Mao J, Chen L, Qian S, Wang Y, Zhao B, Zhao Q, Lu B, Mao X, Zhai P, Zhang Y, Zhang L, Sun X. Transcriptome network analysis of inflammation and fibrosis in keloids.
J Dermatol Sci 2024;
113:62-73. [PMID:
38242738 DOI:
10.1016/j.jdermsci.2023.12.007]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 11/07/2023] [Accepted: 12/24/2023] [Indexed: 01/21/2024]
Abstract
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.
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