Age-Dependent Abundance of CYP450 Enzymes Involved in Metronidazole Metabolism: Application to Pediatric PBPK Modeling.

The expression of cytochrome P450 (CYP) enzymes is highly variable and associated with factors, such as age, genotype, sex, and disease states. In this study, quantification of metronidazole metabolizing CYP isoforms (CYP2A6, CYP2E1, CYP3A4, CYP3A5, and CYP3A7) in human liver microsomes from 115 children and 35 adults was performed using a quantitative proteomics method. The data confirmed age-dependent increase in CYP2A6, CYP2E1, and CYP3A4 abundance, whereas, as expected, CYP3A7 abundance showed postnatal decrease with age. In particular, the fold difference (neonatal to adulthood levels) in the protein abundance of CYP2A6, CYP2E1, and CYP3A4 was 14, 11, and 20, respectively. In contrast, protein abundance of CYP3A7 was > 125-fold higher in the liver microsomes of neonates than of adults. The abundance of CYP2A6 and CYP3A5 was associated with genotypes, rs4803381 and rs776746, respectively. A proteomics-informed physiologically based pharmacokinetic (PBPK) model was developed to describe the pharmacokinetics of metronidazole and its primary metabolite, 2-hydroxymethylmetronidazole. The model revealed an increase in the metabolite-to-parent ratio with age and showed a strong correlation between CYP2A6 abundance and metabolite formation (r2 = 0.75). Notably, the estimated contribution of CYP3A7 was ~ 75% in metronidazole clearance in neonates. These data suggest that variability in CYP2A6 and CYP3A7 in younger children poses the risk of variable pharmacokinetics of metronidazole and its active metabolite with a potential impact on drug efficacy and safety. No sex-dependent difference was observed in the protein abundance of the studied CYPs. The successful integration of hepatic CYP ontogeny data derived from a large liver bank into the pediatric PBPK model of metronidazole can be extended to other drugs metabolized by the studied CYPs.

Transcriptomic comparison of in vitro models of the human placenta.

Studying the human placenta through in vitro cell culture methods is necessary due to limited access and amenability of human placental tissue to certain experimental methods as well as distinct anatomical and physiological differences between animal and human placentas. Selecting an in vitro culture model of the human placenta is challenging due to representation of different trophoblast cell types with distinct biological roles and limited comparative studies that define key characteristics of these models. Therefore, the aim of this research was to create a comprehensive transcriptomic comparison of common in vitro models of the human placenta compared to bulk placental tissue from the CANDLE and GAPPS cohorts (N=1083). We performed differential gene expression analysis on publicly available RNA sequencing data from 6 common in vitro models of the human placenta (HTR-8/SVneo, BeWo, JEG-3, JAR, Primary Trophoblasts, and Villous Explants) and compared to CANDLE and GAPPS bulk placental tissue or cytotrophoblast, syncytiotrophoblast, and extravillous trophoblast cell types derived from bulk placental tissue. All in vitro placental models had a substantial number of differentially expressed genes (DEGs, FDR<0.01) compared to the CANDLE and GAPPS placentas (Average DEGs=10,873), and the individual trophoblast cell types (Average DEGs=5,346), indicating that there are vast differences in gene expression compared to bulk and cell-type specific human placental tissue. Hierarchical clustering identified 53 gene clusters with distinct expression profiles across placental models, with 22 clusters enriched for specific KEGG pathways, 7 clusters enriched for high-expression placental genes, and 7 clusters enriched for absorption, distribution, metabolism, and excretion genes. In vitro placental models were classified by fetal sex based on expression of Y-chromosome genes that identified HTR-8/SVneo cells as being of female origin, while JEG-3, JAR, and BeWo cells are of male origin. Overall, none of the models were a close approximation of the transcriptome of bulk human placental tissue, highlighting the challenges with model selection. To enable researchers to select appropriate models, we have compiled data on differential gene expression, clustering, and fetal sex into an accessible web application: "Comparative Transcriptomic Placental Model Atlas (CTPMA)" which can be utilized by researchers to make informed decisions about their selection of in vitro placental models.

