Originally published as JCO Early Release 10.1200/JCO.2006.05.6861 on August 8 2006

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Pharmacogenomic Predictor of Sensitivity to Preoperative Chemotherapy With Paclitaxel and Fluorouracil, Doxorubicin, and Cyclophosphamide in Breast Cancer

Kenneth R. Hess, Keith Anderson, W. Fraser Symmans, Vicente Valero, Nuhad Ibrahim, Jaime A. Mejia, Daniel Booser, Richard L. Theriault, Aman U. Buzdar, Peter J. Dempsey, Roman Rouzier, Nour Sneige, Jeffrey S. Ross, Tatiana Vidaurre, Henry L. Gómez, Gabriel N. Hortobagyi, Lajos Pusztai

From the Departments of Biostatistics and Applied Mathematics, Pathology, Breast Medical Oncology and Radiology, The University of Texas M.D. Anderson Cancer Center, Houston, TX; Breast Cancer Unit and Unité Propre de l'Enseignement Supérieur; Equipe d'Accueil 3535 of the Institut Gustave Roussy, Villejuif, France; Albany Medical College, Albany NY; Departamento de Medicina Instituto Nacional de Enfermedades Neoplásicas, Lima, Perú

Address reprint requests to Lajos Pusztai, MD, DPhil, Department of Breast Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Unit 1354, PO Box 301439, Houston, TX 77230-1439; e-mail: lpusztai{at}mdanderson.org

Purpose We developed a multigene predictor of pathologic complete response (pCR) to preoperative weekly paclitaxel and fluorouracil-doxorubicin-cyclophosphamide (T/FAC) chemotherapy and assessed its predictive accuracy on independent cases.

Patients and Methods One hundred thirty-three patients with stage I-III breast cancer were included. Pretreatment gene expression profiling was performed with oligonecleotide microarrays on fine-needle aspiration specimens. We developed predictors of pCR from 82 cases and assessed accuracy on 51 independent cases.

Results Overall pCR rate was 26% in both cohorts. In the training set, 56 probes were identified as differentially expressed between pCR versus residual disease, at a false discovery rate of 1%. We examined the performance of 780 distinct classifiers (set of genes + prediction algorithm) in full cross-validation. Many predictors performed equally well. A nominally best 30-probe set Diagonal Linear Discriminant Analysis classifier was selected for independent validation. It showed significantly higher sensitivity (92% v 61%) than a clinical predictor including age, grade, and estrogen receptor status. The negative predictive value (96% v 86%) and area under the curve (0.877 v 0.811) were nominally better but not statistically significant. The combination of genomic and clinical information yielded a predictor not significantly different from the genomic predictor alone. In 31 samples, RNA was hybridized in replicate with resulting predictions that were 97% concordant.

Conclusion A 30-probe set pharmacogenomic predictor predicted pCR to T/FAC chemotherapy with high sensitivity and negative predictive value. This test correctly identified all but one of the patients who achieved pCR (12 of 13 patients) and all but one of those who were predicted to have residual disease had residual cancer (27 of 28 patients).

published online ahead of print at www.jco.org on August 7, 2006.

Supported by grants from the National Cancer Institute (RO1-CA106290), the Breast Cancer Research Foundation, the Gilder Foundation, the Dee Simmons Fund, and the Nellie B. Connally Breast Cancer Research Fund.

Terms in blue are defined in the glossary, found at the end of this article and online at www.jco.org.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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