Literature DB >> 16335783

Proteome profiling of human epithelial ovarian cancer cell line TOV-112D.

Jean-Philippe Gagné1, Pierre Gagné, Joanna M Hunter, Marie-Eve Bonicalzi, Jean-François Lemay, Isabelle Kelly, Cécile Le Page, Diane Provencher, Anne-Marie Mes-Masson, Amaud Droit, David Bourgais, Guy G Poirier.   

Abstract

A proteome profiling of the epithelial ovarian cancer cell line TOV-112D was initiated as a protein expression reference in the study of ovarian cancer. Two complementary proteomic approaches were used in order to maximise protein identification: two-dimensional gel electrophoresis (2DE) protein separation coupled to matrix assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and one-dimensional gel electrophoresis (1DE) coupled to liquid-chromatography tandem mass spectrometry (LC MS/MS). One hundred and seventy-two proteins have been identified among 288 spots selected on two-dimensional gels and a total of 579 proteins were identified with the 1DE LC MS/MS approach. This proteome profiling covers a wide range of protein expression and identifies several proteins known for their oncogenic properties. Bioinformatics tools were used to mine databases in order to determine whether the identified proteins have previously been implicated in pathways associated with carcinogenesis or cell proliferation. Indeed, several of the proteins have been reported to be specific ovarian cancer markers while others are common to many tumorigenic tissues or proliferating cells. The diversity of proteins found and their association with known oncogenic pathways validate this proteomic approach. The proteome 2D map of the TOV-112D cell line will provide a valuable resource in studies on differential protein expression of human ovarian carcinomas while the 1DE LC MS/MS approach gives a picture of the actual protein profile of the TOV-112D cell line. This work represents one of the most complete ovarian protein expression analysis reports to date and the first comparative study of gene expression profiling and proteomic patterns in ovarian cancer.

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Year:  2005        PMID: 16335783     DOI: 10.1007/s11010-005-7556-1

Source DB:  PubMed          Journal:  Mol Cell Biochem        ISSN: 0300-8177            Impact factor:   3.396


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