Integrating evidence from protein domains to identify cancer driver mutations.

ABSTRACT: Cancer can develop through the accumulation of somatic mutations that drive uncontrolled cell proliferation. A central objective in cancer research is to identify mutations that provide a selective growth advantage to tumor cells, so-called driver mutations. Many computational methods infer driver missense mutations in proteins by assessing their recurrence. However, such an approach suffers from the limited capacity to detect those driver mutations that occur infrequently across tumor samples. One strategy to overcome this limitation is to aggregate mutations from proteins sharing the same protein domain. Here we constructed a benchmark of cancer driver and passenger mutations, based on the known experimental and clinical studies, and systematically evaluated the applicability of methods

SUBMITTER: Ostroverkhova D 

PROVIDER: S-EPMC12817466 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature