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 this malignancy. Several sialyltransferase genes have been shown to be up-regulated at both mRNA and and protein levels in a number of cancers, including that of the ovary. In the present study, we have analyzed the glycosylation patterns of kallikrein 6 in the context of ovarian cancer. We have discovered that the carbohydrate structures found at the single N-glycosylation site of kallikrein 6 derived from ovarian cancer cells found in the ascites fluid of ovarian cancer patients is enriched in sialic acid moieties and has an increased branching pattern when compared to controls. We have also developed a reliable anion-exchange HPLC-based methodology capable of quantifying different glycoform subpopulations of kallikrein 6 in serum and other biological fluids, which was capable of differentiating between samples from ovarian cancer patients and healthy controls. A variety of classic molecular biology and mass spectrometry based techniques were utilized in these experiments. Based on the results of the analysis of kallikrein 6 glycosylation and other literature reports showing upregulated sialylation of proteins in ovarian cancer, we have also identified sialylated glycoproteins from ovarian cancer proximal fluids and conditioned media of ovarian cancer cell lines. Sialylated proteins were enriched utilizing lectin affinity or hydrazide chemistry. In total, 333 sialylated glycoproteins and 579 glycosylation sites were identified. A list of 21 potential candidate ovarian cancer biomarkers was produced from proteins that were identified solely in ovarian cancer proximal fluids, which could form the basis for any future studies.
Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/35871 |
Date | 08 August 2013 |
Creators | Kuzmanov, Uros |
Contributors | Diamandis, Eleftherios P. |
Source Sets | University of Toronto |
Language | en_ca |
Detected Language | English |
Type | Thesis |
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