The seminal paper on the CYP2D6 Activity Score (AS) was first published ten years ago and, since its introduction in 2008, it has been widely accepted in the field of pharmacogenetics. This scoring system facilitates the translation of highly complex CYP2D6 diplotype data into a patient’s phenotype to guide drug therapy and is at the core of all CYP2D6 gene/drug pair guidelines issued by the Clinical Pharmacogenetics Implementation Consortium (CPIC). The AS, however, only explains a portion of the variability observed among individuals and ethnicities. In this review, we provide an overview of sources in addition to CYP2D6 genotype that contribute to the variability in CYP2D6-mediated drug metabolism and discuss other factors, genetic and non-genetic, that likely contribute to the observed variability in CYP2D6 enzymatic activity.

Protein expression of renal uptake and efflux transporters was quantified by quantitative targeted proteomics using the surrogate peptide approach. Renal uptake transporters assessed in this study included organic anion transporters (OAT1-OAT4), organic cation transporter 2 (OCT2), organic/carnitine cation transporters (OCTN1 and OCTN2), and sodium-glucose transporter 2 (SGLT2); efflux transporters included P-glycoprotein, breast cancer resistance protein, multidrug resistance proteins (MRP2 and MRP4), and multidrug and toxin extrusion proteins (MATE1 and MATE2-K). Total membrane was isolated from the cortex of human kidneys (N = 41). The isolated membranes were digested by trypsin and the digest was subjected to liquid chromatography-tandem mass spectrometry analysis. The mean expression of surrogate peptides was as follows (given with the standard deviation, in picomoles per milligram of total membrane protein): OAT1 (5.3 6 1.9), OAT2 (0.9 6 0.3), OAT3 (3.5 6 1.6), OAT4 (0.5 6 0.2), OCT2 (7.4 6 2.8), OCTN1 (1.3 6 0.6), OCTN2 (0.6 6 0.2), P-glycoprotein (2.1 6 0.8), MRP2 (1.4 6 0.6), MRP4 (0.9 6 0.6), MATE1 (5.1 6 2.3), and SGLT2 (3.7 6 1.8). Breast cancer resistance protein (BCRP) and MATE2-K proteins were detectable but were below the lower limit of quantification. Interestingly, the protein expression of OAT1 and OAT3 was significantly correlated (r > 0.8). A significant correlation was also observed between expression of multiple other drug transporters, such as OATs/OCT2 or OCTN1/OCTN2, and SGLT2/OCTNs, OCT, OATs, and MRP2. These renal transporter data should be useful in deriving in vitro to in vivo scaling factors to accurately predict renal clearance and kidney epithelial cell exposure to drugs or their metabolites.

The cytochrome P450 (P450) enzymes are the predominant enzyme system involved in human drug metabolism. Alterations in the expression and/or activity of these enzymes result in changes in pharmacokinetics (and consequently the pharmacodynamics) of drugs that are metabolized by this set of enzymes. Apart from changes in activity as a result of drug-drug interactions (by P450 induction or inhibition), the P450 enzymes can exhibit substantial interindividual variation in basal expression and/or activity, leading to differences in the rates of drug elimination and response. This interindividual variation can result from a myriad of factors, including genetic variation in the promoter or coding regions, variation in transcriptional regulators, alterations in microRNA that affect P450 expression, and ontogenic changes due to exposure to xenobiotics during the developmental and early postnatal periods. Other than administering a probe drug or cocktail of drugs to obtain the phenotype or conducting a genetic analysis to determine genotype, methods to determine interindividual variation are limited. Phenotyping via a probe drug requires exposure to a xenobiotic, and genotyping is not always well correlated with phenotype, making both methodologies less than ideal. This article describes recent work evaluating the effect of some of these factors on interindividual variation in human P450-mediated metabolism and the potential utility of endogenous probe compounds to assess rates of drug metabolism among individuals.

Some women take medication during pregnancy to address a variety of clinical conditions. Because of ethical and logistical concerns, it is impossible to determine fetal drug exposure, and therefore fetal risk, during pregnancy. Hence, alternative approaches need to be developed to predict maternal-fetal drug exposure throughout pregnancy. To do so, we previously developed and verified a maternalfetal physiologically based pharmacokinetic model, which can predict fetal exposure to drugs that passively cross the placenta. However, many drugs are actively transported by the placenta (e.g., human immunodeficiency virus protease inhibitors). To extend our maternal-fetal physiologically based pharmacokinetic model to these actively transported drugs, we determined the gestational age-dependent changes in the protein abundance of placental transporters. Total cellular membrane fractions from first trimester (T1; n = 15), second trimester (T2; n = 19), and term (n = 15) human placentae obtained from uncomplicated pregnancies were isolated by ultracentrifugation. Transporter protein abundance was determined by targeted quantitative proteomics using liquid chromatography tandem mass specrometry. We observed that breast cancer resistance protein and P-glycoprotein abundance significantly decreased from T1 to term by 55% and 69%, respectively (per gram of tissue). Organic anion-transporting polypeptide (OATP) 2B1 abundance significantly decreased from T1 to T2 by 32%. In contrast, organic cation transporter (OCT) 3 and organic anion transporter 4 abundance significantly increased with gestational age (2-fold from T1 to term, 1.6-fold from T2 to term). Serotonin transporter and norepinephrine transporter did not change with gestational age. The abundance of bile salt export pump, multidrug resistance-associated protein 1-5, Na +-taurocholate cotransporting polypeptide, OATP1B1, OATP1B3, OCTN1-2, concentrative nucleoside transporter 1-3, equilibrative nucleoside transporter 2, and multidrug and toxin extrusion 1 could not be quantified. These data can be incorporated into our maternal-fetal physiologically based pharmacokinetic model to predict fetal exposure to drugs that are actively transported across the placenta. SIGNIFICANCE STATEMENT We quantified the protein abundance of key placental uptake and efflux transporters [organic cation transporter (OCT) 3, P-glycoprotein (P-gp), breast cancer resistance protein (BCRP)] across gestational ages (first trimester, second trimester, and term) using quantitative targeted proteomics. We observed that the protein abundance of P-gp and BCRP decreased, whereas that of OCT3 increased with gestational age. Incorporating the protein abundance determined in this study into maternal-fetal physiologically based pharmacokinetic model can help us better predict fetal drug exposure to substrates of these transporters.

