糖肽
化学
胰腺癌
糖蛋白组学
糖基化
蛋白质组学
计算生物学
色谱法
癌症
生物化学
内科学
生物
医学
基因
抗生素
作者
Luyao Liu,Bin Zhu,Zheng Fang,Na Zhang,Hongqiang Qin,Zhimou Guo,Xinmiao Liang,Zhenzhen Yao,Mingliang Ye
标识
DOI:10.1021/acs.analchem.1c00645
摘要
Bottom-up proteomics has been increasingly applied in clinical research to study the disease pathophysiology and to discover disease biomarkers. However, glycoproteomic analysis always requires tedious experimental steps for intact glycopeptide enrichment, which has been the technique bottleneck for large-scale analysis of clinical samples. Herein, we developed an automated glycopeptide enrichment method for the analysis of serum site-specific N-glycoproteome. This automated method allowed for processing one sample within 20 min. It showed higher enrichment specificity, more intact glycopeptide identifications, and better quantitative reproducibility than the traditional manual method using microtip enrichment devices. We further applied this method to investigate the serum site-specific N-glycosylation changes between four patients with pancreatic cancer and seven healthy controls. The principal component analysis of intact N-glycopeptides showed good clustering across cancer and normal groups. Furthermore, we found that the site-specific glycoforms, monofucosylated and nonsialylated oligosaccharides, on IgG1 site 180 expressed a significant decrease in pancreatic cancer patients compared to healthy controls. Together, the automated method is a powerful tool for site-specific N-glycoproteomic analysis of complex biological samples, and it has great potential for clinical utilities.
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