Identification of sialylated glycoproteins from metabolically oligosaccharide engineered pancreatic cells

In this study, we investigated the use of metabolic oligosaccharide engineering and bio-orthogonal ligation reactions combined with lectin microarray and mass spectrometry to analyze sialoglycoproteins in the SW1990 human pancreatic cancer line. Specifically, cells were treated with the azido N-acet...

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Bibliographic Details
Published in:Clinical proteomics 2015-04, Vol.12 (1), p.11-11, Article 11
Main Authors: Tian, Yuan, Almaraz, Ruben T, Choi, Caitlin H, Li, Qing Kay, Saeui, Christopher, Li, Danni, Shah, Punit, Bhattacharya, Rahul, Yarema, Kevin J, Zhang, Hui
Format: Article
Language:English
Subjects:
Analysis
Glycoproteins
Hostages
Lectins
Mass spectrometry
Organic acids
Pancreatic cancer
Polysaccharides
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Summary:In this study, we investigated the use of metabolic oligosaccharide engineering and bio-orthogonal ligation reactions combined with lectin microarray and mass spectrometry to analyze sialoglycoproteins in the SW1990 human pancreatic cancer line. Specifically, cells were treated with the azido N-acetylmannosamine analog, 1,3,4-Bu3ManNAz, to label sialoglycoproteins with azide-modified sialic acids. The metabolically labeled sialoglyproteins were then biotinylated via the Staudinger ligation, and sialoglycopeptides containing azido-sialic acid glycans were immobilized to a solid support. The peptides linked to metabolically labeled sialylated glycans were then released from sialoglycopeptides and analyzed by mass spectrometry; in parallel, the glycans from azido-sialoglycoproteins were characterized by lectin microarrays. This method identified 75 unique N-glycosite-containing peptides from 55 different metabolically labeled sialoglycoproteins of which 42 were previously linked to cancer in the literature. A comparison of two of these glycoproteins, LAMP1 and ORP150, in histological tumor samples showed overexpression of these proteins in the cancerous tissue demonstrating that our approach constitutes a viable strategy to identify and discover sialoglycoproteins associated with cancer, which can serve as biomarkers for cancer diagnosis or targets for therapy.
ISSN:1542-6416
1559-0275
DOI:10.1186/s12014-015-9083-8