Dataset Information

Profiling of IgG N-glycome in gastric cancer by MALDI-TOF-MS

ABSTRACT: Background: Alterations in IgG glycosylation have been observed in many inflammatory activities and diseases progression, uncovering IgG glycome contributes to deciphering the molecular mechanism of human diseases. Gastric cancer (GC) associated IgG glycosylation was rarely investigated.Methods: We comprehensively characterized IgG N-glycome profile in GC by high-throughput orthogonal mass spectrometry assay, and analyzed the difference of glycosylation between controls and GC patients through multiple statistical tools. Bioinformatics analysis was performed to study the candidate glycogens and their biological functions involved in GC. Results: GC associates with decrease in galactosylation and sialylation of IgG, and increase in bisection and agalactosylation of IgG.Bioinformatics analysis verified the differential expression of significantly changed IgG glycan associated glycogens, indicating the crucial role of IgG glycosylation in the pathogenesis of GC.Conclusions: This study demonstrates the potential diagnostic merits of specific IgG glycans for early detection of GC, as well as revealing molecular mechanism in the development of this cancer.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Cell, Blood Serum

DISEASE(S): Stomach Carcinoma

SUBMITTER: Si Liu

LAB HEAD: Si Liu

PROVIDER: PXD028368 | Pride | 2025-05-06

REPOSITORIES: Pride

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Publications

Site-specific immunoglobulin G N-glycosylation is associated with gastric cancer progression.

Xu Tingting T Huang Jianmin J Lin Jiajing J Liu Yuanyuan Y Wang Yi Y Shen Wenkang W He Jianjie J Chen Shuyun S Zhu Xi X Que Yuqin Y Hu Mengting M Chen Yu Y Cheng Liming L He Honghao H Liu Xin X Liu Si S

BMC cancer 20250207 1

<h4>Background</h4>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.<h4>Methods</h4>The IgG N-glycome in GC was characterized using a custom high-throughput orthogonal mass spectrometry approach. Multiva ...[more]

PMID: 39920693

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Project description:Changes in IgG glycosylation have been reported to be associated with colorectal cancer (CRC), but the alteration in specific subclass of IgG is unknown. Herein, we optimized five common IgG glycopeptides enrichment methods to acquire comprehensive profiling of IgG glycoproteomics in CRC. Notably, incomplete tryptic digestion of IgG occurred when using ordinary ratio of protease to protein, which significantly impacted the final statistical analysis of association between IgG glycosylation and CRC. We introduced a method based on two-step enzymatic digestion, enabling the complete digestion of IgG glycopeptides and further improving the detection intensity of the target glycopeptides. By this approach, total 47 IgG glycopeptides can be identified by nanoLC-ESI-MS/MS. Following rapid and automatic data processing through the self-developed program, we observed that IgG1_H3N4F1 and IgG1_H3N4 were substantially increased in CRC, while IgG1_H5N5F1, IgG1_H5N4F1S1and IgG2_H5N4F1 were markedly decreased. Strikingly, these four glycopeptides were continually significantly changed in early and late stages of CRC. Further evaluation of the diagnostic performance showed they all obtained a fair performance in discriminating the patients from the normal. In terms of the glycan features, it demonstrated that CRC progression associates with the increased agalactosylation, and the decreased digalactosylation and galactosylation per antenna on diantennay glycans of IgG1 and IgG2. Concurrently, the decreased sialylation of IgG1 was strongly correlated with CRC. Moreover, tumor-specific glycosylation analysis showed that the alterations of subclass-specific IgG glycosylation were more significant in colon cancer, and no obvious difference between colon and rectal cancer was found. More importantly, all these findings were validated in an independent cohort. This two-step enzymatic approach is crucial to explore the relationship between the disease progression and IgG glycosylation.

Project description:<p><strong>BACKGROUND:</strong> Novel biomarkers are urgently needed to distinguish between benign and malignant thyroid nodules and detect thyroid cancer in the early stage. The associations between serum IgG N-glycosylation and thyroid cancer risk have been revealed. We aimed to explore the potential of IgG N-glycan traits as biomarkers in the differential diagnosis of thyroid cancer.</p><p><strong>METHODS:</strong> Plasma IgG N-glycome analysis was applied to a discovery cohort followed by independent validation. IgG N-glycan profiles were obtained using a robust quantitative strategy based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. IgG N-glycans were relatively quantified, and classification performance was evaluated based on directly detected and derived glycan traits.</p><p><strong>RESULTS: </strong>Four directly detected glycans were significantly changed in thyroid cancer patients compared to that in non-cancer controls. Derived glycan traits and a classification glycol-panel were generated based on the directly detected glycan traits. In the discovery cohort, derived trait BN (bisecting type neutral N-glycans) and the glyco-panel showed potential in distinguishing between thyroid cancer and non-cancer controls with AUCs of 0.920 and 0.917, respectively. The diagnostic potential was further validated. Derived trait BN and the glycol-panel displayed “accurate” performance (AUC>0.8) in discriminating thyroid cancer from benign thyroid nodules and healthy controls in the validation cohort. Meanwhile, derived trait BN and the glycol-panel also showed diagnostic potential in detecting early-stage thyroid cancer.</p><p><strong>CONCLUSIONS:</strong> IgG N-glycome analysis revealed N-glycomic differences that allow classification of thyroid cancer from non-cancer controls. Our results suggested that derived trait BN and the classification glyco-panel rather than single N-glycans may serve as candidate biomarkers for further validation.</p>

			Action	DRS
	Benign.rar	Other
	Benign_GlycanFeatures.txt	Txt
	Benign_IndividualGlycan.txt	Txt
	Cancer.rar	Other
	Cancer_GlycanFeatures.txt	Txt