N-glycoproteins are involved in various biological processes. Certain distinctive glycoforms on specific glycoproteins enhance the specificity and/or sensitivity of cancer diagnosis. Therefore, the characterization of plasma N-glycoproteome is essential for a new biomarker discovery. The absence of suitable analytical methods for in-depth and large-scale analyses of low-abundance plasma glycoproteins makes it challenging to investigate the role of glycosylation. In this study, we developed an integrated method termed Glyco-CPLL, which integrates combinatorial peptide ligand libraries, high-pH reversed-phase prefractionation, hydrophilic interaction chromatography, trypsin and PNGase F digestion, shotgun proteomics, and various analysis software (MaxQuant and pGlyco2.0) for the low-abundance plasma glycoproteomic profiling. Then, we utilized the method to perform a comparative study and to explore papillary thyroid carcinoma-related proteins and glycosylations with reference to healthy controls. Finally, a large and comprehensive human plasma N-glycoproteomic database was established, containing 786 proteins, 369 N-glycoproteins, 862 glycosites, 171 glycan compositions, and 1644 unique intact N-glycopeptides. Additionally, several low-abundance plasma glycoproteins were identified, including SVEP1 (∼0.54 ng/mL), F8 (∼0.83 ng/mL), and ADAMTS13 (∼1.2 ng/mL). These results suggest that this method will be useful for analyzing plasma intact glycopeptides in future studies. Besides, the Glyco-CPLL method has a great potential to be translated to clinical applications. Data are available via ProteomeXchange with identifier PXD016428.
Keywords: N-glycoproteomics; combinatorial peptide ligand library; mass spectrometry; papillary thyroid carcinoma.