PURPOSE: Paclitaxel is used for the treatment of several solid tumors and displays a high interindividual variation in exposure and toxicity. Neurotoxicity is one of the most prominent side effects of paclitaxel. This study explores potential predictive pharmacokinetic and pharmacogenetic determinants for the onset and severity of neurotoxicity. EXPERIMENTAL DESIGN: In an exploratory cohort of patients (n = 261) treated with paclitaxel, neurotoxicity incidence, and severity, pharmacokinetic parameters and pharmacogenetic variants were determined. Paclitaxel plasma concentrations were measured by high-performance liquid chromatography or liquid chromatography/tandem mass spectrometry, and individual pharmacokinetic parameters were estimated from previously developed population pharmacokinetic models by nonlinear mixed effects modeling. Genetic variants of paclitaxel pharmacokinetics tested were CYP3A4*22, CYP2C8*3, CYP2C8*4, and ABCB1 3435 C>T. The association between CYP3A4*22 and neurotoxicity observed in the exploratory cohort was validated in an independent patient cohort (n = 239). RESULTS: Exposure to paclitaxel (logAUC) was correlated with severity of neurotoxicity (P < 0.00001). Female CYP3A4*22 carriers were at increased risk of developing neurotoxicity (P = 0.043) in the exploratory cohort. CYP3A4*22 carrier status itself was not associated with pharmacokinetic parameters (CL, AUC, Cmax, or T>0.05) of paclitaxel in males or females. Other genetic variants displayed no association with neurotoxicity. In the subsequent independent validation cohort, CYP3A4*22 carriers were at risk of developing grade 3 neurotoxicity (OR = 19.1; P = 0.001). CONCLUSIONS: Paclitaxel exposure showed a relationship with the severity of paclitaxel-induced neurotoxicity. In this study, female CYP3A4*22 carriers had increased risk of developing severe neurotoxicity during paclitaxel therapy. These observations may guide future individualization of paclitaxel treatment.
PURPOSE:Paclitaxel is used for the treatment of several solid tumors and displays a high interindividual variation in exposure and toxicity. Neurotoxicity is one of the most prominent side effects of paclitaxel. This study explores potential predictive pharmacokinetic and pharmacogenetic determinants for the onset and severity of neurotoxicity. EXPERIMENTAL DESIGN: In an exploratory cohort of patients (n = 261) treated with paclitaxel, neurotoxicity incidence, and severity, pharmacokinetic parameters and pharmacogenetic variants were determined. Paclitaxel plasma concentrations were measured by high-performance liquid chromatography or liquid chromatography/tandem mass spectrometry, and individual pharmacokinetic parameters were estimated from previously developed population pharmacokinetic models by nonlinear mixed effects modeling. Genetic variants of paclitaxel pharmacokinetics tested were CYP3A4*22, CYP2C8*3, CYP2C8*4, and ABCB1 3435 C>T. The association between CYP3A4*22 and neurotoxicity observed in the exploratory cohort was validated in an independent patient cohort (n = 239). RESULTS: Exposure to paclitaxel (logAUC) was correlated with severity of neurotoxicity (P < 0.00001). Female CYP3A4*22 carriers were at increased risk of developing neurotoxicity (P = 0.043) in the exploratory cohort. CYP3A4*22 carrier status itself was not associated with pharmacokinetic parameters (CL, AUC, Cmax, or T>0.05) of paclitaxel in males or females. Other genetic variants displayed no association with neurotoxicity. In the subsequent independent validation cohort, CYP3A4*22 carriers were at risk of developing grade 3 neurotoxicity (OR = 19.1; P = 0.001). CONCLUSIONS:Paclitaxel exposure showed a relationship with the severity of paclitaxel-induced neurotoxicity. In this study, female CYP3A4*22 carriers had increased risk of developing severe neurotoxicity during paclitaxel therapy. These observations may guide future individualization of paclitaxel treatment.
Authors: Anja Henningsson; Sharon Marsh; Walter J Loos; Mats O Karlsson; Adam Garsa; Klaus Mross; Stephan Mielke; Lucia Viganò; Alberta Locatelli; Jaap Verweij; Alex Sparreboom; Howard L McLeod Journal: Clin Cancer Res Date: 2005-11-15 Impact factor: 12.531
Authors: R B Lipton; S C Apfel; J P Dutcher; R Rosenberg; J Kaplan; A Berger; A I Einzig; P Wiernik; H H Schaumburg Journal: Neurology Date: 1989-03 Impact factor: 9.910
Authors: Marie-Rose B S Crombag; Stijn L W Koolen; Sophie Wijngaard; Markus Joerger; Thomas P C Dorlo; Nielka P van Erp; Ron H J Mathijssen; Jos H Beijnen; Alwin D R Huitema Journal: Pharm Res Date: 2019-10-15 Impact factor: 4.200
Authors: Daniel L Hertz; Kelley M Kidwell; Kiran Vangipuram; Feng Li; Manjunath P Pai; Monika Burness; Jennifer J Griggs; Anne F Schott; Catherine Van Poznak; Daniel F Hayes; Ellen M Lavoie Smith; N Lynn Henry Journal: Clin Cancer Res Date: 2018-04-27 Impact factor: 12.531
Authors: Shailly Mehrotra; Manish R Sharma; Elizabeth Gray; Kehua Wu; William T Barry; Clifford Hudis; Eric P Winer; Alan P Lyss; Deborah L Toppmeyer; Alvaro Moreno-Aspitia; Thomas E Lad; Mario Valasco; Beth Overmoyer; Hope Rugo; Mark J Ratain; Jogarao V Gobburu Journal: AAPS J Date: 2017-06-15 Impact factor: 4.009
Authors: Shuiying Hu; Kevin M Huang; Elizabeth J Adams; Charles L Loprinzi; Maryam B Lustberg Journal: Clin Cancer Res Date: 2019-05-23 Impact factor: 12.531
Authors: Amy L Pasternak; Kristen M Ward; Jasmine A Luzum; Vicki L Ellingrod; Daniel L Hertz Journal: Physiol Genomics Date: 2017-09-08 Impact factor: 3.107
Authors: Aparna Chhibber; Deanna L Kroetz; Kelan G Tantisira; Michael McGeachie; Cheng Cheng; Robert Plenge; Eli Stahl; Wolfgang Sadee; Marylyn D Ritchie; Sarah A Pendergrass Journal: Pharmacogenomics Date: 2014-12 Impact factor: 2.533