Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.
PURPOSE Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by its late diagnosis, poor prognosis and rapid development of drug resistance. Using the data-independent acquisition (DIA) technique, the authors applied a spectral library-based proteomic approach to analyze N-glycosylated peptides in human plasma, in the context of pancreatic cancer study. EXPERIMENTAL DESIGN The authors extended the application of DIA to the quantification of N-glycosylated peptides enriched from plasma specimens from a clinically well-defined cohort that consists of patients with early stage PDAC, chronic pancreatitis and healthy subjects. RESULTS The analytical platform was evaluated in light of its robustness for quantitative analysis of large-scale clinical specimens. The authors analysis indicated that the level of N-glycosylated peptides derived from galectin-3 binding proteins (LGALS3BP) were frequently elevated in plasma from PDAC patients, concurrent with the altered N-glycosylation of LGALS3BP observed in the tumor tissue. CONCLUSION AND CLINICAL RELEVANCE The glycosylation form of LGALS3BP influences its function in the galectin network, which profoundly involves in cancer progression, immune response and drug resistance. As one of the major binding ligands of galectin network, discovery of site specific N-glycosylation changes of LGALS3BP in association of PDAC may provide useful clues to facilitate cancer detection or phenotype stratification.