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. Molecular & Cellular Proteomics 8:913-923, 2009.

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Cancer cell metastasis is a major cause of cancer death. Unfortunately, the underlying molecular mechanisms remain unknown, which results in the lack of efficient diagnosis, therapy and prevention approaches. Nevertheless, the dysregulation of the cancer cell secretome is known to play key roles in tumor transformation and progression. The majority of proteins in the secretome are secretory proteins and membrane-released proteins, and, mostly, the glycosylated proteins. Until recently, few studies have explored protein N-glycosylation changes in the secretome, although protein glycosylation has received increasing attention in the study of tumor development processes. Here, the N-glycoproteins in the secretome of two human hepatocellular carcinoma (HCC) cell lines with low (MHCC97L) or high (HCCLM3) metastatic potential were investigated with a in-depth characterization of the N-glycosites by combining two general glycopeptide enrichment approaches, hydrazide chemistry and zwitterionic hydrophilic interaction chromatography (zic-HILIC), with mass spectrometry analysis. A total of 1,213 unique N-glycosites from 611 N-glycoproteins were confidently identified. These N-glycoproteins were primarily localized to the extracellular space and plasma membrane, supporting the important role of N-glycosylation in the secretory pathway. Coupling label-free quantification with a hierarchical clustering strategy, we determined the differential regulation of several N-glycoproteins that are related to metastasis, among which AFP, DKK1, FN1, CD151 and TGFβ2 were up-regulated in HCCLM3 cells. The inclusion of the well-known metastasis-related proteins AFP and DKK1 in this list provides solid supports for our study. Further western blotting experiments detecting FN1 and FAT1 confirmed our discovery. The glycoproteome strategy in this study provides an effective means to explore potential cancer biomarkers.

N-linked glycosylation is an important protein posttranslational modification that is involved in numerous biological processes. Different methods, including chemical reaction and affinity interaction, have been developed to enrich glycosylated peptides or proteins from biological systems. However, due to the common occurrence of low glycosites occupancy in proteins and the low efficiency of enrichment approaches, only a small fraction of protein glycosites have been reported. In this study, we combined the glycopeptide enrichment strategy for broad analysis of human serum N-glycoproteins using a tandem enrichment method coupling lectin affinity capture with HILIC. This strategy was applied to profile the human serum N-linked glycoproteome, and it resulted in 32 and 14% more N-glycosites than could be identified with the common lectin affinity capture or HILIC approaches, respectively. With an additional dimension of glycopeptides separation using high-pH reversed phase liquid chromatography or off-gel electrophoresis, the number of identified glycosites was increased by 3.1-fold and 1.8-fold, respectively. These results demonstrate that tandem enrichment methods, especially when followed by high-pH reversed-phase prefractionation, can greatly improve the power of N-glycoproteome analysis. In total, 615 N-glycosites from 312 glycoproteins (protein group) were mapped using high-accuracy mass spectrometry.

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