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Department of Oncology [S. G., Å. B., M. F.] and Complex Systems Division, Department of Theoretical Physics [M. R., C. P.], Lund University, SE-221 00 Lund, Sweden, and Cancer Genetics Branch, National Human Genome Research Institute [S. G., M. R., Y. C., S. P., L. H. S., P. S. M.], NIH, Bethesda, Maryland 20892
To investigate the phenotype associated with estrogen receptor 
(ER) expression in breast carcinoma, gene expression profiles of 58 node-negative breast carcinomas discordant for ER status were determined using DNA microarray technology. Using artificial neural networks as well as standard hierarchical clustering techniques, the tumors could be classified according to ER status, and a list of genes which discriminate tumors according to ER status was generated. The artificial neural networks could accurately predict ER status even when excluding top discriminator genes, including ER itself. By reference to the serial analysis of gene expression database, we found that only a small proportion of the 100 most important ER discriminator genes were also regulated by estradiol in MCF-7 cells. The results provide evidence that ER+ and ER- tumors display remarkably different gene-expression phenotypes not solely explained by differences in estrogen responsiveness.
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