Literature DB >> 15897907

Identification of molecular apocrine breast tumours by microarray analysis.

Pierre Farmer1, Herve Bonnefoi, Veronique Becette, Michele Tubiana-Hulin, Pierre Fumoleau, Denis Larsimont, Gaetan Macgrogan, Jonas Bergh, David Cameron, Darlene Goldstein, Stephan Duss, Anne-Laure Nicoulaz, Cathrin Brisken, Maryse Fiche, Mauro Delorenzi, Richard Iggo.   

Abstract

Previous microarray studies on breast cancer identified multiple tumour classes, of which the most prominent, named luminal and basal, differ in expression of the oestrogen receptor alpha gene (ER). We report here the identification of a group of breast tumours with increased androgen signalling and a 'molecular apocrine' gene expression profile. Tumour samples from 49 patients with large operable or locally advanced breast cancers were tested on Affymetrix U133A gene expression microarrays. Principal components analysis and hierarchical clustering split the tumours into three groups: basal, luminal and a group we call molecular apocrine. All of the molecular apocrine tumours have strong apocrine features on histological examination (P=0.0002). The molecular apocrine group is androgen receptor (AR) positive and contains all of the ER-negative tumours outside the basal group. Kolmogorov-Smirnov testing indicates that oestrogen signalling is most active in the luminal group, and androgen signalling is most active in the molecular apocrine group. ERBB2 amplification is commoner in the molecular apocrine than the other groups. Genes that best split the three groups were identified by Wilcoxon test. Correlation of the average expression profile of these genes in our data with the expression profile of individual tumours in four published breast cancer studies suggest that molecular apocrine tumours represent 8-14% of tumours in these studies. Our data show that it is possible with microarray data to divide mammary tumour cells into three groups based on steroid receptor activity: luminal (ER+ AR+), basal (ER- AR-) and molecular apocrine (ER- AR+).

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Year:  2005        PMID: 15897907     DOI: 10.1038/sj.onc.1208561

Source DB:  PubMed          Journal:  Oncogene        ISSN: 0950-9232            Impact factor:   9.867


  303 in total

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