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Updated: Aug 1, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
Published on: March 14, 2013
Metabolic Profiling of Canertinib: A Comprehensive Cross-Species Investigation Using Advanced UPLC-MS/MS and
Weiqi Yuan1, Gang Shi1, Lantu Gou1
1State Key Laboratory of Biotherapy and Cancer Center/Collaborative Innovation Center for Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Abstract:
Canertinib is an EGFR tyrosine kinase inhibitor intended for the treatment of leukemia and non-small cell lung cancer. This study described a UPLC-MS/MS method for quantitatively assessing the metabolic stability of canertinib in liver microsomes. The developed method showed excellent linearity over the concentration range of 10-1000 nM, which is suitable for in vitro high-throughput screening. Canertinib showed marked species-dependent metabolism, with CLin vitro, mic following the order: human (28.3 μL/min/mg protein) < rat (48.2 μL/min/mg protein) < monkey (77.8 μL/min/mg protein). An LC-Orbitrap-HRMS facilitated structural characterization of the metabolites via accurate mass measurements and MS/MS fragmentation interpretation. Post-acquisition data-mining strategies, specifically high-resolution extracted ion chromatograms and multimass defect filtering, were employed to screen the putative metabolite candidates. Sixteen NADPH-dependent metabolites and one GSH conjugate were structurally characterized. Cross-species comparative analysis revealed notable interspecies variations: metabolites M9 and M17 were identified as human-specific, while M15 and M16 demonstrated monkey-specificity. The metabolic pathways of canertinib included oxidative defluorination, O-dealkylation, oxidative deamination, piperidine ring opening, lactam formation, and GSH conjugation. This work represents the first cross-species metabolic investigation of canertinib, providing critical insights into interspecies metabolic disparities. The elucidated metabolic framework advances mechanistic understanding of the compound's pharmacological activity and toxicity profiles.
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