Dataset Information

Application of PBPK Modeling and Virtual Clinical Study Approaches to Predict the Outcomes of CYP2D6 Genotype-Guided Dosing of Tamoxifen.

ABSTRACT: The Tamoxifen Response by CYP2D6 Genotype-based Treatment-1 (TARGET-1) study (n?=?180) was conducted from 2012-2017 in Japan to determine the efficacy of tamoxifen dosing guided by cytochrome P450 2D6 (CYP2D6) genotypes. To predict its outcomes prior to completion, we constructed the comprehensive physiologically based pharmacokinetic (PBPK) models of tamoxifen and its metabolites and performed virtual TARGET-1 studies. Our analyses indicated that the expected probability to achieve the end point (demonstrating the superior efficacy of the escalated tamoxifen dose over the standard dose in patients carrying CYP2D6 variants) was 0.469 on average. As the population size of this virtual clinical study (VCS) increased, the expected probability was substantially increased (0.674 for n?=?260). Our analyses also informed that the probability to achieve the end point in the TARGET-1 study was negatively impacted by a large variability in endoxifen levels. Our current efforts demonstrate the promising utility of the PBPK modeling and VCS approaches in prospectively designing effective clinical trials.

SUBMITTER: Nakamura T

PROVIDER: S-EPMC6063740 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Application of PBPK Modeling and Virtual Clinical Study Approaches to Predict the Outcomes of CYP2D6 Genotype-Guided Dosing of Tamoxifen.

Nakamura Toshimichi T Toshimoto Kota K Lee Wooin W Imamura Chiyo K CK Tanigawara Yusuke Y Sugiyama Yuichi Y

CPT: pharmacometrics & systems pharmacology 20180619 7

The Tamoxifen Response by CYP2D6 Genotype-based Treatment-1 (TARGET-1) study (n = 180) was conducted from 2012-2017 in Japan to determine the efficacy of tamoxifen dosing guided by cytochrome P450 2D6 (CYP2D6) genotypes. To predict its outcomes prior to completion, we constructed the comprehensive physiologically based pharmacokinetic (PBPK) models of tamoxifen and its metabolites and performed virtual TARGET-1 studies. Our analyses indicated that the expected probability to achieve the end poin ...[more]

PMID: 29920987

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Project description:ObjectiveTo evaluate evidence on the association between CYP2D6 genotype and tamoxifen response through.DesignSystematic review and meta-analysis of prospective, cross-sectional and case-control studies published to 2012. For each study, relative risks and 95% confidence intervals were extracted and pooled with a fixed and random effects model. Heterogeneity, publication bias, subgroup, and meta-regression analyses were performed.Data sourcesPubMed (inception-2012) and EMBASE (inception-2012).Eligibility criteria for selecting studiesCriteria for inclusion were studies reporting breast cancer outcomes in patients treated with tamoxifen and genotyped for polymorphisms in the CYP2D6 gene.ResultsTwenty-five studies of 13,629 individuals were identified, of which 22 investigated the association of CYP2D6 genotype with outcomes in breast cancer women all receiving tamoxifen treatment ("treatment-only" design). Three randomized trials evaluated the effect of CYP2D6 genotype on tamoxifen response ("effect modification" design). In analysis of treatment-only studies, the relative risk (RR) of all-cause mortality (>307 events in 4,936 patients) for carriers of a CYP2D6 reduced function allele was 1.11 (95% confidence interval (CI): 0.94 to 1.31) compared to individuals with normal/increased function CYP2D6 alleles. When we investigated a composite outcome including all-cause mortality and surrogate endpoints for overall survival (>307 events in 6,721 patients), carriers of a CYP2D6 reduced function allele had a RR of 1.27 (95% CI: 1.11 to 1.45). From two randomized trials that permitted effect-modification analysis, one had only 154 patients and showed evidence of effect modification of tamoxifen by CYP2D6 genotype for distant recurrence but was directionally opposite to that predicted, whereas a larger trial of 2,537 patients failed to show evidence of effect modification for breast cancer-free interval (P values for interaction 0.02 and 0.44, respectively).ConclusionsBased on these findings, there is insufficient evidence to recommend CYP2D6 genotyping to guide tamoxifen treatment.

