Exposure-response relationship of cabozantinib in patients with metastatic renal cell carcinoma treated in routine care.

BACKGROUND: Interindividual pharmacokinetic variability may influence the clinical benefit or toxicity of cabozantinib in metastatic renal cell carcinoma (mRCC). We aimed to investigate the exposure-toxicity and exposure-response relationship of cabozantinib in unselected mRCC patients treated in routine care. METHODS: This ambispective multicenter study enrolled consecutive patients receiving cabozantinib in monotherapy. Steady-state trough concentration (Cmin,ss) within the first 3 months after treatment initiation was used for the PK/PD analysis with dose-limiting toxicity (DLT) and survival outcomes. Logistic regression and Cox proportional-hazards models were used to identify the risk factors of DLT and inefficacy in patients, respectively. RESULTS: Seventy-eight mRCC patients were eligible for the statistical analysis. Fifty-two patients (67%) experienced DLT with a median onset of 2.1 months (95%CI 0.7-8.2). In multivariate analysis, Cmin,ss was identified as an independent risk factor of DLT (OR 1.46, 95%CI [1.04-2.04]; p = 0.029). PFS and OS were not statistically associated with the starting dose (p = 0.81 and p = 0.98, respectively). In the multivariate analysis of PFS, Cmin, ss > 336 ng/mL resulted in a hazard ratio of 0.28 (95%CI, 0.10-0.77, p = 0.014). By contrast, Cmin, ss > 336 ng/mL was not statistically associated with longer OS. CONCLUSION: Early plasma drug monitoring may be useful to optimise cabozantinib treatment in mRCC patients treated in monotherapy, especially in frail patients starting at a lower than standard dose.

Dihydropyrimidine dehydrogenase gene variants for predicting grade 4-5 fluoropyrimidine-induced toxicity: FUSAFE individual patient data meta-analysis.

BACKGROUND: Dihydropyrimidine dehydrogenase (DPD) deficiency is the main known cause of life-threatening fluoropyrimidine (FP)-induced toxicities. We conducted a meta-analysis on individual patient data to assess the contribution of deleterious DPYD variants *2A/D949V/*13/HapB3 (recommended by EMA) and clinical factors, for predicting G4-5 toxicity. METHODS: Study eligibility criteria included recruitment of Caucasian patients without DPD-based FP-dose adjustment. Main endpoint was 12-week haematological or digestive G4-5 toxicity. The value of DPYD variants *2A/p.D949V/*13 merged, HapB3, and MIR27A rs895819 was evaluated using multivariable logistic models (AUC). RESULTS: Among 25 eligible studies, complete clinical variables and primary endpoint were available in 15 studies (8733 patients). Twelve-week G4-5 toxicity prevalence was 7.3% (641 events). The clinical model included age, sex, body mass index, schedule of FP-administration, concomitant anticancer drugs. Adding *2A/p.D949V/*13 variants (at least one allele, prevalence 2.2%, OR 9.5 [95%CI 6.7-13.5]) significantly improved the model (p < 0.0001). The addition of HapB3 (prevalence 4.0%, 98.6% heterozygous), in spite of significant association with toxicity (OR 1.8 [95%CI 1.2-2.7]), did not improve the model. MIR27A rs895819 was not associated with toxicity, irrespective of DPYD variants. CONCLUSIONS: FUSAFE meta-analysis highlights the major relevance of DPYD *2A/p.D949V/*13 combined with clinical variables to identify patients at risk of very severe FP-related toxicity.

Model-Informed Precision Dosing of Intravenous Busulfan in Thai Pediatrics Undergoing Hematopoietic Stem Cell Transplantation.