Sex and the Kidney Drug-Metabolizing Enzymes and Transporters: Are Preclinical Drug Disposition Data Translatable to Humans?

Cross-species differences in drug transport and metabolism are linked to poor translation of preclinical pharmacokinetic and toxicology data to humans, often resulting in the failure of new chemical entities (NCEs) during clinical drug development. Specifically, inaccurate prediction of renal clearance and renal accumulation of NCEs due to differential abundance of enzymes and transporters in kidneys can lead to differences in pharmacokinetics and toxicity between experimental animals and humans. We carried out liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based protein quantification of 78 membrane drug-metabolizing enzymes and transporters (DMETs) in the kidney membrane fractions of humans, rats, and mice for characterization of cross-species and sex-dependent differences. In general, majority of DMET proteins were higher in rodents than in humans. Significant cross-species differences were observed in 30 out of 33 membrane DMET proteins quantified in all three species. Although no significant sex-dependent differences were observed in humans, the abundance of 28 and 46 membrane proteins showed significant sex dependence in rats and mice, respectively. These cross-species and sex-dependent quantitative abundance data are valuable for gaining a mechanistic understanding of drug renal disposition and accumulation. Further, these data can also be integrated into systems pharmacology tools, such as physiologically based pharmacokinetic models, to enhance the interpretation of preclinical pharmacokinetic and toxicological data.

Effects of alcohol consumption and tobacco smoking on the composition of the ensemble of drug metabolizing enzymes and transporters in human liver.

We examined the effect of alcohol consumption and smoking on the abundance of drug-metabolizing enzymes and transporters (DMET) in human liver microsomes (HLM) isolated from liver tissues of 94 donors. Global proteomics analysis was performed and DMET protein levels were analyzed in relation to alcohol consumption levels, smoking history, and sex using non-parametric tests (p-value ≤ 0.05; cutoff of 1.25-fold change, FC). The examination of the alcohol-induced changes was further enforced by correlational analysis, where we used arbitrary alcohol consumption grade (ACG) scaling from 0 to 4 to establish a set of protein markers. We elaborated a provisional index of alcohol exposure (PIAE) based on a combination of relative abundances of four proteins (ER chaperone HSPA5, protein disulfide isomerases PDIA3 and P4HB, and cocaine esterase CES2) best correlating with ACG. The PIAE index was then used to find its correlations with the abundances of DMET proteins. Our results demonstrate considerable alcohol-induced changes in composition of the pool of cytochrome P450 enzymes in HLM. We observed significantly increased abundances of CYP2E1, CYP2B6, CYP2J2, and NADPH-cytochrome P450 reductase. In contrast, CYP1A2, CYP2C8, CYP2C9, CYP4A11, and cytochrome b5 protein levels were downregulated. Significant alteration in abundances of UDP-glucuronosyltransferase (UGT) were also detected, comprising of elevated UGT1A6, UGT1A9, and UGT2A1, and reduced UGT1A3, UGT1A4, UGT2B7, UGT2B10, and UGT2B15 levels. Important alcohol-induced changes were also observed in the expression of non-CYP and non-UGT DMET. Additionally, tobacco smoke was associated with elevated CYP1A2, UGT1A6, UGT2A1, and UGT2B4 and decreased FMO3, FMO4, and FMO5 levels.

Quantitative Proteomics for Translational Pharmacology and Precision Medicine: State of The Art and Future Outlook.

Over the past 20 years, quantitative proteomics has contributed a wealth of protein expression data, which are currently used for a variety of systems pharmacology applications, as a complement or a surrogate for activity of the corresponding proteins. A symposium at the 25th North American ISSX meeting, in Boston, in September 2023, was held to explore current and emerging applications of quantitative proteomics in translational pharmacology and strategies for improved integration into model-informed drug development based on practical experience of each of the presenters. A summary of the talks and discussions is presented in this perspective alongside future outlooks that were outlined for future meetings. Significance Statement This perspective explores current and emerging applications of quantitative proteomics in translational pharmacology and precision medicine, and outlines outlooks for improved integration into model-informed drug development.

Ontogeny of Human Liver Aldehyde Oxidase: Developmental Changes and Implications for Drug Metabolism.

