Association of off targets of ALK inhibitors with their adverse reactions revealed by a novel comprehensive phosphorylation profiling platform

Introduction : Five ALK inhibitors are currently approved for clinical use. Although all target ALK fusion proteins, their side-effect profiles differ markedly. These variations are suspected to result from off-target kinase interactions, but the molecular links remain unclear. We aimed to reveal this connection using a novel phosphorylation-based profiling system that comprehensively maps kinase-substrate relationships and pathway activations. Materials and Methods : Using a recently developed cell-free phosphorylation array, we measured the overall phosphorylation activity within cells. This system does not focus on specific phosphorylation sites; instead, it identifies substrates that become phosphorylated under each experimental condition from a pool of 1,492 proteins (816 substrates for 190 kinases and 845 proteins constituting 273 pathways).Cell lysates treated with ALK inhibitors were applied to the array, enabling phosphorylation reactions that mimic intracellular kinase activity. Computational analyses extracted three layers of information, condition-specifically phosphorylated substrates, activated pathways and kinases, allowing simultaneous assessment of both on-target and off-target effects. Results : Phosphorylation profiles induced by five ALK inhibitors were measured in EML4-ALK mutant cell line (NCI-H2228 [H2228]), and analyzed across substrates, kinases, and pathways. Each drug exhibited a distinct inhibition signature, indicating specific kinases and pathways selectively affected beyond ALK. Several off-target kinases and pathways associated with known clinical adverse reactions, providing mechanistic insight into drug-specific toxicities. Conclusion : This comprehensive phosphorylation profiling platform enabled simultaneous evaluation of on-target and off-target effects of kinase inhibitors. By linking molecular signaling changes to clinical side effects, the system provides a powerful approach for understanding complex kinase networks and guiding the development of safer next-generation inhibitors.