Discovering functional evolutionary dependencies in human cancers

Cancer cells retain genomic alterations that provide a selective advantage. The prediction and validation of advantageous alterations are major challenges in cancer genomics. Moreover, it is crucial to understand how the coexistence of specific alterations alters response to genetic and therapeutic perturbations. In the present study, we inferred functional alterations and preferentially selected combinations of events in >9,000 human tumors. Using a Bayesian inference framework, we validated computational predictions with high-throughput readouts from genetic and pharmacological screenings on 2,000 cancer cell lines. Mutually exclusive and co-occurring cancer alterations reflected, respectively, functional redundancies able to rescue the phenotype of individual target inhibition, or synergistic interactions, increasing oncogene addiction. Among the top scoring dependencies, co-alteration of the phosphoinositide 3-kinase (PI3K) subunit PIK3CA and the nuclear factor NFE2L2 was a synergistic evolutionary trajectory in squamous cell carcinomas. By integrating computational, experimental and clinical evidence, we provide a framework to study the combinatorial functional effects of cancer genomic alterations. Computational analysis of over 9,000 cancer genomes, coupled with functional validation in cell lines, highlights combinations of mutations required for tumor progression. This integrated approach provides a framework to stratify patients on the basis of interdependent genetic aberrations.