Mutual exclusivity analysis identifies oncogenic network modules

Giovanni Ciriello1, Ethan Cerami, Chris Sander

  • 1Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA.

Genome Research
|September 13, 2011
PubMed

Insights

We developed Mutual Exclusivity Modules in cancer (MEMo) to identify cancer gene pathways. MEMo reveals distinct genomic alterations in glioblastoma and ovarian cancer, aiding in understanding cancer development and potential therapies.

Area of Science:

  • Cancer Genomics
  • Systems Biology
  • Network Medicine

Background:

  • Tumors exhibit diverse genomic alterations, yet these often affect limited biological pathways.
  • Alterations within the same cancer-related pathway typically do not co-occur in the same patient.
  • Current knowledge of oncogenic pathway modules is incomplete.

Purpose of the Study:

  • To systematically identify oncogenic pathway modules using a novel computational method.
  • To analyze genomic alteration patterns in glioblastoma and serous ovarian cancer.

Main Methods:

  • Developed Mutual Exclusivity Modules in cancer (MEMo) algorithm.
  • Utilized correlation analysis and statistical tests to identify network modules based on recurrence, biological process participation, and mutual exclusivity of alterations.
  • Applied MEMo to The Cancer Genome Atlas (TCGA) data.

Main Results:

  • Identified known altered modules in glioblastoma, emphasizing mutual exclusivity in PI(3)K, p53, and Rb pathways.
  • Observed mutual exclusivity between BRCA1/2 inactivation and CCNE1 amplification/RB1 inactivation in serous ovarian cancer.
  • Identified RBBP8 as a candidate oncogene in Rb-mediated cell cycle control.

Conclusions:

  • MEMo effectively identifies oncogenic pathway modules and patterns of mutual exclusivity.
  • Findings suggest distinct mechanisms of genomic instability in ovarian cancer.
  • The method can nominate driver alterations and inform therapeutic combination strategies.

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