瘢痕疙瘩炎症和纤维化的转录组网络分析

IF 4.6
Jiayi Mao , Lu Chen , Shutong Qian , Yuhuan Wang , Binfan Zhao , Qiuyu Zhao , Bolun Lu , Xiyuan Mao , Peisong Zhai , Yuguang Zhang , Liucheng Zhang , Xiaoming Sun
{"title":"瘢痕疙瘩炎症和纤维化的转录组网络分析","authors":"Jiayi Mao ,&nbsp;Lu Chen ,&nbsp;Shutong Qian ,&nbsp;Yuhuan Wang ,&nbsp;Binfan Zhao ,&nbsp;Qiuyu Zhao ,&nbsp;Bolun Lu ,&nbsp;Xiyuan Mao ,&nbsp;Peisong Zhai ,&nbsp;Yuguang Zhang ,&nbsp;Liucheng Zhang ,&nbsp;Xiaoming Sun","doi":"10.1016/j.jdermsci.2023.12.007","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Keloid<span> (KL) is a common benign skin tumor. KL is typically characterized by significant fibrosis and an intensive inflammatory response. Therefore, a comprehensive understanding of the interactions between cellular inflammation and fibrotic cells is essential to elucidate the mechanisms driving the progression of KL and to develop therapeutics.</span></p></div><div><h3>Objective</h3><p>Investigate the transcriptome landscape of inflammation and fibrosis in keloid scars.</p></div><div><h3>Methods</h3><p><span>In this paper, we performed transcriptome sequencing and microRNA (miRNA) sequencing on unselected live cells from six human keloid tissues and normal skin tissues to elucidate a comprehensive transcriptome landscape. In addition, we used single-cell </span>RNA sequencing (scRNA-seq) analysis to analyze intercellular communication networks and enrich fibroblast populations in two additional keloid and normal skin samples to study fibroblast diversity.</p></div><div><h3>Results</h3><p>By RNA sequencing and a miRNA-mRNA-PPI network analysis, we identified miR-615–5p and miR-122b-3p as possible miRNAs associated with keloids, as they differed most significantly in keloids. Similarly, COL3A1, COL1A2, THBS2, TNC, IGTA, THBS4, TGFB3 as genes with significant differences in keloid may be associated with keloid development. Using single-cell RNA sequencing data from 24,086 cells collected from normal or keloid, we report reconstructed intercellular signaling network analysis and aggregation to modules associated with specific cell subpopulations at the cellular level for keloid alterations.</p></div><div><h3>Conclusions</h3><p>Our multitranscriptomic dataset delineates inflammatory and fibro heterogeneity of human keloids, underlining the importance of intercellular crosstalk between inflammatory cells and fibro cells and revealing potential therapeutic targets.</p></div>","PeriodicalId":94076,"journal":{"name":"Journal of dermatological science","volume":"113 2","pages":"Pages 62-73"},"PeriodicalIF":4.6000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Transcriptome network analysis of inflammation and fibrosis in keloids\",\"authors\":\"Jiayi Mao ,&nbsp;Lu Chen ,&nbsp;Shutong Qian ,&nbsp;Yuhuan Wang ,&nbsp;Binfan Zhao ,&nbsp;Qiuyu Zhao ,&nbsp;Bolun Lu ,&nbsp;Xiyuan Mao ,&nbsp;Peisong Zhai ,&nbsp;Yuguang Zhang ,&nbsp;Liucheng Zhang ,&nbsp;Xiaoming Sun\",\"doi\":\"10.1016/j.jdermsci.2023.12.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Keloid<span> (KL) is a common benign skin tumor. KL is typically characterized by significant fibrosis and an intensive inflammatory response. Therefore, a comprehensive understanding of the interactions between cellular inflammation and fibrotic cells is essential to elucidate the mechanisms driving the progression of KL and to develop therapeutics.</span></p></div><div><h3>Objective</h3><p>Investigate the transcriptome landscape of inflammation and fibrosis in keloid scars.</p></div><div><h3>Methods</h3><p><span>In this paper, we performed transcriptome sequencing and microRNA (miRNA) sequencing on unselected live cells from six human keloid tissues and normal skin tissues to elucidate a comprehensive transcriptome landscape. In addition, we used single-cell </span>RNA sequencing (scRNA-seq) analysis to analyze intercellular communication networks and enrich fibroblast populations in two additional keloid and normal skin samples to study fibroblast diversity.</p></div><div><h3>Results</h3><p>By RNA sequencing and a miRNA-mRNA-PPI network analysis, we identified miR-615–5p and miR-122b-3p as possible miRNAs associated with keloids, as they differed most significantly in keloids. Similarly, COL3A1, COL1A2, THBS2, TNC, IGTA, THBS4, TGFB3 as genes with significant differences in keloid may be associated with keloid development. Using single-cell RNA sequencing data from 24,086 cells collected from normal or keloid, we report reconstructed intercellular signaling network analysis and aggregation to modules associated with specific cell subpopulations at the cellular level for keloid alterations.</p></div><div><h3>Conclusions</h3><p>Our multitranscriptomic dataset delineates inflammatory and fibro heterogeneity of human keloids, underlining the importance of intercellular crosstalk between inflammatory cells and fibro cells and revealing potential therapeutic targets.</p></div>\",\"PeriodicalId\":94076,\"journal\":{\"name\":\"Journal of dermatological science\",\"volume\":\"113 2\",\"pages\":\"Pages 62-73\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of dermatological science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0923181123002700\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of dermatological science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0923181123002700","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

