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Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [CGH]

GSE40966 Homo sapiens (human) Genome variation profiling by genome tiling array 463 samples Submitted 2013/05/22 Platform GPL16070
At a glance

human · 463 samples

Organism
Homo sapiens (human)
Samples
463 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI.
Summary (written by the submitters)
From a clinical and molecular perspective, colon cancer (CC) is a heterogeneous disease but to date no classification based on high-density transcriptome data has been established. The aim of this study was to build up a robust molecular classification of mRNA expression profiles (Affymetrix U133Plus2) of a large series of 443 CC and to validate it on an independent serie of 123 CC and 906 public dataset.
Read the full summary ↓
We identified and validated six molecular subtypes in this large cohort as a combination of multiple molecular processes that complement current disease stratification based on clinicopathological variables and molecular markers. The biological relevance of these subtypes was consolidated by significant differences in survival. These insights open new perspectives for improving prognostic models and targeted therapies.
This dataset
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.

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 (GSE40966_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Also filed as BioProject PRJNA175450. Searching any of these in the dataset finder brings you back here.

Samples in this study

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