Expression profiling to predict outcome in breast cancer: the influence of sample selection
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* Corresponding author: Paul S Meltzer pmeltzer@mail.nih.gov
1 Department of Oncology, The Jubileum Institute, Lund University Hospital, Lund, Sweden
2 Complex Systems Division, Department of Theoretical Physics, Lund University, Lund, Sweden
3 Cancer Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
Breast Cancer Res 2003, 5:23-26 doi:10.1186/bcr548
Published: 11 October 2002Abstract
Gene expression profiling of tumors using DNA microarrays is a promising method for predicting prognosis and treatment response in cancer patients. It was recently reported that expression profiles of sporadic breast cancers could be used to predict disease recurrence better than currently available clinical and histopathological prognostic factors. Having observed an overlap in those data between the genes that predict outcome and those that predict estrogen receptor-α status, we examined their predictive power in an independent data set. We conclude that it may be important to define prognostic expression profiles separately for estrogen receptor-α-positive and estrogen receptor-α-negative tumors.