Identification of Common Driver Gene Modules and Associations between Cancers through Integrated Network Analysis.
driver gene module
gene mutation
mutual exclusivity
network analysis
signaling pathway
Journal
Global challenges (Hoboken, NJ)
ISSN: 2056-6646
Titre abrégé: Glob Chall
Pays: Germany
ID NLM: 101705641
Informations de publication
Date de publication:
Sep 2021
Sep 2021
Historique:
received:
20
01
2021
revised:
26
04
2021
entrez:
10
9
2021
pubmed:
11
9
2021
medline:
11
9
2021
Statut:
epublish
Résumé
High-throughput biological data has created an unprecedented opportunity for illuminating the mechanisms of tumor emergence and evolution. An important and challenging problem in deciphering cancers is to investigate the commonalities of driver genes and pathways and the associations between cancers. Aiming at this problem, a tool ComCovEx is developed to identify common cancer driver gene modules between two cancers by searching for the candidates in local signaling networks using an exclusivity-coverage iteration strategy and outputting those with significant coverage and exclusivity for both cancers. The associations of the cancer pairs are further evaluated by Fisher's exact test. Being applied to 11 TCGA cancer datasets, ComCovEx identifies 13 significantly associated cancer pairs with plenty of biologically significant common gene modules. The novel results of cancer relationship and common gene modules reveal the relevant pathological basis of different cancer types and provide new clues to diagnosis and drug treatment in associated cancers.
Identifiants
pubmed: 34504716
doi: 10.1002/gch2.202100006
pii: GCH2202100006
pmc: PMC8414517
doi:
Types de publication
Journal Article
Langues
eng
Pagination
2100006Informations de copyright
© 2021 The Authors. Global Challenges published by Wiley‐VCH GmbH.
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.
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