Graduate School of Informatics, Middle East Technical University, Ankara, 06800, Turkey.
Department of Chemical and Biological Engineering, College of Engineering, Koc University, Istanbul, 34450, Turkey.
NPJ Syst Biol Appl. 2022 Apr 19;8(1):11. doi: 10.1038/s41540-022-00219-8.
Drugs not only perturb their immediate protein targets but also modulate multiple signaling pathways. In this study, we explored networks modulated by several drugs across multiple cancer cell lines by integrating their targets with transcriptomic and phosphoproteomic data. As a result, we obtained 236 reconstructed networks covering five cell lines and 70 drugs. A rigorous topological and pathway analysis showed that chemically and functionally different drugs may modulate overlapping networks. Additionally, we revealed a set of tumor-specific hidden pathways with the help of drug network models that are not detectable from the initial data. The difference in the target selectivity of the drugs leads to disjoint networks despite sharing a similar mechanism of action, e.g., HDAC inhibitors. We also used the reconstructed network models to study potential drug combinations based on the topological separation and found literature evidence for a set of drug pairs. Overall, network-level exploration of drug-modulated pathways and their deep comparison may potentially help optimize treatment strategies and suggest new drug combinations.
药物不仅会扰乱其直接的蛋白质靶标，还会调节多种信号通路。在这项研究中，我们通过将药物靶标与转录组和磷酸化蛋白质组数据整合，探索了多种药物在多种癌细胞系中调节的网络。结果，我们获得了涵盖五个细胞系和 70 种药物的 236 个重建网络。严格的拓扑和通路分析表明，化学和功能上不同的药物可能会调节重叠的网络。此外，我们借助药物网络模型揭示了一组肿瘤特异性隐藏通路，这些通路在初始数据中是无法检测到的。尽管作用机制相似，如组蛋白去乙酰化酶抑制剂，但药物的靶标选择性差异导致网络不相交。我们还使用重建的网络模型基于拓扑分离来研究潜在的药物组合，并找到了一组药物对的文献证据。总的来说，对药物调节的通路进行网络层面的探索及其深入比较，可能有助于优化治疗策略并提出新的药物组合。