BACKGROUND: Conditioning bifunctional agent, busulfan, is commonly used on children before hematopoietic stem cell transplantation. Currently, at the Ramathibodi hospital, Bangkok, Thailand, initial dosing is calculated according to age and body surface area, and 7 samples per day are used for therapeutic drug monitoring (TDM). This study aimed to identify the best strategies for individual dosages a priori from patient characteristics and a posteriori based on TDM. METHODS: The pharmacokinetic data set consisted of 2018 plasma concentrations measured in 135 Thai (n = 135) pediatric patients (median age = 8 years) and were analyzed using a population approach. RESULTS: Body weight, presence of malignant disease, and genetic polymorphism of Glutathione S-transferase Alpha-1 (GSTA1) were predictors of clearance. The optimum sampling times for TDM concentration measurements were 0.25, 2, and 5 hours after a 3-hour infusion. This was sufficient to obtain a Bayesian estimate of clearance a posteriori. Simulations showed the poor performance of a priori formula-based dose calculations with 90% of patients demonstrating a 69%-151% exposure interval around the target. This interval shrank to 85%-124% if TDM was carried out only at day 1 and to 90%-116% with TDM at days 1 and 3. CONCLUSIONS: This comprehensive study reinforces the interest of TDM in managing interindividual variability in busulfan exposure. Therapeutic drug monitoring can reliably be implemented from 3 samples using the Bayesian approach, preferably over 2 days. If using the latter is not possible, the formulas developed herein could present an alternative in Thai patients.

Can we identify patients carrying targeted deleterious DPYD variants with plasma uracil and dihydrouracil? A GPCO-RNPGx retrospective analysis.

OBJECTIVES: Dihydropyrimidine dehydrogenase (DPD) deficiency is the main cause of severe fluoropyrimidine-related toxicities. The best strategy for identifying DPD-deficient patients is still not defined. The EMA recommends targeted DPYD genotyping or uracilemia (U) testing. We analyzed the concordance between both approaches. METHODS: This study included 19,376 consecutive French patients with pre-treatment plasma U, UH2 and targeted DPYD genotyping (*2A, *13, D949V, *7) analyzed at Eurofins Biomnis (2015-2022). RESULTS: Mean U was 9.9 ± 10.1 ng/mL (median 8.7, range 1.6-856). According to French recommendations, 7.3 % of patients were partially deficient (U 16-150 ng/mL) and 0.02 % completely deficient (U≥150 ng/mL). DPYD variant frequencies were *2A: 0.83 %, *13: 0.17 %, D949V: 1.16 %, *7: 0.05 % (2 homozygous patients with U at 22 and 856 ng/mL). Variant carriers exhibited higher U (median 13.8 vs. 8.6 ng/mL), and lower UH2/U (median 7.2 vs. 11.8) and UH2/U2 (median 0.54 vs. 1.37) relative to wild-type patients (p<0.00001). Sixty-six% of variant carriers exhibited uracilemia <16 ng/mL, challenging correct identification of DPD deficiency based on U. The sensitivity (% patients with a deficient phenotype among variant carriers) of U threshold at 16 ng/mL was 34 %. The best discriminant marker for identifying variant carriers was UH2/U2. UH2/U2<0.942 (29.7 % of patients) showed enhanced sensitivity (81 %) in identifying deleterious genotypes across different variants compared to 16 ng/mL U. CONCLUSIONS: These results reaffirm the poor concordance between DPD phenotyping and genotyping, suggesting that both approaches may be complementary and that targeted DPYD genotyping is not sufficiently reliable to identify all patients with complete deficiency.

Discrepancies between dihydropyrimidine dehydrogenase phenotyping and genotyping: What are the explanatory factors?

AIM: Dihydropyrimidine dehydrogenase (DPD) deficiency can be detected by phenotyping (measurement of plasma uracil [U], with U ≥ 16 µg/L defining a partial deficiency) and/or by genotyping (screening for the four most frequent DPYD variants). We aimed to determine the proportion of discrepancies between phenotypic and genotypic approaches and to identify possible explanatory factors. METHODS: Data from patients who underwent both phenotyping and genotyping were retrospectively collected. Complementary genetic analyses (genotyping of the variant c.557A>G and DPYD sequencing) were performed for patients with U ≥ 16 µg/L without any common variants. The characteristics of patients classified according to the congruence of the phenotyping and genotyping approaches were compared (Kruskal-Wallis test), and determinants of U levels were studied in the whole cohort (linear model). RESULTS: Among the 712 included patients, phenotyping and genotyping were discordant for 12.5%, with 63 (8.8%) having U ≥ 16 µg/L in the absence of a common variant. Complementary genetic investigations marginally reduced the percentage of discrepancies to 12.1%: Among the nine additional identified variants, only the c.557A>G variant, carried by three patients, had been previously reported to be associated with DPD deficiency. Liver dysfunction could explain certain discordances, as ASAT, ALP, GGT and bilirubin levels were significantly elevated, with more frequent liver metastases in patients with U ≥ 16 µg/L and the absence of a DPYD variant. The impact of cytolysis was confirmed, as ASAT levels were independently associated with increased U (p < 0.001). CONCLUSION: The frequent discordances between DPD phenotyping and genotyping approaches highlight the need to perform these two approaches to screen for all DPD deficiencies.

