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High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis
The glycoproteome has emerged as a prominent target for screening biomarkers, as altered glycosylation is a hallmark of cancer cells. In this work, we incorporated tandem mass tag labeling into quantitative glycoproteomics by developing a chemical labeling-assisted complementary dissociation method...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9985154/ https://www.ncbi.nlm.nih.gov/pubmed/36879659 http://dx.doi.org/10.1093/nsr/nwac059 |
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author | Sun, Zhenyu Fu, Bin Wang, Guoli Zhang, Lei Xu, Ruofan Zhang, Ying Lu, Haojie |
author_facet | Sun, Zhenyu Fu, Bin Wang, Guoli Zhang, Lei Xu, Ruofan Zhang, Ying Lu, Haojie |
author_sort | Sun, Zhenyu |
collection | PubMed |
description | The glycoproteome has emerged as a prominent target for screening biomarkers, as altered glycosylation is a hallmark of cancer cells. In this work, we incorporated tandem mass tag labeling into quantitative glycoproteomics by developing a chemical labeling-assisted complementary dissociation method for the multiplexed analysis of intact N-glycopeptides. Benefiting from the complementary nature of two different mass spectrometry dissociation methods for identification and multiplex labeling for quantification of intact N-glycopeptides, we conducted the most comprehensive site-specific and subclass-specific N-glycosylation profiling of human serum immunoglobulin G (IgG) to date. By analysing the serum of 90 human patients with varying severities of liver diseases, as well as healthy controls, we identified that the combination of IgG1-H3N5F1 and IgG4-H4N3 can be used for distinguishing between different stages of liver diseases. Finally, we used targeted parallel reaction monitoring to successfully validate the expression changes of glycosylation in liver diseases in a different sample cohort that included 45 serum samples. |
format | Online Article Text |
id | pubmed-9985154 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-99851542023-03-05 High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis Sun, Zhenyu Fu, Bin Wang, Guoli Zhang, Lei Xu, Ruofan Zhang, Ying Lu, Haojie Natl Sci Rev Research Article The glycoproteome has emerged as a prominent target for screening biomarkers, as altered glycosylation is a hallmark of cancer cells. In this work, we incorporated tandem mass tag labeling into quantitative glycoproteomics by developing a chemical labeling-assisted complementary dissociation method for the multiplexed analysis of intact N-glycopeptides. Benefiting from the complementary nature of two different mass spectrometry dissociation methods for identification and multiplex labeling for quantification of intact N-glycopeptides, we conducted the most comprehensive site-specific and subclass-specific N-glycosylation profiling of human serum immunoglobulin G (IgG) to date. By analysing the serum of 90 human patients with varying severities of liver diseases, as well as healthy controls, we identified that the combination of IgG1-H3N5F1 and IgG4-H4N3 can be used for distinguishing between different stages of liver diseases. Finally, we used targeted parallel reaction monitoring to successfully validate the expression changes of glycosylation in liver diseases in a different sample cohort that included 45 serum samples. Oxford University Press 2022-04-05 /pmc/articles/PMC9985154/ /pubmed/36879659 http://dx.doi.org/10.1093/nsr/nwac059 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Sun, Zhenyu Fu, Bin Wang, Guoli Zhang, Lei Xu, Ruofan Zhang, Ying Lu, Haojie High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis |
title | High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis |
title_full | High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis |
title_fullStr | High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis |
title_full_unstemmed | High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis |
title_short | High-throughput site-specific N-glycoproteomics reveals glyco-signatures for liver disease diagnosis |
title_sort | high-throughput site-specific n-glycoproteomics reveals glyco-signatures for liver disease diagnosis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9985154/ https://www.ncbi.nlm.nih.gov/pubmed/36879659 http://dx.doi.org/10.1093/nsr/nwac059 |
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