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 inFrontiers in immunology Vol. 12; p. 783907
Main Authors Xie, Jiaheng, Chen, Liang, Cao, Yuan, Wu, Dan, Xiong, Wenwen, Zhang, Kai, Shi, Jingping, Wang, Ming
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 22.12.2021
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Online AccessGet full text
ISSN1664-3224
1664-3224
DOI10.3389/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.
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
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Keywords keloid
single-cell sequencing
weighted co-expression network analysis
differential expression analysis
Tenascin-c
Language English
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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
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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
URI https://www.ncbi.nlm.nih.gov/pubmed/35003102
https://www.proquest.com/docview/2618513973
https://pubmed.ncbi.nlm.nih.gov/PMC8728089
https://doaj.org/article/b7bb54fbecf74900a97d7eb84d1abab2
Volume 12
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