Dextromethorphan as a phenotyping test to predict endoxifen exposure in patients on tamoxifen treatment

Item does not contain fulltextPURPOSE: Tamoxifen, a widely used agent for the prevention and treatment of breast cancer, is mainly metabolized by CYP2D6 and CYP3A to form its most abundant active metabolite, endoxifen. Interpatient variability in toxicity and efficacy of tamoxifen is substantial. Contradictory results on the value of CYP2D6 genotyping to reduce the variable efficacy have been reported. In this pharmacokinetic study, we investigated the value of dextromethorphan, a known probe drug for both CYP2D6 and CYP3A enzymatic activity, as a potential phenotyping probe for tamoxifen pharmacokinetics. METHODS: In this prospective study, 40 women using tamoxifen for invasive breast cancer received a single dose of dextromethorphan 2 hours after tamoxifen intake. Dextromethorphan, tamoxifen, and their respective metabolites were quantified. Exposure parameters of all compounds were estimated, log transformed, and subsequently correlated. RESULTS: A strong and highly significant correlation (r = -0.72; P < .001) was found between the exposures of dextromethorphan (0 to 6 hours) and endoxifen (0 to 24 hours). Also, the area under the plasma concentration-time curve of dextromethorphan (0 to 6 hours) and daily trough endoxifen concentration was strongly correlated (r = -0.70; P < .001). In a single patient using the potent CYP2D6 inhibitor paroxetine, the low endoxifen concentration was accurately predicted by dextromethorphan exposure. CONCLUSION: Dextromethorphan exposure after a single administration adequately predicted endoxifen exposure in individual patients with breast cancer taking tamoxifen. This test could contribute to the personalization and optimization of tamoxifen treatment, but it needs additional validation and simplification before being applicable in future dosing strategies

The impact of CYP2D6-predicted phenotype on tamoxifen treatment outcome in patients with metastatic breast cancer

Abstract BACKGROUND: Cytochrome P450 2D6 (CYP2D6) has a crucial role in the metabolic conversion of tamoxifen into the active metabolite endoxifen. In this cohort study, the effect of CYP2D6-predicted phenotype, defined as the combined effect of CYP2D6 genetic variation and concomitant use of CYP2D6-inhibiting medication, on time to breast cancer progression (TTP) and overall survival (OS) in women who use tamoxifen for metastatic breast cancer (MBC) was examined. METHODS: We selected patients treated with tamoxifen (40 mg per day) for hormone receptor-positive MBC from whom a blood sample for pharmacogenetic analysis (CYP2D6*3, *4, *5, *6, *10 and *41) was available. Patient charts (n=102) were reviewed to assess TTP and OS, and to determine whether CYP2D6 inhibitors were prescribed during tamoxifen treatment. RESULTS: OS was significantly shorter in patients with a poor CYP2D6 metaboliser phenotype, compared with extensive metabolisers (HR=2.09; P=0.034; 95% CI: 1.06-4.12). Co-administration of CYP2D6 inhibitors alone was also associated with a worse OS (HR=3.55; P=0.002; 95% CI: 1.59-7.96) and TTP (HR=2.97; P=0.008; 95% CI: 1.33-6.67) compared with patients without CYP2D6 inhibitors. CONCLUSION: CYP2D6 phenotype is an important predictor of treatment outcome in women who are receiving tamoxifen for MBC. Co-administration of CYP2D6 inhibitors worsens treatment outcome of tamoxifen and should therefore be handled with care

CYP2D6 phenotype indicative for optimized antiestrogen efficacy associates with outcome in early breast cancer patients

