| Literature DB >> 18076136 |
Limor Gortzak-Uzan1, 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 Shaw, Igor Jurisica, Thomas Kislinger.
Abstract
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 I (2)D ( 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.Entities:
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Year: 2007 PMID: 18076136 DOI: 10.1021/pr0703223
Source DB: PubMed Journal: J Proteome Res ISSN: 1535-3893 Impact factor: 4.466