ArticleClinical and experimental medicine2017
Validation of N-glycan markers that improve the performance of CA19-9 in pancreatic cancer.
Article in Clinical and experimental medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 31 citations in OpenAlex.
- Efficacy of LNP@2DG-DON liposomal nanoparticles in tumor inhibition and immune activation.Journal of translational medicine · 2026Article
- Fucosylated N-Glycan Landscape of Triple-Negative Breast Cancer.Molecular cancer research : MCR · 2025Article
- Characterization of Oral Microbiome and Exploration of Potential Biomarkers in Patients with Pancreatic Cancer.BioMed research international · 2020Article
- Aberrant glycosylation and cancer biomarker discovery: a promising and thorny journey.Clinical chemistry and laboratory medicine · 2019Review
- Diagnostic Significance of Serum IgG Galactosylation in CA19-9-Negative Pancreatic Carcinoma Patients.Frontiers in oncology · 2019Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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