Association analysis of SNPs present in plasma with adverse events and population pharmacokinetics in Chinese sunitinib treated patients with renal cell carcinoma

// Yuanyuan Zhang 1, * , Haixing Mai 2, * , Gang Guo 3 , Guofang Bi 1 , Guangtao Hao 1 , Yuanyuan Li 1 , Xiaofang Wang 1 , Longmei Cheng 1 , Jing Wang 1 , Ruihua Dong 1 , Zeyuan Liu 1 , Lijun Chen 2 and Hengyan Qu 1 1 Department of Clinical Pharmacology, Academy of Military Medical Sciences Affiliated Hospital, 307 Clinical College, Anhui Medical University, Beijing 100071, China 2 Department of Urology Department, Academy of Military Medical Sciences Affiliated Hospital, Beijing 100071, China 3 Department of Urology Department, The General Hospital of the People's Liberation Army, Beijing 100853, China * These authors contributed equally to this work Correspondence to: Hengyan Qu, email: quhengyan@hotmail.com Keywords: single-nucleotide polymorphisms; cell-free DNA; pharmacokinetics; sunitinib; renal-cell carcinoma Received: December 27, 2016 Accepted: November 11, 2017 Epub: January 03, 2018 Published: March 06, 2018 ABSTRACT Background: Sunitinib is a tyrosine kinase inhibitor with effective therapeutic outcomes in patients with renal-cell carcinoma. The study were to analyze the association of single-nucleotide polymorphisms present in cell-free DNA and pharmacokinetics with sunitinib treatment-emergent adverse events in Chinese patients with renal-cell carcinoma. Materials and Methods: We genotyped 8 keys SNPs in 6 candidate genes. The plasma concentrations of sunitinib and N-desethyl sunitinib were measured using a high performance liquid chromatography-tandam mass spectrometry method. Correlations between the single-nucleotide polymorphisms and adverse events were investigated by univariate and multivariate logistic regression and we quantitatively evaluated the effect of single-nucleotide polymorphisms on the pharmacokinetics of sunitinib by using a population PK model. Results: Necessary dose reductions of sunitinib were significantly correlated with SNP rs1933437 in FLT3 . A higher severity of AEs were collected with SNP rs2032582 in ABCB1 and rs1800812 in PDGFRα . Thrombocytopenia was collected with rs1800812 in PDGFRα . Our study provides a population PK model of sunitinib with the ABCB1 genotype as a predictive covariate for apparent oral clearance. Conclusions: Our study preliminarily confirmed the hypothesis that the pharmacokinetics of sunitinib is affected by the SNPs of enzyme in Chinese renal-cell carcinoma patients, and this affects the different distribution and severity of adverse events of sunitinib.