MEG3 shuttled by exosomes released from human bone marrow mesenchymal stem cells promotes TP53 stability to regulate MCM5 transcription in keloid fibroblasts.

BACKGROUND: Despite the interest in mesenchymal stem cells (MSC), their potential to treat abnormal scarring, especially keloids, is yet to be described. The present study aimed to investigate the therapeutic potential of exosomes derived from human bone marrow MSCs (hBMSC-Exos) in alleviating keloid formation. METHODS: Exosomes were isolated from hBMSC, and keloid fibroblasts (KFs) were treated with hBMSC-Exos. Cell counting kit-8, wound healing, transwell invasion, immunofluorescence, and western blot assays were conducted to study the malignant phenotype of KFs. Mice were induced with keloids and treated with hBMSC-Exos. The effect of hBMSC-Exos on keloid formation in vivo was evaluated by hematoxylin and eosin staining, Masson staining, immunohistochemistry, and western blotting. The GSE182192 dataset was screened for differentially expressed long non-coding RNA during keloid formation. Next, maternally expressed gene 3 (MEG3) was knocked down in hBMSC to obtain hBMSC-Exossh-MEG3. The molecular mechanism of MEG3 was investigated by bioinformatic screening, and the relationship between MEG3 and TP53 or MCM5 was verified. RESULTS: hBMSC-Exos inhibited the malignant proliferation, migration, and invasion of KFs at same time as promoting their apoptosis, Moreover, hBMSC-Exos reduced the expression of fibrosis- and collagen-related proteins in the cells and the formation of keloids caused by KFs. The reduction in MEG3 enrichment in hBMSC-Exos weakened the inhibitory effect of hBMSC-Exos on KF activity. hBMSC-Exos delivered MEG3 to promote MCM5 transcription by TP53 in KFs. Overexpression of MCM5 in KFs reversed the effects of hBMSC-Exossh-MEG3, leading to reduced KF activity. CONCLUSIONS: hBMSC-Exos delivered MEG3 to promote the protein stability of TP53, thereby activating MCM5 and promoting KF activity.

miRSNP rs188493331: A key player in genetic control of microRNA-induced pathway activation in hypertrophic scars and keloids.

BACKGROUND: Our study aims to delineate the miRSNP-microRNA-gene-pathway interactions in the context of hypertrophic scars (HS) and keloids. MATERIALS AND METHODS: We performed a computational biology study involving differential expression analysis to identify genes and their mRNAs in HS and keloid tissues compared to normal skin, identifying key hub genes and enriching their functional roles, comprehensively analyzing microRNA-target genes and related signaling pathways through bioinformatics, identifying MiRSNPs, and constructing a pathway-based network to illustrate miRSNP-miRNA-gene-signaling pathway interactions. RESULTS: Our results revealed a total of 429 hub genes, with a strong enrichment in signaling pathways related to proteoglycans in cancer, focal adhesion, TGF-ß, PI3K/Akt, and EGFR tyrosine kinase inhibitor resistance. Particularly noteworthy was the substantial crosstalk between the focal adhesion and PI3K/Akt signaling pathways, making them more susceptible to regulation by microRNAs. We also identified specific miRNAs, including miRNA-1279, miRNA-429, and miRNA-302e, which harbored multiple SNP loci, with miRSNPs rs188493331 and rs78979933 exerting control over a significant number of miRNA target genes. Furthermore, we observed that miRSNP rs188493331 shared a location with microRNA302e, microRNA202a-3p, and microRNA20b-5p, and these three microRNAs collectively targeted the gene LAMA3, which is integral to the focal adhesion signaling pathway. CONCLUSIONS: The study successfully unveils the complex interactions between miRSNPs, miRNAs, genes, and signaling pathways, shedding light on the genetic factors contributing to HS and keloid formation.

Identification of inflammation-related biomarkers in keloids.

