The fibroblast heterogeneity across keloid, normal and tumor samples from single-cell resolution.

Keloids are defined as a benign dermal fibroproliferative disorder, with excessive fibroblast proliferation, and excessive overproduction of collagen. Although the heterogeneity during keloid development has been extensively studied, the heterogeneity across different skin states is still unclear. So, a global comparison across skin states is needed. In this study, we collected samples from 5 states of skin, including melanoma, cutaneous squamous cell carcinoma, keloid skin, scar skin, and healthy control samples. The heterogeneity of cell types and subtypes was analyzed and compared across 5 states, and we observed significant differences among them. Our results showed a cancer-like fibroblast, which is not in normal samples, may play an important role in antigen processing and presentation. We also noticed that the mesenchymal fibroblast increased in keloid samples, which highly expressed POSTN. And POSTN may participate in epithelial-mesenchymal transition and collagen overexpression to promote keloid growth. These findings help to understand the alteration among different skin states and provide potential genetic basis for keloid therapies.

Identification of potential therapeutic target SPP1 and related RNA regulatory pathway in keloid based on bioinformatics analysis.

OBJECTIVE: To explore the complex mechanisms of keloid, new approaches have been developed by different strategies. However, conventional treatment did not significantly reduce the recurrence rate. This study aimed to identify new biomarkers and mechanisms for keloid progression through bioinformatics analyses. METHODS: In our study, microarray datasets for keloid were downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by R software. Multiple bioinformatics tools were used to identify hub genes, and reverse predict upstream miRNAs and lncRNA molecules of target hub genes. Finally, the total RNA-sequencing technique and miRNA microarray were combined to validate the identified genes. RESULTS: Thirty-one DEGs were screened out and the upregulated hub gene SPP1 was finally identified, which was consistent with our RNA-sequencing analysis results and validation dataset. In addition, a ceRNA network of mRNA (SPP1)-miRNA (miR-181a-5p)-lncRNA (NEAT1, MALAT1, LINC00667, NORAD, XIST and MIR4458HG) was identified by the bioinformatics databases. The results of our miRNA microarray showed that miR-181a-5p was upregulated in keloid, also we found that the lncRNA NEAT1 could affect keloid progression by retrieving the relevant literature. CONCLUSIONS: We speculate that SPP1 is a potential candidate biomarker and therapeutic target for patients with keloid, and NEAT1/miR-181a-5p/SPP1 might be the RNA regulatory pathway that regulates keloid formation.

Identify new biomarkers in keloid, potentially improve disease diagnosis and treatment.Through a variety of bioinformatics analysis tools, we found that the miRNA pathway NEAT1/miR-181a-5p/SPP1 may participant in controlling disease progression in the keloid.Providing insight into the mechanisms of disease development in the keloid at the transcriptome level.

Identification of novel immune-related signatures for keloid diagnosis and treatment: insights from integrated bulk RNA-seq and scRNA-seq analysis.

