Title : A strategy for precise and large scale identification of core fucosylated
glycoproteins
Abstract :
- Core fucosylation (CF) patterns of some glycoproteins are more sensitive and specific than evaluation of their total respective protein levels for diagnosis of many diseases, such as cancers
- Global profiling and quantitative characterization of CF glycoproteins may reveal potent biomarkers for clinical applications
- However, current techniques are unable to reveal CF glycoproteins precisely on a large scale
- Here we developed a robust strategy that integrates molecular weight cutoff, neutral loss-dependent MS(3), database-independent candidate spectrum filtering, and optimization to effectively identify CF glycoproteins
- The rationale for spectrum treatment was innovatively based on computation of the mass distribution in spectra of CF glycopeptides
- The efficacy of this strategy was demonstrated by implementation for plasma from healthy subjects and subjects with hepatocellular carcinoma
- Over 100 CF glycoproteins and CF sites were identified, and over 10,000 mass spectra of CF glycopeptide were found
- The scale of identification results indicates great progress for finding biomarkers with a particular and attractive prospect, and the candidate spectra will be a useful resource for the improvement of database searching methods for glycopeptides