Key Takeaways & Executive Findings
- •• Single-cell transcriptomic analysis reveals significant alterations in cell composition in keloid tissues, with fibroblasts as the predominant cell type. • Pseudotime analysis indicates that keloid fibroblasts are at an early differentiation stage with high developmental potential. • HOXC4 is identified as a key diagnostic biomarker for keloids, showing high expression in keloid tissues and good diagnostic performance. • HOXC4 expression correlates with immune cell infiltration, suggesting its role in immune regulation within the keloid microenvironment.
Abstract
BACKGROUND: Keloid is a chronic fibrotic skin disorder driven by abnormal fibroblast activation and dysregulated immune responses. However, its underlying molecular mechanisms remain largely unclear. With the advancement of single-cell transcriptomic technologies, integrating public databases with systematic bioinformatics analyses offers new opportunities to identify diagnostic biomarkers and therapeutic targets. OBJECTIVE: To identify key biomarkers associated with fibroblast heterogeneity and immune cell interactions in the pathogenesis of keloids. METHODS: Single-cell transcriptomic dataset GSE181297 and bulk transcriptomic dataset GSE14572 were retrieved from the Gene Expression Omnibus (GEO) public database. Cell subtypes were annotated and analyzed for changes in cellular composition. Pseudotime analysis was applied to infer differentiation trajectories of various cell populations. Weighted gene co-expression network analysis and differential gene expression analysis were conducted to identify fibroblast-related differentially expressed genes. Functional enrichment analyses, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, were used to determine the involved biological processes and pathways. Protein-protein interaction network analysis, combined with three machine learning algorithms, was employed to identify hub genes. Receiver operating characteristic curve analysis was conducted to assess the diagnostic value of the candidate biomarkers. The expression patterns and correlation of hub genes in immune cells were evaluated. RESULTS AND CONCLUSION: Single-cell transcriptomic analysis revealed significantly increased proportions of endothelial cells, fibroblasts, smooth muscle cells, T cells, mast cells, macrophages, and lymphatic endothelial cells in keloid tissues, with fibroblasts being the predominant cell type. Pseudotime analysis showed that fibroblasts were mainly distributed in states 1, 2, and 3, at the initial stage of differentiation, with high developmental potential. Differential analysis identified 80 fibroblast-related differentially expressed genes, mainly enriched in regionalization, skeletal system morphogenesis, and embryonic skeletal development pathways. Integrating protein-protein interaction network and multiple machine learning models, HOXC4 was finally identified as a key biomarker. Receiver operating characteristic curve analysis indicated that HOXC4 had good diagnostic performance and was highly expressed in keloid tissues. Correlation analysis showed that HOXC4 was significantly positively correlated with resting natural killer cells, while negatively correlated with activated dendritic cells and activated natural killer cells. This study systematically revealed the heterogeneity of keloid fibroblasts and their association with the immune microenvironment. HOXC4 was identified as a key biomarker related to fibroblast functional status and immune regulation, providing a potential new target for early diagnosis and targeted therapy of keloids.
1. Introduction
Keloid is a fibroproliferative disease resulting from dysregulated wound healing, characterized by excessive deposition of extracellular matrix (including collagen) in the dermis, forming hard nodules that extend beyond the original wound boundaries [1]. It is most common in African American and Asian populations [2]. Although keloids are often considered a cosmetic issue, they cause pruritus and pain in and around the lesions, and affect the normal mobility of the affected area [3]. The annual intervention cost is as high as billions of dollars [4], severely reducing patients' quality of life and increasing psychological burden [5-6]. Moreover, keloids do not regress over time and can continue to grow for years [7-8]. Surgery is the main treatment for various types of keloids, but the recurrence rate is as high as 70% [9]. Currently, there is no single effective treatment for keloids, highlighting the insufficient understanding of the pathogenesis of keloids. Therefore, further research is urgently needed to better understand the molecular mechanisms underlying the abnormal activity of keloids, which may pave the way for identifying new targets for future diagnosis and treatment.
Keloid fibroblasts are the key cell type in keloid formation. Studies have found that the immune system plays an important role in the deposition of keloid fibroblasts [10], and alterations in immune-related factors are also crucial for the abnormal proliferation of fibroblasts and excessive deposition of extracellular matrix components. There is interaction between fibroblasts and various immune cells [11]. Previous studies have shown that signaling axes such as transforming growth factor beta, interleukin-6/signal transducer and activator of transcription 3, and C-C chemokine ligand 2/C-C chemokine receptor 2 play important roles in the 'crosstalk' between immune cells and fibroblasts [6]. In studying the mechanism of keloids, a new perspective suggests that immunity plays a vital role in preventing pathogen invasion, inducing inflammation, and regulating scar fibroblasts.
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Guo Tao, Liu Yuxin, Yan Meirong, Wang Xiaoni (2026). Keloid pathogenesis is correlated with fibroblast heterogeneity genes: single-cell transcriptomic analysis based on GEO database. Chinese Journal of Tissue Engineering Research. https://doi.org/10.12307/2026.21308
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Frequently Asked Questions
What is the main objective of this study?
The main objective is to identify key biomarkers associated with fibroblast heterogeneity and immune cell interactions in the pathogenesis of keloids using single-cell transcriptomic analysis.
What datasets were used in this study?
The study used single-cell transcriptomic dataset GSE181297 and bulk transcriptomic dataset GSE14572 from the Gene Expression Omnibus (GEO) public database.
What is the key finding of this study?
The key finding is that HOXC4 is identified as a potential diagnostic biomarker for keloids, showing high expression in keloid tissues and correlation with immune cell infiltration.
How was HOXC4 identified as a key biomarker?
HOXC4 was identified through differential expression analysis, weighted gene co-expression network analysis, protein-protein interaction network, and three machine learning algorithms, followed by receiver operating characteristic curve analysis to evaluate its diagnostic value.
What is the clinical significance of this study?
The study provides a potential new target for early diagnosis and targeted therapy of keloids, which may help improve treatment outcomes and reduce recurrence rates.
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