BACKGROUND: Keloid is a disease characterized by proliferation of fibrous tissue after the healing of skin tissue, which seriously affects the daily life of patients. However, the clinical treatment of keloids still has limitations, that is, it is not effective in controlling keloids, resulting in a high recurrence rate. Thus, it is urgent to identify new signatures to improve the diagnosis and treatment of keloids. METHOD: Bulk RNA seq and scRNA seq data were downloaded from the GEO database. First, we used WGCNA and MEGENA to co-identify keloid/immune-related DEGs. Subsequently, we used three machine learning algorithms (Randomforest, SVM-RFE, and LASSO) to identify hub immune-related genes of keloid (KHIGs) and investigated the heterogeneous expression of KHIGs during fibroblast subpopulation differentiation using scRNA-seq. Finally, we used HE and Masson staining, quantitative reverse transcription-PCR, western blotting, immunohistochemical, and Immunofluorescent assay to investigate the dysregulated expression and the mechanism of retinoic acid in keloids. RESULTS: In the present study, we identified PTGFR, RBP5, and LIF as KHIGs and validated their diagnostic performance. Subsequently, we constructed a novel artificial neural network molecular diagnostic model based on the transcriptome pattern of KHIGs, which is expected to break through the current dilemma faced by molecular diagnosis of keloids in the clinic. Meanwhile, the constructed IG score can also effectively predict keloid risk, which provides a new strategy for keloid prevention. Additionally, we observed that KHIGs were also heterogeneously expressed in the constructed differentiation trajectories of fibroblast subtypes, which may affect the differentiation of fibroblast subtypes and thus lead to dysregulation of the immune microenvironment in keloids. Finally, we found that retinoic acid may treat or alleviate keloids by inhibiting RBP5 to differentiate pro-inflammatory fibroblasts (PIF) to mesenchymal fibroblasts (MF), which further reduces collagen secretion. CONCLUSION: In summary, the present study provides novel immune signatures (PTGFR, RBP5, and LIF) for keloid diagnosis and treatment, and identifies retinoic acid as potential anti-keloid drugs. More importantly, we provide a new perspective for understanding the interactions between different fibroblast subtypes in keloids and the remodeling of their immune microenvironment.

BMP1 Promotes Keloid by Inducing Fibroblast Inflammation and Fibrogenesis.

Keloid is a typical fibrotic and inflammatory skin disease with unclear mechanisms and few therapeutic targets. In this study, we found that BMP1 was significantly increased in a collagen high-expressing subtype of fibroblast by reanalyzing a public single-cell RNA-sequence data set of keloid. The number of BMP1-positive fibroblast cells was increased in keloid fibrotic loci. Increased levels of BMP1 were further validated in the skin tissues and fibroblasts from keloid patients. Additionally, a positive correlation between BMP1 and the Keloid Area and Severity Index was found in keloid patients. In vitro analysis revealed collagen production, the phosphorylation levels of p65, and the IL-1ß secretion decreased in BMP1 interfered keloid fibroblasts. Besides, the knockdown of BMP1 inhibited the growth and migration of keloid fibroblast cells. Mechanistically, BMP1 inhibition downregulated the noncanonical TGF-ß pathways, including p-p38 and p-ERK1/2 signaling. Furthermore, we found the delivery of BMP1 siRNAs could significantly alleviate keloid in human keloid-bearing nude mice. Collectively, our results indicated that BMP1 exhibited various pathogenic effects on keloids as promoting cell proliferation, migration, inflammation, and ECM deposition of fibroblast cells by regulating the noncanonical TGF-ß/p38 MAPK, and TGF-ß/ERK pathways. BMP1-lowing strategies may appear as a potential new therapeutic target for keloid.

Serum deprivation protein response intervenes in the proliferation, motility, and extracellular matrix production in keloid fibroblasts by blocking the amplification of TGF-ß1/SMAD signal cascade via ERK1/2.

Keloid formation has been linked to abnormal fibroblast function, such as excessive proliferation and extracellular matrix (ECM) production. Serum deprivation protein response (SDPR) is a crucial regulator of cellular function under diverse pathological conditions, yet its role in keloid formation remains unknown. The current work investigated the function of SDPR in regulating the proliferation, motility, and ECM production of keloid fibroblasts (KFs), as well as to decipher the mechanisms involved. Analysis of RNA sequencing data from the GEO database demonstrated significant down-regulation of SDPR in KF compared to normal fibroblasts (NFs). This down-regulation was also observed in clinical keloid specimens and isolated KFs. Overexpression of SDPR suppressed the proliferation, motility, and ECM production of KFs, while depletion of SDPR exacerbated the enhancing impact of TGF-ß1 on the proliferation, motility, and ECM production of NFs. Mechanistic studies revealed that SDPR overexpression repressed TGF-ß/Smad signal cascade activation in KFs along with decreased levels of phosphorylated Samd2/3, while SDPR depletion exacerbated TGF-ß/Smad activation in TGF-ß1-stimulated NFs. SDPR overexpression also repressed ERK1/2 activation in KFs, while SDPR depletion exacerbated ERK1/2 activation in TGF-ß1-stimulated NFs. Inhibition of ERK1/2 abolished SDPR-depletion-induced TGF-ß1/Smad activation, cell proliferation, motility, and ECM production in NFs. In conclusion, SDPR represses the proliferation, motility, and ECM production in KFs by blocking the TGF-ß1/Smad pathway in an ERK1/2-dependent manner. The findings highlight the role of SDPR in regulating abnormal behaviors of fibroblasts associated with keloid formation and suggest it as a potential target for anti-keloid therapy development.

