Literature DB >> 12874874

Study of the development of chemoresistance in melanoma cell lines using proteome analysis.

Pranav Sinha1, Julia Poland, Sandro Kohl, Martina Schnölzer, Heike Helmbach, Gero Hütter, Hermann Lage, Dirk Schadendorf.   

Abstract

Malignant melanomas have poor prognosis since treatment with anti-neoplastic agents is mostly ineffective. The biological mechanisms of this strong intrinsic therapy resistance are unknown. In order to identify new molecular factors potentially associated with the drug-resistant phenotype of malignant melanoma, a panel of human melanoma cell variants exhibiting low and high levels of resistance to four commonly used anticancer drugs in melanoma treatment, i.e., vindesine, etoposide, cisplatin, and fotemustine, was characterized using proteomic tools (two-dimensional electrophoresis for protein fractionation and matrix assisted laser desorption/ionization-time of flight (MALDI-TOF)-mass spectrometry for protein identification). In the neutral and weak acidic milieu (pH 4.0-8.0) a total number of 14 proteins showed alterations in expression whereas 20 proteins were differentially expressed in the basic milieu (pH 8.0-11.0). Besides proteins with unknown physiologic function, several factors were identified that show chaperone activity. Moreover, proteins involved in drug detoxification, metabolism, and regulation of apoptotic pathways could be identified. The possible role of these proteins in the development of chemoresistance is discussed, although detailed functional tests with these proteins have still to be performed. Nevertheless, it is clear that this proteomic approach for studying chemoresistance phenomena is a prerequisite before further investigation can yield insight into the biology and development of drug resistance in malignant melanoma.

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Year:  2003        PMID: 12874874     DOI: 10.1002/elps.200305456

Source DB:  PubMed          Journal:  Electrophoresis        ISSN: 0173-0835            Impact factor:   3.535


  15 in total

1.  A proteomic investigation into adriamycin chemo-resistance of human leukemia K562 cells.

Authors:  Xingchen Peng; Fengming Gong; Gang Xie; Yuwei Zhao; Minghai Tang; Luoting Yu; Aiping Tong
Journal:  Mol Cell Biochem       Date:  2011-01-18       Impact factor: 3.396

2.  Cellular accumulation and activity of quinolones in ciprofloxacin-resistant J774 macrophages.

Authors:  Jean-Michel Michot; Marie F Heremans; Nancy E Caceres; Marie-Paule Mingeot-Leclercq; Paul M Tulkens; Françoise Van Bambeke
Journal:  Antimicrob Agents Chemother       Date:  2006-05       Impact factor: 5.191

3.  A systems biology analysis of metastatic melanoma using in-depth three-dimensional protein profiling.

Authors:  Mee-Jung Han; Huan Wang; Lynn A Beer; Hsin-Yao Tang; Meenhard Herlyn; David W Speicher
Journal:  Proteomics       Date:  2010-11-17       Impact factor: 3.984

4.  Quantitative proteomic analysis reveals the perturbation of multiple cellular pathways in jurkat-T cells induced by doxorubicin.

Authors:  Xiaoli Dong; Lei Xiong; Xinning Jiang; Yinsheng Wang
Journal:  J Proteome Res       Date:  2010-09-23       Impact factor: 4.466

5.  Quantitative proteomic analysis reveals the perturbation of multiple cellular pathways in HL-60 cells induced by arsenite treatment.

Authors:  Lei Xiong; Yinsheng Wang
Journal:  J Proteome Res       Date:  2010-02-05       Impact factor: 4.466

Review 6.  Use of comparative proteomics to identify potential resistance mechanisms in cancer treatment.

Authors:  Jian-Ting Zhang; Yang Liu
Journal:  Cancer Treat Rev       Date:  2007-09-12       Impact factor: 12.111

7.  Proteomic profiling reveals that resveratrol inhibits HSP27 expression and sensitizes breast cancer cells to doxorubicin therapy.

Authors:  José Díaz-Chávez; Miguel A Fonseca-Sánchez; Elena Arechaga-Ocampo; Ali Flores-Pérez; Yadira Palacios-Rodríguez; Guadalupe Domínguez-Gómez; Laurence A Marchat; Lizeth Fuentes-Mera; Guillermo Mendoza-Hernández; Patricio Gariglio; César López-Camarillo
Journal:  PLoS One       Date:  2013-05-27       Impact factor: 3.240

8.  Proteomics in melanoma biomarker discovery: great potential, many obstacles.

Authors:  Michael S Sabel; Yashu Liu; David M Lubman
Journal:  Int J Proteomics       Date:  2011-10-11

9.  Functional classification of cellular proteome profiles support the identification of drug resistance signatures in melanoma cells.

Authors:  Verena Paulitschke; Verena Haudek-Prinz; Johannes Griss; Walter Berger; Thomas Mohr; Hubert Pehamberger; Rainer Kunstfeld; Christopher Gerner
Journal:  J Proteome Res       Date:  2013-06-19       Impact factor: 4.466

10.  Proteomic analysis of glioma chemoresistance.

Authors:  Kyoungho Suk
Journal:  Curr Neuropharmacol       Date:  2012-03       Impact factor: 7.363

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