A correction for this article has been published in BMC Genomics 2007, 8:101

Research article

Discovery and validation of breast cancer subtypes

Amy V Kapp¹ , Stefanie S Jeffrey² , Anita Langerød³ , Anne-Lise Børresen-Dale^3,4 , Wonshik Han⁵ , Dong-Young Noh⁵ , Ida RK Bukholm^6,7 , Monica Nicolau² , Patrick O Brown⁸ and Robert Tibshirani^1,9

¹Department of Statistics, Stanford University, Stanford, CA, USA

²Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA

³Department of Genetics, Institute for Cancer Research, Rikshospitalet-Radiumhospitalet Medical Center, Oslo, Norway

⁴Medical Faculty, University of Oslo, Oslo, Norway

⁵Department of Surgery, Seoul National University College of Medicine, Seoul, Korea

⁶Department of Surgery, Akershus University Hospital, Nordbyhagen, Norway

⁷University of Oslo, Oslo, Norway

⁸Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA

⁹Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA, USA

author email corresponding author email

BMC Genomics 2006, 7:231doi:10.1186/1471-2164-7-231

Published:	11 September 2006

Abstract

Background

Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2⁺.

Results

Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1⁺/ERBB2^-, ESR1^-/ERBB2^-, and ERBB2⁺ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability.

Conclusion

As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.