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

Abstract

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 decisionmaking 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 laboratoryspecific methodologies relating to peptide choice.

Quantitative Characterization of Major Hepatic UDP-Glucuronosyltransferase Enzymes in Human Liver Microsomes: Comparison of Two Proteomic Methods and Correlation with Catalytic Activity

“…Particularly, with recent advances in proteomic methods, robust analyses of the protein expression patterns of UGT enzymes in different tissues and in vitro systems Fallon et al, 2013b) made it possible to derive reliable relative expression factors (REFs) essential to these drug-related simulation exercises (Knights et al, 2016). More recent reports have, however, highlighted significant levels of interlaboratory discrepancy between abundance measurements of drugmetabolizing enzymes and drug transporters (Achour et al, 2014c;Badée et al, 2015), even when matched samples were analyzed (Harwood et al, 2016a), necessitating further investigations into the factors contributing to these discrepancies. To illustrate this point, the present study reports comparative analysis of a set of eight UGT enzymes quantified by two distinct proteomic methodologies (SIL and QconCAT-based approaches) in matching samples, with correlation of these abundances against rates of glucuronidation for seven UGT substrates, highlighting large interlaboratory discrepancies between the reported protein levels of these enzymes.…”

“…In addition, digestion efficiency and quality (both purity and stability) of standards used for quantification can also contribute to differences in measurement. UGT enzymes introduce additional complexity at the level of peptide choice due to sequence homology, with some peptides being released more readily than others on proteolysis, most likely due to hydrophobicity and proximity to membrane embedded domains (Harwood et al, 2016a). These discrepancies seen especially with the QconCAT-based dataset will warrant further investigation into the sources of differences in reported end-point proteomic measurements of UGT enzymes, which will be the subject of a future publication.…”

“…Interlaboratory differences recorded in the abundance levels of the characterized UGT enzymes reached .30-fold in the cases of UGT1A3 and UGT1A6, with the QconCAT-based technique tending to consistently overestimate. A recent cross-laboratory study that looked into differences in measured abundances of two intestinal efflux transporters, P-glycoprotein (ABCB1) and breast cancer resistance protein (ABCG2), reported up to three-and fivefold differences in abundance measured in matched human jejunal and Caco-2 samples, respectively (Harwood et al, 2016a). However, the laboratory-specific IVIVE relative expression factors (REFs) generated for these proteins were within twofold for both transporters and did not reflect significant differences in simulated pharmacokinetic outcomes (Harwood et al, 2016b), suggesting that systematic bias in methodology can lead to valid IVIVE conclusions if more suitable study designs are implemented, where specific REF values of ADME proteins are generated in the same or a similar setting.…”

“…The effects of several steps of proteomic analysis on the outcome of quantification in these methodological workflows have been investigated, with such factors as solubilization of membrane proteins and selection of peptide standards (Harwood et al, 2016a) being suggested to influence end-point measurement. Sample preparation can also contribute to this variability, with proteins either quantified directly in whole cell/tissue lysate (Weiß et al, 2015;Wi sniewski et al, 2016) or in enriched subcellular fractions Gröer et al, 2013).…”

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

“…These were compared with REFs generated from two different LC-MS/MS workflows (two independent laboratories; matching samples) for P-gp and BCRP in human jejunum and 21-daycultivated Caco-2 monolayers. Methodological details and individual values are provided in the companion study (Harwood et al, 2016).…”