Department of Pharmacology, University of Washington, Seattle, WA 98195, USA.
Department of Pharmacology, University of Washington, Seattle, WA 98195, USA.
Mol Cell. 2023 Mar 2;83(5):803-818.e8. doi: 10.1016/j.molcel.2023.01.015. Epub 2023 Feb 2.
Dynamic changes in protein-protein interaction (PPI) networks underlie all physiological cellular functions and drive devastating human diseases. Profiling PPI networks can, therefore, provide critical insight into disease mechanisms and identify new drug targets. Kinases are regulatory nodes in many PPI networks; yet, facile methods to systematically study kinase interactome dynamics are lacking. We describe kinobead competition and correlation analysis (kiCCA), a quantitative mass spectrometry-based chemoproteomic method for rapid and highly multiplexed profiling of endogenous kinase interactomes. Using kiCCA, we identified 1,154 PPIs of 238 kinases across 18 diverse cancer lines, quantifying context-dependent kinase interactome changes linked to cancer type, plasticity, and signaling states, thereby assembling an extensive knowledgebase for cell signaling research. We discovered drug target candidates, including an endocytic adapter-associated kinase (AAK1) complex that promotes cancer cell epithelial-mesenchymal plasticity and drug resistance. Our data demonstrate the importance of kinase interactome dynamics for cellular signaling in health and disease.
蛋白质-蛋白质相互作用（PPI）网络的动态变化是所有生理细胞功能的基础，并导致严重的人类疾病。因此，分析 PPI 网络可以深入了解疾病机制并确定新的药物靶点。激酶是许多 PPI 网络中的调节节点；然而，缺乏系统研究激酶互作组动力学的简便方法。我们描述了一种基于定量质谱的化学蛋白质组学方法——激酶珠竞争和相关分析（kiCCA），用于快速和高度多重化的内源性激酶互作组分析。使用 kiCCA，我们在 18 种不同的癌症系中鉴定了 238 种激酶的 1154 个 PPI，定量了与癌症类型、可塑性和信号状态相关的上下文相关激酶互作组变化，从而为细胞信号研究构建了一个广泛的知识库。我们发现了药物靶标候选物，包括促进癌细胞上皮-间充质可塑性和耐药性的内吞衔接相关激酶（AAK1）复合物。我们的数据表明激酶互作组动力学对于健康和疾病中的细胞信号非常重要。