STAT3-induced lncRNA GNAS-AS1 accelerates keloid formation by mediating the miR-196a-5p/CXCL12/STAT3 axis in a feedback loop.

Keloids are pathological scar tissue resulting from skin trauma or spontaneous formation, often accompanied by itching and pain. Although GNAS antisense RNA 1 (GNAS-AS1) shows abnormal upregulation in keloids, the underlying molecular mechanism is unclear. The levels of genes and proteins in clinical tissues from patients with keloids and human keloid fibroblasts (HKFs) were measured using quantitative reverse transcription PCR, western blot and enzyme-linked immunosorbent assay. The features of HKFs, including proliferation and migration, were evaluated using cell counting kit 8 and a wound healing assay. The colocalization of GNAS-AS1 and miR-196a-5p in HKFs was measured using fluorescence in situ hybridization. The relationships among GNAS-AS1, miR-196a-5p and C-X-C motif chemokine ligand 12 (CXCL12) in samples from patients with keloids were analysed by Pearson correlation analysis. Gene interactions were validated by chromatin immunoprecipitation and luciferase reporter assays. GNAS-AS1 and CXCL12 expression were upregulated and miR-196a-5p expression was downregulated in clinical tissues from patients with keloids. GNAS-AS1 knockdown inhibited proliferation, migration, and extracellular matrix (ECM) accumulation of HKFs, all of which were reversed by miR-196a-5p downregulation. Signal transducer and activator of transcription 3 (STAT3) induced GNAS-AS1 transcription through GNAS-AS1 promoter interaction, and niclosamide, a STAT3 inhibitor, decreased GNAS-AS1 expression. GNAS-AS1 positively regulated CXCL12 by sponging miR-196-5p. Furthermore, CXCL12 knockdown restrained STAT3 phosphorylation in HKFs. Our findings revealed a feedback loop of STAT3/GNAS-AS1/miR-196a-5p/CXCL12/STAT3 that promoted HKF proliferation, migration and ECM accumulation and affected keloid progression.

No Association of Polymorphisms in the Genes Encoding Interleukin-6 and Interleukin-6 Receptor Subunit Alpha with the Risk of Keloids in Polish Patients.

A keloid is a benign fibroproliferative hypertrophy of scar tissue that extends outside the original wound and invades adjacent healthy skin. Keloid formation is thought to be a complex process including overactivity of the interleukin-6 signaling pathway and genetic susceptibility. The aim of the study was to investigate possible associations between rs1800797, rs1800796, and rs1800795 polymorphisms in the promoter of the IL6 gene encoding interleukin-6 and the rs2228145 polymorphism in the IL6R gene encoding the interleukin-6 receptor subunit alpha with the predisposition to keloids in Polish patients. The genetic polymorphisms were identified either using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) or sequencing of samples of genomic DNA extracted from blood leukocytes of 86 adult patients with keloids and 100 newborns comprising a control group. No significant differences in the distributions of IL6 or IL6R alleles or genotypes were found between keloid patients and newborn controls. There were also no significant differences between both groups in the distribution of IL6 haplotypes. The IL6 rs1800797, rs1800796 and rs1800795 and IL6R rs2228145 polymorphisms were not found to predispose individuals in the study group to keloids. IL6 promoter haplotypes were not found to be associated with a higher risk of keloids in the studied group.

