907P - Impact of CYP3A4*22 on pazopanib pharmacokinetics in cancer patients

Date 10 September 2017
Event ESMO 2017 Congress
Session Poster display session
Topics Cytotoxic agents
Renal Cell Cancer
Genitourinary Cancers
Clinical research
Basic Scientific Principles
Biological therapy
Presenter Stijn Koolen
Citation Annals of Oncology (2017) 28 (suppl_5): v295-v329. 10.1093/annonc/mdx371
Authors S.L.W. Koolen1, A. Huitema2, P. Laven1, S. El Bouazzaoui3, H. Yu2, N.P. Erp4, C.M.L. Herpen5, P. Hamberg6, H. Gelderblom7, N. Steeghs8, S. Sleijfer1, R.H.N. van Schaik3, R.H.J. Mathijssen1, S. Bins1
  • 1Medical Oncology, Erasmus MC Cancer Institute, 3008EA - Rotterdam/NL
  • 2Dept. Of Pharmacy & Pharmacology, Netherlands Cancer Institute, Amsterdam/NL
  • 3Clinical Chemistry, Erasmus University Medical Center, 3015 CE - Rotterdam/NL
  • 4Clinical Pharmacy, Radboud University Medical Center, Nijmegen/NL
  • 5Medical Oncology, Radboud University Medical Center, Nijmegen/NL
  • 6Internal Medicine, Franciscus Gasthuis, Rotterdam/NL
  • 7Medical Oncology, Leiden University Medical Center (LUMC), 2300 RC - Leiden/NL
  • 8Medical Oncology, The Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, 1066 CX - Amsterdam/NL



Pazopanib is characterized by a large interpatient variability in systemic drug exposure. As pazopanib trough levels (>20.5 mg/L) are correlated with clinical outcome (Suttle et al, BJC 2014) in metastatic renal cell carcinoma (mRCC) patients, it is vital to identify factors that influence pazopanib pharmacokinetics (PK). The objective of the current analysis was to evaluate if single nucleotide polymorphisms (SNPs) in the metabolic pathway of pazopanib (i.e. CYP3A4, ABCB1 and ABCG2) affect systemic pazopanib concentrations.


We analyzed 97 patients who participated in 3 pazopanib PK studies. Starting point of the current analysis was a population PK model for pazopanib (Yu et al, Clin Pharmacokinet 2017). Four SNPs located on 3 genes, that were associated with decrease of function were analyzed using real time PCR: CYP3A4 15389 C>T (*22), ABCB1 3435 C>T, and the ABCG2 SNPs 421 C>A, and 34G>A. The influence of these SNPs on pazopanib bioavailability and clearance (CL) was explored with NONMEM. Statistical significance was determined with the likelihood ratio test using the objective function value (OFV). Trough concentrations (Ctrough) at 6 weeks after start with doses of 400 to 800 mg once daily (OD), were simulated. A threshold Ctrough of 20.5 mg/L was used as reference.


From 3 patients, insufficient DNA was isolated to run a PCR analysis. All SNPs were in Hardy-Weinberg equilibrium. Eleven patients (12%) had a variant allele at CYP3A4*22, all of whom were heterozygous. Incorporation of CYP3A4*22 in the NONMEM model resulted in a 35% lower CL for the variant carriers (0.18 L/h vs 0.27 L/h; ΔOFV = -7.8; P 


Our analysis shows that CYP3A4*22 carriers have a clinically relevant lower pazopanib CL. Prospective analysis should point out whether CYP3A4*22 carriers are at risk for more toxicity and require a lower pazopanib starting dose.

Clinical trial identification

Legal entity responsible for the study

Erasmus MC, Rotterdam, The Netherlands




All authors have declared no conflicts of interest.