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Clinical Research

Abstract 1767: Gene expression signatures as predictors of chemotherapeutic response in breast cancer

Marcia V. Fournier and Katherine J. Martin
Marcia V. Fournier
1Bioarray Therapeutics Inc., Belmont, MA.
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Katherine J. Martin
1Bioarray Therapeutics Inc., Belmont, MA.
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DOI: 10.1158/1538-7445.AM10-1767 Published April 2010
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Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC

Abstract

The purpose of this study is to evaluate a novel 22-gene signature as a predictor of response to chemotherapy in breast cancer. The extent of residual viable tumor following chemotherapy is the most important predictor of long-term outcome in breast cancer. It is essential to identify patients who will not respond to chemotherapy to avoid ineffective therapies as well as unnecessary side effects. The rate of complete pathologic response to chemotherapy is relatively low, ranging from 3% to 27% of patients. Much work has been performed to predict chemotherapy responsiveness, but, as of yet, no test is effective and widely used in the clinic. Gene expression signatures are a multifaceted approach to characterizing disease states. They offer the potential to tailor a chemotherapy regimen to an individual patient. Here we compare the ability of multiple gene signatures, including the 70-gene prognostic signature (MammaPrint) and the 22-gene signature among others, to accurately predict response to multiple different regimens of primary chemotherapy in breast cancer. Predictive ability is compared in independent microarray datasets totaling approximately 157 breast cancer patients treated with primary chemotherapy. Sensitivity, specificity, and overall accuracy were evaluated by receiver operating characteristics (ROC) graphs, a technique for visualizing, organizing, and selecting classifiers based on their performance. Results show that the 22-gene signature accurately predicts response to multiple primary chemotherapies (p<0.05). Importantly, the 22-gene signature outperformed other signatures with highly significant p-values in all datasets tested. This signature potentially represents a clinically useful method to select a personalized chemotherapy regimen for breast cancer patients.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1767.

  • ©2010 American Association for Cancer Research
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Cancer Research: 70 (8 Supplement)
April 2010
Volume 70, Issue 8 Supplement
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Abstract 1767: Gene expression signatures as predictors of chemotherapeutic response in breast cancer
Marcia V. Fournier and Katherine J. Martin
Cancer Res April 15 2010 (70) (8 Supplement) 1767; DOI: 10.1158/1538-7445.AM10-1767

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Abstract 1767: Gene expression signatures as predictors of chemotherapeutic response in breast cancer
Marcia V. Fournier and Katherine J. Martin
Cancer Res April 15 2010 (70) (8 Supplement) 1767; DOI: 10.1158/1538-7445.AM10-1767
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Cancer Research Online ISSN: 1538-7445
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