Open Access Highly Accessed Research article

Predicting a local recurrence after breast-conserving therapy by gene expression profiling

Dimitry SA Nuyten123, Bas Kreike123, Augustinus AM Hart1, Jen-Tsan Ashley Chi4, Julie B Sneddon4, Lodewyk FA Wessels2, Hans J Peterse2, Harry Bartelink1, Patrick O Brown45, Howard Y Chang5 and Marc J van de Vijver2*

Author Affiliations

1 Department of Radiation Oncology, The Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands

2 Department of Diagnostic Oncology, The Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands

3 Department of Experimental Therapy, The Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands

4 Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA

5 Program in Epithelial Biology, Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA

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Breast Cancer Research 2006, 8:R62  doi:10.1186/bcr1614

Published: 30 October 2006

Abstract

Introduction

To tailor local treatment in breast cancer patients there is a need for predicting ipsilateral recurrences after breast-conserving therapy. After adequate treatment (excision with free margins and radiotherapy), young age and incompletely excised extensive intraductal component are predictors for local recurrence, but many local recurrences can still not be predicted. Here we have used gene expression profiling by microarray analysis to identify gene expression profiles that can help to predict local recurrence in individual patients.

Methods

By using previously established gene expression profiles with proven value in predicting metastasis-free and overall survival (wound-response signature, 70-gene prognosis profile and hypoxia-induced profile) and training towards an optimal prediction of local recurrences in a training series, we establish a classifier for local recurrence after breast-conserving therapy.

Results

Validation of the different gene lists shows that the wound-response signature is able to separate patients with a high (29%) or low (5%) risk of a local recurrence at 10 years (sensitivity 87.5%, specificity 75%). In multivariable analysis the classifier is an independent predictor for local recurrence.

Conclusion

Our findings indicate that gene expression profiling can identify subgroups of patients at increased risk of developing a local recurrence after breast-conserving therapy.