1. Polymorphisms in human CYP2C8 decrease metabolism of the anticancer drug paclitaxel and arachidonic acid.
作者:Dai D , Zeldin D C , Blaisdell J A , Chanas B , Coulter S J , Ghanayem B I , Goldstein J A
期刊:Pharmacogenetics
日期:2001-10-01
DOI :10.1097/00008571-200110000-00006
Cytochrome P450 (CYP) 2C8 is the principal enzyme responsible for the metabolism of the anti-cancer drug paclitaxel (Taxol). It is also the predominant P450 responsible for the metabolism of arachidonic acid to biologically active epoxyeicosatrienoic acids (EETs) in human liver and kidney. In this study, we describe two new CYP2C8 alleles containing coding changes: CYP2C8*2 has an Ile269Phe substitution in exon 5 and CYP2C8*3 includes both Arg139Lys and Lys399Arg amino acid substitutions in exons 3 and 8. CYP2C8*2 was found only in African-Americans, while CYP2C8*3 occurred primarily in Caucasians. Neither occurred in Asians. The frequency of the CYP2C8*2 allele was 0.18 in African-Americans, and that of CYP2C8*3 was 0.13 in Caucasians. CYP2C8*1 (wild-type), CYP2C8*2 and CYP2C8*3 cDNAs were expressed in Escherichia coli, and the ability of these enzymes to metabolize both paclitaxel and arachidonic acid was assessed. Recombinant CYP2C8*3 was defective in the metabolism of both substrates. The turnover number of CYP2C8*3 for paclitaxel was 15% of CYP2C8*1. CYP2C8*2 had a two-fold higher Km and two-fold lower intrinsic clearance for paclitaxel than CYP2C8*1. CYP2C8*3 was also markedly defective in the metabolism of arachidonic acid to 11,12- and 14,15-EET (turnover numbers 35-40% that of CYP2C8*1). Thus, CYP2C8*3 is defective in the metabolism of two important CYP2C8 substrates: the anticancer drug paclitaxel and the physiologically important compound arachidonic acid. This polymorphism has important clinical and physiological implications in individuals homozygous for this allele.
添加收藏
创建看单
引用
4区Q3影响因子: 1.9
跳转PDF
登录
英汉
2. Patients carrying CYP2C8*3 have shorter systemic paclitaxel exposure.
作者:Marcath Lauren A , Kidwell Kelley M , Robinson Adam C , Vangipuram Kiran , Burness Monika L , Griggs Jennifer J , Poznak Catherine Van , Schott Anne F , Hayes Daniel F , Henry Norah Lynn , Hertz Daniel L
期刊:Pharmacogenomics
日期:2018-12-06
DOI :10.2217/pgs-2018-0162
AIM:First, evaluate if patients carrying putatively diminished activity CYP2C8 genotype have longer paclitaxel exposure (e.g., time above threshold concentration of 0.05 μM [T]). Second, screen additional pharmacogenes for associations with T. Methods: Pharmacogene panel genotypes were translated into genetic phenotypes for associations with T (n = 58). RESULTS:Patients with predicted low-activity CYP2C8 had shorter T after adjustment for age, body surface area and race (9.65 vs 11.03 hrs, β = 5.47, p = 0.02). This association was attributed to CYP2C8*3 (p = 0.006), not CYP2C8*4 (p = 0.58). Patients with predicted low-activity SLCO1B1 had longer T (12.12 vs 10.15 hrs, β = 0.85, p = 0.012). CONCLUSION:Contrary to previous publications, CYP2C8*3 may confer increased paclitaxel metabolic activity. SLCO1B1 and CYP2C8 genotype may explain some paclitaxel pharmacokinetic variability.
添加收藏
创建看单
引用
2区Q1影响因子: 4
英汉
3. Absorption, Distribution, Metabolism, and Excretion of [C]iptacopan in Healthy Male Volunteers and in In Vivo and In Vitro Studies.
