Matthew R. Russell

Simultaneous Quantification of the Abundance of Several Cytochrome P450 and Uridine 5′-Diphospho-Glucuronosyltransferase Enzymes in Human Liver Microsomes Using Multiplexed Targeted Proteomics

Cytochrome P450 (P450) and uridine 5′-diphospho-glucuronosyltransferase (UGT) enzymes mediate a major proportion of phase I and phase II metabolism of xenobiotics. In vitro-in vivo extrapolation (IVIVE) of hepatic clearance in conjunction with physiologically-based pharmacokinetics (PBPK) has become common practice in drug development. However, prediction of xenobiotic kinetics in virtual populations requires knowledge of both enzyme abundances and the extent to which these correlate. A multiplexed quantification concatemer (QconCAT) strategy was used in this study to quantify the expression of several P450 and UGT enzymes simultaneously and to establish correlations between various enzyme abundances in 24 individual liver samples (ages 27–66, 14 male). Abundances were comparable to previously reported values, including CYP2C9 (40.0 ± 26.0 pmol mg−1), CYP2D6 (11.9 ± 13.2 pmol mg−1), CYP3A4 (68.1 ± 52.3 pmol mg−1), UGT1A1 (33.6 ± 34.0 pmol mg−1), and UGT2B7 (82.9 ± 36.1 pmol mg−1), expressed as mean ± S.D. Previous reports of correlations in expression of various P450 (CYP3A4/CYP3A5*1/*3, CYP2C8/CYP2C9, and CYP3A4/CYP2B6) were confirmed. New correlations were demonstrated between UGTs [including UGT1A6/UGT1A9 (rs = 0.82, P < 0.0001) and UGT2B4/UGT2B15 (rs = 0.71, P < 0.0001)]. Expression of some P450 and UGT enzymes were shown to be correlated [including CYP1A2/UGT2B4 (rs = 0.67, P = 0.0002)]. The expression of CYP3A5 in individuals with *1/*3 genotype (n = 11) was higher than those with *3/*3 genotype (n = 10) (P < 0.0001). No significant effect of gender or history of smoking or alcohol use on enzyme expression was observed; however, expression of several enzymes declined with age. The correlation matrix produced for the first time by this study can be used to generate more realistic virtual populations with respect to abundance of various enzymes.

Alternative fusion protein strategies to express recalcitrant QconCAT proteins for quantitative proteomics of human drug metabolizing enzymes and transporters

QconCAT is a tool for quantitative proteomics, consisting of an artificial protein, expressed from an artificial gene, made up of a concatenated string of proteotypic peptides selected from the proteins under study. Isotopically labeled QconCAT (usually containing (13)C6-arginine and (13)C6-lysine) provides a standard for each proteotypic peptide included in its sequence. In practice, some QconCAT proteins fail to express at sufficient levels for the purpose of quantitative analysis. Two complementary methods are presented to express recalcitrant QconCAT proteins intended to quantify human hepatic enzymes and transporters.

Application of an LC-MS/MS method for the simultaneous quantification of human intestinal transporter proteins absolute abundance using a QconCAT technique.

Transporter proteins expressed in the gastrointestinal tract play a major role in the oral absorption of some drugs, and their involvement may lead to drug-drug interaction (DDI) susceptibility when given in combination with drugs known to inhibit gut wall transporters. Anticipating such liabilities and predicting the magnitude of the impact of transporter proteins on oral drug absorption and DDIs requires quantification of their expression in human intestine, and linking these to data obtained through in vitro experiments. A quantitative targeted absolute proteomic method employing liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) together with a quantitative concatenation (QconCAT) strategy to provide proteotypic peptide standards has been applied to quantify ATP1A1 (sodium/potassium-ATPase; Na/K-ATPase), CDH17 (human peptide transporter 1; HPT1), ABCB1 (P-glycoprotein; P-gp), ABCG2 (breast cancer resistance protein; BCRP), ABCC2 (multidrug resistance-associated protein 2; MRP2) and SLC51A (Organic Solute Transporter subunit alpha; OST-α), in human distal jejunum (n=3) and distal ileum (n=1) enterocyte membranes. Previously developed selected reaction monitoring (SRM) schedules were optimised to enable quantification of the proteotypic peptides for each transporter. After harvesting enterocytes by calcium chelation elution and generating a total membrane fraction, the proteins were subjected to proteolytic digestion. To account for losses of peptides during the digestion procedure, a gravimetric method is also presented. The linearity of quantifying the QconCAT from an internal standard (correlation coefficient, R(2)=0.998) and quantification of all target peptides in a pooled intestinal quality control sample (R(2)≥ 0.980) was established. The assay was also assessed for within and between-day precision, demonstrating a <15% coefficient of variation for all peptides across 3 separate analytical runs, over 2 days. The methods were applied to obtain the absolute abundances for all targeted proteins. In all samples, Na/K-ATPase, HPT1, P-gp and BCRP were detected above the lower limit of quantitation (i.e., >0.2 fmol/μg membrane protein). MRP2 abundance could be quantified in distal jejunum but not in the distal ileum sample. OST-α was not detected in 2 out of 3 jejunum samples. This study highlights the utility of a QconCAT strategy to quantify absolute transporter abundances in human intestinal tissues.

