PT  - JOURNAL ARTICLE
AU  - Brahim Achour
AU  - Hajar Al-Feteisi
AU  - Francesco Lanucara
AU  - Amin Rostami-Hodjegan
AU  - Jill Barber
TI  - Global Proteomic Analysis of Human Liver Microsomes: Rapid Characterization and Quantification of Hepatic Drug-Metabolizing Enzymes
AID  - 10.1124/dmd.116.074732
DP  - 2017 Jan 01
TA  - Drug Metabolism and Disposition
PG  - dmd.116.074732
4099  - http://dmd.aspetjournals.org/content/early/2017/04/03/dmd.116.074732.1.short
4100  - http://dmd.aspetjournals.org/content/early/2017/04/03/dmd.116.074732.1.full
AB  - 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 75 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.