ABSTRACT
Objective:Analyze the correlation between serum immunoglobulin G (IgG) N-glycan and Lauren classification of gastric cancer.Methods:A retrospective study was performed on 17 patients with diffuse type gastric cancer and 21 patients with intestinal type who received treatment in Zhongshan Hospital from 2017 to 2018, and the general medical history data and disease characteristics were summarized. The serum IgG glycome profiles were analyzed by ultraperformance liquid chromatography, and the difference between intestinal type and diffuse type gastric cance was compared.Logistic regression was used to evaluate the correlation between serum IgG N-glycan and Lauren classification.Results:IgG N-glycome analysis included 27 directly detected glycans and 4 derived traits. H=Hexose, N=N-acetylglucosamine, F=Fucose, S=Sialic acid.There was no significant difference in IgG N-glycan among different chemotherapy protocol. Compared with intestinal type, H3N3F1 ( t=3.785, P=0.001), H3N4( t=3.919, P=0.002), H3N4F1( t=2.770, P=0.005), H3N5F1( t=2.888, P=0.010) were decreased in diffuse type; H4N4F1(6)( t=?3.488, P<0.001), H5N4F1( t=?3.401, P=0.003), H5N5F1( t=?2.303, P=0.023), H5N4F1S1 ( t=?3.068, P=0.008) were increased.H3N3F1( OR:1.20, P=0.008), H3N4( OR:1.32, P=0.005), H3N4F1 ( OR:1.13, P=0.017), H3N5F1 ( OR:1.78, P=0.015), H4N4F1(6)( OR:0.43, P=0.008), H5N4F1(6)( OR:0.74, P=0.008), H5N5F1 ( OR:0.32, P=0.036), H5N4F1S1( OR:0.48, P=0.009) were significantly correlated with Lauren classification. Sialylated ( t=?2.717, P=0.012) and galactosylated ( t=?3.400, P=0.001) IgG N-glycan were reduced in patients with intestinal type gastric cancer.Galactosylated ( OR:0.87, P=0.007) and sialylated ( OR:0.62, P=0.015) IgG N-glycan were significantly correlated with Lauren classification. Conclusion:Some IgG N-glycan are significantly correlated with Lauren classification, which can be used as potential biomarkers.
ABSTRACT
Changes in protein glycosylation modification have been found to be closely related to cancer and other diseases. Profiling glycosylation change has become an effective way to explore the diagnosis and treatment markers. The accuracy of quantitative technology is the key to reveal the mystery of glycosylation, and the screening and validation of glycosylation disease markers is dependant on the study of large clinical samples. Therefore, glycomic technology are expected to be simple, rapid, high-throughput, accurate and practical. In this paper, the characteristics of some commonly used glycomic analysis techniques and their applications in glycan markers are briefly discussed, and the characteristics, progress and applications of high-throughput precision glycome quantitative methods based on MALDI MS are emphasized.