Imaging of cyclosporine inhibition of P-glycoprotein activity using 11C-verapamil in the brain: studies of healthy humans.

Department of Radiology, University of Washington, Seattle, Washington 98195-6004, USA.
Journal of Nuclear Medicine (Impact Factor: 5.77). 09/2009; 50(8):1267-75. DOI: 10.2967/jnumed.108.059162
Source: PubMed

ABSTRACT The multiple-drug resistance (MDR) transporter P-glycoprotein (P-gp) is highly expressed at the human blood-brain barrier (BBB). P-gp actively effluxes a wide variety of drugs from the central nervous system, including anticancer drugs. We have previously demonstrated P-gp activity at the human BBB using PET of (11)C-verapamil distribution into the brain in the absence and presence of the P-gp inhibitor cyclosporine-A (CsA). Here we extend the initial noncompartmental analysis of these data and apply compartmental modeling to these human verapamil imaging studies.
Healthy volunteers were injected with (15)O-water to assess blood flow, followed by (11)C-verapamil to assess BBB P-gp activity. Arterial blood samples and PET images were obtained at frequent intervals for 5 and 45 min, respectively, after injection. After a 60-min infusion of CsA (intravenously, 2.5 mg/kg/h) to inhibit P-gp, a second set of water and verapamil PET studies was conducted, followed by (11)C-CO imaging to measure regional blood volume. Blood flow was estimated using dynamic (15)O-water data and a flow-dispersion model. Dynamic (11)C-verapamil data were assessed by a 2-tissue-compartment (2C) model of delivery and retention and a 1-tissue-compartment model using the first 10 min of data (1C(10)).
The 2C model was able to fit the full dataset both before and during P-pg inhibition. CsA modulation of P-gp increased blood-brain transfer (K(1)) of verapamil into the brain by 73% (range, 30%-118%; n = 12). This increase was significantly greater than changes in blood flow (13%; range, 12%-49%; n = 12, P < 0.001). Estimates of K(1) from the 1C(10) model correlated to estimates from the 2C model (r = 0.99, n = 12), indicating that a short study could effectively estimate P-gp activity.
(11)C-verapamil and compartmental analysis can estimate P-gp activity at the BBB by imaging before and during P-gp inhibition by CsA, indicated by a change in verapamil transport (K(1)). Inhibition of P-gp unmasks verapamil trapping in brain tissue that requires a 2C model for long imaging times; however, transport can be effectively measured using a short scan time with a 1C(10) model, avoiding complications with labeled metabolites and tracer retention.

1 Bookmark
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Multidrug resistance (MDR) is a complex phenomenon principally due to the overexpression of some transmembrane proteins belonging to the ATP binding cassette (ABC) transporter family. Among these transporters, P-glycoprotein (P-gp) is mostly involved in MDR and its overexpression is the major cause of cancer therapy failure. The classical approach used to overcome MDR is the co-administration of a P-gp inhibitor and the classic antineoplastic drugs, although the results were often unsatisfactory. Different classes of P-gp ligands have been developed and, among them, Tariquidar has been extensively studied both in vitro and in vivo. Although Tariquidar has been considered for several years as the lead compound for the development of P-gp inhibitors, recent studies demonstrated it to be a substrate and inhibitor, in a dose-dependent manner. Moreover, Tariquidar structure-activity relationship studies were difficult to carry out because of the complexity of the structure that does not allow establishing the role of each moiety for P-gp activity. For this purpose, SMALL molecules bearing different scaffolds such as tetralin, biphenyl, arylthiazole, furoxane, furazan have been developed. Many of these ligands have been tested both in in vitro assays and in in vivo PET studies. These preliminary evaluations lead to obtain a library of P-gp interacting agents useful to conjugate chemotherapeutic agents displaying reduced pharmacological activity and appropriate small molecules. These molecules could get over the limits due to the antineoplastic-P-gp inhibitor co-administration since pharmacokinetic and pharmacodynamic profiles are related to a dual innovative drug.
    Frontiers in Oncology 01/2014; 4:2.
  • Source
    Clinical Pharmacology &#38 Therapeutics 03/2014; · 6.85 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Drug transporter expression in tissues (in vivo) usually differs from that in cell lines used to measure transporter activity (in vitro). Therefore, quantification of transporter expression in tissues and cell lines is important to develop scaling factor for in vitro to in vivo extrapolation (IVIVE) of transporter-mediated drug disposition. Since traditional immunoquantification methods are semiquantitative, targeted proteomics is now emerging as a superior method to quantify proteins, including membrane transporters. This superiority is derived from the selectivity, precision, accuracy, and speed of analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring (MRM) mode. Moreover, LC-MS/MS proteomics has broader applicability because it does not require selective antibodies for individual proteins. There are a number of recent research and review papers that discuss the use of LC-MS/MS for transporter quantification. Here, we have compiled from the literature various elements of MRM proteomics to provide a comprehensive systematic strategy to quantify drug transporters. This review emphasizes practical aspects and challenges in surrogate peptide selection, peptide qualification, peptide synthesis and characterization, membrane protein isolation, protein digestion, sample preparation, LC-MS/MS parameter optimization, method validation, and sample analysis. In particular, bioinformatic tools used in method development and sample analysis are discussed in detail. Various pre-analytical and analytical sources of variability that should be considered during transporter quantification are highlighted. All these steps are illustrated using P-glycoprotein (P-gp) as a case example. Greater use of quantitative transporter proteomics will lead to a better understanding of the role of drug transporters in drug disposition.
    The AAPS Journal 04/2014; · 4.39 Impact Factor

Full-text (3 Sources)

Available from
May 22, 2014