Background: The relationship between inflammation-related genes (IRGs) and keloid disease (KD) is currently unclear. The aim of this study was to identify a new set of inflammation-related biomarkers in KD. Methods: GSE145725 and GSE7890 datasets were used in this study. A list of 3026 IRGs was obtained from the Molecular Signatures Database. Differentially expressed inflammation-related genes (DEGs) were obtained by taking the intersection of DEGs between KD and control samples and the list of IRGs. Candidate genes were selected using least absolute shrinkage and selection operator (LASSO) regression analysis. Candidate genes with consistent expression differences between KD and control in both GSE145725 and GSE7890 datasets were screened as biomarkers. An alignment diagram was constructed and validated, and in silico immune infiltration analysis and drug prediction were performed. Finally, RT-qPCR was performed on KD samples to analyze the expression of the identified biomarkers. Results: A total of 889 DEGs were identified from the GSE145725 dataset, 169 of which were IRGs. Three candidate genes (TRIM32, LPAR1 and FOXF1) were identified by the LASSO regression analysis, and expression validation analysis suggested that FOXF1 and LPAR1 were down-regulated in KD samples and TRIM32 was up-regulated. All three candidate genes had consistent changes in expression in both the GSE145725 and GSE7890 datasets. An alignment diagram was constructed to predict KD. Effector memory CD4 T cells, T follicular helper cell, Myeloid derived suppressor cell, activated dendritic cell, Immature dendritic cell and Monocyte were differentially expressed between the KD and control group. Sixty-seven compounds that may act on FOXF1, 108 compounds that may act on LPAR1 and 56 compounds that may act on TRIM32 were predicted. Finally, RT-qPCR showed that the expression of LPAR1 was significantly lower in KD samples compared to normal samples whereas TRIM32 was significantly higher, while there was no difference in the expression of FOXF1. Conclusion: This study provides a new perspective to study the relationship between IRGs and KD.

Macrophage phenotype is determinant for fibrosis development in keloid disease.

Keloid refers to a fibroproliferative disorder characterized by an accumulation of extracellular matrix (ECM) components at the dermis level, overgrowth beyond initial wound, and formation of tumor-like nodule areas. Treating keloid is still an unmet clinical need and the lack of an efficient therapy is clearly related to limited knowledge about keloid etiology, despite the growing interest of the scientific community in this pathology. In past decades, keloids were often studied in vitro through the sole prism of fibroblasts considered as the major effector of ECM deposition. Nevertheless, development of keloids results from cross-interactions of keloid fibroblasts (KFs) and their surrounding microenvironment, including immune cells such as macrophages. Our study aimed to evaluate the effect of M1 and M2 monocyte-derived macrophages on KFs in vitro. We focused on the effects of the macrophage secretome on fibrosis-related criteria in KFs, including proliferation, migration, differentiation, and ECM synthesis. First, we demonstrated that M2-like macrophages enhanced the fibrogenic profile of KFs in culture. Then, we surprisingly founded that M1-like macrophages can have an anti-fibrogenic effect on KFs, even in a pro-fibrotic environment. These results demonstrate, for the first time, that M1 and M2 macrophage subsets differentially impact the fibrotic fate of KFs in vitro, and suggest that restoring the M1/M2 balance to favor M1 in keloids could be an efficient therapeutic lever to prevent or treat keloid fibrosis.

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.

Identification of novel biomarkers of ferroptosis involved in keloid based on bioinformatics analysis.

