Literature DB >> 9804615

Using the national cancer institute anticancer drug screen to assess the effect of MRP expression on drug sensitivity profiles.

M Alvarez1, R Robey, V Sandor, K Nishiyama, Y Matsumoto, K Paull, S Bates, T Fojo.   

Abstract

The MRP gene contributes to one form of multidrug resistance. To identify drugs interacting with MRP, we measured MRP mRNA expression by quantitative PCR in 60 cell lines of the National Cancer Institute Anticancer Drug Screen. Expression was detected in all cell lines (highest in lung carcinomas and central nervous system tumors) with a range of 14-fold. A mean graph of MRP mRNA levels was constructed to determine Pearson correlation coefficients (PCCs) with mean graphs of >40,000 compounds using the COMPARE analysis. Only 20 compounds had PCCs of >/=0.500. The PCCs for VP-16, doxorubicin, and vincristine were 0.008, 0.13, and 0.257, respectively. Initially, 36 compounds with PCCs of >/=0.428 were analyzed using two MRP-overexpressing cell lines; low levels of cross-resistance was demonstrated for 23 compounds (1.3-9.4-fold). Twenty-four compounds also were available for further studies. Using a fluorescence activated cell sorter assay to measure competition of calcein efflux from MRP-overexpressing cells, 10 compounds were found to increase calcein retention by >/=2-fold. Ten compounds also were able to reduce ATP-dependent [3H]LTC4 transport into vesicles from MRP-overexpressing cells. These results contrast with previous studies with MDR-1 in which high correlations were found and confirmed for a large number of compounds. Although other assays may be more revealing, in these unselected cell lines, MRP mRNA expression was a poor predictor of drug sensitivity. This raises the possibility that other factors, including conjugating enzymes, glutathione levels, or other transporters, confound the MRP effect.

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Year:  1998        PMID: 9804615     DOI: 10.1124/mol.54.5.802

Source DB:  PubMed          Journal:  Mol Pharmacol        ISSN: 0026-895X            Impact factor:   4.436


  10 in total

1.  A multivariate insight into the in vitro antitumour screen database of the National Cancer Institute: classification of compounds, similarities among cell lines and the influence of molecular targets.

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Review 3.  A cheminformatic toolkit for mining biomedical knowledge.

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4.  Identification of compounds that correlate with ABCG2 transporter function in the National Cancer Institute Anticancer Drug Screen.

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Journal:  Mol Pharmacol       Date:  2009-07-24       Impact factor: 4.436

5.  A High-Throughput Screen of a Library of Therapeutics Identifies Cytotoxic Substrates of P-glycoprotein.

Authors:  Tobie D Lee; Olivia W Lee; Kyle R Brimacombe; Lu Chen; Rajarshi Guha; Sabrina Lusvarghi; Bethilehem G Tebase; Carleen Klumpp-Thomas; Robert W Robey; Suresh V Ambudkar; Min Shen; Michael M Gottesman; Matthew D Hall
Journal:  Mol Pharmacol       Date:  2019-09-12       Impact factor: 4.436

6.  A strategy for primary high throughput cytotoxicity screening in pharmaceutical toxicology.

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Review 9.  Prediction of individual response to anticancer therapy: historical and future perspectives.

Authors:  Florian T Unger; Irene Witte; Kerstin A David
Journal:  Cell Mol Life Sci       Date:  2014-11-12       Impact factor: 9.261

10.  Expression of multidrug resistance-related transporters in human breast carcinoma.

Authors:  A Kanzaki; M Toi; K Nakayama; H Bando; M Mutoh; T Uchida; M Fukumoto; Y Takebayashi
Journal:  Jpn J Cancer Res       Date:  2001-04
  10 in total

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