title: Detecting cancer gene networks characterized by recurrent genomic alterations in a population.
abstract: High resolution, system-wide characterizations have demonstrated the capacity to identify genomic regions that undergo genomic aberrations. Such research efforts often aim at associating these regions with disease etiology and outcome. Identifying the corresponding biologic processes that are responsible for disease and its outcome remains challenging. Using novel analytic methods that utilize the structure of biologic networks, we are able to identify the specific networks that are highly significantly, nonrandomly altered by regions of copy number amplification observed in a systems-wide analysis. We demonstrate this method in breast cancer, where the state of a subset of the pathways identified through these regions is shown to be highly associated with disease survival and recurrence.
authors.affiliation: The Mina & Everard Faculty of Life Science, Bar Ilan University, Ramat Gan, Israel.
authors.forename: Sol
authors.initials: S
authors.lastname: Efroni
authors.forename: Rotem
authors.initials: R
authors.lastname: Ben-Hamo
authors.forename: Michael
authors.initials: M
authors.lastname: Edmonson
authors.forename: Sharon
authors.initials: S
authors.lastname: Greenblum
authors.forename: Carl F
authors.initials: CF
authors.lastname: Schaefer
authors.forename: Kenneth H
authors.initials: KH
authors.lastname: Buetow
mesh_terms: D001943:Breast Neoplasms; D019295:Computational Biology / Q000379:methods*; D056915:DNA Copy Number Variations; D005260:Female; D053263:Gene Regulatory Networks; D055106:Genome-Wide Association Study / Q000379:methods*; D042822:Genomic Instability; D006801:Humans; D008722:Methods; D009369:Neoplasms / Q000209:etiology / Q000235:genetics*; D012008:Recurrence; D049490:Systems Biology / Q000379:methods