Multiplexed kinase interactome profiling quantifies cellular network activity and plasticity

Area of Science:

• Biochemistry
• Molecular Biology
• Proteomics

Background:

• Protein-protein interaction (PPI) networks are crucial for cellular functions and disease pathogenesis.
• Kinases are key regulatory components within these networks, but studying their dynamic interactions remains challenging.
• Existing methods lack the speed and multiplexing capability for systematic analysis of kinase interactome dynamics.

Purpose of the Study:

• To develop and validate a novel chemoproteomic method for profiling kinase interactome dynamics.
• To investigate context-dependent changes in kinase interactomes across diverse cancer types.
• To identify novel kinase-associated drug targets and understand their role in cancer progression.

Main Methods:

• Kinobead competition and correlation analysis (kiCCA), a quantitative mass spectrometry-based chemoproteomic technique.
• High-throughput, multiplexed profiling of endogenous kinase interactomes.
• Analysis of kinase PPIs across 18 cancer cell lines to assess context-specific alterations.

Main Results:

• Identification of 1,154 protein-protein interactions involving 238 kinases.
• Quantification of dynamic kinase interactome changes correlated with cancer type, plasticity, and signaling states.
• Discovery of novel drug target candidates, including the endocytic adapter-associated kinase 1 (AAK1) complex.

Conclusions:

• The kiCCA method enables rapid and comprehensive profiling of kinase interactome dynamics.
• Kinase interactome plasticity is a significant factor in cancer cell signaling, progression, and drug resistance.
• Targeting specific kinase complexes, such as AAK1, offers potential therapeutic strategies for cancer treatment.