Weiss Andrea, Berndsen Robert H, Ding Xianting, Ho Chih-Ming, Dyson Paul J, van den Bergh Hubert, Griffioen Arjan W, Nowak-Sliwinska Patrycja
Institute of Chemical Sciences and Engineering, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Angiogenesis Laboratory, Department of Medical Oncology, VU University Medical Center, Amsterdam, The Netherlands.
Sci Rep. 2015 Sep 29;5:14508. doi: 10.1038/srep14508.
A major key to improvement of cancer therapy is the combination of drugs. Mixing drugs that already exist on the market may offer an attractive alternative. Here we report on a new model-based streamlined feedback system control (s-FSC) method, based on a design of experiment approach, for rapidly finding optimal drug mixtures with minimal experimental effort. We tested combinations in an in vitro assay for the viability of a renal cell adenocarcinoma (RCC) cell line, 786-O. An iterative cycle of in vitro testing and s-FSC analysis was repeated a few times until an optimal low dose combination was reached. Starting with ten drugs that target parallel pathways known to play a role in the development and progression of RCC, we identified the best overall drug combination, being a mixture of four drugs (axitinib, erlotinib, dasatinib and AZD4547) at low doses, inhibiting 90% of cell viability. The removal of AZD4547 from the optimized drug combination resulted in 80% of cell viability inhibition, while still maintaining the synergistic interaction. These optimized drug combinations were significantly more potent than monotherapies of all individual drugs (p < 0.001, CI < 0.3).
改善癌症治疗效果的一个关键因素是药物联合使用。将市面上已有的药物混合使用可能是一种有吸引力的选择。在此，我们报告一种基于实验设计方法的新型基于模型的简化反馈系统控制（s-FSC）方法，该方法可通过最少的实验工作量快速找到最佳药物组合。我们在体外试验中测试了针对肾细胞腺癌（RCC）细胞系786-O活力的药物组合。体外测试和s-FSC分析的迭代循环重复了几次，直到达到最佳低剂量组合。从针对已知在RCC发生和发展中起作用的平行途径的十种药物开始，我们确定了最佳的总体药物组合，即低剂量的四种药物（阿昔替尼、厄洛替尼、达沙替尼和AZD4547）的混合物，可抑制90%的细胞活力。从优化后的药物组合中去除AZD4547导致细胞活力抑制率为80%，同时仍保持协同相互作用。这些优化后的药物组合比所有单一药物的单一疗法显著更有效（p < 0.001，CI < 0.3）。
