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Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid
BACKGROUND: The pathophysiology of keloid formation is not yet understood, so the identification of biomarkers for kelod can be one step towards designing new targeting therapies which will improve outcomes for patients with keloids or at risk of developing keloids. METHODS: In this study, we perfor...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8728089/ https://www.ncbi.nlm.nih.gov/pubmed/35003102 http://dx.doi.org/10.3389/fimmu.2021.783907 |
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author | Xie, Jiaheng Chen, Liang Cao, Yuan Wu, Dan Xiong, Wenwen Zhang, Kai Shi, Jingping Wang, Ming |
author_facet | Xie, Jiaheng Chen, Liang Cao, Yuan Wu, Dan Xiong, Wenwen Zhang, Kai Shi, Jingping Wang, Ming |
author_sort | Xie, Jiaheng |
collection | PubMed |
description | BACKGROUND: The pathophysiology of keloid formation is not yet understood, so the identification of biomarkers for kelod can be one step towards designing new targeting therapies which will improve outcomes for patients with keloids or at risk of developing keloids. METHODS: In this study, we performed single-cell RNA sequencing analysis, weighted co-expression network analysis, and differential expression analysis of keloids based on public databases. And 3 RNA sequencing data from keloid patients in our center were used for validation. Besides, we performed QRT-PCR on keloid tissue and adjacent normal tissues from 16 patients for further verification. RESULTS: We identified the sensitive biomarker of keloid: Tenascin-C (TNC). Then, Pseudotime analysis found that the expression level of TNC decreased first, then stabilized and finally increased with fibroblast differentiation, suggesting that TNC may play an potential role in fibroblast differentiation. In addition, there were differences in the infiltration level of macrophages M0 between the TNC-high group and the TNC-low group. Macrophages M0 had a higher infiltration level in low TNC- group (P<0.05). CONCLUSION: Our results can provide a new idea for the diagnosis and treatment of keloid. |
format | Online Article Text |
id | pubmed-8728089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87280892022-01-06 Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid Xie, Jiaheng Chen, Liang Cao, Yuan Wu, Dan Xiong, Wenwen Zhang, Kai Shi, Jingping Wang, Ming Front Immunol Immunology BACKGROUND: The pathophysiology of keloid formation is not yet understood, so the identification of biomarkers for kelod can be one step towards designing new targeting therapies which will improve outcomes for patients with keloids or at risk of developing keloids. METHODS: In this study, we performed single-cell RNA sequencing analysis, weighted co-expression network analysis, and differential expression analysis of keloids based on public databases. And 3 RNA sequencing data from keloid patients in our center were used for validation. Besides, we performed QRT-PCR on keloid tissue and adjacent normal tissues from 16 patients for further verification. RESULTS: We identified the sensitive biomarker of keloid: Tenascin-C (TNC). Then, Pseudotime analysis found that the expression level of TNC decreased first, then stabilized and finally increased with fibroblast differentiation, suggesting that TNC may play an potential role in fibroblast differentiation. In addition, there were differences in the infiltration level of macrophages M0 between the TNC-high group and the TNC-low group. Macrophages M0 had a higher infiltration level in low TNC- group (P<0.05). CONCLUSION: Our results can provide a new idea for the diagnosis and treatment of keloid. Frontiers Media S.A. 2021-12-22 /pmc/articles/PMC8728089/ /pubmed/35003102 http://dx.doi.org/10.3389/fimmu.2021.783907 Text en Copyright © 2021 Xie, Chen, Cao, Wu, Xiong, Zhang, Shi and Wang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Xie, Jiaheng Chen, Liang Cao, Yuan Wu, Dan Xiong, Wenwen Zhang, Kai Shi, Jingping Wang, Ming Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid |
title | Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid |
title_full | Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid |
title_fullStr | Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid |
title_full_unstemmed | Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid |
title_short | Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid |
title_sort | single-cell sequencing analysis and weighted co-expression network analysis based on public databases identified that tnc is a novel biomarker for keloid |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8728089/ https://www.ncbi.nlm.nih.gov/pubmed/35003102 http://dx.doi.org/10.3389/fimmu.2021.783907 |
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