Despite the increasing importance of aldehyde oxidase (AO) in the drug metabolism of clinical candidates, ontogeny data for AO are limited. The objective of our study was to characterize the age-dependent AO content and activity in the human liver cytosolic fraction (HLC) and human hepatocytes (HH). HLC (n = 121 donors) and HH (n = 50 donors) were analyzed for (1) AO protein content by quantitative proteomics and (2) enzyme activity using carbazeran as a probe substrate. AO activity showed high technical variability and poor correlation with the content in HLC samples, whereas hepatocyte samples showed a strong correlation between the content and activity. Similarly, AO content and activity showed no significant age-dependent differences in HLC samples, whereas the average AO content and activity in hepatocytes increased significantly (∼20-40-fold) from the neonatal levels (0-28 days). Based on the hepatocyte data, the age at which 50% of the adult AO content is reached (age50) was 3.15 years (0.32-13.97 years, 95% CI). Metabolite profiling of carbazeran revealed age-dependent metabolic switching and the role of non-AO mechanisms (glucuronidation and desmethylation) in carbazeran elimination. The content-activity correlation in hepatocytes improved significantly (R2 = 0.95; p < 0.0001) in samples showing <10% contribution of glucuronidation toward the overall metabolism, confirming that AO-mediated oxidation and glucuronidation are the key routes of carbazeran metabolism. Considering the confounding effect of glucuronidation on AO activity, AO content-based ontogeny data are a more direct reflection of developmental changes in protein expression. The comprehensive ontogeny data of AO in HH samples are more reliable than HLC data, which are important for developing robust physiologically based pharmacokinetic models for predicting AO-mediated metabolism in children.

Differential tissue abundance of membrane-bound drug metabolizing enzymes and transporter proteins by global proteomics.

Protein abundance data of drug-metabolizing enzymes and transporters (DMETs) are critical for scaling in vitro and animal data to humans for accurate prediction and interpretation of drug clearance and toxicity. Targeted DMET proteomics which relies on synthetic stable isotope-labeled surrogate peptides as calibrators, is routinely used for the quantification of selected proteins; however, the technique is limited to the quantification of a small number of proteins. Although the global proteomics-based total protein approach (TPA) is emerging as a better alternative for large-scale protein quantification, the conventional TPA doesn't consider differential sequence coverage by identifying unique peptides across proteins. Here, we optimized the TPA approach by correcting protein abundance data by the sequence coverage (SC-TPA), which was applied to quantify 54 DMETs for characterization of i) differential tissue DMET abundance in the human liver, kidney, and intestine, and ii) interindividual variability of DMET proteins in individual intestinal samples (n=13). UGT2B7, MGST1, MGST2, MGST3, CES2, and MRP2 were expressed in all three tissues, whereas, as expected CYP3A4, CYP3A5, CYP2C9, CYP4F2, UGT1A1, UGT2B17, CES1, FMO5, MRP3, and P-gp were present in the liver and intestine. The top three DMET proteins in individual tissues were: CES1>CYP2E1>UGT2B7 (liver), CES2>UGT2B17>CYP3A4 (intestine), and MGST1>UGT1A6>MGST2 (kidney). CYP3A4, CYP3A5, UGT2B17, CES2, and MGST2 showed high interindividual variability in the intestine. These data are relevant for enhancing in vitro to in vivo extrapolation (IVIVE) of drug absorption and disposition and can be used to enhance the accuracy of physiologically based pharmacokinetic (PBPK) prediction of systemic and tissue concentration of drugs. Significance Statement We quantified the abundance and compositions of drug-metabolizing enzymes and transporters (DMETs) in pooled human liver, intestine, and kidney microsomes using an optimized sequence coverage-informed total protein approach. The quantification of DMETs revealed quantitative differences in their levels in the liver, intestine, and kidney. Further, the analysis of individual intestine samples confirmed high variability in the levels of CYP3A4, CYP3A5, UGT2B17, CES2, and MGST2. These data are applicable for the prediction of first-pass metabolism and tissue-specific drug clearance.

