48 research outputs found

    Fulvestrant: pharmacokinetics and pharmacology

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    Fulvestrant is a new type of oestrogen receptor (ER) antagonist with no agonist activity and a novel pharmacological profile. Fulvestrant has been shown to significantly reduce cellular levels of the ER and progesterone receptor in both preclinical studies and in clinical trials of postmenopausal women with primary breast cancer. This paper reviews the pharmacokinetics and metabolism of fulvestrant, which support the rationale for drug delivery as a single, once-monthly intramuscular injection, and show that this agent has minimal potential to be the subject, or cause, of significant cytochrome p450-mediated drug interactions

    Relationship between intratumoral expression of genes coding for xenobiotic-metabolizing enzymes and benefit from adjuvant tamoxifen in estrogen receptor alpha-positive postmenopausal breast carcinoma

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    INTRODUCTION: Little is known of the function and clinical significance of intratumoral dysregulation of xenobiotic-metabolizing enzyme expression in breast cancer. One molecular mechanism proposed to explain tamoxifen resistance is altered tamoxifen metabolism and bioavailability. METHODS: To test this hypothesis, we used real-time quantitative RT-PCR to quantify the mRNA expression of a large panel of genes coding for the major xenobiotic-metabolizing enzymes (12 phase I enzymes, 12 phase II enzymes and three members of the ABC transporter family) in a small series of normal breast (and liver) tissues, and in estrogen receptor alpha (ERα)-negative and ERα-positive breast tumors. Relevant genes were further investigated in a well-defined cohort of 97 ERα-positive postmenopausal breast cancer patients treated with primary surgery followed by adjuvant tamoxifen alone. RESULTS: Seven of the 27 genes showed very weak or undetectable expression in both normal and tumoral breast tissues. Among the 20 remaining genes, seven genes (CYP2A6, CYP2B6, FMO5, NAT1, SULT2B1, GSTM3 and ABCC11) showed significantly higher mRNA levels in ERα-positive breast tumors than in normal breast tissue, or showed higher mRNA levels in ERα-positive breast tumors than in ERα-negative breast tumors. In the 97 ERα-positive breast tumor series, most alterations of these seven genes corresponded to upregulations as compared with normal breast tissue, with an incidence ranging from 25% (CYP2A6) to 79% (NAT1). Downregulation was rare. CYP2A6, CYP2B6, FMO5 and NAT1 emerged as new putative ERα-responsive genes in human breast cancer. Relapse-free survival was longer among patients with FMO5-overexpressing tumors or NAT1-overexpressing tumors (P = 0.0066 and P = 0.000052, respectively), but only NAT1 status retained prognostic significance in Cox multivariate regression analysis (P = 0.0013). CONCLUSIONS: Taken together, these data point to a role of genes coding for xenobiotic-metabolizing enzymes in breast tumorigenesis, NAT1 being an attractive candidate molecular predictor of antiestrogen responsiveness

    Comparison of four different colorimetric and fluorometric cytotoxicity assays in a zebrafish liver cell line

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    Background: A broad spectrum of cytotoxicity assays is currently used in the fields of (eco)toxicology and pharmacology. To choose an appropriate assay, different parameters like test compounds, detection mechanism, specificity, and sensitivity have to be considered. Furthermore, tissue or cell line can influence test performance. For zebrafish (Danio rerio), as emerging model organism, cell lines are now increasingly used, but few studies examined cytotoxicity in these cell systems. Therefore, we compared four cytotoxicity assays in the zebrafish liver cell line, ZFL, to test four differently acting model compounds. The tests comprised two colorimetric assays (MTT assay using 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide, and the LDH assay detecting lactate dehydrogenase activity) and two fluorometric assays (alamarBlue® using resazurin, and CFDA-AM based on 5-carboxyfluorescein diacetate acetoxymethyl ester). Model compounds were the pharmaceutical Tamoxifen, its metabolite 4-Hydroxy-Tamoxifen, the fungicide Flusilazole and the polycyclic aromatic hydrocarbon Benzo[a]pyrene. Results: All four assays performed well in the ZFL cells and led to reproducible dose-response curves for all test compounds. Effective concentrations causing 10% or 50% loss of cell viability (EC10 and EC50 values) varied by a maximum factor of 7.0 for the EC10 values and a maximum factor of 1.8 for the EC50 values. The EC values were not statistically different between the four assays, which is due to the assessed unspecific effects of the compounds. However, most often, the MTT assay and LDH assay showed the highest and lowest EC values, respectively. Nevertheless, the LDH assay showed the highest intra- and inter-assay variabilities and the lowest signal-to-noise ratios. In contrast to MTT, the other three assays have the advantage of being non-destructive, easy to handle, and less time consuming. Furthermore, AB and CFDA-AM can be combined on the same set of cells without damaging the cells, allowing later on their use for the investigation of other endpoints. Conclusions: We recommend the alamarBlue and CFDA-AM assays for cytotoxicity assessment in ZFL cells, which can be applied either singly or combined.JRC.H.5-Rural, water and ecosystem resource

