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Updated: May 29, 2025

Immunoglobulin G N-Glycan Analysis by Ultra-Performance Liquid Chromatography
Published on: January 18, 2020
Site-specific immunoglobulin G N-glycosylation is associated with gastric cancer progression
Tingting Xu1, Jianmin Huang2, Jiajing Lin3
1Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, 350122, China.
Background:
The relationship between cancer development and alterations in IgG N-glycosylation has been well-established. However, comprehensive profiling of the N-glycome and N-glycoproteome in gastric cancer (GC) remains limited. Furthermore, the prognostic potential of IgG N-glycan patterns in identifying precursors to GC has yet to be fully elucidated.
Methods:
The IgG N-glycome in GC was characterized using a custom high-throughput orthogonal mass spectrometry approach. Multivariate analysis was employed to identify and assess glycomic alterations. A comprehensive bioinformatics analysis was also conducted to investigate the differential expression of N-glycosylation-related genes and their potential roles in GC pathogenesis. Additionally, interleukin-11 (IL-11) levels were quantified using a standardized enzyme-linked immunosorbent assay (ELISA).
Results:
Galactosylation and sialylation of IgG decreased mainly in the IgG1 and IgG2 subclasses in GC, with subclass-specific changes in IgG3 and IgG4 galactosylation. These glycan modifications were represented by unique glycopeptides (IgG1_H5N5, IgG2_H4N3F1, IgG2_H4N4, IgG2_H4N4F1S1, IgG3/4_H4N4F1, IgG3/4_H4N4F1S1), which outperformed CA72-4 for GC diagnosis. Analysis of key glycogenes revealed differential expression patterns, implicating a functional role for IgG N-glycosylation in GC. Notably, the abundance of specific IgG glycosylation exhibited a significant correlation with serum level of IL-11.
Conclusions:
Alterations in subclass-specific IgG N-glycosylation represent promising biomarkers for the detection and monitoring of GC progression, potentially influenced by cytokine-driven inflammation. Understanding these changes could improve our knowledge of molecular mechanisms, aiding in diagnostic improvements and therapeutic development.
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