Adaptation of a mutual exclusivity framework to identify driver mutations within oncogenic pathways.

ABSTRACT: Distinguishing genomic alterations in cancer-associated genes that have functional impact on tumor growth and disease progression from the ones that are passengers and confer no fitness advantage have important clinical implications. Evidence-based methods for nominating drivers are limited by existing knowledge on the oncogenic effects and therapeutic benefits of specific variants from clinical trials or experimental settings. As clinical sequencing becomes a mainstay of patient care, applying computational methods to mine the rapidly growing clinical genomic data holds promise in uncovering functional candidates beyond the existing knowledge base and expanding the patient population that could potentially benefit from genetically targeted therapies. We propose a statistical and computati

SUBMITTER: Wang X 

PROVIDER: S-EPMC10870134 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature