A proteome resource of ovarian cancer ascites: integrated proteomic and bioinformatic analyses to identify putative biomarkers.
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.
Gortzak-Uzan
Limor
L
Ontario Cancer Institute, Division of Cancer Genomics and Proteomics, Canada.
Ignatchenko
Alex
A
Evangelou
Andreas I
AI
Agochiya
Mahima
M
Brown
Kevin A
KA
St Onge
Peter
P
Kireeva
Inga
I
Schmitt-Ulms
Gerold
G
Brown
Theodore J
TJ
Murphy
Joan
J
Rosen
Barry
B
Shaw
Patricia
P
Jurisica
Igor
I
Kislinger
Thomas
T
D001201:Ascites; D014408:Biomarkers, Tumor; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D005260:Female; D006801:Humans; D009363:Neoplasm Proteins / Q000032:analysis*; D010051:Ovarian Neoplasms / Q000737:chemistry* / Q000175:diagnosis; D020543:Proteome / Q000032:analysis*; D040901:Proteomics / Q000379:methods
D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins; D020543:Proteome