GEO series

Whole-transcript and exon-level expression data for human primary and metastatic prostate cancer samples and control normal adjacent benign prostate

GSE21034 Homo sapiens (human) Expression microarray 370 samples Submitted 2010/06/24 Platform GPL5188Platform GPL10264

At a glance

Expression microarray · human · 370 samples

What it is: Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism: Homo sapiens (human)
Samples: 370 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

Current knowledge of prostate cancer genomes is largely based on relatively small patient cohorts using single modality analysis platforms. Here we report concordant assessment of DNA copy number, mRNA and microRNA expression and focused exon resequencing in prostate tumors from 218 patients with primary or metastatic prostate cancer with a median of 5 years clinical follow-up, now made available as a public resource.

Read the full summary ↓

Mutations in known, commonly mutated oncogenes and tumor suppressor genes such as PIK3CA, KRAS, BRAF and TP53 are present but generally rare. However, integrative analysis of mutations with copy number alterations (CNAs) and expression changes reveal alterations in the PI3K, RAS/RAF and androgen receptor (AR) pathways in nearly all metastatic samples and in a higher frequency of primary samples than previously suspected based on single-gene studies. Other new findings include evidence that the nuclear receptor coactivator NCOA2 functions as a driver oncogene in ~20 percent of primaries. Tumors with the androgen-driven TMPRSS2-ERG fusion were significantly associated with a small, previously unrecognized, prostate-specific 3p14 deletion that, through mRNA expression and resequencing analysis, implicates FOXP1, RYBP and SHQ1 as candidate cooperative tumor suppressors. Comparison of transcriptome and DNA copy number data from primary tumors for prognostic impact revealed that CNAs robustly define clusters of low- and high-risk disease beyond that achieved by Gleason score. In sum, this integrative genomic analysis of a substantial cohort of tumors clarifies the role of several known cancer pathways in prostate cancer, implicates several new ones, reveals a previously unappreciated role for CNAs in prognosis and provides a blueprint for clinical development of pathway inhibitors.

This dataset

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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 (GSE21034_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 PRJNA129695. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 20579941) ↗

Samples in this study

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+ 370 more — browse all 370 samples with per-sample file links →

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