Quantitative impact of pre-analytical process on plasma uracil when testing for dihydropyrimidine dehydrogenase deficiency.

AIMS: Determining dihydropyrimidine dehydrogenase (DPD) activity by measuring patient's uracil (U) plasma concentration is mandatory before fluoropyrimidine (FP) administration in France. In this study, we aimed to refine the pre-analytical recommendations for determining U and dihydrouracil (UH2 ) concentrations, as they are essential in reliable DPD-deficiency testing. METHODS: U and UH2 concentrations were collected from 14 hospital laboratories. Stability in whole blood and plasma after centrifugation, the type of anticoagulant and long-term plasma storage were evaluated. The variation induced by time and temperature was calculated and compared to an acceptability range of ±20%. Inter-occasion variability (IOV) of U and UH2 was assessed in 573 patients double sampled for DPD-deficiency testing. RESULTS: Storage of blood samples before centrifugation at room temperature (RT) should not exceed 1 h, whereas cold (+4°C) storage maintains the stability of uracil after 5 hours. For patients correctly double sampled, IOV of U reached 22.4% for U (SD = 17.9%, range = 0-99%). Notably, 17% of them were assigned with a different phenotype (normal or DPD-deficient) based on the analysis of their two samples. For those having at least one non-compliant sample, this percentage increased up to 33.8%. The moment of blood collection did not affect the DPD phenotyping result. CONCLUSION: Caution should be taken when interpreting U concentrations if the time before centrifugation exceeds 1 hour at RT, since it rises significantly afterwards. Not respecting the pre-analytical conditions for DPD phenotyping increases the risk of DPD status misclassification.

Multigene Panel Sequencing Identifies a Novel Germline Mutation Profile in Male Breast Cancer Patients.

Even though male breast cancer (MBC) risk encompasses both genetic and environmental aetiologies, the primary risk factor is a germline pathogenic variant (PV) or likely pathogenic variant (LPV) in BRCA2, BRCA1 and/or PALB2 genes. To identify new potential MBC-specific predisposition genes, we sequenced a panel of 585 carcinogenesis genes in an MBC cohort without BRCA1/BRCA2/PALB2 PV/LPV. We identified 14 genes carrying rare PVs/LPVs in the MBC population versus noncancer non-Finnish European men, predominantly coding for DNA repair and maintenance of genomic stability proteins. We identified for the first time PVs/LPVs in PRCC (pre-mRNA processing), HOXA9 (transcription regulation), RECQL4 and WRN (maintenance of genomic stability) as well as in genes involved in other cellular processes. To study the specificity of this MBC PV/LPV profile, we examined whether variants in the same genes could be detected in a female breast cancer (FBC) cohort without BRCA1/BRCA2/PALB2 PV/LPV. Only 5/109 women (4.6%) carried a PV/LPV versus 18/85 men (21.2%) on these genes. FBC did not carry any PV/LPV on 11 of these genes. Although 5.9% of the MBC cohort carried PVs/LPVs in PALLD and ERCC2, neither of these genes were altered in our FBC cohort. Our data suggest that in addition to BRCA1/BRCA2/PALB2, other genes involved in DNA repair/maintenance or genomic stability as well as cell adhesion may form a specific MBC PV/LPV signature.

Pharmacokinetic and Pharmacogenetic Study of Etoposide in High-Dose Protocol (TI-CE) for Advanced Germ Cell Tumors.

