Nagasaki Koichi, Miki Yoshio
Genome Center, Cancer Institute, Japanese Foundation for Cancer Research, 3-10-6 Ariake, Koto-ku, Tokyo, 135-8550, Japan.
Breast Cancer. 2008;15(2):117-20. doi: 10.1007/s12282-008-0031-6.
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 identification 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 treatment-specific response in breast cancer. Taken together with our recent trial about the construction of a high-throughput functional screening system for chemo-sensitivity related genes, studies for drug sensitivity will provide rational strategies for establishment of the prediction system with high accuracy, and identification of ideal targets for drug intervention.
乳腺癌被认为对化疗相对敏感，多种细胞毒性药物组合被用作标准治疗方法。尽管观察到并非所有方案在所有患者群体中都同样有效，但化疗仍是凭经验应用。目前尚无预测癌症化疗反应的临床测试，而且单个标志物的预测价值很小。一些微阵列研究已经证明，基因组数据，特别是基因表达特征，可作为乳腺癌的临床预后因素。识别最有可能对治疗产生反应的患者亚群是近期个性化医疗的核心目标。我们设计了实验来识别能够预测乳腺癌治疗特异性反应的基因集。结合我们最近关于构建化疗敏感性相关基因高通量功能筛选系统的试验，药物敏感性研究将为建立高精度预测系统和识别药物干预的理想靶点提供合理策略。
