Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Helsinki Institute for Information Technology (HIIT), Aalto University, Espoo, Finland.
PLoS Comput Biol. 2020 Feb 3;16(2):e1007604. doi: 10.1371/journal.pcbi.1007604. eCollection 2020 Feb.
Drug combinations are becoming a standard treatment of many complex diseases due to their capability to overcome resistance to monotherapy. In the current preclinical drug combination screening, the top combinations for further study are often selected based on synergy alone, without considering the combination efficacy and toxicity effects, even though these are critical determinants for the clinical success of a therapy. To promote the prioritization of drug combinations based on integrated analysis of synergy, efficacy and toxicity profiles, we implemented a web-based open-source tool, SynToxProfiler (Synergy-Toxicity-Profiler). When applied to 20 anti-cancer drug combinations tested both in healthy control and T-cell prolymphocytic leukemia (T-PLL) patient cells, as well as to 77 anti-viral drug pairs tested in Huh7 liver cell line with and without Ebola virus infection, SynToxProfiler prioritized as top hits those synergistic drug pairs that showed higher selective efficacy (difference between efficacy and toxicity), which offers an improved likelihood for clinical success.
由于能够克服单药治疗的耐药性，药物联合治疗正在成为许多复杂疾病的标准治疗方法。在当前的临床前药物联合筛选中，通常仅根据协同作用选择进一步研究的最佳组合，而不考虑组合的疗效和毒性作用，尽管这些是治疗临床成功的关键决定因素。为了基于协同作用、疗效和毒性特征的综合分析来促进药物组合的优先级排序，我们开发了一个基于网络的开源工具 SynToxProfiler（协同-毒性-分析器）。当将其应用于在健康对照和 T 细胞前淋巴细胞白血病（T-PLL）患者细胞中测试的 20 种抗癌药物组合，以及在有和没有埃博拉病毒感染的 Huh7 肝细胞系中测试的 77 种抗病毒药物对时，SynToxProfiler 将那些显示更高选择性疗效（疗效与毒性之间的差异）的协同药物对优先列为最佳组合，这提高了临床成功的可能性。
