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Gene Expression Programs in Response to Hypoxia: Cell Type Specificity and Prognostic Significance in Human Cancers

GSE4185 Homo sapiens (human) Expression microarray 57 samples Submitted 2006/02/25 Platform GPL3291Platform GPL3335Platform GPL3428
At a glance

Expression microarray · human · 57 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Homo sapiens (human)
Samples
57 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
This 58 arrays are the basis of our hypoxia story published in PLoS Medicine. The cell type, oxygen tension and time points are indicated. Abstract: BACKGROUND: Inadequate oxygen (hypoxia) triggers a multifaceted cellular response that has important roles in normal physiology and in many human diseases. A transcription factor, hypoxia-inducible factor (HIF), plays a central role in the hypoxia response; its activity is regulated by the oxygen-dependent degradation of the HIF-1alpha protein.
Read the full summary ↓
Despite the ubiquity and importance of hypoxia responses, little is known about the variation in the global transcriptional response to hypoxia among different cell types or how this variation might relate to tissue- and cell-specific diseases. METHODS AND FINDINGS: We analyzed the temporal changes in global transcript levels in response to hypoxia in primary renal proximal tubule epithelial cells, breast epithelial cells, smooth muscle cells, and endothelial cells with DNA microarrays. The extent of the transcriptional response to hypoxia was greatest in the renal tubule cells. This heightened response was associated with a uniquely high level of HIF-1alpha RNA in renal cells, and it could be diminished by reducing HIF-1alpha expression via RNA interference. A gene-expression signature of the hypoxia response, derived from our studies of cultured mammary and renal tubular epithelial cells, showed coordinated variation in several human cancers, and was a strong predictor of clinical outcomes in breast and ovarian cancers. In an analysis of a large, published gene-expression dataset from breast cancers, we found that the prognostic information in the hypoxia signature was virtually independent of that provided by the previously reported wound signature and more predictive of outcomes than any of the clinical parameters in current use. CONCLUSIONS: The transcriptional response to hypoxia varies among human cells. Some of this variation is traceable to variation in expression of the HIF1A gene. A gene-expression signature of the cellular response to hypoxia is associated with a significantly poorer prognosis in breast and ovarian cancer. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set
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 (GSE4185_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

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 PRJNA95149. Searching any of these in the dataset finder brings you back here.

Samples in this study

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