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Clin Chem Lab Med. 2013 Jul;51(7):1467-76. doi: 10.1515/cclm-2012-0642.

Glycoproteomic identification of potential glycoprotein biomarkers in ovarian cancer proximal fluids.

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  • 1Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.



Ovarian cancer is the leading cause of death among all gynecological disorders. Aberrant glycosylation, or more specifically, increased sialylation of proteins has been observed in ovarian cancer. Several sialyltransferase genes have been shown to be up-regulated at both the mRNA and protein levels in a number of cancers, including that of the ovary. ST6GAL1 (β-galactosamide α2,6-sialyltranferase 1) gene expression has previously been shown to be upregulated in ovarian cancers of all major subtypes.


We have identified the sialome (i.e., sialic acid containing glycoproteins) of biological fluids from ovarian cancer patients and ovarian cancer cell lines utilizing tandem mass spectrometry as a potential pool of novel biomarker candidates. The sialoglycopeptides from four ovarian cancer cell lines, pooled ascites (n=13) and ovarian cyst (n=14) fluids from ovarian cancer patients were enriched utilizing affinity to agarose-immobilized Elderberry lectin (Sambucus nigra agglutinin) and magnetic hydrazide beads folowing periodate-mediated oxidation of sialic acids. Benign ovarian cyst (n=10) and peritoneal effusion (n=20) fluids were analyzed in the same fashion to serve as controls. PNGase F deglycosylated peptides were identified using electrospray ionization-LTQ Orbitrap tandem mass spectrometry.


In all of the samples analyzed in the glycoproteomic portion of the study, we have identified 579 glycosylation sites on 333 proteins. Of these, 13 were exclusively identified in biological fluids from ovarian cancer patients, and another eight were common to these fluids and the ovarian cancer cell line supernatants.


The proteins identified in the present study could form the basis for future studies examining and quantifying their sialylation status as biomarkers of ovarian cancer.

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