e-MutPath: computational modeling reveals the functional landscape of genetic mutations rewiring interactome networks.
Journal
Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011
Informations de publication
Date de publication:
11 01 2021
11 01 2021
Historique:
accepted:
20
10
2020
revised:
07
10
2020
received:
07
04
2020
pubmed:
20
11
2020
medline:
2
2
2021
entrez:
19
11
2020
Statut:
ppublish
Résumé
Understanding the functional impact of cancer somatic mutations represents a critical knowledge gap for implementing precision oncology. It has been increasingly appreciated that the interaction profile mediated by a genomic mutation provides a fundamental link between genotype and phenotype. However, specific effects on biological signaling networks for the majority of mutations are largely unknown by experimental approaches. To resolve this challenge, we developed e-MutPath (edgetic Mutation-mediated Pathway perturbations), a network-based computational method to identify candidate 'edgetic' mutations that perturb functional pathways. e-MutPath identifies informative paths that could be used to distinguish disease risk factors from neutral elements and to stratify disease subtypes with clinical relevance. The predicted targets are enriched in cancer vulnerability genes, known drug targets but depleted for proteins associated with side effects, demonstrating the power of network-based strategies to investigate the functional impact and perturbation profiles of genomic mutations. Together, e-MutPath represents a robust computational tool to systematically assign functions to genetic mutations, especially in the context of their specific pathway perturbation effect.
Identifiants
pubmed: 33211847
pii: 5992298
doi: 10.1093/nar/gkaa1015
pmc: PMC7797045
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
e2Subventions
Organisme : NIGMS NIH HHS
ID : R35 GM133658
Pays : United States
Organisme : NCI NIH HHS
ID : K99 CA240689
Pays : United States
Informations de copyright
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.
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