CORRELATING DIFFERENTIAL ENDOGENOUS METABOLITE PROFILES WITH THE PHARMACOKINETICS OF GEFITINIB AND ITS ASSOCIATED DRUG METABOLITES USING AN ION MOBILITY BASED APPROACH

Correlating Differential Endogenous Metabolite Profiles with Pharmacokinetics of Gefitinib Using UPLC-IM-MS

Importance of the Topic

Understanding both the metabolic fate of Gefitinib and its impact on endogenous metabolites is essential for optimizing therapeutic efficacy and safety in non-small cell lung cancer treatment. High-throughput analytical platforms that combine chromatographic, ion mobility, and high-resolution mass spectrometry enable comprehensive profiling of drug and biological responses in a single workflow.

Study Objectives and Overview

This work aimed to apply a HILIC-UPLC-ion mobility spectrometry-MS (IMS-MS) approach to characterize Gefitinib-related metabolites and track endogenous metabolic changes in mouse urine over a 24-hour period following both oral and intravenous administration.

Methodology

Chromatographic separation was achieved using hydrophilic interaction liquid chromatography (HILIC) coupled to an ultra-performance LC system. A cyclic ion mobility device provided an additional separation dimension and collision cross section (CCS) values. High-resolution MS acquisition captured accurate mass data.

Instrumentation

• UPLC system with HILIC column
• Cyclic ion mobility spectrometer (cIMS)
• High-resolution mass spectrometer
• Data processing with Progenesis QI, MetaboAnalyst, and Reactome pathway tools

Main Results and Discussion

• A Gefitinib metabolite at m/z 449 exhibited a clear pharmacokinetic profile, peaking at 3–8 hours postdose and returning to baseline by 24 hours.
• Unsupervised PCA of endogenous metabolites mirrored the drug profile, indicating systemic metabolic responses aligned with plasma exposure.
• Statistical feature selection and Pearson correlation revealed compound classes with positive correlation (steroidal metabolites) and negative correlation (dipeptides, carnitine derivatives).
• Pathway enrichment highlighted perturbations in spermidine/spermine biosynthesis, steroidogenesis, amino acid metabolism, and immune-related signaling.

Practical Benefits and Applications

• High-throughput drug metabolism and endogenous metabolome profiling in a single assay accelerates biomarker discovery.
• Correlation of metabolite trends with pharmacokinetic data supports mechanistic insights and safety assessment.
• The approach is compatible with modern drug discovery pipelines requiring rapid turnaround times.

Future Trends and Potential Applications

• Extension to clinical studies for patient stratification and therapeutic monitoring.
• Integration with proteomics and transcriptomics for multi-omics insights.
• Application of machine learning to enhance pattern recognition and predictive modeling.
• Continued advancements in ion mobility resolution and acquisition speed.

Conclusion

The combined HILIC-UPLC-IMS-MS workflow offers rapid, high-resolution analysis of both drug metabolites and endogenous metabolic responses. This enables deeper understanding of pharmacokinetics and biological impact, supporting drug development and personalized medicine strategies.

Reference

1. Spagou K, et al. HILIC-UPLC-MS for Exploratory Urinary Metabolic Profiling in Toxicological Studies. Analytical Chemistry. 2011;83(2):382–390.
2. Giles K, Ujma J, Wildgoose J, et al. A Cyclic Ion Mobility-Mass Spectrometry System. Analytical Chemistry. 2019;91(13):8564–8573.
3. Chong J, et al. Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis. Current Protocols in Bioinformatics. 2019;68:e86.