Increased expression of bone/cartilage-associated genes and core transcription factors in keloids by RNA sequencing

Single-cell transcriptomics analysis of proliferative diabetic retinopathy fibrovascular membranes reveals AEBP1 as fibrogenesis modulator

The management of preretinal fibrovascular membranes, a devastating complication of advanced diabetic retinopathy (DR), remains challenging. We characterized the molecular profile of cell populations in these fibrovascular membranes to identify potentially new therapeutic targets. Preretinal fibrovascular membranes were surgically removed from patients and submitted for single-cell RNA-Seq (scRNA-Seq). Differential gene expression was implemented to define the transcriptomics profile of these cells and revealed the presence of endothelial, inflammatory, and stromal cells. Endothelial cell reclustering identified subclusters characterized by noncanonical transcriptomics profile and active angiogenesis. Deeper investigation of the inflammatory cells showed a subcluster of macrophages expressing proangiogenic cytokines, presumably contributing to angiogenesis. The stromal cell cluster included a pericyte-myofibroblast transdifferentiating subcluster, indicating the involvement of pericytes in fibrogenesis. Differentially expressed gene analysis showed that Adipocyte Enhancer-binding Protein 1, AEBP1, was significantly upregulated in myofibroblast clusters, suggesting that this molecule may have a role in transformation. Cell culture experiments with human retinal pericytes (HRP) in high-glucose condition confirmed the molecular transformation of pericytes toward myofibroblastic lineage. AEBP1 siRNA transfection in HRP reduced the expression of profibrotic markers in high glucose. In conclusion, AEBP1 signaling modulates pericyte-myofibroblast transformation, suggesting that targeting AEBP1 could prevent scar tissue formation in advanced DR.

Defining a Unique Gene Expression Profile in Mature and Developing Keloids

Keloids are benign, fibroproliferative dermal tumors that typically form owing to abnormal wound healing. The current standard of care is generally ineffective and does not prevent recurrence. To characterize keloid scars and better understand the mechanism of their formation, we performed transcriptomic profiling of keloid biopsies from a total of 25 subjects of diverse racial and ethnic origins, 15 of whom provided a paired nonlesional sample, a longitudinal sample, or both. The transcriptomic signature of nonlesional skin biopsies from subjects with keloids resembled that of control skin at baseline but shifted to closely match that of keloid skin after dermal trauma. Peripheral keloid skin and rebiopsied surrounding normal skin both showed upregulation of epithelial-mesenchymal transition markers, extracellular matrix organization, and collagen genes. These keloid signatures strongly overlapped those from healthy wound healing studies, usually with greater perturbations, reinforcing our understanding of keloids as dysregulated and exuberant wound healing. In addition, 219 genes uniquely regulated in keloids but not in normal injured or uninjured skin were also identified. This study provides insights into mature and developing keloid signatures that can act as a basis for further validation and target identification in the search for transformative keloid treatments.

Identification and characterization of bone/cartilage-associated signatures in common fibrotic skin diseases

Background: Fibrotic skin diseases are characterized by excessive accumulation of the extracellular matrix (ECM) and activation of fibroblasts, leading to a global healthcare burden. However, effective treatments of fibrotic skin diseases remain limited, and their pathological mechanisms require further investigation. This study aims to investigate the common biomarkers and therapeutic targets in two major fibrotic skin diseases, namely, keloid and systemic sclerosis (SSc), by bioinformatics analysis.

Methods: The keloid (GSE92566) and SSc (GSE95065) datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, followed by functional enrichment analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We then constructed a protein–protein interaction (PPI) network for the identification of hub genes. We explored the possibility of further functional enrichment analysis of hub genes on the Metascape, GeneMANIA, and TissueNexus platforms. Transcription factor (TF)–hub gene and miRNA–hub gene networks were established using NetworkAnalyst. We fixed GSE90051 and GSE76855 as the external validation datasets. Student’s t-test and receiver operating characteristic (ROC) curve were used for candidate hub gene validation. Hub gene expression was assessed in vitro by quantitative real-time PCR.

Results: A total of 157 overlapping DEGs (ODEGs) were retrieved from the GSE92566 and GSE95065 datasets, and five hub genes (COL11A1, COL5A2, ASPN, COL10A1, and COMP) were identified and validated. Functional studies revealed that hub genes were predominantly enriched in bone/cartilage-related and collagen-related processes. FOXC1 and miR-335-5p were predicted to be master regulators at both transcriptional and post‐transcriptional levels.

Conclusion: COL11A1, COL5A2, ASPN, COL10A1, and COMP may help understand the pathological mechanism of the major fibrotic skin diseases; moreover, FOXC1 and miR-355-5p could build a regulatory network in keloid and SSc.