A Proteome Resource of Ovarian Cancer Ascites: Integrated Proteomic and Bioinformatic Analyses To Identify Putative Biomarkers

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• 作者：Limor Gortzak-Uzan ; Alex Ignatchenko ; Andreas I. Evangelou ; Mahima Agochiya ; Kevin A. Brown ; Peter St.Onge ; Inga Kireeva ; Gerold Schmitt-Ulms ; Theodore J. Brown ; Joan Murphy ; Barry Rosen ; Patricia Sha
• 刊名：Journal of Proteome Research
• 出版年：2008
• 出版时间：January 2008
• 年：2008
• 卷：7
• 期：1
• 页码：339 - 351
• 全文大小：1647K
• 年卷期：v.7,no.1(January 2008)
• ISSN：1535-3907

文摘

Epithelial ovarian cancer is the most lethal gynecological malignancy, and disease-specific biomarkers are urgently needed to improve diagnosis, prognosis, and to predict and monitor treatment efficiency. We present an in-depth proteomic analysis of selected biochemical fractions of human ovarian cancer ascites, resulting in the stringent and confident identification of over 2500 proteins. Rigorous filter schemes were applied to objectively minimize the number of false-positive identifications, and we only report proteins with substantial peptide evidence. Integrated computational analysis of the ascites proteome combined with several recently published proteomic data sets of human plasma, urine, 59 ovarian cancer related microarray data sets, and protein–protein interactions from the Interologous Interaction Database I²D (id.utoronto.ca/i2d" target="_blank">http://ophid.utoronto.ca/i2d) resulted in a short-list of 80 putative biomarkers. The presented proteomics analysis provides a significant resource for ovarian cancer research, and a framework for biomarker discovery.