Cytochrome P450 Family 4F2 and 4F11 Haplotype Mapping and Association with Hepatic Gene Expression and Vitamin K Hydroxylation Activity.

This study evaluated the underlying mechanistic links between genetic variability in vitamin K metabolic pathway genes (CYP4F2 and CYP4F11) and phylloquinone hydroxylation activity using genotype- and haplotype-based approaches. Specifically, we characterized genetic variability in the CYP4F2/CYP4F11 locus and compared common single allele genotypes and common haplotypes as predictors of hepatic gene expression, enzyme abundance, and phylloquinone (VK1) ω-hydroxylation kinetics. We measured CYP4F2 and CYP4F11 mRNA levels, CYP4F2 and CYP4F11 protein abundances, and the VK1 concentration-dependent ω-hydroxylation rate in matched human liver nucleic acid and microsome samples, utilizing a novel in vitro population modeling approach. Results indicate that accounting for the CYP4F2*3 allele alone is sufficient to capture most of the genetic-derived variability in the observed phenotypes. Additionally, our findings highlight the important contribution that CYP4F11 makes toward vitamin K metabolism in the human liver.

Global Proteomics Analysis of Lysophosphatidic Acid Signaling in PC-3 Human Prostate Cancer Cells: Role of CCN1.

Cysteine-rich angiogenic factor 61 (CCN1/Cyr61) is a matricellular protein that is induced and secreted in response to growth factors. Our previous work showed that 18:1-lysophosphatidic acid (LPA), which activates the G protein-coupled receptor LPAR1, induces CCN1 between 2-4 h in PC-3 human prostate cancer cells in a manner than enhances cell-substrate adhesion. While the time course of induction suggests that CCN1 contributes to intermediate events in LPA action, the roles of CCN1 in LPA-mediated signal transduction have not been fully elucidated. This study utilized a comprehensive global proteomics approach to identify proteins up- or down-regulated in response to treatment of PC-3 cells with LPA for three hours, during the time of peak CCN1 levels. In addition, the effects of siRNA-mediated CCN1 knockdown on LPA responses were analyzed. The results show that, in addition to CCN1, LPA increased the levels of multiple proteins. Proteins up-regulated by LPA included metastasis-associated in colon cancer protein 1 (MACC1) and thrombospondin-1 (TSP1/THBS1); both MACC1 and TSP1 regulated cancer cell adhesion and motility. LPA down-regulated thioredoxin interacting protein (TXNIP). CCN1 knockdown suppressed the LPA-induced up-regulation of 30 proteins; these included MACC1 and TSP1, as confirmed by immunoblotting. Gene ontology and STRING analyses revealed multiple pathways impacted by LPA and CCN1. These results indicate that CCN1 contributes to LPA signaling cascades that occur during the intermediate phase after the initial stimulus. The study provides a rationale for the development of interventions to disrupt the LPA-CCN1 axis.

Promiscuity and Quantitative Contribution of UGT2B17 in Drug and Steroid Metabolism Determined by Experimental and Computational Approaches.

Uridine 5'-diphospho-glulcuronosyltransferase 2B17 (UGT2B17) is important in the metabolism of steroids and orally administered drugs due to its high interindividual variability. However, the structural basis governing the substrate selectivity or inhibition of UGT2B17 remains poorly understood. This study investigated 76 FDA-approved drugs and 20 steroids known to undergo glucuronidation for their metabolism by UGT2B17. Specifically, we assessed the substrate selectivity for UGT2B17 over other UGT enzymes using recombinant human UGT2B17 (rUGT2B17), human intestinal microsomes, and human liver microsomes. The quantitative contribution of intestinal UGT2B17 in the glucuronidation of these compounds was characterized using intestinal microsomes isolated from UGT2B17 expressors and nonexpressors. In addition, a structure-based pharmacophore model for UGT2B17 substrates was built and validated using the studied pool of substrates and nonsubstrates. The results show that UGT2B17 could metabolize 23 out of 96 compounds from various chemical classes, including alcohols and carboxylic acids, particularly in the intestine. Interestingly, amines were less susceptible to UGT2B17 metabolism, though they could inhibit the enzyme. Three main pharmacophoric features of UGT2B17 substrates include (1) the presence of an accessible -OH or -COOH group near His35 residue, (2) a hydrophobic functional group at ∼4.5-5 Šfrom feature 1, and (3) an aromatic ring ∼5-7 Šfrom feature 2. Most of the studied compounds inhibited UGT2B17 activity irrespective of their substrate potential, indicating the possibility of multiple mechanisms. These data suggest that UGT2B17 is promiscuous in substrate selectivity and inhibition and has a high potential to produce significant variability in the absorption and disposition of orally administered drugs.

