Targeted identification of metastasis-associated cell-surface sialoglycoproteins in prostate cancer.
- Citation data:
Molecular & cellular proteomics : MCP, ISSN: 1535-9484, Vol: 10, Issue: 6, Page: M110.007294
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- Repository URL:
- https://digitalcommons.odu.edu/sociology_criminaljustice_fac_pubs/26; https://digitalcommons.odu.edu/bioelectrics_pubs/177
- Biochemistry, Genetics and Molecular Biology; Chemistry; Medicine; Proteins; Cancer cell; Glycans; Glycoproteins; Mass spectrometry; Biochemistry; Medical Biotechnology; Molecular Biology; Oncology
Covalent attachment of carbohydrates to proteins is one of the most common post-translational modifications. At the cell surface, sugar moieties of glycoproteins contribute to molecular recognition events involved in cancer metastasis. We have combined glycan metabolic labeling with mass spectrometry analysis to identify and characterize metastasis-associated cell surface sialoglycoproteins. Our model system used syngeneic prostate cancer cell lines derived from PC3 (N2, nonmetastatic, and ML2, highly metastatic). The metabolic incorporation of AC(4)ManNAz and subsequent specific labeling of cell surface sialylation was confirmed by flow cytometry and confocal microscopy. Affinity isolation of the modified sialic-acid containing cell surface proteins via click chemistry was followed by SDS-PAGE separation and liquid chromatography-tandem MS analysis. We identified 324 proteins from N2 and 372 proteins of ML2. Using conservative annotation, 64 proteins (26%) from N2 and 72 proteins (29%) from ML2 were classified as extracellular or membrane-associated glycoproteins. A selective enrichment of sialoglycoproteins was confirmed. When compared with global proteomic analysis of the same cells, the proportion of identified glycoprotein and cell-surface proteins were on average threefold higher using the selective capture approach. Functional clustering of differentially expressed proteins by Ingenuity Pathway Analysis revealed that the vast majority of glycoproteins overexpressed in the metastatic ML2 subline were involved in cell motility, migration, and invasion. Our approach effectively targeted surface sialoglycoproteins and efficiently identified proteins that underlie the metastatic potential of the ML2 cells.