Keloid is a fibroproliferative disease of unknown aetiology, which has a significant impact the quality of life of patients. Ferroptosis plays an important role in the occurrence and development of fibrosis, but there is still a lack of research related to keloids. The objective of this work was to identify the hub genes related to ferroptosis in keloid to better understand the keloid process. The microarray data (GSE7890 GSE145725, and GSE44270) (23 keloid and 22 normal fibroblast) were analysed via the gene expression comprehensive database (GEO). Only GSE7890 met the FerrDB database. Cell cycle and pathway analysis were performed with gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed to differentially expressed genes (DEG). The differential genes were confirmed in other GEO datasets (GSE145725 and GSE44270), and multi-fibrosis-gene correlation analysed. To validate these hub genes, quantitative real-time PCR (qRT-PCR) was conducted. A total of 581 DEGs were screened, with 417 genes down-regulated and 164 genes up-regulated, with 11 ferroptosis genes significantly up-regulated in both keloid and normal tissue, and 6 genes are consistent with our findings and are associated with multiple fibrosis genes. The qRT-PCR results and tissues of normal skin and keloid agreed with our predictions. Our findings provide new evidence for the ferroptosis-related molecular pathways and biomarker of keloid.

Multi-omics analyses reveal bacteria and catalase associated with keloid disease.

BACKGROUND: The pathology of keloid and especially the roles of bacteria on it were not well understood. METHODS: In this study, multi-omics analyses including microbiome, metaproteomics, metabolomic, single-cell transcriptome and cell-derived xenograft (CDX) mice model were used to explore the roles of bacteria on keloid disease. FINDINGS: We found that the types of bacteria are significantly different between keloid and healthy skin. The 16S rRNA sequencing and metaproteomics showed that more catalase (CAT) negative bacteria, Clostridium and Roseburia existed in keloid compared with the adjacent healthy skin. In addition, protein mass spectrometry shows that CAT is one of the differentially expressed proteins (DEPs). Overexpression of CAT inhibited the proliferation, migration and invasion of keloid fibroblasts, and these characteristics were opposite when CAT was knocked down. Furthermore, the CDX model showed that Clostridium butyricum promote the growth of patient's keloid fibroblasts in BALB/c female nude mice, while CAT positive bacteria Bacillus subtilis inhibited it. Single-cell RNA sequencing verified that oxidative stress was up-regulated and CAT was down-regulated in mesenchymal-like fibroblasts of keloid. INTERPRETATION: In conclusion, our findings suggest that bacteria and CAT contribute to keloid disease. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Comprehensive modular analyses of scar subtypes illuminate underlying molecular mechanisms and potential therapeutic targets.

Pathological scarring resulting from traumas and wounds, such as hypertrophic scars and keloids, pose significant aesthetic, functional and psychological challenges. This study provides a comprehensive transcriptomic analysis of these conditions, aiming to illuminate underlying molecular mechanisms and potential therapeutic targets. We employed a co-expression and module analysis tool to identify significant gene clusters associated with distinct pathophysiological processes and mechanisms, notably lipid metabolism, sebum production, cellular energy metabolism and skin barrier function. This examination yielded critical insights into several skin conditions including folliculitis, skin fibrosis, fibrosarcoma and congenital ichthyosis. Particular attention was paid to Module Cluster (MCluster) 3, encompassing genes like BLK, TRPV1 and GABRD, all displaying high expression and potential implications in immune modulation. Preliminary immunohistochemistry validation supported these findings, showing elevated expression of these genes in non-fibrotic samples rich in immune activity. The complex interplay of different cell types in scar formation, such as fibroblasts, myofibroblasts, keratinocytes and mast cells, was also explored, revealing promising therapeutic strategies. This study underscores the promise of targeted gene therapy for pathological scars, paving the way for more personalised therapeutic approaches. The results necessitate further research to fully ascertain the roles of these identified genes and pathways in skin disease pathogenesis and potential therapeutics. Nonetheless, our work forms a strong foundation for a new era of personalised medicine for patients suffering from pathological scarring.

Non-coding RNAs in hypertrophic scars and keloids: Current research and clinical relevance: A review.

