Background: Natural 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. Results: Here, 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. Conclusions: In 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.

The research leading to these results received funding from the Spanish Ministry of Economy—, Industry and Competitiveness (Plan Nacional BIO2012-39754, BFU2012-31329 and BFU2015-68723-P and to the EMBL partnership), “Centro de Excelencia Severo Ochoa 2013–2017,” SEV-2012–0208, the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement nº. HEALTH-F4-2011–278568 (PRIMES), the European Fund for Regional Development (EFRD), European Union’s Horizon 2020 research and innovation programme under grant agreement Nº 635290 (PanCanRisk), CERCA Programme / Generalitat de Catalunya, the HHMI International Early Career Scientist Program (55007424), Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat’s AGAUR program (2014 SGR 0974), and the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013, ERC grant agreement 335980_EinME). LZ has been supported by the International PhD scholarship program of La Caixa at CRG and MS by the German Research Foundation (SCHA 1933/1-1).