Predictive factors to guide selection of the optimal chemotherapy for the individual patient with primary breast cancer are lacking. Neoadjuvant systemic treatment(NST) provides the opportunity to directly assess tumor response to therapy. As only the achievement of pathologic complete response (pCR) is associated with improved survival, it can serve as a surrogate for optimal chemotherapy efficacy. The direct assessment of the achievement of pCR to a particular treatment enables researchers to rapidly evaluate and validate new predictive factors. Recent technological advances have enabled researchers to scan the expression pattern of thousands of genes, i.e. thousands of possible predictive factors, at once. Thus far, 2 independent trials have been successful in identifying and validating gene expression signatures which predict the achievement of pCR to NST with high overall accuracy. The predictive value of these signatures outperformed single conventional parameters in multivariate analysis. Confirmation trials are ongoing to evaluate whether gene expression signatures can discriminate between likelihoods of response to different chemotherapy regimens. This would allow optimal treatment selection, thereby protecting patients from useless toxicity as well as dramatically reducing treatment costs. Gene expression profiling has the potential to help tailoring systemic breast cancer treatment, which is a major goal of current translational research.

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2006
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