Identifying Driver Interfaces Enriched for Somatic Missense Mutations in Tumors

Abstract

Human cancers often harbor large numbers of somatic mutations. However, only a small proportion of these mutations are expected to contribute to tumor growth and progression. Therefore, determining causal driver mutations and the genes they target is becoming an important challenge in cancer genomics. Here we describe an approach for mapping somatic mutations onto 3D structures of human proteins in complex to identify “driver interfaces.” Our strategy relies on identifying protein-interaction interfaces that are unexpectedly biased toward nonsynonymous mutations, which suggests that these interfaces are subject to positive selection during tumorigenesis, implicating the interacting proteins as candidate drivers.