← BioTransfer GEO Dataset Finder
GEO series

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

GSE9635 Homo sapiens Genome variation profiling by SNP array; SNP genotyping by SNP array 374 samples Submitted 2007/12/11 Platform GPL2005Platform GPL2004
Summary
Comprehensive 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 ~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 may have different biological consequences. 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: SNP analysis, gliomas, chromosomal aberrations
This dataset
Download

Direct links to NCBI, no account and no request form: the whole study as GSE9635_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 374 samples.

Also filed as BioProject PRJNA103491. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Sort into groups and it will be fetched from NCBI.

+ 374 more — browse all 374 samples with per-sample file links →

Similar datasets

Search all human datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.