Literature DB >> 23241603

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

Uros Kuzmanov1, Natasha Musrap, Hari Kosanam, Christopher R Smith, Ihor Batruch, Apostolos Dimitromanolakis, Eleftherios P Diamandis.   

Abstract

BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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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Year:  2013        PMID: 23241603     DOI: 10.1515/cclm-2012-0642

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


  14 in total

Review 1.  Proteomics of ovarian cancer: functional insights and clinical applications.

Authors:  Mohamed A Elzek; Karin D Rodland
Journal:  Cancer Metastasis Rev       Date:  2015-03       Impact factor: 9.264

Review 2.  Sialic acids: biomarkers in endocrinal cancers.

Authors:  Shyamasree Ghosh
Journal:  Glycoconj J       Date:  2015-03-17       Impact factor: 2.916

3.  Estimation of low-level components lost through chromatographic separations with finite detection limits.

Authors:  Nicole M Devitt; Joe M Davis; Mark R Schure
Journal:  J Chromatogr A       Date:  2020-05-31       Impact factor: 4.759

Review 4.  Sialic acids in gynecological cancer development and progression: Impact on diagnosis and treatment.

Authors:  Anna Y Berghuis; Johan F A Pijnenborg; Thomas J Boltje; Johanna M A Pijnenborg
Journal:  Int J Cancer       Date:  2021-11-17       Impact factor: 7.316

5.  The serum glycome to discriminate between early-stage epithelial ovarian cancer and benign ovarian diseases.

Authors:  Karina Biskup; Elena Iona Braicu; Jalid Sehouli; Rudolf Tauber; Véronique Blanchard
Journal:  Dis Markers       Date:  2014-08-12       Impact factor: 3.434

6.  Integrative network analysis of TCGA data for ovarian cancer.

Authors:  Qingyang Zhang; Joanna E Burdette; Ji-Ping Wang
Journal:  BMC Syst Biol       Date:  2014-12-31

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

Authors:  Qing Kay Li; Punit Shah; Yuan Tian; Yingwei Hu; Richard B S Roden; Hui Zhang; Daniel W Chan
Journal:  Clin Proteomics       Date:  2017-05-10       Impact factor: 3.988

Review 8.  Mass spectrometry-based proteomics techniques and their application in ovarian cancer research.

Authors:  Agata Swiatly; Szymon Plewa; Jan Matysiak; Zenon J Kokot
Journal:  J Ovarian Res       Date:  2018-10-01       Impact factor: 4.234

9.  A metabolic labeling approach for glycoproteomic analysis reveals altered glycoprotein expression upon GALNT3 knockdown in ovarian cancer cells.

Authors:  Razan Sheta; Christina M Woo; Florence Roux-Dalvai; Frédéric Fournier; Sylvie Bourassa; Arnaud Droit; Carolyn R Bertozzi; Dimcho Bachvarov
Journal:  J Proteomics       Date:  2016-04-17       Impact factor: 4.044

Review 10.  Ovarian cancer: can proteomics give new insights for therapy and diagnosis?

Authors:  Angela Toss; Elisabetta De Matteis; Elena Rossi; Lara Della Casa; Anna Iannone; Massimo Federico; Laura Cortesi
Journal:  Int J Mol Sci       Date:  2013-04-15       Impact factor: 5.923

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