Hypertrophic scars (HS) and keloids (KD) are lesions that develop as a result of excessive fibroblast proliferation and collagen deposition in response to dermal injury, leading to dysregulation of the inflammatory, proliferative, and remodeling phases during wound healing. HS and KD affect up to 90 % of the population and are associated with lower quality of life, physical health, and mental status in patients. Efficient targeted treatment represents a significant challenge, primarily due to our limited understanding of their underlying pathogenesis. Non-coding RNAs (ncRNAs), which constitute a significant portion of the human transcriptome with minimal or no protein-coding capacity, have been implicated in various cellular physiologies and pathologies and may serve as diagnostic indicators or therapeutic targets. NcRNAs have been found to be aberrantly expressed and regulated in HS and KD. This review provides a summary of the expression profiles and molecular mechanisms of three common ncRNAs, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), in HS and KD. It also discusses their potential as biomarkers for the diagnosis and treatment of these diseases and provides novel insights into epigenetic-based diagnosis and treatment strategies for HS and KD.

The biomarkers associated with epithelial-mesenchymal transition in human keloids.

INTRODUCTION: A keloid is a type of benign fibrotic disease with similar features to malignancies, including anti-apoptosis, over-proliferation, and invasion. Epithelial-mesenchymal transition (EMT) is a crucial mechanism that regulates the metastatic behavior of tumors. Thus, identifying EMT biomarkers is paramount in comprehensively understanding keloid pathogenesis. METHODS: To identify the differentially expressed genes (DEGs) GSE92566 dataset, with 3 normal skin and 4 keloid tissues, was downloaded from GEO databases to identify the differentially expressed genes (DEGs). Further, EMT-related genes were downloaded from dbEMT 2.0 databases and intersected with GSE92566 DEGs to identify EMT-related-DEGs (ERDEGs). Subsequently, the ERDEGs were used for GO, KEGG, gene set enrichment analysis (GSEA), protein-protein interaction (PPI), and miRNAs-mRNAs network analysis. To predict small molecules for EMT inhibition, the ERDEGs were imported to cMAP databases, whereas hub genes were imported to DGidb databases. Finally, we carried out qRT-PCR and in vitro experiments to validate our findings. RESULTS: A total of 122 ERDEGs were identified, including 59 upregulated and 63 down-regulated genes. Moreover, enrichment analysis revealed that focal adhesion, AMPK signal pathway, Wnt signal pathway, and EMT biological process were significantly enriched. STRING databases and Cytoscape software were used to construct the PPI network and EMT-related hub genes. Further, 3 modules were explored from the PPI network using the Molecular Complex Detection (MCODE) plugin. In the Cytohubba plugin, 10 hub genes were explored, including FN1, EGF, SOX9, CDH2, PROM1, EPCAM, KRT19, ITGB1, CD24, and KRT18. These genes were then enriched for the focal adhesion pathway. We constructed a microRNA (miRNA)-mRNA network, which predicted hsa-miR-155-5p (8 edges), hsa-miR-124-3p (7 edges), hsa-miR-145-5p (5 edges), hsa-miR-20a-5p (5 edges) and hsa-let-7b-5p (4 edges) as the most connected miRNAs regulating EMT. Based on the ERDEGs and 10 hub genes mentioned above, ribavirin demonstrated high drug-targeting relevance. Subsequently, qRT-PCR confirmed that the expression of FN1, ITGB1, CDH2, and EPCAM corroborated with previous findings. qRT-PCR also showed that the expression levels of hsa-miR-124-3p and hsa-miR-145-5p were significantly lower in keloids and hsa-miR-155-5p was upregulated in keloids. Finally, by treating human keloid fibroblasts (HKFs) with ribavirin in vitro, we confirmed that ribavirin could inhibit HKFs proliferation and EMT. CONCLUSION: In summary, this work provides novel EMT biomarkers in keloids and predicts new small target molecules for keloid therapy. Our findings improve the understanding of keloid pathogenesis, providing new treatment options.

Weighted gene co-expression network analysis and machine learning identified the lipid metabolism-related gene LGMN as a novel biomarker for keloid.

