than expected. We apply this “evolutionary triage” principle to TCGA data from EGFR-mutant, KRAS-mutant, and NEK (non-EGFR/KRAS) lung adenocarcinomas. We find frequent overlap of evolutionarily selected non-synonymous gene mutations among the subtypes suggesting enrichment for adaptations to common local tissue selection forces. Overlap of conserved genes in the LUAD subtypes is rare suggesting negative evolutionary selection is strongly dependent on initiating mutational events during carcinogenesis. Highly expressed genes are more likely to be conserved and significant changes in expression (>20% increased/decreased) are common in genes with evolutionarily selected mutations but not in conserved genes. EGFR-mut cancers have fewer average mutations (89) than KRAS-mut (228) and NEK (313). Subtype-specific variation in conserved and mutated genes identify critical molecular components in cell signaling, extracellular matrix remodeling, and membrane transporters. These findings demonstrate subtype-specific patterns of co-adaptations between the defining driver mutation and somatically conserved genes as well as novel insights into epigenetic versus genetic contributions to cancer evolution.