In Vitro–In Vivo Extrapolation Scaling Factors for Intestinal P-Glycoprotein and Breast Cancer Resistance Protein: Part I: A Cross-Laboratory Comparison of Transporter-Protein Abundances and Relative Expression Factors in Human Intestine and Caco-2 Cells

Over the last 5 years the quantification of transporter-protein absolute abundances has dramatically increased in parallel to the expanded use of in vitro–in vivo extrapolation (IVIVE) and physiologically based pharmacokinetics (PBPK)-linked models, for decision-making in pharmaceutical company drug development pipelines and regulatory submissions. Although several research groups have developed laboratory-specific proteomic workflows, it is unclear if the large range of reported variability is founded on true interindividual variability or experimental variability resulting from sample preparation or the proteomic methodology used. To assess the potential for methodological bias on end-point abundance quantification, two independent laboratories, the University of Manchester (UoM) and Bertin Pharma (BPh), employing different proteomic workflows, quantified the absolute abundances of Na/K-ATPase, P-gp, and breast cancer resistance protein (BCRP) in the same set of biologic samples from human intestinal and Caco-2 cell membranes. Across all samples, P-gp abundances were significantly correlated (P = 0.04, Rs = 0.72) with a 2.4-fold higher abundance (P = 0.001) generated at UoM compared with BPh. There was a systematically higher BCRP abundance in Caco-2 cell samples quantified by BPh compared with UoM, but not in human intestinal samples. Consequently, a similar intestinal relative expression factor (REF), derived from distal jejunum and Caco-2 monolayer samples, between laboratories was found for P-gp. However, a 2-fold higher intestinal REF was generated by UoM (2.22) versus BPh (1.11). We demonstrate that differences in absolute protein abundance are evident between laboratories and they probably result from laboratory-specific methodologies relating to peptide choice.

Lost in Centrifugation: Accounting for Transporter Protein Losses in Quantitative Targeted Absolute Proteomics

In drug development, considerable efforts are made to extrapolate from in vitro and preclinical findings to predict human drug disposition by using in vitro-in vivo extrapolation (IVIVE) approaches. Use of IVIVE strategies linked with physiologically based pharmacokinetic (PBPK) modeling is widespread, and regulatory agencies are accepting and occasionally requesting model analysis to support licensing submissions. Recently, there has been a drive to improve PBPK models by characterizing the absolute abundance of enzymes, transporters, and receptors within mammalian tissues and in vitro experimental systems using quantitative targeted absolute proteomics (QTAP). The absolute abundance of proteins relevant to processes governing drug disposition provided by QTAP will enable IVIVE-PBPK to incorporate terms for the abundance of enzymes and transporters in target populations. However, most studies that report absolute abundances of enzymes and transporter proteins do so in enriched membrane fractions so as to increase the abundance per sample, and thus the assay’s sensitivity, rather than measuring the expected lower abundance in the more biologically meaningful whole cells or tissues. This communication discusses the balance between protein enrichment and potential loss during the preparation of membrane fractions from whole cells or tissues. Accounting for losses with recovery factors throughout the fractionation procedure provides a means to correct for procedural losses, thereby enabling the scaling of protein abundance from subcellular fractions to whole-cell or organ abundances. PBPK models based on corrected abundances will more closely resemble biological systems and facilitate development of more meaningful IVIVE scaling factors, producing more accurate quantitative predictions of drug disposition.

Protein Z: A putative novel biomarker for early detection of ovarian cancer

Ovarian cancer (OC) has the highest mortality of all gynaecological cancers. Early diagnosis offers an approach to achieving better outcomes. We conducted a blinded‐evaluation of prospectively collected preclinical serum from participants in the multimodal group of the United Kingdom Collaborative Trial of Ovarian Cancer Screening. Using isobaric tags (iTRAQ) we identified 90 proteins differentially expressed between OC cases and controls. A second targeted mass spectrometry analysis of twenty of these candidates identified Protein Z as a potential early detection biomarker for OC. This was further validated by ELISA analysis in 482 serial serum samples, from 80 individuals, 49 OC cases and 31 controls, spanning up to 7 years prior to diagnosis. Protein Z was significantly down‐regulated up to 2 years pre‐diagnosis (p = 0.000000411) in 8 of 19 Type I patients whilst in 5 Type II individuals, it was significantly up‐regulated up to 4 years before diagnosis (p = 0.01). ROC curve analysis for CA‐125 and CA‐125 combined with Protein Z showed a statistically significant (p= 0.00033) increase in the AUC from 77 to 81% for Type I and a statistically significant (p= 0.00003) increase in the AUC from 76 to 82% for Type II. Protein Z is a novel independent early detection biomarker for Type I and Type II ovarian cancer; which can discriminate between both types. Protein Z also adds to CA‐125 and potentially the Risk of Ovarian Cancer algorithm in the detection of both subtypes.

