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

GSE16011 Homo sapiens (human) Expression microarray 284 samples Submitted 2010/04/26 Platform GPL8542
At a glance

Expression microarray · human · 284 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Homo sapiens (human)
Samples
284 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
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.
Read the full summary ↓
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.
This dataset
Open GSE16011 in finder → Find more human microarray datasets →
Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE16011_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

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

NCBI GEO page ↗ Paper (PMID 19920198) ↗
Samples in this study

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