Association analysis of SNPs present in plasma with adverse events and population pharmacokinetics in Chinese sunitinib treated patients with renal cell carcinoma
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Yuanyuan Zhang1,*, Haixing Mai2,*, Gang Guo3, Guofang Bi1, Guangtao Hao1, Yuanyuan Li1, Xiaofang Wang1, Longmei Cheng1, Jing Wang1, Ruihua Dong1, Zeyuan Liu1, Lijun Chen2 and Hengyan Qu1
1Department of Clinical Pharmacology, Academy of Military Medical Sciences Affiliated Hospital, 307 Clinical College, Anhui Medical University, Beijing 100071, China
2Department of Urology Department, Academy of Military Medical Sciences Affiliated Hospital, Beijing 100071, China
3Department of Urology Department, The General Hospital of the People's Liberation Army, Beijing 100853, China
*These authors contributed equally to this work
Hengyan Qu, email: [email protected]
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
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.
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