In Vitro-In Vivo Extrapolation Scaling Factors for Intestinal P-glycoprotein and Breast Cancer Resistance Protein: Part II. The Impact of Cross-Laboratory Variations of Intestinal Transporter Relative Expression Factors on Predicted Drug Disposition

Relative expression factors (REFs) are used to scale in vitro transporter kinetic data via in vitro–in vivo extrapolation linked to physiologically based pharmacokinetic (IVIVE-PBPK) models to clinical observations. Primarily two techniques to quantify transporter protein expression are available, immunoblotting and liquid chromatography–tandem mass spectrometry. Literature-collated REFs ranged from 0.4 to 5.1 and 1.1 to 90 for intestinal P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP), respectively. The impact of using human jejunum–Caco-2 REFs for P-gp (REFiP-gp) and BCRP (REFiBCRP), generated from the same samples and using different proteomic methodologies from independent laboratories, on PBPK outcomes was assessed. A 5-fold decrease in REFiP-gp for a single oral dose of digoxin resulted in a 1.19- and 1.31-fold higher plasma area under the curve and Cmax, respectively. All generated REFiP-gp values led to simulated digoxin Cmax values within observed ranges; however, combining kinetic data generated from a different laboratory with the 5-fold lower REFiP-gp could not recover a digoxin-rifampicin drug-drug interaction, emphasizing the necessity to obtain transporter-specific kinetic estimates and REFs from the same in vitro system. For a theoretical BCRP compound, with absorption taking place primarily in the jejunum, a decrease in the REFiBCRP from 2.22 (University of Manchester) to 1.11 (Bertin Pharma) promoted proximal intestinal absorption while delaying tmax 1.44-fold. Laboratory-specific differences in REF may lead to different IVIVE-PBPK outcomes. To understand the mechanisms underlying projected pharmacokinetic liabilities, it is important to assess the potential impact of bias on the generation of REFs on an interindividual basis within a target population.

Novel risk models for early detection and screening of ovarian cancer

Purpose Ovarian cancer (OC) is the most lethal gynaecological cancer. Early detection is required to improve patient survival. Risk estimation models were constructed for Type I (Model I) and Type II (Model II) OC from analysis of Protein Z, Fibronectin, C-reactive protein and CA125 levels in prospectively collected samples from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Results Model I identifies cancers earlier than CA125 alone, with a potential lead time of 3-4 years. Model II detects a number of high grade serous cancers at an earlier stage (Stage I/II) than CA125 alone, with a potential lead time of 2-3 years and assigns high risk to patients that the ROCA Algorithm classified as normal. Materials and Methods This nested case control study included 418 individual serum samples serially collected from 49 OC cases and 31 controls up to six years pre-diagnosis. Discriminatory logit models were built combining the ELISA results for candidate proteins with CA125 levels. Conclusions These models have encouraging sensitivities for detecting pre-clinical ovarian cancer, demonstrating improved sensitivity compared to CA125 alone. In addition we demonstrate how the models improve on ROCA for some cases and outline their potential future use as clinical tools.

A combined biomarker panel shows improved sensitivity for the early detection of ovarian cancer allowing the identification of the most aggressive type II tumours

Background:There is an urgent need for biomarkers for the early detection of ovarian cancer (OC). The purpose of this study was to assess whether changes in serum levels of lecithin-cholesterol acyltransferase (LCAT), sex hormone-binding globulin (SHBG), glucose-regulated protein, 78 kDa (GRP78), calprotectin and insulin-like growth factor-binding protein 2 (IGFBP2) are observed before clinical presentation and to assess the performance of these markers alone and in combination with CA125 for early detection.Methods:This nested case–control study used samples from the United Kingdom Collaborative Trial of Ovarian Cancer Screening trial. The sample set consisted of 482 serum samples from 49 OC subjects and 31 controls, with serial samples spanning up to 7 years pre-diagnosis. The set was divided into the following: (I) a discovery set, which included all women with only two samples from each woman, the first at<14 months and the second at >32 months to diagnosis; and (ii) a corroboration set, which included all the serial samples from the same women spanning the 7-year period. Lecithin-cholesterol acyltransferase, SHBG, GRP78, calprotectin and IGFBP2 were measured using ELISA. The performance of the markers to detect cancers pre-diagnosis was assessed.Results:A combined threshold model IGFBP2 >78.5 ng ml−1 : LCAT <8.831 μg ml−1 : CA125 >35 U ml−1 outperformed CA125 alone for the earlier detection of OC. The threshold model was able to identify the most aggressive Type II cancers. In addition, it increased the lead time by 5–6 months and identified 26% of Type I subjects and 13% of Type II subjects that were not identified by CA125 alone.Conclusions:Combined biomarker panels (IGFBP2, LCAT and CA125) outperformed CA125 up to 3 years pre-diagnosis, identifying cancers missed by CA125, providing increased diagnostic lead times for Type I and Type II OC. The model identified more aggressive Type II cancers, with women crossing the threshold dying earlier, indicating that these markers can improve on the sensitivity of CA125 alone for the early detection of OC.