Effect of Cimetidine on Metformin Pharmacokinetics and Endogenous Metabolite Levels in Rats.

Tubular secretion is a primary mechanism along with glomerular filtration for renal elimination of drugs and toxicants into urine. Organic cation transporters (OCTs) and multidrug and toxic extrusion (MATE) transporters facilitate the active secretion of cationic substrates, including drugs such as metformin and endogenous cations. We hypothesized that administration of cimetidine, an Oct/Mate inhibitor, will result in increased plasma levels and decreased renal clearance of metformin and endogenous Oct/Mate substrates in rats. A paired rat pharmacokinetic study was carried out in which metformin (5 mg/kg, intravenous) was administered as an exogenous substrate of Oct/Mate transporters to six Sprague-Dawley rats with and without cimetidine (100 mg/kg, intraperitoneal). When co-administered with cimetidine, metformin area under the curve increased significantly by 3.2-fold, and its renal clearance reduced significantly by 73%. Untargeted metabolomics was performed to investigate the effect of cimetidine on endogenous metabolome in the blood and urine samples. Over 8,000 features (metabolites) were detected in the blood, which were shortlisted using optimized criteria, i.e., a significant increase (P value < 0.05) in metabolite peak intensity in the cimetidine-treated group, reproducible retention time, and quality of chromatogram peak. The metabolite hits were classified into three groups that can potentially distinguish inhibition of i) extra-renal uptake transport or catabolism, ii) renal Octs, and iii) renal efflux transporters or metabolite formation. The metabolomics approach identified novel putative endogenous substrates of cationic transporters that could be tested as potential biomarkers to predict Oct/Mate transporter mediated drug-drug interactions in the preclinical stages. SIGNIFICANCE STATEMENT: Endogenous substrates of renal transporters in animal models could be used as potential biomarkers to predict renal drug-drug interactions in early drug development. Here we demonstrated that cimetidine, an inhibitor of organic cation transporters (Oct/Mate), could alter the pharmacokinetics of metformin and endogenous cationic substrates in rats. Several putative endogenous metabolites of Oct/Mate transporters were identified using metabolomics approach, which could be tested as potential transporter biomarkers to predict renal drug-drug interaction of Oct/Mate substrates.

Characterization of Gla proteoforms and non-Gla peptides of gamma carboxylated proteins: Application to quantification of prothrombin proteoforms in human plasma.

Gamma (γ) carboxylation is an essential post-translational modification in vitamin K-dependent proteins (VKDPs), involved in maintaining critical biological homeostasis. Alterations in the abundance or activity of these proteins have pharmacological and pathological consequences. Importantly, low levels of fully γ-carboxylated clotting factors increase plasma des-γ-carboxy precursors resulting in little or no biological activity. Therefore, it is important to characterize the levels of γ-carboxylation that reflect the active state of these proteins. The conventional enzyme-linked immunosorbent assay for protein induced by vitamin K absence or antagonist II (PIVKA-II) quantification uses an antibody that is not applicable to distinguish different γ-carboxylation states. Liquid chromatography-mass spectrometry (LC-MS) approaches have been utilized to distinguish different γ-carboxylated proteoforms, however, these attempts were impeded by poor sensitivity due to spontaneous neutral loss of CO2 and simultaneous cleavage of the backbone bond in the collision cell. In this study, we utilized an alkaline mobile phase in combination with polarity switching (positive and negative ionization modes) to simultaneously identify and quantify γ-carboxylated VKDPs. The method was applied to compare Gla proteomics of prothrombin (FII) in 10 µL plasma samples of healthy control and warfarin-treated adults. We also identified surrogate non-Gla peptides for seven other VKDPs to quantify total (active plus inactive) protein levels. The total protein approach (TPA) was used to quantify absolute levels of the VKDPs in human plasma.

