Scientific Publications

Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma

Publication TypeJournal Article
AuthorsBeroukhim, Rameen, Getz Gad, Nghiemphu Leia, Barretina Jordi, Hsueh Teli, Linhart David, Vivanco Igor, Lee Jeffrey C., Huang Julie H., Alexander Sethu, Du Jinyan, Kau Tweeny, Thomas Roman K., Shah Kinjal, Soto Horacio, Perner Sven, Prensner John, and Debiasi Ralp
AbstractComprehensive knowledge of the genomic alterations that underlie cancer is a critical foundation for diagnostics, prognostics, and targeted therapeutics. Systematic efforts to analyze cancer genomes are underway, but the analysis is hampered by the lack of a statistical framework to distinguish meaningful events from random background aberrations. Here we describe a systematic method, called Genomic Identification of Significant Targets in Cancer (GISTIC), designed for analyzing chromosomal aberrations in cancer. We use it to study chromosomal aberrations in 141 gliomas and compare the results with two prior studies. Traditional methods highlight hundreds of altered regions with little concordance between studies. The new approach reveals a highly concordant picture involving approximately 35 significant events, including 16-18 broad events near chromosome-arm size and 16-21 focal events. Approximately half of these events correspond to known cancer-related genes, only some of which have been previously tied to glioma. We also show that superimposed broad and focal events may have different biological consequences. Specifically, gliomas with broad amplification of chromosome 7 have properties different from those with overlapping focalEGFR amplification: the broad events act in part through effects on MET and its ligand HGF and correlate with MET dependence in vitro. Our results support the feasibility and utility of systematic characterization of the cancer genome.
Year of Publication2007
JournalProceedings of the National Academy of Sciences of the United States of America
Volume104
Issue50
Pages20007 - 12
Date Published (YYYY/MM/DD)2007/12/11/
ISBN Number1091-6490
KeywordsCancer, Cell Line, Chromosome Aberrations, Data Interpretation, Glioma, Humans, Polymorphism, Probability, Single Nucleotide, Statistical, Tumor