BACKGROUND: Etoposide dosing is based on body surface area. We evaluated if further dose individualization would be required for high dose (HD) etoposide within the TI-CE (taxol, ifosfamide, carboplatin, and etoposide) protocol. METHODS: Eighty-eight patients received 400 mg/m2/day of etoposide as a 1-hour IV infusion on 3 consecutive days over 3 cycles as part of a phase II trial evaluating efficacy of therapeutic drug monitoring (TDM) of carboplatin in the TI-CE HD protocol. Pharmacokinetic (PK) data were analyzed using population PK model on NONMEM to quantify inter- and intra-individual variabilities. Relationship between etoposide exposure and pharmacodynamic (PD) endpoints, and between selected genetic polymorphisms and tumor response or toxicity were evaluated. RESULTS: The inter-patient, inter- and intra-cycle variabilities of clearance were 16%, 9% and 0.1%, respectively. The PK-PD relationship was not significant despite a trend toward higher etoposide exposure in patients responding to treatment. A significant correlation was found between exposure and extended neutropenia at cycle 3. A significant association between UGT1A1*28 polymorphism and late neutropenia was observed but needs further evaluation. CONCLUSIONS: The present study suggests that neither a priori dose individualization nor dose adaptation using TDM is required validating body surface area dosing of etoposide in the TI-CE protocol.

Cetuximab pharmacokinetic/pharmacodynamics relationships in advanced head and neck carcinoma patients.

AIMS: Cetuximab associated with cisplatin and 5-fluorouracil is used to treat patients with inoperable or metastatic head and neck squamous cell carcinomas (HNSCC) up until disease progression or unacceptable toxicities. To date, no biomarkers of efficacy are available to select patients who will benefit from treatment. METHODS: An ancillary pharmacokinetics (PK) exploration was performed in the context of a prospective study investigating circulating-tumour cells vs progression-free survival (PFS). Cetuximab plasma concentrations were analysed according to a population PK model. Individual exposure parameters were confronted with soluble epidermal growth factor receptor (sEGFR) concentrations, tumour response and PFS. RESULTS: PK data (28 patients, 203 observations) were best described by a two-compartment model with linear elimination. Performance status (PS) significantly correlated to both cetuximab clearance and central volume of distribution with both parameters increasing by 33.3% (95% CI 1-65.6) for each 1-point increase of PS compared to PS = 0. Univariate analysis showed that patients with higher trough cetuximab concentrations at Day 7 (Cmin,D7 ) had better tumour response (P = 0.03) and longer PFS (P = 0.035). However, multivariate analysis revealed that only PS and tumour size at baseline remained significantly associated with PFS. Levels of sEGFR increased during cetuximab treatment but were not associated with PFS in the multivariate analysis. CONCLUSIONS: Our study prospectively indicates that PS is likely a confounding factor in the relationship between cetuximab PK and PFS, patients with a poor PS having lower cetuximab plasma exposure and lower PFS.

Estimation of Unbound Carboplatin Clearance From Total Plasma Concentrations as a Means of Facilitating Therapeutic Drug Monitoring.

BACKGROUND: Therapeutic drug monitoring of carboplatin is based on its unbound clearance (CLU) determined by Bayesian analysis on unbound (U) concentrations. However, the ultrafiltration of plasma samples presents technical and time constraints. Therefore, this study aims to estimate CLU using total plasma (P) concentrations. METHODS: U and P concentration data of 407 patients were obtained from 2 clinical studies in which actual CLU had been determined for each patient. The patients were then split into development (277 patients) and prospective data sets (130 patients). Two approaches were evaluated. PK-model-only approach: a 3-compartment pharmacokinetic (PK) model based on U and P concentrations and taking into account the protein binding process was developed. The model with patient covariates was also evaluated. Linear regression approach: an equation (CLU = aCLP + b) was obtained by linear regression analysis between actual CLU and CLP, which is the total plasma clearance obtained by analyzing P concentrations according to a 2-compartment PK model. Predictive performance was then assessed within the prospective data set by estimating CLU from P concentrations using each approach and computing the relative percentage error (PE) between estimated CLU and actual CLU. RESULTS: The linear regression equation was CLU (L/h) = 1.15 CLP (L/h) + 0.13. The mean PE (MPE) between CLU (estimated using the equation) and the actual CLU was +1.2% (ranging from -31% to +33%) and the mean absolute PE (MAPE) was 9.7%. With the 3-compartment PK model, the MPE was +2.3% (ranging from -41% to +31%) and the MAPE was 11.1%. Inclusion of covariates in the 3-compartment model did not improve the estimation of CLU [MPE = +6.3% (from -33% to +37%); MAPE = 11.4%]. CONCLUSIONS: The linear equation gives a relatively good estimation of CLU based on P concentrations, making PK-based carboplatin dose adaptation possible for centers without ultrafiltration facilities.