期刊:Drug metabolism and disposition: the biological fate of chemicals
日期:2023-06-12
DOI :10.1124/dmd.123.001290
Iptacopan (LNP023) is an oral, small-molecule, first-in-class, highly potent proximal complement inhibitor that specifically binds factor B and inhibits the alternative complement pathway. Iptacopan is currently in development as a targeted treatment of paroxysmal nocturnal hemoglobinuria and multiple other complement-mediated diseases. In this study, the absorption, distribution, metabolism, and excretion (ADME) of iptacopan was characterized in six healthy volunteers after a single 100 mg oral dose of [C]iptacopan. This was supplemented with an in vivo rat ADME study and metabolite exposure comparisons between human, rat, and dog, in addition to in vitro assays, to better understand the clearance pathways and enzymes involved in the metabolism of iptacopan. The fraction of [C]iptacopan absorbed was estimated to be about 71%, with a time to maximum concentration of 1.5 hours and elimination half-life from plasma of 12.3 hours. Following a single dose of [C]iptacopan, 71.5% of the radioactivity was recovered in feces and 24.8% in urine. [C]iptacopan was primarily eliminated by hepatic metabolism. The main biotransformation pathways were oxidative metabolism via CYP2C8, with M2 being the major oxidative metabolite, and acyl glucuronidation via UGT1A1. The two acyl glucuronide metabolites in human plasma, M8 and M9, each accounted for ≤ 10% of the total circulating drug-related material; systemic exposure was also observed in toxicology studies in rat and dog, suggesting a low risk associated with these metabolites. Binding of iptacopan to its target, factor B, in the bloodstream led to a concentration-dependent blood:plasma distribution and plasma protein binding of [C]iptacopan. SIGNIFICANCE STATEMENT: We characterized the pharmacokinetics, excretion, metabolism and elimination of [C]iptacopan (an oral, selective small-molecule inhibitor of factor B) in healthy human subjects. [C]iptacopan was primarily eliminated by metabolism. The primary biotransformation pathways were oxidative metabolism via CYP2C8 and acyl glucuronidation via UGT1A1. Direct secretion of iptacopan into urine and potentially bile represented additional elimination mechanisms. Binding of iptacopan to its target, factor B, in the bloodstream led to a concentration-dependent blood:plasma distribution and plasma protein binding of [C]iptacopan.
添加收藏
创建看单
引用
2区Q1影响因子: 4
英汉
4. Predictive In Vitro-In Vivo Extrapolation for Time Dependent Inhibition of CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6 Using Pooled Human Hepatocytes, Human Liver Microsomes, and a Simple Mechanistic Static Model.
期刊:Drug metabolism and disposition: the biological fate of chemicals
日期:2021-11-17
DOI :10.1124/dmd.121.000718
Inactivation of Cytochrome P450 (CYP450) enzymes can lead to significant increases in exposure of comedicants. The majority of reported in vitro to in vivo extrapolation (IVIVE) data have historically focused on CYP3A, leaving the assessment of other CYP isoforms insubstantial. To this end, the utility of human hepatocytes (HHEP) and human liver microsomes (HLM) to predict clinically relevant drug-drug interactions was investigated with a focus on CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6. Evaluation of IVIVE for CYP2B6 was limited to only weak inhibition. A search of the University of Washington Drug-Drug Interaction Database was conducted to identify a clinically relevant weak, moderate, and strong inhibitor for selective substrates of CYP1A2, CYP2C8, CYP2C9, CYP2C19, and CYP2D6, resulting in 18 inhibitors for in vitro characterization against 119 clinical interaction studies. Pooled human hepatocytes and HLM were preincubated with increasing concentrations of inhibitors for designated timepoints. Time dependent inhibition was detected in HLM for four moderate/strong inhibitors, suggesting that some optimization of incubation conditions (i.e., lower protein concentrations) is needed to capture weak inhibition. Clinical risk assessment was conducted by incorporating the in vitro derived kinetic parameters maximal rate of enzyme inactivation (min) (k) and concentration of inhibitor resulting in 50% of the maximum enzyme inactivation (K) into static equations recommended by regulatory authorities. Significant overprediction was observed when applying the basic models recommended by regulatory agencies. Mechanistic static models, which consider the fraction of metabolism through the impacted enzyme, using the unbound hepatic inlet concentration lead to the best overall prediction accuracy with 92% and 85% of data from HHEPs and HLM, respectively, within twofold of the observed value. SIGNIFICANCE STATEMENT: Coupling time-dependent inactivation parameters derived from pooled human hepatocytes and human liver microsomes (HLM) with a mechanistic static model provides an easy and quantitatively accurate means to determine clinical drug-drug interaction risk from in vitro data. Optimization is needed to evaluate time-dependent inhibition (TDI) for weak and moderate inhibitors using HLM. Recommendations are made with respect to input parameters for in vitro to in vivo extrapolation (IVIVE) of TDI with non-CYP3A enzymes using available data from HLM and human hepatocytes.