Literature DB >> 7488425

Flow cytometric functional analysis of multidrug resistance by Fluo-3: a comparison with rhodamine-123.

S Koizumi1, M Konishi, T Ichihara, H Wada, H Matsukawa, K Goi, S Mizutani.   

Abstract

Using four cell lines including drug-sensitive K562/Parent cells, P-glycoprotein (Pgp)-mediated multidrug resistant (MDR) K562/VCR, K562/ADR and revertant K562/ADR-R cells, two fluorescent agents, Fluo-3 and rhodamine-123 (Rh-123), were compared as indicators in a functional assay of MDR. Cells were incubated with 4 microM Fluo-3 or 1 microM Rh-123 for 45 min and then the intracellular accumulation of the agent was measured using a flow cytometer. Verapamil (20 microM) or cepharanthine (biscoclaurine alkaloid, 10 microM) was added just before the fluorescent agents. Efflux patterns were also studied 60 min after incubation with or without verapamil and cepharanthine. Increased intracellular accumulation and a delayed efflux pattern of Fluo-3 by verapamil and cepharanthine were demonstrated in multidrug resistant K562/VCR and K562/ADR cells, indicating that Fluo-3 is another good indicator of MDR. However, a similar, but lower, increase in uptake and a delayed efflux pattern of Fluo-3 by verapamil and cepharanthine were also demonstrated even in Pgp-non-overexpressed K562/Parent cells. In contrast, accumulation of Rh-123 was not affected by verapamil and cepharanthine. To further study the Pgp dependency of Fluo-3, another cell line, K562/NC16 expressing minimum MDR1 mRNA, was cloned. Increased uptake and a delayed efflux pattern of Fluo-3, but not Rh-123, with verapamil or cepharanthine were again demonstrated in K562/NC16 cells, indicating that intracellular accumulation of Fluo-3 may be non-specifically influenced by verapamil and cepharanthine at very low levels of Pgp-related MDR, while the influx and efflux patterns of Rh-123 may be specifically affected by Pgp overexpression.

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Year:  1995        PMID: 7488425     DOI: 10.1016/0959-8049(95)00288-t

Source DB:  PubMed          Journal:  Eur J Cancer        ISSN: 0959-8049            Impact factor:   9.162


  3 in total

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Journal:  Parasitol Res       Date:  2014-02-07       Impact factor: 2.289

Review 2.  Discovering natural product modulators to overcome multidrug resistance in cancer chemotherapy.

Authors:  Chung-Pu Wu; Shinobu Ohnuma; Suresh V Ambudkar
Journal:  Curr Pharm Biotechnol       Date:  2011-04       Impact factor: 2.837

3.  A Machine Learning-Based Prediction Platform for P-Glycoprotein Modulators and Its Validation by Molecular Docking.

Authors:  Onat Kadioglu; Thomas Efferth
Journal:  Cells       Date:  2019-10-21       Impact factor: 6.600

  3 in total

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