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<p>Keloids are benign fibroproliferative skin lesions characterized by excessive collagen deposition and growth beyond the original wound margins. However, the cellular heterogeneity and molecular mechanisms underlying keloid pathogenesis remain incompletely understood. Publicly available single-cell RNA sequencing (scRNA-seq) data from keloid tissues of eight patients were obtained from the NCBI Gene Expression Omnibus (GEO) database. High-dimensional weighted gene co-expression network analysis (hdWGCNA) was performed to identify disease-associated gene modules. Mendelian randomization (MR) analysis was performed using summary statistics from BioBank Japan to evaluate potential associations between gene expression and keloid susceptibility. ATAC-seq data were used to assess chromatin accessibility, and SCENIC analysis was performed to infer transcription factor regulon activity. Correlation analysis was then used to assess potential associations between candidate transcription factors and target genes. We analyzed 73,790 cells and identified nine major cell types. Fibroblasts showed substantial heterogeneity and were further classified into 6 subpopulations. Trajectory analysis suggested a differentiation continuum among disease-associated fibroblasts, and cell-cell communication analysis indicated that MSC-like fibroblasts may function as a signaling hub. hdWGCNA identified a turquoise co-expression module significantly enriched in MSC-like fibroblasts. MR analysis highlighted CLEC2B, MGST3, and SFRP2 as candidate genes potentially associated with keloids, and qRT-PCR validated their differential mRNA expression between normal dermal and keloid fibroblasts. ATAC-seq analysis identified 4,607 differentially accessible chromatin peaks. Integrated motif enrichment and SCENIC analyses identified CREB3L1 and ZEB1 as candidate transcription factors. Correlation analysis further suggested potential regulatory relationships between these transcription factors and the candidate genes. This study provides an integrative multi-omics characterization of cellular heterogeneity in keloids. It identifies CLEC2B, MGST3, and SFRP2 as key candidate genes, as well as CREB3L1 and ZEB1 as candidate transcription factors potentially involved in keloid pathogenesis. These findings improve our understanding of keloid biology and may provide a basis for future therapeutic research.</p>

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Integrated multi-omics analysis reveals key molecular mechanisms underlying fibroproliferation and immune dysregulation in keloids

  • 期刊论文

  • 发表日期：

    2026年7月7日

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  • Qianqian Luo,
  • Xianwei Zhu,
  • Huihui Zhou,
  • Chunlei Wang,
  • Yongtao Su

摘要

Keloids are benign fibroproliferative skin lesions characterized by excessive collagen deposition and growth beyond the original wound margins. However, the cellular heterogeneity and molecular mechanisms underlying keloid pathogenesis remain incompletely understood. Publicly available single-cell RNA sequencing (scRNA-seq) data from keloid tissues of eight patients were obtained from the NCBI Gene Expression Omnibus (GEO) database. High-dimensional weighted gene co-expression network analysis (hdWGCNA) was performed to identify disease-associated gene modules. Mendelian randomization (MR) analysis was performed using summary statistics from BioBank Japan to evaluate potential associations between gene expression and keloid susceptibility. ATAC-seq data were used to assess chromatin accessibility, and SCENIC analysis was performed to infer transcription factor regulon activity. Correlation analysis was then used to assess potential associations between candidate transcription factors and target genes. We analyzed 73,790 cells and identified nine major cell types. Fibroblasts showed substantial heterogeneity and were further classified into 6 subpopulations. Trajectory analysis suggested a differentiation continuum among disease-associated fibroblasts, and cell-cell communication analysis indicated that MSC-like fibroblasts may function as a signaling hub. hdWGCNA identified a turquoise co-expression module significantly enriched in MSC-like fibroblasts. MR analysis highlighted CLEC2B, MGST3, and SFRP2 as candidate genes potentially associated with keloids, and qRT-PCR validated their differential mRNA expression between normal dermal and keloid fibroblasts. ATAC-seq analysis identified 4,607 differentially accessible chromatin peaks. Integrated motif enrichment and SCENIC analyses identified CREB3L1 and ZEB1 as candidate transcription factors. Correlation analysis further suggested potential regulatory relationships between these transcription factors and the candidate genes. This study provides an integrative multi-omics characterization of cellular heterogeneity in keloids. It identifies CLEC2B, MGST3, and SFRP2 as key candidate genes, as well as CREB3L1 and ZEB1 as candidate transcription factors potentially involved in keloid pathogenesis. These findings improve our understanding of keloid biology and may provide a basis for future therapeutic research.