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Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer

Inter-tumor heterogeneity is a result of genomic, transcriptional, translational, and post-translational molecular features. To investigate the roles of protein glycosylation in the heterogeneity of high-grade serous ovarian carcinoma (HGSC), we perform mass spectrometry-based glycoproteomic charact...

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Autores principales: Pan, Jianbo, Hu, Yingwei, Sun, Shisheng, Chen, Lijun, Schnaubelt, Michael, Clark, David, Ao, Minghui, Zhang, Zhen, Chan, Daniel, Qian, Jiang, Zhang, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708455/
https://www.ncbi.nlm.nih.gov/pubmed/33262351
http://dx.doi.org/10.1038/s41467-020-19976-3
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author Pan, Jianbo
Hu, Yingwei
Sun, Shisheng
Chen, Lijun
Schnaubelt, Michael
Clark, David
Ao, Minghui
Zhang, Zhen
Chan, Daniel
Qian, Jiang
Zhang, Hui
author_facet Pan, Jianbo
Hu, Yingwei
Sun, Shisheng
Chen, Lijun
Schnaubelt, Michael
Clark, David
Ao, Minghui
Zhang, Zhen
Chan, Daniel
Qian, Jiang
Zhang, Hui
author_sort Pan, Jianbo
collection PubMed
description Inter-tumor heterogeneity is a result of genomic, transcriptional, translational, and post-translational molecular features. To investigate the roles of protein glycosylation in the heterogeneity of high-grade serous ovarian carcinoma (HGSC), we perform mass spectrometry-based glycoproteomic characterization of 119 TCGA HGSC tissues. Cluster analysis of intact glycoproteomic profiles delineates 3 major tumor clusters and 5 groups of intact glycopeptides. It also shows a strong relationship between N-glycan structures and tumor molecular subtypes, one example of which being the association of fucosylation with mesenchymal subtype. Further survival analysis reveals that intact glycopeptide signatures of mesenchymal subtype are associated with a poor clinical outcome of HGSC. In addition, we study the expression of mRNAs, proteins, glycosites, and intact glycopeptides, as well as the expression levels of glycosylation enzymes involved in glycoprotein biosynthesis pathways in each tumor. The results show that glycoprotein levels are mainly controlled by the expression of their individual proteins, and, furthermore, that the glycoprotein-modifying glycans correspond to the protein levels of glycosylation enzymes. The variation in glycan types further shows coordination to the tumor heterogeneity. Deeper understanding of the glycosylation process and glycosylation production in different subtypes of HGSC may provide important clues for precision medicine and tumor-targeted therapy.
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spelling pubmed-77084552020-12-03 Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer Pan, Jianbo Hu, Yingwei Sun, Shisheng Chen, Lijun Schnaubelt, Michael Clark, David Ao, Minghui Zhang, Zhen Chan, Daniel Qian, Jiang Zhang, Hui Nat Commun Article Inter-tumor heterogeneity is a result of genomic, transcriptional, translational, and post-translational molecular features. To investigate the roles of protein glycosylation in the heterogeneity of high-grade serous ovarian carcinoma (HGSC), we perform mass spectrometry-based glycoproteomic characterization of 119 TCGA HGSC tissues. Cluster analysis of intact glycoproteomic profiles delineates 3 major tumor clusters and 5 groups of intact glycopeptides. It also shows a strong relationship between N-glycan structures and tumor molecular subtypes, one example of which being the association of fucosylation with mesenchymal subtype. Further survival analysis reveals that intact glycopeptide signatures of mesenchymal subtype are associated with a poor clinical outcome of HGSC. In addition, we study the expression of mRNAs, proteins, glycosites, and intact glycopeptides, as well as the expression levels of glycosylation enzymes involved in glycoprotein biosynthesis pathways in each tumor. The results show that glycoprotein levels are mainly controlled by the expression of their individual proteins, and, furthermore, that the glycoprotein-modifying glycans correspond to the protein levels of glycosylation enzymes. The variation in glycan types further shows coordination to the tumor heterogeneity. Deeper understanding of the glycosylation process and glycosylation production in different subtypes of HGSC may provide important clues for precision medicine and tumor-targeted therapy. Nature Publishing Group UK 2020-12-01 /pmc/articles/PMC7708455/ /pubmed/33262351 http://dx.doi.org/10.1038/s41467-020-19976-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Pan, Jianbo
Hu, Yingwei
Sun, Shisheng
Chen, Lijun
Schnaubelt, Michael
Clark, David
Ao, Minghui
Zhang, Zhen
Chan, Daniel
Qian, Jiang
Zhang, Hui
Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer
title Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer
title_full Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer
title_fullStr Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer
title_full_unstemmed Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer
title_short Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer
title_sort glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708455/
https://www.ncbi.nlm.nih.gov/pubmed/33262351
http://dx.doi.org/10.1038/s41467-020-19976-3
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