Abstract
BackgroundNatural selection shapes cancer genomes. Previous studies used signatures of positive selection to identify genes driving malignant transformation. However, the contribution of negative selection against somatic mutations that affect essential tumor functions or specific domains remains a controversial topic.ResultsHere, we analyze 7546 individual exomes from 26 tumor types from TCGA data to explore the portion of the cancer exome under negative selection. Although we find most of the genes neutrally evolving in a pan-cancer framework, we identify essential cancer genes and immune-exposed protein regions under significant negative selection. Moreover, our simulations suggest that the amount of negative selection is underestimated. We therefore choose an empirical approach to identify genes, functions, and protein regions under negative selection. We find that expression and mutation status of negatively selected genes is indicative of patient survival. Processes that are most strongly conserved are those that play fundamental cellular roles such as protein synthesis, glucose metabolism, and molecular transport. Intriguingly, we observe strong signals of selection in the immunopeptidome and proteins controlling peptide exposition, highlighting the importance of immune surveillance evasion. Additionally, tumor type-specific immune activity correlates with the strength of negative selection on human epitopes.ConclusionsIn summary, our results show that negative selection is a hallmark of cell essentiality and immune response in cancer. The functional domains identified could be exploited therapeutically, ultimately allowing for the development of novel cancer treatments.
Highlights
IntroductionPrevious studies used signatures of positive selection to identify genes driving malignant transformation
Among the 39 significantly selected genes, we found 14 to be under positive selection and 25 to be under negative selection (Table 1, Additional file 1: Table S3)
Upon comparing the precision and recall to a previously published gold standard of cancer drivers [30], we found that only a substantial relaxation of the false discovery rate (FDR) cut-off leads to a recovery of most known cancer drivers (Additional file 3: Figure S1)
Summary
Previous studies used signatures of positive selection to identify genes driving malignant transformation. The contribution of negative selection against somatic mutations that affect essential tumor functions or specific domains remains a controversial topic. The hallmarks of evolution include positive selection towards increasing the frequency of tumor-beneficial mutations and negative selection towards preventing the accumulation of harmful ones. Zapata et al Genome Biology (2018) 19:67 these initiatives have revealed an extensive landscape of somatic point mutations in driver genes across tumor types (mutational drivers). The number of cancer genes undergoing positive selection of somatic point mutations identified by in silico approaches is in the range of approximately 100–500 [6, 12,13,14]
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