Abstract
Many genetic and environmental factors lead to inter-individual variations in metabolism and transport of drugs, profoundly affecting efficacy and toxicity. Precision dosing, targeting drug dose to a well-characterised sub-population, is dependent on quantitative models of the profiles of drug-metabolizing enzymes and transporters within that sub-population, informed by quantitative proteomics. We report the first use of ion mobility-mass spectrometry for this
purpose, allowing rapid, robust, label-free quantification of human liver microsomal (HLM) proteins from distinct individuals. Approximately 1000 proteins were quantified in four samples, including an average of 70 drug-metabolizing enzymes. Technical and biological variability were distinguishable, technical variability accounting for about 10% of total variability. The biological variation between patients was clearly identified, with samples showing a range of expression profiles for cytochrome P450 and uridine 5ˈ-diphosphoglucuronosyltransferase enzymes. Our results showed excellent agreement with previous data from targeted methods. The label-free methodology, however, allowed a fuller characterization of the in vitro system, showing, for the first time, that HLMs are significantly heterogeneous. Further, the traditional units of measurement of drug-metabolizing enzymes (pmol mg-1 HLM protein) are shown to introduce error arising from variability in unrelated,
highly abundant proteins. Simulations of this variability suggest that up to 1.7-fold variation in apparent CYP3A4 abundance is artefactual, as are background positive correlations of up to 0.2 (Spearman correlation coefficient) between the abundances of drug-metabolizing enzymes. We suggest that protein concentrations used in pharmacokinetic predictions and scaling to in vivo clinical situations (PBPK-IVIVE) should be referenced instead to tissue mass.
purpose, allowing rapid, robust, label-free quantification of human liver microsomal (HLM) proteins from distinct individuals. Approximately 1000 proteins were quantified in four samples, including an average of 70 drug-metabolizing enzymes. Technical and biological variability were distinguishable, technical variability accounting for about 10% of total variability. The biological variation between patients was clearly identified, with samples showing a range of expression profiles for cytochrome P450 and uridine 5ˈ-diphosphoglucuronosyltransferase enzymes. Our results showed excellent agreement with previous data from targeted methods. The label-free methodology, however, allowed a fuller characterization of the in vitro system, showing, for the first time, that HLMs are significantly heterogeneous. Further, the traditional units of measurement of drug-metabolizing enzymes (pmol mg-1 HLM protein) are shown to introduce error arising from variability in unrelated,
highly abundant proteins. Simulations of this variability suggest that up to 1.7-fold variation in apparent CYP3A4 abundance is artefactual, as are background positive correlations of up to 0.2 (Spearman correlation coefficient) between the abundances of drug-metabolizing enzymes. We suggest that protein concentrations used in pharmacokinetic predictions and scaling to in vivo clinical situations (PBPK-IVIVE) should be referenced instead to tissue mass.
Original language | English |
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Pages (from-to) | 666-675 |
Number of pages | 10 |
Journal | Drug Metabolism and Disposition |
Volume | 45 |
Issue number | 6 |
DOIs | |
Publication status | Published - 11 May 2017 |
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Biological Mass Spectrometry (BioMS) Facility
Knight, D. (Platform Lead), Warwood, S. (Senior Technical Specialist), Selley, J. (Technical Specialist), Taylor, G. (Technical Specialist), Fullwood, P. (Technical Specialist), Keevill, E.-J. (Senior Technician) & Allsey, J. (Technician)
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