Copy number losses of oncogenes and gains of tumor suppressor genes generate common driver events of human cancer

Cancer driver genes can be under positive selection for various types of genetic alterations, including gain-of-function or loss-of-function point mutations (single-nucleotide variants, SNV), small indels, copy number alterations (CNA) and other structural variants. We studied the landscape of interactions between these different types of alterations affecting the same gene by a statistical method, MutMatch, which can test for significant differences in selection, while accounting for various causes of mutation risk heterogeneity. Analyzing [~]18,000 cancer exomes and genomes, we found that known oncogenes simultaneously exhibit signatures of positive selection and also negative selection, where the latter can mask the former. Consistently, focussing on known positively selected regions identifies additional tumor types where an oncogene is relevant. Next, we characterized the landscape of CNA-dependent selection effects, revealing a general trend of increased positive selection on oncogene mutations not only upon CNA gains but also upon CNA deletions. Conversely, we observe a positive interaction between mutations and CNA gains in tumor suppressor genes. Thus, two-hit events involving point mutations and CNA are universally observed on driver genes regardless of the type of CNA, and may signal new therapeutic opportunities that have been overlooked. An explicit focus on the somatic CNA two-hit events can identify additional driver genes relevant to a tumor type. By a global analysis of CNA-selection effects across many driver genes and tissues, we identified at least four independently varying signatures, and thus generated a comprehensive, data-driven classification of cancer genes by mechanisms of (in)activation by genetic alterations.