背景瘢痕疙瘩(KL)是一种常见的良性皮肤肿瘤。瘢痕疙瘩的典型特征是明显的纤维化和密集的炎症反应。因此,全面了解细胞炎症和纤维化细胞之间的相互作用对于阐明KL进展的驱动机制和开发治疗方法至关重要。方法本文中,我们对来自6个人类瘢痕疙瘩组织和正常皮肤组织的未选择活细胞进行了转录组测序和microRNA(miRNA)测序,以阐明全面的转录组图谱。结果通过RNA测序和miRNA-mRNA-PPI网络分析,我们发现miR-615-5p和miR-122b-3p可能与瘢痕疙瘩有关,因为它们在瘢痕疙瘩中差异最大。同样,在瘢痕疙瘩中差异显著的 COL3A1、COL1A2、THBS2、TNC、IGTA、THBS4、TGFB3 基因也可能与瘢痕疙瘩的发生有关。结论我们的多转录组数据集描述了人类瘢痕疙瘩的炎症和纤维异质性,强调了炎症细胞和纤维细胞之间细胞间串联的重要性,并揭示了潜在的治疗靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transcriptome network analysis of inflammation and fibrosis in keloids

Background

Keloid (KL) is a common benign skin tumor. KL is typically characterized by significant fibrosis and an intensive inflammatory response. Therefore, a comprehensive understanding of the interactions between cellular inflammation and fibrotic cells is essential to elucidate the mechanisms driving the progression of KL and to develop therapeutics.

Objective

Investigate the transcriptome landscape of inflammation and fibrosis in keloid scars.

Methods

In this paper, we performed transcriptome sequencing and microRNA (miRNA) sequencing on unselected live cells from six human keloid tissues and normal skin tissues to elucidate a comprehensive transcriptome landscape. In addition, we used single-cell RNA sequencing (scRNA-seq) analysis to analyze intercellular communication networks and enrich fibroblast populations in two additional keloid and normal skin samples to study fibroblast diversity.

Results

By RNA sequencing and a miRNA-mRNA-PPI network analysis, we identified miR-615–5p and miR-122b-3p as possible miRNAs associated with keloids, as they differed most significantly in keloids. Similarly, COL3A1, COL1A2, THBS2, TNC, IGTA, THBS4, TGFB3 as genes with significant differences in keloid may be associated with keloid development. Using single-cell RNA sequencing data from 24,086 cells collected from normal or keloid, we report reconstructed intercellular signaling network analysis and aggregation to modules associated with specific cell subpopulations at the cellular level for keloid alterations.

Conclusions

Our multitranscriptomic dataset delineates inflammatory and fibro heterogeneity of human keloids, underlining the importance of intercellular crosstalk between inflammatory cells and fibro cells and revealing potential therapeutic targets.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
7.60
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信