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ROS1 抑制剂的差异网络分析揭示了 lorlatinib 通过共同靶向 PYK2 的多药理学。

Differential network analysis of ROS1 inhibitors reveals lorlatinib polypharmacology through co-targeting PYK2.

发表日期:2023 Oct 05
作者: Yi Liao, Lily L Remsing Rix, Xueli Li, Bin Fang, Victoria Izumi, Eric A Welsh, Andrii Monastyrskyi, Eric B Haura, John M Koomen, Robert C Doebele, Uwe Rix
来源: Cell Chemical Biology

摘要:

通常会针对同一适应症开发多种酪氨酸激酶抑制剂 (TKI)。然而,它们的相对整体功效常常不完全被理解,并且它们可能含有与预期目标合作的未被识别的目标。我们比较了几种 ROS1 TKI 对 ROS1 融合阳性肺癌细胞活力、ROS1 自磷酸化和激酶活性的抑制作用,这表明一种 TKI(劳拉替尼)具有不成比例的更高细胞效力。四种 ROS1 TKI 的定量化学和磷酸蛋白质组学以及差异网络分析表明,lorlatinib 对粘着斑信号传导具有独特的影响。使用药理学探针、RNA干扰和CRISPR-Cas9敲除的功能验证揭示了lorlatinib通过双重靶向ROS1和PYK2的多药理学机制,ROS1和PYK2与SRC形成多蛋白复合物。通过将 lorlatinib 与 SRC 抑制剂结合使用,该复合物的合理多靶点表现出显着的协同作用。综上所述,我们表明基于系统药理学的差异网络分析可以剖析多种 TKI 的混合典型/非典型多药理学机制,从而能够设计合理的药物组合。版权所有 © 2023 Elsevier Ltd. 保留所有权利。
Multiple tyrosine kinase inhibitors (TKIs) are often developed for the same indication. However, their relative overall efficacy is frequently incompletely understood and they may harbor unrecognized targets that cooperate with the intended target. We compared several ROS1 TKIs for inhibition of ROS1-fusion-positive lung cancer cell viability, ROS1 autophosphorylation and kinase activity, which indicated disproportionately higher cellular potency of one TKI, lorlatinib. Quantitative chemical and phosphoproteomics across four ROS1 TKIs and differential network analysis revealed that lorlatinib uniquely impacted focal adhesion signaling. Functional validation using pharmacological probes, RNA interference, and CRISPR-Cas9 knockout uncovered a polypharmacology mechanism of lorlatinib by dual targeting ROS1 and PYK2, which form a multiprotein complex with SRC. Rational multi-targeting of this complex by combining lorlatinib with SRC inhibitors exhibited pronounced synergy. Taken together, we show that systems pharmacology-based differential network analysis can dissect mixed canonical/non-canonical polypharmacology mechanisms across multiple TKIs enabling the design of rational drug combinations.Copyright © 2023 Elsevier Ltd. All rights reserved.