Jin Yi, Hu Ran, Gu Yufan, Wei Ailin, Li Ang, Zhang Yong
Department of Pancreatic Surgery and Institutes for Systems Genetics, West China Hospital, Sichuan University, 37 Guoxue Alley, Chengdu, Sichuan, 610041, China.
Department of Pancreatic Surgery and Institutes for Systems Genetics, West China Hospital, Sichuan University, Keyuan 4th Road, Gaopeng Avenue, Hi-tech Zone, Chengdu, Sichuan, 610041, China.
Clin Proteomics. 2024 Dec 30;21(1):68. doi: 10.1186/s12014-024-09522-4.
Pancreatic cancer is a highly aggressive tumor with a poor prognosis due to a low early detection rate and a lack of biomarkers. Most of pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC). Alterations in the N-glycosylation of plasma immunoglobulin G (IgG) have been shown to be closely associated with the onset and development of several cancers and could be used as biomarkers for diagnosis. The study aimed to explore intact N-glycosylation profile of IgG in patients with PDAC and find relation between intact N-glycosylation profile of IgG and clinical information such as diagnosis and prognosis.
In this study, we employed a well-evaluated approach (termed GlycoQuant) to assess the site-specific N-glycosylation profile of human plasma IgG in both healthy individuals and patients with pancreatic ductal adenocarcinoma (PDAC). The datasets generated and analyzed during the current study are available in the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) via the iProX partner repository, with the dataset identifier PXD051436.
The analysis of rapidly purified IgG samples from 100 patients with different stages of PDAC, in addition to 30 healthy controls, revealed that the combination of carbohydrate antigen 19 - 9 (CA19-9), IgG1-GP05 (IgG1-TKPREEQYNSTYR-HexNAc [4]Hex [5]Fuc [1]NeuAc [1]), and IgG4-GP04 (IgG4-EEQFNSTYR- HexNAc [4]Hex [5]Fuc [1]NeuAc [1]) can be used to distinguish between PDAC patients and healthy individuals (AUC = 0.988). In addition, cross validation of the diagnosis model showed satisfactory result.
The study demonstrated that the integrated quantitative method can be utilized for large-scale clinical N-glycosylation research to identify novel N-glycosylated biomarkers. This could facilitate the development of clinical glycoproteomics.
胰腺癌是一种侵袭性很强的肿瘤，由于早期检测率低且缺乏生物标志物，其预后较差。大多数胰腺癌为胰腺导管腺癌（PDAC）。血浆免疫球蛋白G（IgG）的N-糖基化改变已被证明与多种癌症的发生和发展密切相关，可作为诊断生物标志物。本研究旨在探讨PDAC患者IgG的完整N-糖基化谱，并找出IgG完整N-糖基化谱与诊断和预后等临床信息之间的关系。
在本研究中，我们采用了一种经过充分评估的方法（称为GlycoQuant）来评估健康个体和胰腺导管腺癌（PDAC）患者血浆中人IgG的位点特异性N-糖基化谱。在当前研究中生成和分析的数据集可通过iProX合作伙伴库在蛋白质组交换联盟（http://www.proteomexchange.org/）中获取，数据集标识符为PXD051436。
对100例不同分期的PDAC患者以及30例健康对照者的快速纯化IgG样本进行分析后发现，碳水化合物抗原19-9（CA19-9）、IgG1-GP05（IgG1-TKPREEQYNSTYR-HexNAc[4]Hex[5]Fuc[1]NeuAc[1]）和IgG4-GP04（IgG4-EEQFNSTYR-HexNAc[4]Hex[5]Fuc[1]NeuAc[1]）的组合可用于区分PDAC患者和健康个体（AUC = 0.988）。此外，诊断模型的交叉验证显示结果令人满意。
该研究表明，综合定量方法可用于大规模临床N-糖基化研究，以识别新的N-糖基化生物标志物。这有助于临床糖蛋白质组学的发展。
