Abstract
Tucatinib is a small molecule tyrosine kinase inhibitor indicated for HER2-positive breast cancer. This recently approved drug is primarily metabolized by cytochrome P450 (P450) 2C8 and CYP3A. Given the interindividual variability in the pharmacokinetics of some kinase inhibitors, the present study explored how variability in CYP2C8 and CYP3A activities and concentrations can influence variability in overall tucatinib metabolic clearance in vitro. Tucatinib depletion, P450 activities, and P450 concentrations were measured in human liver microsomes from 21 donors (males n = 11, females n = 10). CYP2C8 and CYP3A activities were quantitated by liquid chromatography-tandem mass spectrometry analysis using the following marker reactions: amodiaquine N-deethylation and midazolam 1'-hydroxylation, respectively. CYP2C8, CYP3A4, and CYP3A5 protein concentrations were measured using quantitative targeted absolute proteomics. The minimum clearance rate was 2.01 μL/mg/min, and the maximum clearance rate was 28.9 μL/mg/min, indicating a 14.3-fold variation in the apparent tucatinib clearance between donors. Tucatinib clearance was significantly correlated with both CYP2C8 and CYP3A enzyme activities and protein concentrations in this donor cohort (r = 0.781, r = 0.904, r = 0.907, and r = 0.882, respectively). A multiple linear regression model was developed to determine the most significant parameters influencing tucatinib clearance. Overall, we found that CYP2C8 and CYP3A activities were significant predictors of tucatinib apparent clearance in human liver microsomes from individual donors. Proteomics data are available with identifier PXD057282 via ProteomeXchange. SIGNIFICANCE STATEMENT: The results from this study demonstrate a strong relationship between CYP2C8 and CYP3A phenotypes and interindividual variability in tucatinib metabolism. By elucidating how variability in CYP2C8 and CYP3A phenotypes influence tucatinib pharmacokinetics, this study has the potential to provide the framework for future studies that could inform dosing to minimize adverse events and improve therapeutic outcomes. Ultimately, understanding how individual cytochrome P450 phenotypes influence the clearance of cancer therapeutics will aid in the development of tailored regimens for diverse patient populations.