Medicinal Bioconvergence Research Center, Seoul National University, Seoul, South Korea.
PLoS One. 2012;7(8):e42573. doi: 10.1371/journal.pone.0042573. Epub 2012 Aug 8.
Anticancer therapies that target single signal transduction pathways often fail to prevent proliferation of cancer cells because of overlapping functions and cross-talk between different signaling pathways. Recent research has identified that balanced multi-component therapies might be more efficacious than highly specific single component therapies in certain cases. Ideally, synergistic combinations can provide 1) increased efficacy of the therapeutic effect 2) reduced toxicity as a result of decreased dosage providing equivalent or increased efficacy 3) the avoidance or delayed onset of drug resistance. Therefore, the interest in combinatorial drug discovery based on systems-oriented approaches has been increasing steadily in recent years.
Here we describe the development of Combinatorial Drug Assembler (CDA), a genomics and bioinformatics system, whereby using gene expression profiling, multiple signaling pathways are targeted for combinatorial drug discovery. CDA performs expression pattern matching of signaling pathway components to compare genes expressed in an input cell line (or patient sample data), with expression patterns in cell lines treated with different small molecules. Then it detects best pattern matching combinatorial drug pairs across the input gene set-related signaling pathways to detect where gene expression patterns overlap and those predicted drug pairs could likely be applied as combination therapy. We carried out in vitro validations on non-small cell lung cancer cells and triple-negative breast cancer (TNBC) cells. We found two combinatorial drug pairs that showed synergistic effect on lung cancer cells. Furthermore, we also observed that halofantrine and vinblastine were synergistic on TNBC cells.
CDA provides a new way for rational drug combination. Together with phExplorer, CDA also provides functional insights into combinatorial drugs. CDA is freely available at http://cda.i-pharm.org.
针对单一信号转导通路的抗癌疗法往往无法阻止癌细胞的增殖，因为不同信号通路之间存在重叠的功能和串扰。最近的研究表明，在某些情况下，平衡的多成分疗法可能比高度特异性的单一成分疗法更有效。理想情况下，协同组合可以提供 1）增加治疗效果的功效 2）降低毒性，从而减少剂量，提供等效或增加的疗效 3）避免或延迟耐药性的发生。因此，近年来，基于系统导向方法的组合药物发现的兴趣一直在稳步增加。
在这里，我们描述了组合药物装配器（CDA）的开发，这是一个基因组学和生物信息学系统，通过使用基因表达谱分析，针对多个信号通路进行组合药物发现。CDA 对信号通路组件的表达模式进行匹配，以比较输入细胞系（或患者样本数据）中表达的基因与用不同小分子处理的细胞系中的表达模式。然后，它检测输入基因集相关信号通路中最佳模式匹配的组合药物对，以检测基因表达模式重叠的位置，以及那些预测的药物对可能作为组合疗法应用。我们在非小细胞肺癌细胞和三阴性乳腺癌（TNBC）细胞上进行了体外验证。我们发现了两种对肺癌细胞具有协同作用的组合药物对。此外，我们还观察到卤泛群和长春碱在 TNBC 细胞上具有协同作用。
CDA 为合理药物组合提供了一种新方法。与 phExplorer 一起，CDA 还为组合药物提供了功能见解。CDA 可在 http://cda.i-pharm.org 免费获得。
