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尿糖肽分析用于新型生物标志物的研究。

Urinary Glycopeptide Analysis for the Investigation of Novel Biomarkers.

机构信息

Mosaiques Diagnostics GmbH, 30659 Hannover, Germany.

University Hospital RWTH Aachen, Institute for Molecular Cardiovascular Research (IMCAR), 52074 Aachen, Germany.

出版信息

Proteomics Clin Appl. 2019 May;13(3):e1800111. doi: 10.1002/prca.201800111. Epub 2018 Oct 18.

Abstract

PURPOSE

Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM-centric software-Byonic.

EXPERIMENTAL DESIGN

The urinary peptide profiles of 238 normal subjects, previously analyzed using CE-MS and CE-MS/MS and/or LC-MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma.

RESULTS

A total of 37 intact O-glycopeptides and 23 intact N-glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O-glycoproteins are Apolipoprotein C-III and insulin-like growth factor II, while titin among the N-glycoproteins. Further statistical analysis reveals that three O-glycopeptides and five N-glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects.

CONCLUSIONS AND CLINICAL RELEVANCE

Through the established glycoproteomics workflow, intact O- and N-glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.

摘要

目的

尿液是潜在生物标志物的丰富来源,包括糖蛋白。由于聚糖的高度异质性,糖蛋白质组学分析仍然具有挑战性。然而,糖蛋白质组学软件解决方案的最新进展有助于糖肽的鉴定和表征。本研究旨在使用新型 PTM 为中心的软件 Byonic 研究正常受试者尿液肽谱中的完整糖肽。

实验设计

对先前使用 CE-MS 和 CE-MS/MS 和/或 LC-MS/MS 分析的 238 名正常受试者的尿肽谱进行糖肽分析。此外,还评估了 969 名患有五种不同癌症类型(膀胱癌、前列腺癌和胰腺癌、胆管癌和肾细胞癌)的患者的糖肽分布。

结果

在 238 名正常受试者的尿谱中鉴定出 37 个完整的 O-糖肽和 23 个完整的 N-糖肽。最常见的 O-糖蛋白包括载脂蛋白 C-III 和胰岛素样生长因子 II,而 N-糖蛋白中则是肌联蛋白。进一步的统计分析表明,与正常受试者相比,三种 O-糖肽和五种 N-糖肽在不同癌症类型中的丰度存在显著差异。

结论和临床相关性

通过建立的糖蛋白质组学工作流程,鉴定和表征了人尿液中的完整 O-和 N-糖肽,为进一步探索特定疾病的糖蛋白质组提供了新的见解。

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