The aetiology of keloid formation remains unclear, and existing treatment modalities have not definitively established a successful approach. Therefore, it is necessary to identify reliable and novel keloid biomarkers as potential targets for therapeutic interventions. In this study, we performed differential expression analysis and functional enrichment analysis on the keloid related datasets, and found that multiple metabolism-related pathways were associated with keloid formation. Subsequently, the differentially expressed genes (DEGs) were intersected with the results of weighted gene co-expression network analysis (WGCNA) and the lipid metabolism-related genes (LMGs). Then, three learning machine algorithms (SVM-RFE, LASSO and Random Forest) together identified legumain (LGMN) as the most critical LMGs. LGMN was overexpressed in keloid and had a high diagnostic performance. The protein-protein interaction (PPI) network related to LGMN was constructed by GeneMANIA database. Functional analysis of indicated PPI network was involved in multiple immune response-related biological processes. Furthermore, immune infiltration analysis was conducted using the CIBERSORT method. M2-type macrophages were highly infiltrated in keloid tissues and were found to be significantly and positively correlated with LGMN expression. Gene set variation analysis (GSVA) indicated that LGMN may be related to promoting fibroblast proliferation and inhibiting their apoptosis. Moreover, eight potential drug candidates for keloid treatment were predicted by the DSigDB database. Western blot, qRT-PCR and immunohistochemistry staining results confirmed that LGMN was highly expressed in keloid. Collectively, our findings may identify a new biomarker and therapeutic target for keloid and contribute to the understanding of the potential pathogenesis of keloid.

The HEDGEHOG-GLI1 pathway is important for fibroproliferative properties in keloids and as a candidate therapeutic target.

Keloids are benign fibroproliferative skin tumors caused by aberrant wound healing that can negatively impact patient quality of life. The lack of animal models has limited research on pathogenesis or developing effective treatments, and the etiology of keloids remains unknown. Here, we found that the characteristics of stem-like cells from keloid lesions and the surrounding dermis differ from those of normal skin. Furthermore, the HEDGEHOG (HH) signal and its downstream transcription factor GLI1 were upregulated in keloid patient-derived stem-like cells. Inhibition of the HH-GLI1 pathway reduced the expression of genes involved in keloids and fibrosis-inducing cytokines, including osteopontin. Moreover, the HH signal inhibitor vismodegib reduced keloid reconstituted tumor size and keloid-related gene expression in nude mice and the collagen bundle and expression of cytokines characteristic for keloids in ex vivo culture of keloid tissues. These results implicate the HH-GLI1 pathway in keloid pathogenesis and suggest therapeutic targets of keloids.

Inhibition of Proliferation, Migration, and Invasion of Keloid Fibroblasts By miR-183-5p Through Downregulating EGR1 / Inhibición de la Proliferación, Migración e Invasión de Fibroblastos Queloides por miR-183-5p Mediante la Regulación Negativa de EGR1

SUMMARY: Keloid scar is a unique benign fibroproliferative tumor of the human skin. Previously, it was reported that early growth response 1 (EGR1), a transcription factor, promotes keloid fibrosis; however, the mechanism by which EGR1 modulates keloid formation was not elaborated. In this research, the specific function and the microRNA (miRNA) regulatory network of EGR1 in keloids was examined. Keloid fibroblasts (KFs) were transfected with EGR1-small interfering RNA (siEGR1), EGR1-overexpression plasmid (pcDNA3.1-EGR1), and microRNA (miR-183-5p)-mimics to regulate the expression of EGR1 and miR-183-5p. The study employed dual-luciferase reporter assays to explore the targeting regulation of miR-183-5p on EGR1. Additionally, Western blotting, flow cytometry, qRT-PCR, cell count kit-8 (CCK-8), transwell, and wound healing assays, and RNA sequencing were conducted. EGR1 was upregulated in KFs, and EGR1 silencing diminished proliferation, fibrosis, migration, invasion, and apoptosis of cells. In KFs, the expression of miR- 183-5p was reduced, leading to the inhibition of cell proliferation, migration, and invasion. Conversely, it enhanced apoptosis. By targeting EGR1, miR-183-5p partially counteracted the impact of EGR1 on migration, invasion, and fibrosis in KFs. The findings imply that miR-183-5p suppresses keloid formation by targeting EGR1. As a result, EGR1 holds promise as a potential therapeutic target for preventing and treating keloids.