Effect of probenecid on blood levels and renal elimination of furosemide and endogenous compounds in rats: Discovery of putative organic anion transporter biomarkers.

Transporter-mediated drug-drug interactions (DDIs) are assessed using probe drugs and in vitro and in vivo models during drug development. The utility of endogenous metabolites as transporter biomarkers is emerging for prediction of DDIs during early phases of clinical trials. Endogenous metabolites such as pyridoxic acid and kynurenic acid have shown potential to predict DDIs mediated by organic anion transporters (OAT1 and OAT3). However, these metabolites have not been assessed in rats as potential transporter biomarkers. We carried out a rat pharmacokinetic DDI study using probenecid and furosemide as OAT inhibitor and substrate, respectively. Probenecid administration led to a 3.8-fold increase in the blood concentrations and a 3-fold decrease in renal clearance of furosemide. High inter-individual and intra-day variability in pyridoxic acid and kynurenic acid, and no or moderate effect of probenecid administration on these metabolites suggest their limited utility for prediction of Oat-mediated DDI in rats. Therefore, rat blood and urine samples were further analysed using untargeted metabolomics. Twenty-one m/z features (out of >8000 detected features) were identified as putative biomarkers of rat Oat1 and Oat3 using a robust biomarker qualification approach. These m/z features belong to metabolic pathways such as fatty acid analogues, peptides, prostaglandin analogues, bile acid derivatives, flavonoids, phytoconstituents, and steroids, and can be used as a panel to decrease variability caused by processes other than Oats. When validated, these putative biomarkers will be useful in predicting DDIs caused by Oats in rats.

Analysis of the interplay of physiological response to food intake and drug properties in food-drug interactions.

The effect of food on oral drug absorption is determined by the complex interplay among gut physiological factors and drug properties. The currently used dissolution testing and classification systems (biopharmaceutics classification system, BCS or biopharmaceutics drug disposition classification system, BDDCS) do not account for dynamic changes in gastrointestinal physiology caused by food intake. This study aimed to identify key drug properties that influence food effect (FE) using supervised machine learning approaches. The analysis showed that drugs with high logP, dose number, and extraction ratio have a higher probability of positive FE, while drugs with low permeability and high efflux saturation index have a greater likelihood of negative FE. Weakly acidic drugs also showed a greater probability of positive FE, particularly at pKa >4.3. The importance of drug properties in predicting FE was ranked as logP, dose number, extraction ratio, pKa, and permeability. The accuracy of FE prediction using the models was compared with BCS and extended clearance classification system (ECCS). Overall, the likelihood or magnitude of FE depends on physiological changes to food intake such as altered bile acid secretion rate, intestinal metabolism, transport kinetics, and gastric emptying time, which should be considered along with drug properties (e.g., solubility, logP, and ionization) in predicting FE of orally administered drugs.

Innovations, Opportunities, and Challenges for Predicting Alteration in Drug-Metabolizing Enzyme and Transporter Activity in Specific Populations.

Drug-metabolizing enzymes and transporters (DMETs) are key regulators of the pharmacokinetics, efficacy, and toxicity of therapeutics. Over the past two decades, significant advancements in in vitro methodologies, targeted proteomics, in vitro to in vivo extrapolation methods, and integrated computational approaches such as physiologically based pharmacokinetic modeling have unequivocally contributed to improving our ability to quantitatively predict the role of DMETs in absorption, distribution, metabolism, and excretion and drug-drug interactions. However, the paucity of data regarding alterations in DMET activity in specific populations such as pregnant individuals, lactation, pediatrics, geriatrics, organ impairment, and disease states such as, cancer, kidney, and liver diseases and inflammation has restricted our ability to realize the full potential of these recent advancements. We envision that a series of carefully curated articles in a special supplementary issue of Drug Metabolism and Disposition will summarize the latest progress in in silico, in vitro, and in vivo approaches to characterize alteration in DMET activity and quantitatively predict drug disposition in specific populations. In addition, the supplementary issue will underscore the current scientific knowledge gaps that present formidable barriers to fully understand the clinical implications of altered DMET activity in specific populations and highlight opportunities for multistakeholder collaboration to advance our collective understanding of this rapidly emerging area. SIGNIFICANCE STATEMENT: This commentary highlights current knowledge and identifies gaps and key challenges in understanding the role of drug-metabolizing enzymes and transporters (DMETs) in drug disposition in specific populations. With this commentary for the special issue in Drug Metabolism and Disposition, the authors intend to increase interest and invite potential contributors whose research is focused or has aided in expanding the understanding around the role and impact of DMETs in drug disposition in specific populations.