BACKGROUND: Endoxifen serum concentrations seem to correlate with outcome in breast cancer (BC) patients. Concurrently, cytochrome P450 2D6 (CYP2D6) enzyme activity and dextromethorphan (DM) metabolism are deemed a surrogate marker for the formation of endoxifen. Here, we conducted a matched cohort study to determine the impact of an extensive CYP2D6 phenotype on relapse in patients with early-stage estrogen receptor (ER)-positive BC and adjuvant tamoxifen intake. METHODS: CYP2D6 extensive metabolism was determined upon appropriate dextromethorphan/dextrorphan (DM/DX) urinary excretion ratios (≤0.30). Fifty-nine BC patients were identified as extensive phenotype metabolizers, while for 148 matched controls, CYP2D6 was not determined. Patients and controls did not differ with respect to age, stage, hormone receptor status, HER2, grade, menopausal status, chemotherapy and antihormonal therapy. Survival analysis was performed according to clinical follow-up. RESULTS: Disease-free survival (DFS) of patients identified as extensive CYP2D6 metabolizers did not differ significantly from controls (p = 0.10). However, when patients with ER expression of ≤20 % were excluded from the analysis, DFS was associated with a more favorable outcome (p = 0.06). CONCLUSIONS: This study suggests a positive association between extensive CYP2D6 metabolism and outcome in early-stage ER-positive BC patients using tamoxifen and in particular, when a sufficient number ERs are represented on the primary tumor

The Discriminatory Value of CYP2D6 Genotyping in Predicting the Dextromethorphan/Dextrorphan Phenotype in Women with Breast Cancer

BACKGROUND: The growth inhibitory effect of tamoxifen is used for the treatment of breast cancer. Tamoxifen efficacy is mediated by its biotransformation, predominantly via the cytochrome P450 2D6 (CYP2D6) isoenzyme, to the active metabolite endoxifen. We investigated the relationship of CYP2D6 genotypes to the metabolism of dextromethorphan (DM), which is frequently used as a surrogate marker for the formation of endoxifen. METHODS: The CYP2D6 genotype was determined by polymerase chain reaction (PCR) in previously untreated patients with hormone receptor-positive invasive breast cancer considered to receive antihormonal therapy. The DM/dextrorphan (DX) urinary excretion ratios were obtained in a subset of patients by high-pressure liquid chromatography (HPLC)-mediated urine analysis after intake of 25 mg DM. The relationships of genotype and corresponding phenotype were statistically analyzed for association. RESULTS: From 151 patients predicted based on their genotype data for the 'traditional' CYP2D6 phenotype classes poor, intermediate, extensive and ultrarapid, 83 patients were examined for their DM/DX urinary ratios. The genotype-based poor metabolizer status correlated with the DM/DX ratios, whereas the intermediate, extensive and ultrarapid genotypes could not be distinguished based on their phenotype. Citalopram intake did not significantly influence the phenotype. CONCLUSIONS: The DM metabolism can be reliably used to assess the CYP2D6 enzyme activity. The correlation with the genotype can be incomplete and the metabolic ratios do not seem to be compromised by citalopram. DM phenotyping may provide a standardized tool to better assess the CYP2D6 metabolic capacity

Determining the optimal dose in the development of anticancer agents

Identification of the optimal dose remains a key challenge in drug development. For cytotoxic drugs, the standard approach is based on identifying the maximum tolerated dose (MTD) in phase I trials and incorporating this to subsequent trials. However, this strategy does not take into account important aspects of clinical pharmacology. For targeted agents, the dose-effect relationships from preclinical studies are less obvious, and it is important to change the way these agents are developed to avoid recommending drug doses for different populations without evidence of differential antitumour effects in different diseases. The use of expanded cohorts in phase I trials to better define MTD and refine dose optimization should be further explored together with a focus on efficacy rather than toxicity-based predictions. Another key consideration in dose optimization is related to interindividual pharmacokinetic variability. High variability in intra-individual pharmacokinetics has been observed for many orally-administered drugs, especially those with low bioavailability, which might complicate identification of dose-effect relationships. End-organ dysfunction, interactions with other prescription drugs, herbal supplements, adherence, and food intake can influence pharmacokinetics. It is important these variables are identified during early clinical trials and considered in the development of further phase II and subsequent large-scale phase III studies