Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid
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. In this study, we performed single-cell RNA s...
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Published in | Frontiers in immunology Vol. 12; p. 783907 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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22.12.2021
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ISSN | 1664-3224 1664-3224 |
DOI | 10.3389/fimmu.2021.783907 |
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Abstract | 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.
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.
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).
Our results can provide a new idea for the diagnosis and treatment of keloid. |
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AbstractList | 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.BackgroundThe 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.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.MethodsIn 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.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).ResultsWe 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).Our results can provide a new idea for the diagnosis and treatment of keloid.ConclusionOur results can provide a new idea for the diagnosis and treatment of keloid. BackgroundThe 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.MethodsIn 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.ResultsWe 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).ConclusionOur results can provide a new idea for the diagnosis and treatment of keloid. 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. 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. 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). Our results can provide a new idea for the diagnosis and treatment of keloid. |
Author | Xiong, Wenwen Xie, Jiaheng Chen, Liang Shi, Jingping Zhang, Kai Cao, Yuan Wu, Dan Wang, Ming |
AuthorAffiliation | 5 Department of Dermatology, The First Affiliated Hospital of Zhengzhou University , Zhengzhou , China 4 Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School , Nanjing , China 1 Department of Burn and Plastic Surgery, The First Affiliated Hospital of Nanjing Medical University , Nanjing , China 2 Department of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University , Fuyang , China 3 Fourth School of Clinical Medicine, Nanjing Medical University , Nanjing , China 6 Pancreas Center, The First Affiliated Hospital with Nanjing Medical University, Nanjing , Jiangsu , China |
AuthorAffiliation_xml | – name: 4 Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School , Nanjing , China – name: 6 Pancreas Center, The First Affiliated Hospital with Nanjing Medical University, Nanjing , Jiangsu , China – name: 1 Department of Burn and Plastic Surgery, The First Affiliated Hospital of Nanjing Medical University , Nanjing , China – name: 2 Department of General Surgery, Fuyang Hospital Affiliated to Anhui Medical University , Fuyang , China – name: 3 Fourth School of Clinical Medicine, Nanjing Medical University , Nanjing , China – name: 5 Department of Dermatology, The First Affiliated Hospital of Zhengzhou University , Zhengzhou , China |
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Keywords | keloid single-cell sequencing weighted co-expression network analysis differential expression analysis Tenascin-c |
Language | English |
License | Copyright © 2021 Xie, Chen, Cao, Wu, Xiong, Zhang, Shi and Wang. 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. |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Allison Cowin, University of South Australia, Australia Reviewed by: Ujjal Bhawal, Nihon University, Japan; Xanthe Strudwick, University of South Australia, Australia This article was submitted to Inflammation, a section of the journal Frontiers in Immunology These authors share first authorship |
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Snippet | The pathophysiology of keloid formation is not yet understood, so the identification of biomarkers for kelod can be one step towards designing new... The pathophysiology of keloid formation is not yet understood, so the identification of biomarkers for kelod can be one step towards designing new targeting... BackgroundThe pathophysiology of keloid formation is not yet understood, so the identification of biomarkers for kelod can be one step towards designing new... |
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SubjectTerms | Biomarkers - analysis Cell Differentiation - genetics Datasets as Topic differential expression analysis Fibroblasts - immunology Gene Regulatory Networks Humans Immunology keloid Keloid - diagnosis Keloid - genetics Keloid - immunology Keloid - pathology Macrophages - immunology RNA-Seq Single-Cell Analysis single-cell sequencing Tenascin - analysis Tenascin - genetics Tenascin-c weighted co-expression network analysis |
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Title | Single-Cell Sequencing Analysis and Weighted Co-Expression Network Analysis Based on Public Databases Identified That TNC Is a Novel Biomarker for Keloid |
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