    Genetic variants of CYP3A5, CYP2D6, SULT1A1, UGT2B15 and tamoxifen response in postmenopausal patients with breast cancer

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    INTRODUCTION: Tamoxifen therapy reduces the risk of recurrence and prolongs the survival of oestrogen-receptor-positive patients with breast cancer. Even if most patients benefit from tamoxifen, many breast tumours either fail to respond or become resistant. Because tamoxifen is extensively metabolised by polymorphic enzymes, one proposed mechanism underlying the resistance is altered metabolism. In the present study we investigated the prognostic and/or predictive value of functional polymorphisms in cytochrome P450 3A5 CYP3A5 (*3), CYP2D6 (*4), sulphotransferase 1A1 (SULT1A1; *2) and UDP-glucuronosyltransferase 2B15 (UGT2B15; *2) in tamoxifen-treated patients with breast cancer. METHODS: In all, 677 tamoxifen-treated postmenopausal patients with breast cancer, of whom 238 were randomised to either 2 or 5 years of tamoxifen, were genotyped by using PCR with restriction fragment length polymorphism or PCR with denaturing high-performance liquid chromatography. RESULTS: The prognostic evaluation performed in the total population revealed a significantly better disease-free survival in patients homozygous for CYP2D6*4. For CYP3A5, SULT1A1 and UGT2B15 no prognostic significance was observed. In the randomised group we found that for CYP3A5, homozygous carriers of the *3 allele tended to have an increased risk of recurrence when treated for 2 years with tamoxifen, although this was not statistically significant (hazard ratio (HR) = 2.84, 95% confidence interval (CI) = 0.68 to 11.99, P = 0.15). In the group randomised to 5 years' tamoxifen the survival pattern shifted towards a significantly improved recurrence-free survival (RFS) among CYP3A5*3-homozygous patients (HR = 0.20, 95% CI = 0.07 to 0.55, P = 0.002). No reliable differences could be seen between treatment duration and the genotypes of CYP2D6, SULT1A1 or UGT2B15. The significantly improved RFS with prolonged tamoxifen treatment in CYP3A5*3 homozygotes was also seen in a multivariate Cox model (HR = 0.13, CI = 0.02 to 0.86, P = 0.03), whereas no differences could be seen for CYP2D6, SULT1A1 and UGT2B15. CONCLUSION: The metabolism of tamoxifen is complex and the mechanisms responsible for the resistance are unlikely to be explained by a single polymorphism; instead it is a combination of several mechanisms. However, the present data suggest that genetic variation in CYP3A5 may predict response to tamoxifen therapy

    Physiologically Based Pharmacokinetic Modelling of Cytochrome P450 2C9-Related Tolbutamide Drug Interactions with Sulfaphenazole and Tasisulam

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    Background and Objectives: Cytochrome P450 2C9 (CYP2C9) is involved in the biotransformation of many commonly used drugs, and significant drug interactions have been reported for CYP2C9 substrates. Previously published physiologically based pharmacokinetic (PBPK) models of tolbutamide are based on an assumption that its metabolic clearance is exclusively through CYP2C9; however, many studies indicate that CYP2C9 metabolism is only responsible for 80–90% of the total clearance. Therefore, these models are not useful for predicting the magnitude of CYP2C9 drug–drug interactions (DDIs). This paper describes the development and verification of SimCYP-based PBPK models that accurately describe the human pharmacokinetics of tolbutamide when dosed alone or in combination with the CYP2C9 inhibitors sulfaphenazole and tasisulam. Methods: A PBPK model was optimized in SimCYP for tolbutamide as a CYP2C9 substrate, based on published in vitro and clinical data. This model was verified to replicate the magnitude of DDI reported with sulfaphenazole and was further applied to simulate the DDI with tasisulam, a small molecule investigated for the treatment of cancer. A clinical study (CT registration # NCT01185548) was conducted in patients with cancer to assess the pharmacokinetic interaction of tasisulum with tolbutamide. A PBPK model was built for tasisulam, and the clinical study design was replicated using the optimized tolbutamide model. Results: The optimized tolbutamide model accurately predicted the magnitude of tolbutamide AUC increase (5.3–6.2-fold) reported for sulfaphenazole. Furthermore, the PBPK simulations in a healthy volunteer population adequately predicted the increase in plasma exposure of tolbutamide in patients with cancer (predicted AUC ratio = 4.7–5.4; measured mean AUC ratio = 5.7). Conclusions: This optimized tolbutamide PBPK model was verified with two strong CYP2C9 inhibitors and can be applied to the prediction of CYP2C9 interactions for novel inhibitors. Furthermore, this work highlights the utility of mechanistic models in navigating the challenges in conducting clinical pharmacology studies in cancer patients

    Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

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    Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability
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