4.7 Article

Comparative serum glycoproteomics using lectin selected sialic acid glycoproteins with mass spectrometric analysis: Application to pancreatic cancer serum

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 5, Issue 7, Pages 1792-1802

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/pr060034r

Keywords

serum; glycoprotein; pancreatic cancer; lectin; liquid chromatography; mass spectrometry

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A strategy is developed in this study for identifying sialylated glycoprotein markers in human cancer serum. This method consists of three steps: lectin affinity selection, a liquid separation and characterization of the glycoprotein markers using mass spectrometry. In this work, we use three different lectins (Wheat Germ Agglutinin, (WGA) Elderberry lectin,(SNA), Maackia amurensis lectin, ( MAL)) to extract sialylated glycoproteins from normal and cancer serum. Twelve highly abundant proteins are depleted from the serum using an IgY-12 antibody column. The use of the different lectin columns allows one to monitor the distribution of R( 2,3) and R( 2,6) linkage type sialylation in cancer serum vs that in normal samples. Extracted glycoproteins are fractionated using NPS-RP-HPLC followed by SDS-PAGE. Target glycoproteins are characterized further using mass spectrometry to eludicate the carbohydrate structure and glycosylation site. We applied this approach to the analysis of sialylated glycoproteins in pancreatic cancer serum. Approximately 130 sialylated glycoproteins are identified using mu LC-MS/MS. Sialylated plasma protease C1 inhibitor is identified to be down-regulated in cancer serum. Changes in glycosylation sites in cancer serum are also observed by glycopeptide mapping using mu LC-ESI-TOF-MS where the N83 glycosylation of alpha 1-antitrypsin is down regulated. In addition, the glycan structures of the altered proteins are assigned using MALDI-QIT-MS. This strategy offers the ability to quantitatively analyze changes in glycoprotein abundance and detect the extent of glycosylation alteration as well as the carbohydrate structure that correlate with cancer.

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