Pharmacogenetics of anti-cancer drugs: State of the art and implementation - recommendations of the French National Network of Pharmacogenetics.

Individualized treatment is of special importance in oncology because the drugs used for chemotherapy have a very narrow therapeutic index. Pharmacogenetics may contribute substantially to clinical routine for optimizing cancer treatment to limit toxic effects while maintaining efficacy. This review presents the usefulness of pharmacogenetic tests for some key applications: dihydropyrimidine dehydrogenase (DPYD) genotyping for fluoropyrimidine (5-fluorouracil, capecitabine), UDP glucuronosylstransferase (UGT1A1) for irinotecan and thiopurine S-methyltransferase (TPMT) for thiopurine drugs. Depending on the level of evidence, the French National Network of Pharmacogenetics (RNPGx) has issued three levels of recommendations for these pharmacogenetic tests: essential, advisable, and potentially useful. Other applications, for which the level of evidence is still discussed, will be evoked in the final section of this review.

Pharmacogenetics-based personalized therapy: Levels of evidence and recommendations from the French Network of Pharmacogenetics (RNPGx).

More than 50 laboratories offer pharmacogenetic testing in France. These tests are restricted to a limited number of indications: prevention of serious adverse drug reactions; choice of most appropriate therapeutic option; dose adjustment for a specific drug. A very small proportion of these tests are mentioned in drug information labeling and the data provided (if any) are generally insufficient to ascertain whether a test is required and if it is useful. This article discusses the rationale for evaluating the performance and clinical usefulness of pharmacogenetics and provides, on behalf of the French national network of pharmacogenetics (RNPGx), three levels of recommendation for testing: essential, advisable, and possibly helpful.

Determination of unbound fraction of pazopanib in vitro and in cancer patients reveals albumin as the main binding site.

INTRODUCTION: Pazopanib exhibits wide inter-patient pharmacokinetic variability which may contribute to differences in treatment outcome. Unbound drug concentrations are believed to be more relevant to pharmacological responses than total concentrations. Thus it is desirable to evaluate pazopanib binding on plasma proteins and different factors potentially affecting this process. METHODS: An equilibrium dialysis method coupled with UPLC-MS/MS assay has been optimized and validated for the determination of pazopanib unbound fraction (fu%) in human plasma. Pazopanib binding in the plasma of healthy volunteers and in isolated protein solutions was investigated. The unbound fraction was determined for 24 cancer patients treated daily with pazopanib. RESULTS: We found that pazopanib was extensively bound in human plasma (>99.9 %) with a mean fu% value of 0.0106 ± 0.0013 % at 40 µg/mL. Protein binding was concentration independent over a clinically relevant range of concentrations. In isolated protein solutions, pazopanib at 40 µg/mL was mainly bound to albumin (40 g/L) and to a lesser extent to α1-acid glycoprotein (1 g/L) and low density lipoproteins (1.2 g/L), with a mean fu% of 0.0073 ± 0.0022 %, 0.992 ± 0.44 % and 7.4 ± 1.7 % respectively. Inter-patient variability (CV%) of fu% in cancer patients was limited (27.2 %). A correlation was observed between individual unbound fraction values and albuminemia. CONCLUSIONS: Pazopanib exhibits extensive binding to plasma proteins in human plasma. Variable albumin concentrations, frequently observed in cancer patients, may affect pazopanib unbound fraction with implications for inter-patient variability in drug efficacy and toxicity.

Identification of non-adherence to adjuvant letrozole using a population pharmacokinetics approach in hormone receptor-positive breast cancer patients.

