학술논문

Multimodal analysis of drug transporter expression in gastrointestinal tissue
Document Type
Academic Journal
Source
AIDS. Jul 31, 2017 31(12):1669-1678
Subject
Language
English
ISSN
0269-9370
Abstract
OBJECTIVES:: Drug transporters affect antiretroviral therapy (ART) tissue disposition, but quantitative measures of drug transporter protein expression across preclinical species are not available. Our objective was to use proteomics to obtain absolute transporter concentrations and assess agreement with corresponding gene and immunometric protein data. DESIGN:: In order to make interspecies comparisons, two humanized mouse [hu-HSC-Rag (n = 41); bone marrow-liver-thymus (n = 13)] and one primate [rhesus macaque (nonhuman primate, n = 12)] models were dosed to steady state with combination ART. Ileum and rectum were collected at necropsy and snap frozen for analysis. METHODS:: Tissues were analyzed for gene (quantitative PCR) and protein [liquid chromatography-mass spectrometry (LC-MS) proteomics and western blot] expression and localization (immunohistochemistry) of ART efflux and uptake transporters. Drug concentrations were measured by LC-MS/MS. Multivariable regression was used to determine the ability of transporter data to predict tissue ART penetration. RESULTS:: Analytical methods did not agree, with different trends observed for gene and protein expression. For example, quantitative PCR analysis showed a two-fold increase in permeability glycoprotein expression in nonhuman primates versus mice; however, proteomics showed a 200-fold difference in the opposite direction. Proteomics results were supported by immunohistochemistry staining showing extensive efflux transporter localization on the luminal surface of these tissues. ART tissue concentration was variable between species, and multivariable regression showed poor predictive power of transporter data. CONCLUSION:: Lack of agreement between analytical techniques suggests that resources should be focused on generating downstream measures of protein expression to predict drug exposure. Taken together, these data inform the use of preclinical models for studying ART distribution and the design of targeted therapies for HIV eradication.