Mutual exclusivity analysis identifies oncogenic network modules Journal Article


Authors: Ciriello, G.; Cerami, E.; Sander, C.; Schultz, N.
Article Title: Mutual exclusivity analysis identifies oncogenic network modules
Abstract: Although individual tumors of the same clinical type have surprisingly diverse genomic alterations, these events tend to occur in a limited number of pathways, and alterations that affect the same pathway tend to not co-occur in the same patient. While pathway analysis has been a powerful tool in cancer genomics, our knowledge of oncogenic pathway modules is incomplete. To systematically identify such modules, we have developed a novel method, Mutual Exclusivity Modules in cancer (MEMo). The method uses correlation analysis and statistical tests to identify network modules by three criteria: (1) Member genes are recurrently altered across a set of tumor samples; (2) member genes are known to or are likely to participate in the same biological process; and (3) alteration events within the modules are mutually exclusive. Applied to data from the Cancer Genome Atlas (TCGA), the method identifies the principal known altered modules in glioblastoma (GBM) and highlights the striking mutual exclusivity of genomic alterations in the PI(3)K, p53, and Rb pathways. In serous ovarian cancer, we make the novel observation that inactivation of BRCA1 and BRCA2 is mutually exclusive of amplification of CCNE1 and inactivation of RB1, suggesting distinct alternative causes of genomic instability in this cancer type; and, we identify RBBP8 as a candidate oncogene involved in Rb-mediated cell cycle control. When applied to any cancer genomics data set, the algorithm can nominate oncogenic alterations that have a particularly strong selective effect and may also be useful in the design of therapeutic combinations in cases where mutual exclusivity reflects synthetic lethality. © 2012 by Cold Spring Harbor Laboratory Press.
Keywords: ovary cancer; brca1 protein; brca2 protein; cancer genetics; oncogene; correlation analysis; statistical analysis; genomic instability; glioblastoma; cell cycle regulation; retinoblastoma protein; retinoblastoma binding protein; ccne1 gene
Journal Title: Genome Research
Volume: 22
Issue: 2
ISSN: 1088-9051
Publisher: Cold Spring Harbor Laboratory Press  
Date Published: 2012-02-01
Start Page: 398
End Page: 406
Language: English
DOI: 10.1101/gr.125567.111
PROVIDER: scopus
PMCID: PMC3266046
PUBMED: 21908773
DOI/URL:
Notes: --- - "Cited By (since 1996): 1" - "Export Date: 1 March 2012" - "CODEN: GEREF" - "Source: Scopus"
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  1. Chris Sander
    210 Sander
  2. Ethan Cerami
    21 Cerami
  3. Nikolaus D Schultz
    491 Schultz