La cicatriz queloide es un tumor fibroproliferativo benigno único de la piel humana. Anteriormente, se informó que la respuesta de crecimiento temprano 1 (EGR1), un factor de transcripción, promueve la fibrosis queloide; sin embargo, no se explicó el mecanismo por el cual EGR1 modula la formación de queloides. En esta investigación, se examinó la función específica y la red reguladora de microARN (miARN) de EGR1 en queloides. Se transfectaron fibroblastos queloides (KF) con ARN de interferencia pequeño de EGR1 (siEGR1), plásmido de sobreexpresión de EGR1 (pcDNA3.1-EGR1) y miméticos de microARN (miR-183-5p) para regular la expresión de EGR1 y miR-183. -5p. El estudio empleó ensayos de indicador de luciferasa dual para explorar la regulación dirigida de miR-183-5p en EGR1. Además, se realizaron pruebas de transferencia Western, citometría de flujo, qRT-PCR, kit de recuento celular-8 (CCK-8), transwell y curación de heridas, y secuenciación de ARN. EGR1 estaba regulado positivamente en KF, y el silenciamiento de EGR1 disminuyó la proliferación, fibrosis, migración, invasión y apoptosis de las células. En KF, la expresión de miR- 183-5p se redujo, lo que llevó a la inhibición de la proliferación, migración e invasión celular. Por el contrario, mejoró la apoptosis. Al apuntar a EGR1, miR-183-5p contrarrestó parcialmente el impacto de EGR1 en la migración, invasión y fibrosis en KF. Los hallazgos implican que miR-183-5p suprime la formación de queloides al apuntar a EGR1. Como resultado, EGR1 es prometedor como objetivo terapéutico potencial para prevenir y tratar los queloides.

Inhibition of keloid by 32P isotope radiotherapy through suppressing TGF-ß/Smad signaling pathway.

BACKGROUND: Keloid seriously affects the appearance, and is accompanied by some symptoms including pain, burning, itching. Radioactive nuclides such as 32P have been proved to be effective in inhibiting the formation of keloid, but the mechanism remains unclear. METHODS: The keloid animal model was established through keloid tissues implantation. Hematoxylin-Eosin (HE) and Masson staining were performed to investigate histological changes and collagen deposition. The mRNA and protein expression were assessed using RT-PCR and western blotting, respectively. Cell apoptosis and cycle were evaluated through flow cytometry. RESULTS: Both 32P isotope injection and skin path significantly reduced the size of keloid, and inhibited TGF-ß/Smad signaling pathway. SRI-011381, the agonist of TGF-ß/Smad signaling pathway, markedly reversed the influence of 32P isotope on cell proliferation, cell apoptosis, cell cycle of LNCaP cells and TGF-ß/Smad signaling pathway. CONCLUSIONS: 32P isotope injection and skin path greatly reduced the size of keloid, and the TGF-ß/Smad signaling pathway was remarkably inhibited by 32P isotope treatment. The regulation of dermal fibroblast by 32P isotope was reversed by SRI-011381. 32P isotope might inhibit keloid through suppressing TGF-ß/Smad signaling pathway. Our study provides a novel therapeutic strategy for the treatment of keloid.

The upregulation of circFoxp1 influences keloid by promoting cell proliferation.

