Expression profiling to predict outcome in breast cancer: the influence of sample selection

doi:10.1186/bcr548

Breast Cancer Res

Volume 5
Issue 1

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Gruvberger SK
Ringnér M
Edén P
Borg Å
Fernö M
Peterson C
Meltzer PS

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Ringnér M
Edén P
Borg Å
Fernö M
Peterson C
Meltzer PS
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Commentary

Expression profiling to predict outcome in breast cancer: the influence of sample selection

Sofia K Gruvberger¹, Markus Ringnér²^,3, Patrik Edén², Åke Borg¹, Mårten Fernö¹, Carsten Peterson² and Paul S Meltzer³

¹Department of Oncology, The Jubileum Institute, Lund University Hospital, Lund, Sweden

²Complex Systems Division, Department of Theoretical Physics, Lund University, Lund, Sweden

³Cancer Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA

author email corresponding author email

Breast Cancer Res 2003, 5:23-26doi:10.1186/bcr548


Published:	11 October 2002

The original version of this commentary contained an error in figure 1. This has been corrected. See reply, http://breast-cancer-research.com/content/5/1/57

Abstract

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.