ArticleClinical proteomics2024
Quantitative site-specific N-glycosylation analysis reveals IgG glyco-signatures for pancreatic cancer diagnosis.
Article in Clinical proteomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Establishment of reference intervals for serum immunoglobulin GThe EPMA journal · 2025Article
- N-glycosylation patterns of plasma immunoglobulin G in anti-synthetase syndrome disease.Frontiers in immunology · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundPancreatic cancer is a highly aggressive tumor with a poor prognosis due to a low early detection rate and a lack of biomarkers. Most of pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC). Alterations in the N-glycosylation of plasma immunoglobulin G (IgG) have been shown to be closely associated with the onset and development of several cancers and could be used as biomarkers for diagnosis. The study aimed to explore intact N-glycosylation profile of IgG in patients with PDAC and find relation between intact N-glycosylation profile of IgG and clinical information such as diagnosis and prognosis.
methodsIn this study, we employed a well-evaluated approach (termed GlycoQuant) to assess the site-specific N-glycosylation profile of human plasma IgG in both healthy individuals and patients with pancreatic ductal adenocarcinoma (PDAC). The datasets generated and analyzed during the current study are available in the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) via the iProX partner repository, with the dataset identifier PXD051436.
resultsThe analysis of rapidly purified IgG samples from 100 patients with different stages of PDAC, in addition to 30 healthy controls, revealed that the combination of carbohydrate antigen 19 - 9 (CA19-9), IgG1-GP05 (IgG1-TKPREEQYNSTYR-HexNAc [4]Hex [5]Fuc [1]NeuAc [1]), and IgG4-GP04 (IgG4-EEQFNSTYR- HexNAc [4]Hex [5]Fuc [1]NeuAc [1]) can be used to distinguish between PDAC patients and healthy individuals (AUC = 0.988). In addition, cross validation of the diagnosis model showed satisfactory result.
conclusionsThe study demonstrated that the integrated quantitative method can be utilized for large-scale clinical N-glycosylation research to identify novel N-glycosylated biomarkers. This could facilitate the development of clinical glycoproteomics.
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