As a result of abnormal wound healing in susceptible individuals, keloids are characterized by hyperproliferation of fibroblasts and excessive deposition of the extracellular matrix (ECM). Current surgical and therapeutic modalities provide limited satisfactory results. Circular ribonucleic acids (circRNAs) play a crucial role in the pathogenesis of various fibrotic diseases, but the potential biological function and expression profile of circRNAs in keloid formation remain unknown. In this study, we explored the function of circFoxp1 on keloid formation. Methods: Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) results revealed that circFoxp1 expression was higher in the keloid tissues. Furthermore, RNA-fluorescence in situ hybridization (RNA-FISH) and RNAscope illustrated that circFoxp1 was present in the cytoplasm. Subsequent cellular experiments demonstrated that circFoxp1 overexpression enhanced proliferation, migration, and ECM deposition. In addition, apoptosis was inhibited. Cell proliferation, inflammatory response, and oxidative phosphorylation of fibroblasts were also observed by RNA sequencing and were closely related to scar formation. The therapeutic potential of circFoxp1 was investigated by establishing keloid implantation models. In vivo, circFoxp1 can promote fibroblast proliferation and ECM deposition. RNA pull-down and western blot assays verified the interaction of circFoxp1 with RACK1. The present study reveals that circFoxp1 contributes to the pathological hyperplasia of keloid, which may improve inflammation and cell proliferation. Our data indicate that circFoxp1 may serve as a novel, promising therapeutic target, presenting a new avenue for understanding the underlying pathogenesis of keloid.

Identification of a potential bioinformatics-based biomarker in keloids and its correlation with immune infiltration.

Keloid formation is a pathological consequence resulting from cutaneous irritation and injury, primarily attributed to excessive collagen matrix deposition and fibrous tissue proliferation. Chronic inflammation, left uncontrolled over an extended period, also stands as a substantial contributing factor. The precise mechanisms underlying keloid formation remain unclear. Therefore, this study aimed to identify key genes for diagnostic purposes. To achieve this, we used two Gene Expression Omnibus (GEO) data sets to identify differentially expressed genes. We identified one particular gene, homeobox C9 (HOXC9), using a thorough strategy involving two algorithms (least absolute shrinkage and selection operator and support vector machine-recursive feature elimination) and weighted gene co-expression network analysis. We then assessed its expression in normal and keloid tissues. In addition, we explored its temporal expression patterns via Mfuzz time clustering analysis. In our comprehensive analysis, we observed that immune infiltration, as well as cell proliferation, are crucial to keloid formation. Thus, we investigated immune cell infiltration in the keloid and normal groups, as well as the correlation between HOXC9 and these immune cells. It was found that HOXC9 was closely associated with the immune microenvironment of keloids. This shows that HOXC9 can serve as a potential biomarker and therapeutic target for keloids.

Joint effect of RRP9 and DDX21 on development of colorectal cancer and keloid.

BACKGROUND: Colorectal cancer (CRC) is a common malignancy in the gastrointestinal tract. Keloid refers to abnormal scar tissue that forms on the skin or mucous membrane. The relationship between RRP9 and DDX21 and the two diseases is unclear. METHODS: Download the colorectal cancer dataset GSE134834, GSE206800, GSE209892 and keloid dataset GSE44270 from the GEO database. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. The construction and analysis of protein-protein interaction (PPI) network, functional enrichment analysis, gene set enrichment analysis (GSEA). Gene expression heat map was drawn. The comparative toxicogenomics database (CTD) analysis was performed to find diseases most related to core genes. TargetScan screened miRNAs that regulated central DEGs. We conducted experimental validation using Western blotting and Polymerase Chain Reaction (PCR). RESULTS: In the colorectal cancer dataset and the scar tissue dataset, we identified 1380 DEGs and 1000 DEGs, respectively. The enrichment pattern for scar tissue was similar to that of colorectal cancer. We identified two core genes, RRP9 and DDX21. CTD analysis indicated that RRP9 and DDX21 are associated with proliferation, scar tissue, colorectal tumors, scleroderma, and inflammation. We found that the core genes (RRP9 and DDX21) were highly expressed in colorectal cancer and scar tissue samples, while their expression was lower in normal samples. This was further validated through Western blotting (WB) and Polymerase Chain Reaction (PCR). CONCLUSIONS: The higher the expression of RRP9 and DDX21 in colorectal cancer and keloid, the worse the prognosis.

miR-15a-5p up-regulates TLR4 and induces the formation of hypertrophic scars and keloids.

