Pathway perturbations in signaling networks: Linking genotype to phenotype.

Genetic mutations Interactome and regulome Network perturbations Protein interactions Signaling pathways

Journal

Seminars in cell & developmental biology
ISSN: 1096-3634
Titre abrégé: Semin Cell Dev Biol
Pays: England
ID NLM: 9607332

Informations de publication

Date de publication:
03 2020
Historique:
received: 06 10 2017
revised: 29 03 2018
accepted: 04 05 2018
pubmed: 9 5 2018
medline: 12 3 2021
entrez: 9 5 2018
Statut: ppublish

Résumé

Genes and gene products interact with each other to form signal transduction networks in the cell. The interactome networks are under intricate regulation in physiological conditions, but could go awry upon genome instability caused by genetic mutations. In the past decade with next-generation sequencing technologies, an increasing number of genomic mutations have been identified in a variety of disease patients and healthy individuals. As functional and systematic studies on these mutations leap forward, they begin to reveal insights into cellular homeostasis and disease mechanisms. In this review, we discuss recent advances in the field of network biology and signaling pathway perturbations upon genomic changes, and highlight the success of various omics datasets in unraveling genotype-to-phenotype relationships.

Identifiants

pubmed: 29738884
pii: S1084-9521(17)30528-1
doi: 10.1016/j.semcdb.2018.05.001
pmc: PMC6230320
mid: NIHMS1504092
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

3-11

Subventions

Organisme : NCI NIH HHS
ID : K22 CA214765
Pays : United States
Organisme : Medical Research Council
ID : MC_U105185859
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : P30 CA016672
Pays : United States

Informations de copyright

Copyright © 2018 Elsevier Ltd. All rights reserved.

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Auteurs

Yongsheng Li (Y)

Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Daniel J McGrail (DJ)

Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.

Natasha Latysheva (N)

Medical Research Council Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK.

Song Yi (S)

Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, TX, 78712, USA. Electronic address: stephen.yi@austin.utexas.edu.

M Madan Babu (MM)

Medical Research Council Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK. Electronic address: madanm@mrc-lmb.cam.ac.uk.

Nidhi Sahni (N)

Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA; Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX, 77030, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. Electronic address: nsahni@mdanderson.org.

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