Influence of Slco2b1-knockout and SLCO2B1-humanization on coproporphyrin I and III levels in rats.

BACKGROUND AND PURPOSE: Coproporphyrin (CP) I and III are byproducts of haem synthesis currently investigated as biomarkers for drug-drug interactions involving hepatic organic anion transporting polypeptide (OATP) 1B transporters. Another hepatically expressed OATP-member is OATP2B1. The aim of this study was to test the impact of OATP2B1, which specifically transports CPIII, on CP serum levels, applying novel rat models. EXPERIMENTAL APPROACH: CPIII transport kinetics and the interplay between OATP2B1 and multidrug resistance-associated proteins (MRPs) were determined in vitro using the vTF7 expression system. Novel rSlco2b1-/- and SLCO2B1+/+ rat models were characterized for physiological parameters and for CP serum levels. Hepatic and renal expression of transporters involved in CP disposition were determined by real-time qPCR, Western blot analysis, and immunohistochemistry. KEY RESULTS: In vitro experiments revealed differences in transport kinetics comparing human and rat OATP2B1 and showed a consistent, species-specific interplay with hMRP3/rMRP3. Deletion of rOATP2B1 was associated with a trend towards lower CPI serum levels compared with wildtype rats, while CPIII remained unchanged. Comparing SLCO2B1+/+ with knockout rats revealed an effect of sex: only in females the genetic modification influenced CP serum levels. Analysis of hepatic and renal transporters revealed marginal, but in part, statistically significant differences in rMRP2 abundance, which may contribute to the observed changes in CP serum levels. CONCLUSION AND IMPLICATIONS: Our findings support that factors other than OATP1B transporters are of relevance for basal CP levels. Only in female rats, humanization of SLCO2B1 affects basal CPI and CPIII serum levels, despite isomer selectivity of OATP2B1.

Label-Free but Still Constrained: Assessment of Global Proteomic Strategies for the Quantification of Hepatic Enzymes and Transporters.

Building and refining pharmacology models require "system" data derived from tissues and in vitro systems analyzed by quantitative proteomics. Label-free global proteomics offers a wide scope of analysis, allowing simultaneous quantification of thousands of proteins per sample. The data generated from such analysis offer comprehensive protein expression profiles that can address existing gaps in models. In this study, we assessed the performance of three widely used label-free proteomic methods, "high N" ion intensity approach (HiN), intensity-based absolute quantification (iBAQ) and total protein approach (TPA), in relation to the quantification of enzymes and transporters in 27 human liver microsomal samples. Global correlations between the three methods were highly significant (R2 > 0.70, P < 0.001, n = 2232 proteins). Absolute abundances of 57 pharmacokinetic targets measured by standard-based label-free methods (HiN and iBAQ) showed good agreement, whereas the TPA overestimated abundances by two- to threefold. Relative abundance distribution of enzymes was similar for the three methods, while differences were observed with TPA in the case of transporters. Variability (CV) was similar across methods, with consistent between-sample relative quantification. The back-calculated amount of protein in the samples based on each method was compared with the nominal protein amount analyzed in the proteomic workflow, revealing overall agreement with data from the HiN method with bovine serum albumin as standard. The findings herein present a critique of label-free proteomic data relevant to pharmacokinetics and evaluate the possibility of retrospective analysis of historic datasets. SIGNIFICANCE STATEMENT: This study provides useful insights for using label-free methods to generate abundance data applicable for populating pharmacokinetic models. The data demonstrated overall correlation between intensity-based label-free proteomic methods (HiN, iBAQ and TPA), whereas iBAQ and TPA overestimated the total amount of protein in the samples. The extent of overestimation can provide a means of normalization to support absolute quantification. Importantly, between-sample relative quantification was consistent (similar variability) across methods.