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Research Articles: Therapeutics, Targets, and Development

Gene expression profiles do not consistently predict the clinical treatment response in locally advanced breast cancer

¹ Department of Genetics, Institute for Cancer Research, Rikshospitalet-Radiumhospitalet Medical Center; ² Medical Faculty, University of Oslo, Oslo, Norway; ³ Lineberger Comprehensive Cancer Center and Departments of Genetics and Pathology and Laboratory Medicine and ⁴ Department of Statistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; ⁵ Department of Medicine, Section of Oncology, Haukeland University Hospital; ⁶ The Gade Institute, Section for Pathology, University of Bergen, Bergen, Norway; and ⁷ Department of Molecular Biology, 140 Carl Icahn Laboratory, Princeton University, Princeton, New Jersey

Requests for reprints: Per Eystein Lønning, Department of Medicine, Section of Oncology, Haukeland University Hospital, N-5021 Bergen, Norway. Phone: 47-55975000; Fax: 47-55973599. E-mail: per.lonning{at}helse-bergen.no

Abstract

Neoadjuvant treatment offers an opportunity to correlate molecular variables to treatment response and to explore mechanisms of drug resistance in vivo. Here, we present a statistical analysis of large-scale gene expression patterns and their relationship to response following neoadjuvant chemotherapy in locally advanced breast cancers. We analyzed cDNA expression data from 81 tumors from two patient series, one treated with doxorubicin alone (51) and the other treated with 5-fluorouracil and mitomycin (30), and both were previously studied for correlations between TP53 status and response to therapy. We observed a low frequency of progressive disease within the luminal A subtype from both series (2 of 36 versus 13 of 45 patients; P = 0.0089) and a high frequency of progressive disease among patients with luminal B type tumors treated with doxorubicin (5 of 8 patients; P = 0.0078); however, aside from these two observations, no other consistent associations between response to chemotherapy and tumor subtype were observed. These specific associations could possibly be explained by covariance with TP53 mutation status, which also correlated with tumor subtype. Using supervised analysis, we could not uncover a gene profile that could reliably (>70% accuracy and specificity) predict response to either treatment regimen. [Mol Cancer Ther 2006;5(11):2914–8]

Grant support: Norwegian Cancer Society, Norwegian Research Council, "SalusAnsvar" Award (A-L. Børresen-Dale), National Cancer Institute Breast Specialized Program of Research Excellence program grant P50-CA58223-09A1, and Breast Cancer Research Foundation (C.M. Perou).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: The analyses of the data presented in this report are original work of the authors and have not been presented previously. Some molecular data on these cases have been used in two previous studies (see refs. 3 and 4), and the raw microarray data have been published in a different context (see ref. 9).

⁸ Supplementary material for this article is available at Molecular Cancer Therapeutics Online (http://mct.aacrjournals.org/).

⁹ http://www.microarray.org/sfgf/jsp/home.

¹⁰ http://genome-www.stanford.edu/breast_cancer/.

Received 3/ 7/06; revised 6/ 4/06; accepted 9/25/06.