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.

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.

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.

Targeting the nuclear long noncoding transcript LSP1P5 abrogates extracellular matrix deposition by trans-upregulating CEBPA in keloids.

Keloids are characterized by fibroblast hyperproliferation and excessive accumulation of extracellular matrix (ECM) and are a major global health care burden among cutaneous diseases. However, the function of long noncoding RNA (lncRNA)-mediated ECM remodeling during the pathogenesis of keloids is still unclear. Herein, we identified a long noncoding transcript, namely, lymphocyte-specific protein 1 pseudogene 5 (LSP1P5), that modulates ECM component deposition in keloids. First, high-throughput transcriptome analysis showed that LSP1P5 was selectively upregulated in keloids and correlated with more severe disease in a clinical keloid cohort. Therapeutically, the attenuation of LSP1P5 significantly decreased the expression of ECM markers (COL1, COL3, and FN1) both in vitro and in vivo. Intriguingly, an antifibrotic gene, CCAAT enhancer binding protein alpha (CEBPA), is a functional downstream candidate of LSP1P5. Mechanistically, LSP1P5 represses CEBPA expression by hijacking Suppressor of Zeste 12 to the promoter of CEBPA, thereby enhancing the polycomb repressive complex 2-mediated H3K27me3 and changing the chromosomal opening status of CEBPA. Taken together, these findings indicate that targeting LSP1P5 abrogates fibrosis in keloids through epigenetic regulation of CEBPA, revealing a novel antifibrotic therapeutic strategy that bridges our current understanding of lncRNA regulation, histone modification and ECM remodeling in keloids.

Inhibition of keloid fibroblast proliferation by artesunate is mediated by targeting the IRE1α/XBP1 signaling pathway and decreasing TGF-ß1.

BACKGROUND: Keloid is a benign hyperplastic dermatosis with high recurrence rate and complex pathogenesis. There is no universally effective treatment yet. New therapies and elucidation of pathogenesis are urgently required. AIMS: To explore the function of IRE1α/XBP1 in keloid fibroblasts and to investigate the potential mechanism of artesunate in inhibiting keloid hyperplasia. METHODS: Human keloid fibroblasts (KFs) were cultured, and the expressions of XBP1 and TGF-ß1 were detected by immunohistochemistry. The expression of IRE1 was interfered with through cell transfection and the effects of IRE1 interference on cell proliferation and the cell cycle were assessed using MTS, colony formation assays, and flow cytometry. Detection of the expressions of XBP1 and TGF-ß1 by qRT-PCR and Western blot. Then artesunate was applied to a subset of the cells, and its effects on cell viability and the expression of related proteins using the same methods. RESULTS: The IRE1α/XBP1 pathway was activated in KFs. Knocking out the gene IRE1α can inhibit the expression of TGF-ß1, in addition, the cell viability and cell cycle progression of KFs were also significantly affected. After artesunate treatment, there was a remarkable reduction in cell proliferation. Meanwhile, the cell cycle of KFs treated with artesunate was blocked in G1 phase.After upregulating the expression of IRE1α and treating KFs with artesunate, both cell cycle and proliferation showed inhibitory effects, and related proteins also exhibited suppressed expression. CONCLUSIONS: The IRE1α/XBP1 pathway is activated in keloid, and inhibiting the expression of this pathway can affect the cell proliferation activity. In addition, artesunate also has a significant effect on fibroblast proliferation, and the IRE1α/XBP1 pathway may participate in this process. These findings suggest that IRE1α/XBP1 signal pathway may be a potential target for scar treatment, and artesunate could also be a powerful candidate for keloid treatment.

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.

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.

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 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.

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.

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.