The formation of hypertrophic scar and keloid is considered to be a very complex pathological process. Our previous studies have shown that miR-15a-5p is an important miRNA in HTS tissues, and its expression level is significantly increased. Therefore, the potential mechanism of action of miR-15a-5p in scarring arouses our interest. This study preliminarily investigated the expression level of miR-15a-5p in HTS tissue and normal skin tissue and further explored the molecular mechanism. The results of this study once again confirmed that the expression level of miR-15a-5p was increased in HTS tissues and cells, and the closely related mRNA and protein levels of MyD88 and TGF-ß were also highly expressed. The relative expression levels of fibrosis-related indicators in HTsFb cells were up-regulated, such as collagen-Ⅰ, collagen-III and α-SMA. We constructed the HTS cell model and BALB/c nude animal model, and down-regulating miR-15a-5p, the HTsFb cells proliferation was inhibited, and qRT-PCR results showed that the fibrosis index mRNA was also reduced, and significantly reduce the pathological state of scar tissue. In conclusion, miR-15a-5p may participate in the formation and development of HTS through TLR/MyD88 signaling pathway and TGF-ß1 signaling pathway.

[Keloid nomogram prediction model based on weighted gene co-expression network analysis and machine learning].

Keloids are benign skin tumors resulting from the excessive proliferation of connective tissue in wound skin. Precise prediction of keloid risk in trauma patients and timely early diagnosis are of paramount importance for in-depth keloid management and control of its progression. This study analyzed four keloid datasets in the high-throughput gene expression omnibus (GEO) database, identified diagnostic markers for keloids, and established a nomogram prediction model. Initially, 37 core protein-encoding genes were selected through weighted gene co-expression network analysis (WGCNA), differential expression analysis, and the centrality algorithm of the protein-protein interaction network. Subsequently, two machine learning algorithms including the least absolute shrinkage and selection operator (LASSO) and the support vector machine-recursive feature elimination (SVM-RFE) were used to further screen out four diagnostic markers with the highest predictive power for keloids, which included hepatocyte growth factor (HGF), syndecan-4 (SDC4), ectonucleotide pyrophosphatase/phosphodiesterase 2 (ENPP2), and Rho family guanosine triphophatase 3 (RND3). Potential biological pathways involved were explored through gene set enrichment analysis (GSEA) of single-gene. Finally, univariate and multivariate logistic regression analyses of diagnostic markers were performed, and a nomogram prediction model was constructed. Internal and external validations revealed that the calibration curve of this model closely approximates the ideal curve, the decision curve is superior to other strategies, and the area under the receiver operating characteristic curve is higher than the control model (with optimal cutoff value of 0.588). This indicates that the model possesses high calibration, clinical benefit rate, and predictive power, and is promising to provide effective early means for clinical diagnosis.

Uterine leiomyomata and keloids fibrosis origins: a mini-review of fibroproliferative diseases.

Diseases such as uterine leiomyomata (fibroids and benign tumors of the uterus) and keloids (raised scars) may share common etiology. Fibroids and keloids can co-occur in individuals, and both are highly heritable, suggesting they may share common genetic risk factors. Fibroproliferative diseases are common and characterized by scarring and overgrowth of connective tissue, impacting multiple organ systems. These conditions both have racial disparities in prevalence, with the highest prevalence observed among individuals of African ancestry. Several fibroproliferative diseases are more severe and common in populations of sub-Saharan Africa. This mini-review aims to provide a broad overview of the current knowledge of the evolutionary origins and causes of fibroproliferative diseases. We also discuss current hypotheses proposing that the increased prevalence of these diseases in African-derived populations is due to the selection for profibrotic alleles that are protective against helminth infections and provide examples from knowledge of uterine fibroid and keloid research.