High-Throughput Assay of Cytochrome P450-Dependent Drug Demethylation Reactions and Its Use to Re-Evaluate the Pathways of Ketamine Metabolism.

In a search for a reliable, inexpensive, and versatile technique for high-throughput kinetic assays of drug metabolism, we elected to rehire an old-school approach based on the determination of formaldehyde (FA) formed in cytochrome P450-dependent demethylation reactions. After evaluating several fluorometric techniques for FA detection, we chose the method based on the Hantzsch reaction with acetoacetanilide as the most sensitive, robust, and adaptable to high-throughput implementation. Here we provide a detailed protocol for using our new technique for automatized assays of cytochrome P450-dependent drug demethylations and discuss its applicability for high-throughput scanning of drug metabolism pathways in the human liver. To probe our method further, we applied it to re-evaluating the pathways of metabolism of ketamine, a dissociative anesthetic and potent antidepressant increasingly used in the treatment of alcohol withdrawal syndrome. Probing the kinetic parameters of ketamine demethylation by ten major cytochrome P450 (CYP) enzymes, we demonstrate that in addition to CYP2B6 and CYP3A enzymes, which were initially recognized as the primary metabolizers of ketamine, an important role is also played by CYP2C19 and CYP2D6. At the same time, the involvement of CYP2C9 suggested in the previous reports was deemed insignificant.

Impact of CYP2C:TG Haplotype on CYP2C19 Substrates Clearance In Vivo, Protein Content, and In Vitro Activity.

A novel haplotype composed of two non-coding variants, CYP2C18 NM_000772.3:c.*31T (rs2860840) and NM_000772.2:c.819+2182G (rs11188059), referred to as "CYP2C:TG," was recently associated with ultrarapid metabolism of various CYP2C19 substrates. As the underlying mechanism and clinical relevance of this effect remain uncertain, we analyzed existing in vivo and in vitro data to determine the magnitude of the CYP2C:TG haplotype effect. We assessed variability in pharmacokinetics of CYP2C19 substrates, including citalopram, sertraline, voriconazole, omeprazole, pantoprazole, and rabeprazole in 222 healthy volunteers receiving one of these six drugs. We also determined its impact on CYP2C8, CYP2C9, CYP2C18, and CYP2C19 protein abundance in 135 human liver tissue samples, and on CYP2C18/CYP2C19 activity in vitro using N-desmethyl atomoxetine formation. No effects were observed according to CYP2C:TG haplotype or to CYP2C19*1+TG alleles (i.e., CYP2C19 alleles containing the CYP2C:TG haplotype). In contrast, CYP2C19 intermediate (e.g., CYP2C19*1/*2) and poor metabolizers (e.g., CYP2C19*2/*2) showed significantly higher exposure in vivo, lower CYP2C19 protein abundance in human liver microsomes, and lower activity in vitro compared with normal, rapid (i.e., CYP2C19*1/*17), and ultrarapid metabolizers (i.e., CYP2C19*17/*17). Moreover, a tendency toward lower exposure was observed in ultrarapid metabolizers compared with rapid metabolizers and normal metabolizers. Furthermore, when the CYP2C19*17 allele was present, CYP2C18 protein abundance was increased suggesting that genetic variation in CYP2C19 may be relevant to the overall metabolism of certain drugs by regulating not only its expression levels, but also those of CYP2C18. Considering all available data, we conclude that there is insufficient evidence supporting clinical CYP2C:TG testing to inform drug therapy.