Project description:BackgroundAdjuvant tamoxifen therapy substantially decreases the risk of recurrence and mortality in women with hormone (estrogen and/or progesterone) receptor-positive breast cancer. Previous studies have suggested that metabolic conversion of tamoxifen to endoxifen by cytochrome P450 2D6 (CYP2D6) is required for patient benefit from tamoxifen therapy.MethodsTumor specimens from a subset of postmenopausal patients with hormone receptor-positive early-stage (stages I, II, and IIIA) breast cancer, who were enrolled in the randomized double-blind Arimidex, Tamoxifen, Alone or in Combination (ATAC) clinical trial, were genotyped for variants in CYP2D6 (N = 1203 patients: anastrozole [trade name: Arimidex] group, n = 615 patients; tamoxifen group, n = 588 patients) and UDP-glucuronosyltransferase-2B7 (UGT2B7), whose gene product inactivates endoxifen (N = 1209 patients; anastrozole group, n = 606 patients; tamoxifen group, n = 603 patients). Genotyping was performed using polymerase chain reaction-based TaqMan assays. Based on the genotypes for CYP2D6, patients were classified as poor metabolizer (PM), intermediate metabolizer (IM), or extensive metabolizer (EM) phenotypes. We evaluated the association of CYP2D6 and UGT2B7 genotype with distant recurrence (primary endpoint) and any recurrence (secondary endpoint) by estimating the hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) using Cox proportional hazards models. All statistical tests were two-sided.ResultsAfter a median follow-up of 10 years, no statistically significant associations were observed between CYP2D6 genotype and recurrence in tamoxifen-treated patients (PM vs EM: HR for distant recurrence = 1.25, 95% CI = 0.55 to 3.15, P = .64; HR for any recurrence = 0.99, 95% CI = 0.48 to 2.08, P = .99). A near-null association was observed between UGT2B7 genotype and recurrence in tamoxifen-treated patients. No associations were observed between CYP2D6 and UGT2B7 genotypes and recurrence in anastrozole-treated patients.ConclusionThe results do not support the hypothesis that CYP2D6 genotype predicts clinical benefit of adjuvant tamoxifen treatment among postmenopausal breast cancer patients.

Project description:The cytochrome P450 2D6 (CYP2D6) is a key xenobiotic-metabolizing enzyme involved in the clearance of many drugs. Genetic polymorphisms in CYP2D6 contribute to the large inter-individual variability in drug metabolism and could affect metabolic phenotyping of CYP2D6 probe substances such as dextromethorphan (DXM). To study this question, we (i) established an extensive pharmacokinetics dataset for DXM; and (ii) developed and validated a physiologically based pharmacokinetic (PBPK) model of DXM and its metabolites dextrorphan (DXO) and dextrorphan O-glucuronide (DXO-Glu) based on the data. Drug-gene interactions (DGI) were introduced by accounting for changes in CYP2D6 enzyme kinetics depending on activity score (AS), which in combination with AS for individual polymorphisms allowed us to model CYP2D6 gene variants. Variability in CYP3A4 and CYP2D6 activity was modeled based on in vitro data from human liver microsomes. Model predictions are in very good agreement with pharmacokinetics data for CYP2D6 polymorphisms, CYP2D6 activity as described by the AS system, and CYP2D6 metabolic phenotypes (UM, EM, IM, PM). The model was applied to investigate the genotype-phenotype association and the role of CYP2D6 polymorphisms for metabolic phenotyping using the urinary cumulative metabolic ratio (UCMR), DXM/(DXO + DXO-Glu). The effect of parameters on UCMR was studied via sensitivity analysis. Model predictions indicate very good robustness against the intervention protocol (i.e. application form, dosing amount, dissolution rate, and sampling time) and good robustness against physiological variation. The model is capable of estimating the UCMR dispersion within and across populations depending on activity scores. Moreover, the distribution of UCMR and the risk of genotype-phenotype mismatch could be estimated for populations with known CYP2D6 genotype frequencies. The model can be applied for individual prediction of UCMR and metabolic phenotype based on CYP2D6 genotype. Both, model and database are freely available for reuse.

Dataset Information

Application of PBPK Modeling and Virtual Clinical Study Approaches to Predict the Outcomes of CYP2D6 Genotype-Guided Dosing of Tamoxifen.

Publications

Application of PBPK Modeling and Virtual Clinical Study Approaches to Predict the Outcomes of CYP2D6 Genotype-Guided Dosing of Tamoxifen.

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