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
Read ManuscriptComprehensive 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.
| Description | Link/Filename |
|---|---|
| Expression Files (272 MB) | ftp://ftp.broad.mit.edu/pub/gistic/Expression.zip |
| Manuscript | GISTIC_071020.pdf |
| 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 |