Pancreatic cancer (PC) has a high mortality rate because it is usually diagnosed late. Glycosylation of proteins is known to change in tumor cells during the development of PC. The objectives of this study were to identify and validate the diagnostic value of novel biomarkers based on N-glycomic profiling for PC. In total, 217 individuals including subjects with PC, pancreatitis, and healthy controls were divided randomly into a training group (n = 164) and validation groups (n = 53). Serum N-glycomic profiling was analyzed by DSA-FACE. The diagnostic model was constructed based on N-glycan markers with logistic stepwise regression. The diagnostic performance of the model was assessed further in validation cohort. The level of total core fucose residues was increased significantly in PC. Two diagnostic models designated GlycoPCtest and PCmodel (combining GlycoPCtest and CA19-9) were constructed to differentiate PC from normal. The area under the receiver operating characteristic curve (AUC) of PCmodel was higher than that of CA19-9 (0.925 vs. 0.878). The diagnostic models based on N-glycans are new, valuable, noninvasive alternatives for identifying PC. The diagnostic efficacy is improved by combined GlycoPCtest and CA19-9 for the discrimination of patients with PC from healthy controls.
Keywords: Biomarker; Diagnostic model; N-glycan profiling; Pancreatic cancer.