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Intrinsic Gene Expression Profiles of Gliomas are a Better Predictor of Survival than Histology

GSE16011 Homo sapiens Expression profiling by array 284 samples Submitted 2010/04/26 Platform GPL8542
Summary
Histological classification of gliomas guides treatment decisions. Because of the high interobserver variability, we aimed to improve classification by performing gene expression profiling on a large cohort of glioma samples of all histological subtypes and grades. The seven identified intrinsic molecular subtypes are different from histological subgroups and correlate better to patient survival. Our data indicate that distinct molecular subgroups clearly benefit from treatment. Specific genetic changes (EGFR amplification, IDH1 mutation, 1p/19q LOH) segregate in -and may drive- the distinct molecular subgroups. Our findings were validated on three large independent sample cohorts (TCGA, REMBRANDT, and GSE12907). We provide compelling evidence that expression profiling is a more accurate and objective method to classify gliomas than histology.
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Direct links to NCBI, no account and no request form: the whole study as GSE16011_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 284 samples.

Whole study · RAW.tar ↓ Series matrix ↓ All supplementary files ↗

Also filed as BioProject PRJNA115435. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 19920198) ↗
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