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. 2004 Aug;4(8):2476-95.
doi: 10.1002/pmic.200300763.

Comprehensive proteome analysis of ovarian cancers using liquid phase separation, mass mapping and tandem mass spectrometry: a strategy for identification of candidate cancer biomarkers

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Comprehensive proteome analysis of ovarian cancers using liquid phase separation, mass mapping and tandem mass spectrometry: a strategy for identification of candidate cancer biomarkers

Haixing Wang et al. Proteomics. 2004 Aug.

Abstract

A two-dimensional (2-D) liquid phase separation method, liquid isoelectric focusing followed by nonporous reversed-phase high performance liquid chromatography (HPLC), was used to separate proteins from human ovarian epithelial whole cell lysates. HPLC eluent was interfaced on-line to an electrospray ionization (ESI) time of flight (TOF) mass spectrometer to obtain accurate intact protein molecular weights (Mr). 2-D protein expression maps were generated displaying protein isoelectric point (pI) versus intact protein Mr. Resulting 2-D images effectively displayed quantitative differential protein expression in ovarian cancer cells versus non-neoplastic ovarian epithelial cells. Protein peak fractions were collected from the HPLC eluent, enzymatically digested, and analyzed by matrix-assisted laser desorption/ionization (MALDI) TOF-mass spectrometry (MS) peptide mass fingerprinting and by MALDI-quadrupole TOF tandem mass spectrometry peptide sequencing. Interlysate comparisons of differential protein expression between two ovarian adenocarcinoma cell lines, ES2 and MDAH-2774, and ovarian surface epithelial cells was performed. Five pI fractions from each sample were selected for comparative study and over 300 unique proteins were positively identified from the 2-D liquid expression maps using MS, which covered around 60% of proteins detected by on-line ESI-TOF-MS. This represents one of the most comprehensive proteomic analyses of ovarian cancer samples to date. Protein bands with significant up- or down-regulation in one cell line versus another as viewed in the 2-D expression maps were identified. This strategy may prove useful in identifying novel ovarian cancer marker proteins.

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