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DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer Bashashati, Ali; Haffari, Gholamreza; Ding, Jiarui; Ha, Gavin; Lui, Kenneth; Rosner, Jamie; Huntsman, David G.; Caldas, Carlos; Aparicio, Samuel, 1963-; Shah, Sohrab P.

Abstract

Simultaneous interrogation of tumor genomes and transcriptomes is underway in unprecedented global efforts. Yet, despite the essential need to separate driver mutations modulating gene expression networks from transcriptionally inert passenger mutations, robust computational methods to ascertain the impact of individual mutations on transcriptional networks are underdeveloped. We introduce a novel computational framework, DriverNet, to identify likely driver mutations by virtue of their effect on mRNA expression networks. Application to four cancer datasets reveals the prevalence of rare candidate driver mutations associated with disrupted transcriptional networks and a simultaneous modulation of oncogenic and metabolic networks, induced by copy number co-modification of adjacent oncogenic and metabolic drivers. DriverNet is available on Bioconductor or at http://compbio.bccrc.ca/software/drivernet/ .

Item Metadata

Title
DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer
Creator
Bashashati, Ali; Haffari, Gholamreza; Ding, Jiarui; Ha, Gavin; Lui, Kenneth; Rosner, Jamie; Huntsman, David G.; Caldas, Carlos; Aparicio, Samuel, 1963-; Shah, Sohrab P.
Publisher
BioMed Central
Date Issued
2012-12-22
Description
Simultaneous interrogation of tumor genomes and transcriptomes is underway in unprecedented global efforts. Yet, despite the essential need to separate driver mutations modulating gene expression networks from transcriptionally inert passenger mutations, robust computational methods to ascertain the impact of individual mutations on transcriptional networks are underdeveloped. We introduce a novel computational framework, DriverNet, to identify likely driver mutations by virtue of their effect on mRNA expression networks. Application to four cancer datasets reveals the prevalence of rare candidate driver mutations associated with disrupted transcriptional networks and a simultaneous modulation of oncogenic and metabolic networks, induced by copy number co-modification of adjacent oncogenic and metabolic drivers. DriverNet is available on Bioconductor or at http://compbio.bccrc.ca/software/drivernet/ .
Subject
driver mutations; sequencing; cancer; transcriptional networks
Genre
Article
Type
Text
Language
eng
Date Available
2016-01-19
Provider
Vancouver : University of British Columbia Library
Rights
Attribution 4.0 International (CC BY 4.0)
DOI
10.14288/1.0223730
URI
http://hdl.handle.net/2429/56556
Affiliation
Computer Science, Department of; Medicine, Faculty of; Pathology and Laboratory Medicine, Department of; Science, Faculty of; Other UBC
Citation
Genome Biology. 2012 Dec 22;13(12):R124
Publisher DOI
10.1186/gb-2012-13-12-r124
Peer Review Status
Reviewed
Scholarly Level
Faculty
Copyright Holder
Bashashati et al.; licensee BioMed Central Ltd.
Rights URI
http://creativecommons.org/licenses/by/4.0/
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Rights

Attribution 4.0 International (CC BY 4.0)