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

Proc Natl Acad Sci U S A. 2007 Dec 11;104(50):20007-12. Published: 2007.12.10

Rameen Beroukhim, Gad Getz, Leia Nghiemphu, Jordi Barretina, Teli Hsueh, David Linhart, Igor Vivanco, Jeffrey C. Lee, Julie H. Huang, Sethu Alexander, Jinyan Du, Tweeny Kau, Roman K. Thomas, Kinjal Shah, Horacio Soto, Sven Perner, John Prensner, Ralph M. Debiasi, Francesca Demichelis, Charlie Hatton, Mark A. Rubin, Levi A. Garraway, Stan F. Nelson, Linda Liau, Paul Mischel, Tim F. Cloughesy, Matthew Meyerson, Todd R. Golub, Eric S. Lander, Ingo K. Mellinghoff, William R. Sellers

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Abstract

Comprehensive knowledge of the genomic alterations that underlie cancer is a critical foundation for diagnostics, prognostics and targeted therapeutics. Analyses of chromosomal aberrations are 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). We use it to study chromosomal aberrations in 141 gliomas and compare the results with two prior studies. Traditional methods show little concordance between these studies and highlight hundreds of altered regions. The new approach reveals a highly concordant picture involving ~35 significant events, including 16-18 broad events near chromosome-arm size and 16-21 focal events. About 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 need not have the same target. Specifically, gliomas with broad amplification of chromosome 7 have different properties than those with overlapping focal EGFR 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.

Keywords: bioinformatics comparative genomic hybridization copy-number alterations glioblastoma single-nucleotide polymorphism arrays

Supplemental Data

Description Link/Filename
Manuscript GISTIC_071020.pdf
Expression Files (272 MB) ftp://ftp.broad.mit.edu/pub/gistic/Expression.zip
Supplemental Information GISTIC_Supplement_071020.pdf
Affymetrix 50K Hind chip files (2.6 GB) ftp://ftp.broad.mit.edu/pub/gistic/Hind.zip
Segmented Data segmented_data_080520.seg
Affymetrix 50K Xba chip files (2.7 GB) ftp://ftp.broad.mit.edu/pub/gistic/Xba.zip
Array List File for GISTIC Glioma_array_list_080423.txt
Signal intensities & genotypes for all Hind samples (45 MB) ftp://ftp.broad.mit.edu/pub/gistic/Hind_summary.zip
Copy-number Polymorphisms (100K SNP only) 100K_CNVs_080423.txt
Signal intensities & genotypes for all Xba samples (46 MB) ftp://ftp.broad.mit.edu/pub/gistic/Xba_summary.zip
Marker Positions 100K_markerpositions.hg16.txt
Sample information (txt format) Sample_info_070424.txt
Array List File for GISTICPreprocessing Gliomas_normals_array_list_080522.txt
GISTIC FAQ GISTIC FAQ_090320.htm
GISTICPreprocessing for 64-bit Linux PREPROCESSING.tar.gz
GISTIC for 64-bit Linux GISTIC_0_9_2.tar.gz