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Breast Tumor Clinical Implications

GSE3193 Homo sapiens (human) Expression microarray 85 samples Submitted 2005/08/25 Platform GPL180Platform GPL2777Platform GPL2778Platform GPL2776
At a glance

Expression microarray · human · 85 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Homo sapiens (human)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
85 samples: 66 distinct titles, 3 of them repeatedGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
The purpose of this study was to explore the possibility of classifying breast carcinomas based upon variations in gene expression patterns derived from cDNA microarrays, and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing tumor and normal breast tissues from 78 individuals were analyzed by hierarchical-clustering.
Read the full summary ↓
As reported previously, we identified a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized lluminal epithelial/ER-positiven group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets; first, a set of 456 cDNA clones previously selected to reflect the lintrinsicn properties of the tumors and, second, a gene set identified that highly correlated with patient outcome. Survival analyses on the sub-cohort of 51 patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set
This dataset
Open GSE3193 in finder → Find more human microarray datasets → Breast cancer landscape →
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 (GSE3193_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 PRJNA92851. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 11553815) ↗
Study design
66 distinct titles, 3 of them repeated
BC ×15 BC-HBC ×4 Normal Breast ×3

Supports a case/control comparison: 1 samples read as cases, 4 as controls.

How we read this: Read from 85 sample titles: 66 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 45 more — browse all 85 samples with per-sample file links →

More Breast cancer datasets

Search all human microarray datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.