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临床糖组学(糖蛋白质组学)在精准医学中的作用。

The Role of Clinical Glyco(proteo)mics in Precision Medicine.

机构信息

Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.

Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands.

出版信息

Mol Cell Proteomics. 2023 Jun;22(6):100565. doi: 10.1016/j.mcpro.2023.100565. Epub 2023 May 9.

DOI:10.1016/j.mcpro.2023.100565
PMID:37169080
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10326703/
Abstract

Glycoproteomics reveals site-specific O- and N-glycosylation that may influence protein properties including binding, activity, and half-life. The increasingly mature toolbox with glycomic and glycoproteomic strategies is applied for the development of biopharmaceuticals and the discovery and clinical evaluation of glycobiomarkers in various disease fields. Notwithstanding the contributions of glycoscience in identifying new drug targets, the current report is focused on the biomarker modality that is of interest for diagnostic and monitoring purposes. To this end, it is noted that the identification of biomarkers has received more attention than the corresponding quantification. Most analytical methods are very efficient in detecting large numbers of analytes, but developments to accurately quantify these have so far been limited. In this perspective, a parallel is made with earlier proposed tiers for protein quantification using mass spectrometry. Moreover, the foreseen reporting of multimarker readouts is discussed to describe an individual's health or disease state and their role in clinical decision-making. The potential of longitudinal sampling and monitoring of glycomic features for diagnosis and treatment monitoring is emphasized. Finally, different strategies that address the quantification of a multimarker panel are discussed.

摘要

糖蛋白质组学揭示了可能影响蛋白质特性(包括结合、活性和半衰期)的特定位置的 O-和 N-糖基化。糖组学和糖蛋白质组学策略的日益成熟工具包应用于生物制药的开发以及各种疾病领域中糖生物标志物的发现和临床评估。尽管糖科学在确定新的药物靶点方面做出了贡献,但本报告侧重于对诊断和监测有兴趣的生物标志物模式。为此,需要注意的是,与相应的定量相比,生物标志物的鉴定受到了更多的关注。大多数分析方法在检测大量分析物方面非常有效,但到目前为止,对这些分析物进行准确定量的开发还很有限。在这方面,与之前使用质谱法进行蛋白质定量的提议层次进行了平行比较。此外,还讨论了预期的多标志物读出物报告,以描述个体的健康或疾病状态及其在临床决策中的作用。强调了对聚糖特征进行纵向采样和监测用于诊断和治疗监测的潜力。最后,讨论了解决多标志物面板定量的不同策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6678/10326703/478ce7bd46a5/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6678/10326703/b39ad368a255/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6678/10326703/a35654d209fb/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6678/10326703/478ce7bd46a5/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6678/10326703/b39ad368a255/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6678/10326703/a35654d209fb/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6678/10326703/478ce7bd46a5/gr2.jpg

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