BACKGROUND: Letrozole, an aromatase inhibitor metabolised via CYP2A6 and CYP3A4/5 enzymes, is used as adjuvant therapy for women with hormone receptor (HR)-positive early breast cancer. The objective of this study was to quantify the impact of CYP2A6 genotype on letrozole pharmacokinetics (PK), to identify non-adherent patients using a population approach and explore the possibility of a relationship between non-adherence and early relapse. METHODS: Breast cancer patients enrolled in the prospective PHACS study (ClinicalTrials.gov NCT01127295) and treated with adjuvant letrozole 2.5 mg/day were included. Trough letrozole concentrations (Css,trough) were measured every 6 months for 3 years by a validated LC-MS/MS method. Concentration-time data were analysed using non-linear mixed effects modelling. Three methods were evaluated for identification of non-adherent subjects using the base PK model. RESULTS: 617 patients contributing 2534 plasma concentrations were included and led to a one-compartment PK model with linear absorption and elimination. Model-based methods identified 28 % of patients as non-adherent based on high fluctuations of their Css,trough compared to 3 % based on patient declarations. The covariate analysis performed in adherent subjects revealed that CYP2A6 intermediate (IM) and slow metabolisers (SM) had 21 % (CI95 % = 12 - 30 %) and 46 % (CI95 % = 41 - 51 %) lower apparent clearance, respectively, compared to normal and ultrarapid metabolisers (NM+UM). Early relapse (19 patients) was not associated with model-estimated, concentration-based or declared adherence in the total population (p = 0.41, p = 0.37 and p = 0.45, respectively). CONCLUSIONS: These findings will help future investigations focusing on the exposure-efficacy relationship for letrozole in adjuvant setting.

Nonlinear Mixed-Effects Model of Z-Endoxifen Concentrations in Tamoxifen-Treated Patients from the CEPAM Cohort.

Tamoxifen is widely used in patients with hormone receptor-positive breast cancer. The polymorphic enzyme CYP2D6 is primarily responsible for metabolic activation of tamoxifen, resulting in substantial interindividual variability of plasma concentrations of its most important metabolite, Z-endoxifen. The Z-endoxifen concentration thresholds below which tamoxifen treatment is less efficacious have been proposed but not validated, and prospective trials of individualized tamoxifen treatment to achieve Z-endoxifen concentration thresholds are considered infeasible. Therefore, we aim to validate the association between Z-endoxifen concentration and tamoxifen treatment outcomes, and identify a Z-endoxifen concentration threshold of tamoxifen efficacy, using pharmacometric modeling and simulation. As a first step, the CYP2D6 Endoxifen Percentage Activity Model (CEPAM) cohort was created by pooling data from 28 clinical studies (> 7,000 patients) with measured endoxifen plasma concentrations. After cleaning, data from 6,083 patients were used to develop a nonlinear mixed-effect (NLME) model for tamoxifen and Z-endoxifen pharmacokinetics that includes a conversion factor to allow inclusion of studies that measured total endoxifen but not Z-endoxifen. The final parent-metabolite NLME model confirmed the primary role of CYP2D6, and contributions from body weight, CYP2C9 phenotype, and co-medication with CYP2D6 inhibitors, on Z-endoxifen pharmacokinetics. Future work will use the model to simulate Z-endoxifen concentrations in patients receiving single agent tamoxifen treatment within large prospective clinical trials with long-term survival to identify the Z-endoxifen concentration threshold below which tamoxifen is less efficacious. Identification of this concentration threshold would allow personalized tamoxifen treatment to improve outcomes in patients with hormone receptor-positive breast cancer.

Current diagnostic and clinical issues of screening for dihydropyrimidine dehydrogenase deficiency.

Fluoropyrimidine drugs (FP) are the backbone of many chemotherapy protocols for treating solid tumours. The rate-limiting step of fluoropyrimidine catabolism is dihydropyrimidine dehydrogenase (DPD), and deficiency in DPD activity can result in severe and even fatal toxicity. In this review, we survey the evidence-based pharmacogenetics and therapeutic recommendations regarding DPYD (the gene encoding DPD) genotyping and DPD phenotyping to prevent toxicity and optimize dosing adaptation before FP administration. The French experience of mandatory DPD-deficiency screening prior to initiating FP is discussed.

Pharmacogenomics in solid cancers and hematologic malignancies: Improving personalized drug prescription.

The discovery of molecular alterations involved in oncogenesis is evolving rapidly and has led to the development of new innovative targeted therapies in oncology. High-throughput sequencing techniques help to identify genomic targets and to provide predictive molecular biomarkers of response to guide alternative therapeutic strategies. Besides the emergence of these theranostic markers for the new targeted treatments, pharmacogenetic markers (corresponding to genetic variants existing in the constitutional DNA, i.e., the host genome) can help to optimize the use of chemotherapy. In this review, we present the current clinical applications of constitutional PG and the recent concepts and advances in pharmacogenomics, a rapidly evolving field that focuses on various molecular alterations identified on constitutional or somatic (tumor) genome.