Abstract. Drug transporter expression in tissues (in vivo) usually differs from that in cell lines used to measure transporter activity (in vitro). Therefore, quantification of transporter expression in tissues and cell lines is important to develop scaling factor for in vitro to in vivo extrapolation (IVIVE) of transporter-mediated drug disposition. Since traditional immunoquantification methods are semiquantitative, targeted proteomics is now emerging as a superior method to quantify proteins, including membrane transporters. This superiority is derived from the selectivity, precision, accuracy, and speed of analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring (MRM) mode. Moreover, LC-MS/MS proteomics has broader applicability because it does not require selective antibodies for individual proteins. There are a number of recent research and review papers that discuss the use of LC-MS/MS for transporter quantification. Here, we have compiled from the literature various elements of MRM proteomics to provide a comprehensive systematic strategy to quantify drug transporters. This review emphasizes practical aspects and challenges in surrogate peptide selection, peptide qualification, peptide synthesis and characterization, membrane protein isolation, protein digestion, sample preparation, LC-MS/MS parameter optimization, method validation, and sample analysis. In particular, bioinformatic tools used in method development and sample analysis are discussed in detail. Various pre-analytical and analytical sources of variability that should be considered during transporter quantification are highlighted. All these steps are illustrated using P-glycoprotein (Pgp) as a case example. Greater use of quantitative transporter proteomics will lead to a better understanding of the role of drug transporters in drug disposition.

The major objective of this study was to investigate the association of genetic and nongenetic factors with variability in protein abundance and in vitro activity of the androgen-metabolizing enzyme UGT2B17 in human liver microsomes ( = 455). UGT2B17 abundance was quantified by liquid chromatography-tandem mass spectrometry proteomics, and enzyme activity was determined by using testosterone and dihydrotestosterone as in vitro probe substrates. Genotyping or gene resequencing and mRNA expression were also evaluated. Multivariate analysis was used to test the association of UGT2B17 copy number variation, single nucleotide polymorphisms (SNPs), age, and sex with its mRNA expression, abundance, and activity. UGT2B17 gene copy number and SNPs (rs7436962, rs9996186, rs28374627, and rs4860305) were associated with gene expression, protein levels, and androgen glucuronidation rates in a gene dose-dependent manner. UGT2B17 protein (mean ± S.D. picomoles per milligram of microsomal protein) is sparsely expressed in children younger than 9 years (0.12 ± 0.24 years) but profoundly increases from age 9 years to adults (∼10-fold) with ∼2.6-fold greater abundance in males than in females (1.2 vs. 0.47). Association of androgen glucuronidation with UGT2B15 abundance was observed only in the low UGT2B17 expressers. These data can be used to predict variability in the metabolism of UGT2B17 substrates. Drug companies should include UGT2B17 in early phenotyping assays during drug discovery to avoid late clinical failures.

[(11)C]-RSV can be used to dynamically and noninvasively quantify hepatobiliary transport and hepatic concentration of the drug, in the absence and presence of drug interactions, in rats and could be used for the same purpose in humans.

Hepatic flavin-containing mono-oxygenase 3 (FMO3) metabolizes a broad array of nucleophilic heteroatom (e.g., or)-containing xenobiotics (e.g., amphetamine, sulindac, benzydamine, ranitidine, tamoxifen, nicotine, and ethionamide), as well as endogenous compounds (e.g., catecholamine and trimethylamine). To predict the effect of genetic and nongenetic factors on the hepatic metabolism of FMO3 substrates, we quantified FMO3 protein abundance in human liver microsomes (HLMs; = 445) by liquid chromatography-tandem mass chromatography proteomics. Genotyping/gene resequencing, mRNA expression, and functional activity (with benzydamine as probe substrate) of FMO3 were also evaluated. FMO3 abundance increased 2.2-fold (13.0 ± 11.4 pmol/mg protein vs. 28.0 ± 11.8 pmol/mg protein) from neonates to adults. After 6 years of age, no significant difference in FMO3 abundance was found between children and adults. Female donors exhibited modestly higher mRNA fragments per kilobase per million reads values (139.9 ± 76.9 vs. 105.1 ± 73.1; < 0.001) and protein FMO3 abundance (26.7 ± 12.0 pmol/mg protein vs. 24.1 ± 12.1 pmol/mg protein; < 0.05) compared with males. Six single nucleotide polymorphisms (SNPs), including rs2064074, rs28363536, rs2266782 (E158K), rs909530 (N285N), rs2266780 (E308G), and rs909531, were associated with significantly decreased protein abundance. FMO3 abundance in individuals homozygous and heterozygous for haplotype 3 (H3), representing variant alleles for all these SNPs (except rs2066534), were 50.8% ( < 0.001) and 79.5% ( < 0.01), respectively, of those with the reference homozygous haplotype (H1, representing wild-type). In summary, FMO3 protein abundance is significantly associated with age, gender, and genotype. These data are important in predicting FMO3-mediated heteroatom-oxidation of xenobiotics and endogenous biomolecules in the human liver.