研究发现，尽管乳腺癌对化疗相对敏感，但并非所有治疗方案对所有患者都有效。当前缺乏有效的化疗反应预测临床测试，现有的个体标记物预测价值有限。通过微阵列研究，基因表达谱被证实可以作为乳腺癌的临床预测因素。实验旨在识别预测特定治疗反应的基因集，结合高通量功能筛选系统，为建立高精度预测系统和药物干预理想靶点提供策略。
摘要：
Breast cancer is considered to be relatively sensitive to chemotherapy, and multiple combinations of cytotoxic agents are used as standard therapy. Chemotherapy is applied empirically despite the observation that not all regimens are equally effective across the population of patients. Up-to-date clinical tests for predicting cancer chemotherapy response are not available, and individual markers have shown little predictive value. A number of microarray studies have demonstrated the use of genomic data, particularly gene expression signatures, as clinical prognostic factors in breast cancer. The identifi cation of patient subpopulations most likely to respond to therapy is a central goal of recent personalized medicine. We have designed experiments to identify gene sets that will predict treatmentspecifi c response in breast cancer. Taken together with our recent trial of construction of a high-throughput functional screening system for chemosensitivity-related genes, studies for drug sensitivity will provide rational strategies for establishment of the prediction system with high accuracy and identifi cation of ideal targets for drug intervention.
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