The Plasma Membrane Monoamine Transporter is Highly Expressed in Neuroblastoma and Functions as an mIBG Transporter.

Neuroblastoma (NB) is a pediatric cancer with low survival rates in high-risk patients. 131I-mIBG has emerged as a promising therapy for high-risk NB and kills tumor cells by radiation. Consequently, 131I-mIBG tumor uptake and retention are major determinants for its therapeutic efficacy. mIBG enters NB cells through the norepinephrine transporter (NET), and accumulates in mitochondria through unknown mechanisms. Here we evaluated the expression of monoamine and organic cation transporters in high-risk NB tumors and explored their relationship with MYCN amplification and patient survival. We found that NB mainly expresses NET, the plasma membrane monoamine transporter (PMAT), and the vesicular membrane monoamine transporter 1/2 (VMAT1/2), and that the expression of these transporters is significantly reduced in MYCN-amplified tumor samples. PMAT expression is the highest and correlates with overall survival in high-risk NB patients without MYCN amplification. Immunostaining showed that PMAT resides intracellularly in NB cells and co-localizes with mitochondria. Using cells expressing PMAT, mIBG was identified as a PMAT substrate. In mitochondria isolated from NB cell lines, mIBG uptake was reduced by ∼50% by a PMAT inhibitor. Together, our data suggest that PMAT is a previously unrecognized transporter highly expressed in NB and could impact intracellular transport and therapeutic response to 131I-mIBG. SIGNIFICANCE STATEMENT: This study identified that plasma membrane monoamine transporter (PMAT) is a novel transporter highly expressed in neuroblastoma and its expression level is associated with overall survival rate in high-risk patients without MYCN amplification. PMAT is expressed intracellularly in neuroblastoma cells, transports meta-iodobenzylguanidine (mIBG) and thus could impact tumor retention and response to 131I-mIBG therapy. These findings have important clinical implications as PMAT could represent a novel molecular marker to help inform disease prognosis and predict response to 131I-mIBG therapy.

Dissecting Parameters Contributing to the Underprediction of Aldehyde Oxidase-Mediated Metabolic Clearance of Drugs.

We investigated the effect of variability and instability in aldehyde oxidase (AO) content and activity on the scaling of in vitro metabolism data. AO content and activity in human liver cytosol (HLC) and five recombinant human AO preparations (rAO) were determined using targeted proteomics and carbazeran oxidation assay, respectively. AO content was highly variable as indicated by the relative expression factor (REF; i.e., HLC to rAO content) ranging from 0.001 to 1.7 across different in vitro systems. The activity of AO in HLC degrades at a 10-fold higher rate in the presence of the substrate as compared with the activity performed after preincubation without substrate. To scale the metabolic activity from rAO to HLC, a protein-normalized activity factor (pnAF) was proposed wherein the activity was corrected by AO content, which revealed up to sixfold higher AO activity in HLC versus rAO systems. A similar value of pnAF was observed for another substrate, ripasudil. Physiologically based pharmacokinetic (PBPK) modeling revealed a significant additional clearance (CL; 66%), which allowed for the successful prediction of in vivo CL of four other substrates, i.e., O-benzyl guanine, BIBX1382, zaleplon, and zoniporide. For carbazeran, the metabolite identification study showed that the direct glucuronidation may be contributing to around 12% elimination. Taken together, this study identified differential protein content, instability of in vitro activity, role of additional AO clearance, and unaccounted metabolic pathways as plausible reasons for the underprediction of AO-mediated drug metabolism. Consideration of these factors and integration of REF and pnAF in PBPK models will allow better prediction of AO metabolism. SIGNIFICANCE STATEMENT: This study elucidated the plausible reasons for the underprediction of aldehyde oxidase (AO)-mediated drug metabolism and provided recommendations to address them. It demonstrated that integrating protein content and activity differences and accounting for the loss of AO activity, as well as consideration of extrahepatic clearance and additional pathways, would improve the in vitro to in vivo extrapolation of AO-mediated drug metabolism using physiologically based pharmacokinetic modeling.