GEO series

Definition of clinically distinct molecular subtypes in estrogen receptor positive breast carcinomas using genomic grade

GSE6532 Homo sapiens (human) Expression microarray 741 samples Submitted 2007/03/01 Platform GPL96Platform GPL97Platform GPL570

At a glance

Expression microarray · human · 741 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: 741 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

Purpose: A number of microarray studies have reported distinct molecular profiles of breast cancers (BC): basal-like, ErbB2-like and two to three luminal-like subtypes. These were associated with different clinical outcomes. However, although the basal and the ErbB2 subtypes are repeatedly recognized, identification of estrogen receptor (ER)-positive subtypes has been inconsistent.

Read the full summary ↓

Refinement of their molecular definition is therefore needed. Materials and methods: We have previously reported a gene-expression grade index (GGI) which defines histological grade based on gene expression profiles. Using this algorithm, we assigned ER-positive BC to either high or low genomic grade subgroups and compared these to previously reported ER-positive molecular classifications. As further validation, we classified 666 ER-positive samples into subtypes and assessed their clinical outcome. Results: Two ER-positive molecular subgroups (high and low genomic grade) could be defined using the GGI. Despite tracking a single biological pathway, these were highly comparable to the previously described luminal A and B classification and significantly correlated to the risk groups produced using the 21-gene recurrence score. The two subtypes were associated with statistically distinct clinical outcome in both systemically untreated and tamoxifen-treated populations. Conclusions: The use of genomic grade can identify two clinically distinct ER-positive molecular subtypes in a simple and highly reproducible manner across multiple datasets. This study emphasizes the important role of proliferation-related genes in predicting prognosis in ER-positive BC. Keywords: disease state analysis

This dataset

Open GSE6532 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 (GSE6532_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 PRJNA98807. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 17401012) ↗

Samples in this study

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+ 741 more — browse all 741 samples with per-sample file links →

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