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Engineering >> 2023, Volume 26, Issue 7 doi: 10.1016/j.eng.2023.02.008

High-Throughput Profiling of Serological Immunoglobulin G N-Glycome as a Noninvasive Biomarker of Gastrointestinal Cancers

a School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250117, China
b State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
c School of Stomatology, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250117, China
d Beijing Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, Beijing 100069, China
e Beijing Sanbo Brain Hospital, Capital Medical University, Beijing 100093, China
f Department of Gastroenterology, The Second Affiliated Hospital of Shandong First Medical University, Taian 271000, China
g Department of Epidemiology, School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250117, China

# These authors contributed equally to this work.

Received: 2022-09-28 Revised: 2023-02-20 Accepted: 2023-02-21 Available online: 2023-04-07

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Abstract

Immunoglobulin G (IgG) N-glycosylation plays a crucial role in the development of inflammatory diseases. This study aimed to evaluate the diagnostic performance of IgG for gastrointestinal (GI) cancer subtypes. A total of 749 GI cancer patients were enrolled from the Cancer Hospital, Chinese Academy of Medical Sciences, including esophageal cancer (EC), gastric cancer (GC), colorectal cancer (CRC), and pancreatic cancer (PC) patients. Hydrophilic interaction liquid chromatography using ultra-performance liquid chromatography (HILIC-UPLC) was employed to analyze the composition of the plasma IgG N-glycome. The levels of circulating inflammatory cytokines were detected by means of a Bio-Plex Pro Human Th17 Cytokine Assay. Canonical correlation analysis (CCA) was used to explore the correlation between IgG N-glycosylation patterns and inflammatory cytokines. A Lasso algorithm, accompanied by a logistic regression model, was used to develop a glycan-based model for differentiating GI cancer patients from healthy individuals. The levels of sialylation and galactosylation were significantly decreased among EC, GC, CRC, and PC patients, whereas the abundance of glycans with bisecting Nacetylglucosamine (GlcNAc) was increased in GI cancer patients in comparison with the healthy controls. Moreover, only PC patients had a decreased level of fucosylation. The levels of interleukin 1β (IL-1β), IL- 31, and soluble CD40 ligand (sCD40L) were significantly higher in GI cancer patients than in the controls. In addition, the composition of IgG N-glycans was correlated with that of inflammatory cytokines (r = 0.556). The glycan-based models for diagnosing GI cancers exhibited an excellent performance, with areas under the receiver operating characteristic curves (AUCs) of 0.972 for EC, 0.871 for GC, 0.867 for CRC, and 0.907 for PC. Our findings demonstrate that IgG N-glycosylation plays an important role in modulating the pathogenesis of GI cancers. Serological IgG N-glycosylation is thus a potential candidate for noninvasively assisting in the clinical diagnosis of GI cancer subtypes.

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