In vitro-in vivo extrapolation 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

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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 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 inter-individual variability or experimental variability, due to 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 BCRP in the same set of biological 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 the UoM compared to BPh. There was a systematically higher BCRP abundance in Caco-2 cell samples quantified by BPh compared to UoM, but not in human intestinal samples. Consequently, a similar intestinal relative expression factor (REF), based on distal jejunum and Caco-2 monolayer samples, between laboratories was found for P-gp. However, a 2-fold higher intestinal REF was generated by the UoM (2.22) versus BPh (1.11). We demonstrate that differences in absolute protein abundance are evident between laboratories and those are likely to be founded on laboratory-specific methodologies relating to peptide choice.

Keyword(s)

Cell models, efflux transporters (P-gp, BCRP, MRP, MATE, BSEP, etc), in vitro-in vivo prediction (IVIVE), mass spectrometry/MS, modeling and simulation, pharmacokinetics, physiologically-based pharmacokinetic modeling/PBPK, proteomics

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