An integrated proteomic and glycoproteomic approach uncovers differences in glycosylation occupancy from benign and malignant epithelial ovarian tumors

综合蛋白质组学和糖蛋白质组学方法揭示良性和恶性上皮性卵巢肿瘤的糖基化占有率差异

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作者:Qing Kay Li #, Punit Shah #, Yuan Tian, Yingwei Hu, Richard B S Roden, Hui Zhang, Daniel W Chan

Background

Epithelial ovarian carcinomas encompass a heterogeneous group of diseases with a poor 5-year survival rate. Serous carcinoma is the most common type. Most FDA-approved serum tumor markers are glycoproteins. These glycoproteins on cell surface or shed into the bloodstream could serve as therapeutic targets as well as surrogates of tumor. In addition to glycoprotein expressions, the analysis of protein glycosylation occupancy could be important for the understanding of cancer biology as well as the identification of potential glycoprotein changes in cancer. In this study, we used an integrated proteomics and glycoproteomics approach to analyze global glycoprotein abundance and glycosylation occupancy for proteins from high-grade ovarian serous carcinoma (HGSC) and serous cystadenoma, a benign epithelial ovarian tumor, by using LC-MS/MS-based technique.

Conclusion

In this study, we presented an integrated proteomics and glycoproteomics approach to identify changes of glycoproteins in protein expression and glycosylation occupancy in HGSC and serous cystadenoma and determined the changes of glycosylation occupancy that are associated with malignant and benign tumor tissues. Specific changes in glycoprotein expression or glycosylation occupancy have the potential to be used in the discrimination between benign and malignant epithelial ovarian tumors and to improve our understanding of ovarian cancer biology.

Methods

Fresh-frozen ovarian HGSC tissues and benign serous cystadenoma cases were quantitatively analyzed using isobaric tags for relative and absolute quantitation for both global and glycoproteomic analyses by two dimensional fractionation followed by LC-MS/MS analysis using a Orbitrap Velos mass spectrometer.

Results

Proteins and N-linked glycosite-containing peptides were identified and quantified using the integrated global proteomic and glycoproteomic approach. Among the identified N-linked glycosite-containing peptides, the relative abundances of glycosite-containing peptide and the glycoprotein levels were compared using glycoproteomic and proteomic data. The glycosite-containing peptides with unique changes in glycosylation occupancies rather than the protein expression levels were identified.

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