Multiplexed kinase interactome profiling quantifies cellular network activity and plasticity

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 dis-ease 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.

Automated summary

Dynamic changes in protein-protein interaction networks have significant implications for cellular functions and human diseases. Our study presents a quantitative mass spectrometry-based chemoproteomic method called kinobead competition and correlation analysis (kiCCA) that enables rapid and extensive profiling of kinase interactomes. Using kiCCA, we identified context-dependent kinase interactome changes in diverse cancer lines and discovered potential drug targets. Our findings highlight the importance of studying kinase interactome dynamics for understanding cellular signaling in health and disease.