Maximizing the Utility of Transcriptomics Data in Inflammatory Skin Diseases

Integrative bioinformatics and experimental validation of hub genetic markers in acne vulgaris: Toward personalized diagnostic and therapeutic strategies

BACKGROUND

Acne vulgaris is a widespread chronic inflammatory dermatological condition. The precise molecular and genetic mechanisms of its pathogenesis remain incompletely understood. This research synthesizes existing databases, targeting a comprehensive exploration of core genetic markers.

METHODS

Gene expression datasets (GSE6475, GSE108110, and GSE53795) were retrieved from the GEO. Differentially expressed genes (DEGs) were identified using the limma package. Enrichment analyses were conducted using GSVA for pathway assessment and clusterProfiler for GO and KEGG analyses. PPI networks and immune cell infiltration were analyzed using the STRING database and ssGSEA, respectively. We investigated the correlation between hub gene biomarkers and immune cell infiltration using Spearman's rank analysis. ROC curve analysis validated the hub genes' diagnostic accuracy. miRNet, TarBase v8.0, and ChEA3 identified miRNA/transcription factor-gene interactions, while DrugBank delineated drug-gene interactions. Experiments utilized HaCaT cells stimulated with Propionibacterium acnes, treated with retinoic acid and methotrexate, and evaluated using RT-qPCR, ELISA, western blot, lentiviral transduction, CCK-8, wound-healing, and transwell assays.

RESULTS

There were 104 genes with consistent differences across the three datasets of paired acne and normal skin. Functional analyses emphasized the significant enrichment of these DEGs in immune-related pathways. PPI network analysis pinpointed hub genes PTPRC, CXCL8, ITGB2, and MMP9 as central players in acne pathogenesis. Elevated levels of specific immune cell infiltration in acne lesions corroborated the inflammatory nature of the disease. ROC curve analysis identified the acne diagnostic potential of four hub genes. Key miRNAs, particularly hsa-mir-124-3p, and central transcription factors like TFEC were noted as significant regulators. In vitro validation using HaCaT cells confirmed the upregulation of hub genes following Propionibacterium acnes exposure, while CXCL8 knockdown reduced pro-inflammatory cytokines, cell proliferation, and migration. DrugBank insights led to the exploration of retinoic acid and methotrexate, both of which mitigated gene expression upsurge and inflammatory mediator secretion.

CONCLUSION

This comprehensive study elucidated pivotal genes associated with acne pathogenesis, notably PTPRC, CXCL8, ITGB2, and MMP9. The findings underscore potential biomarkers, therapeutic targets, and the therapeutic potential of agents like retinoic acid and methotrexate. The congruence between bioinformatics and experimental validations suggests promising avenues for personalized acne treatments.

Skin in the game: a review of single-cell and spatial transcriptomics in dermatological research

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) are two emerging research technologies that uniquely characterize gene expression microenvironments on a cellular or subcellular level. The skin, a clinically accessible tissue composed of diverse, essential cell populations, serves as an ideal target for these high-resolution investigative approaches. Using these tools, researchers are assembling a compendium of data and discoveries in healthy skin as well as a range of dermatologic pathophysiologies, including atopic dermatitis, psoriasis, and cutaneous malignancies. The ongoing advancement of single-cell approaches, coupled with anticipated decreases in cost with increased adoption, will reshape dermatologic research, profoundly influencing disease characterization, prognosis, and ultimately clinical practice.

Identification of Genes Associated with Decreasing Abundance of Monocytes in Long-Term Peritoneal Dialysis Patients

Purpose

Chronic kidney disease (CKD) will become an end-stage renal disease (ESRD) at stage 5. Peritoneal dialysis (PD) is required for renal replacement therapy. This study aims to identify monocytes-related genes in peritoneal cells from long-term PD (LPD) patients and short-term PD (SPD) patients.

Methods

Bulk RNA-seq data (GSE125498 dataset) and ScRNA-seq data (GSE130888) were downloaded to identify differentially expressed genes, monocytes-related genes, and monocytes marker genes in LPD patients. Immune infiltration was analyzed in the GSE125498 dataset. Core genes associated with monocytes changes were screened out, followed by functional analysis and expression validation using RT-PCR.

Results

Monocytes are the most abundant immune cell in PD. The number of monocytes was remarkably decreased in LPD compared with SPD. A total of 16 up-regulated core genes negatively correlated with the abundance of monocytes were obtained in LPD. The expression of 16 core genes was lower in monocyte clusters than that in other cell clusters. In addition, LCK, CD3G, CD3E, CD3D, and LAT were involved in the signaling pathways of Th1 and Th2 cell differentiation, T cell receptor signaling pathway, and Th17 cell differentiation. CD2 was involved in hematopoietic cell lineage signaling pathway.

Conclusion

Identification of monocytes related-genes and related signaling pathways could be helpful in understanding the molecular mechanism of monocytes changes during PD.

Identification of diagnostic molecules and potential therapeutic agents for atopic dermatitis by single-cell RNA sequencing combined with a systematic computing framework that integrates network pharmacology

Atopic dermatitis (AD) is composed of highly flexible cellular participants. To better understand its pathobiology and molecular regulation mechanisms, it is necessary to combine single-cell RNA sequencing (scRNA-seq) with new computing frameworks or specific technologies, which may contribute to the development of better treatments for AD. The scRNA-seq data of GSE180885 and bulk RNA-seq data of GSE193309 were obtained from Gene Expression Omnibus (GEO) database, and the scRNA-seq data was analyzed by Seurat package to identify the cell types in AD. The genes related to the activity of AD topical drugs were obtained from the ChEMBL database, which provided a variety of bioactivity data such as multiple drugs and targets. AD-related genes were obtained from DisGeNET and CTD databases synthesizing human disease-related genes; the intersection of AD-related genes from these three sources with differentially expressed genes (DEGs) between non-diseased AD and normal human skin (NHS) samples and differential cell type marker genes was taken. The proximity analysis of drug gene network was performed based on the gene with the largest area of receiver operating characteristic (ROC) curve. Ten distinct cell types of AD and NHS were identified, except for phagocytes cells. Three hub genes, F10 and CALCRL and CTSB, were obtained. The area under the curve of ROC based on CTSB expression was the largest, which was 60.15%. By binding drug CTSB-related gene interaction network, we identified 145 potential drugs. Among them, the score of DB07045 and CTSB docking was the lowest, and molecular docking and molecular dynamics (MD) simulation confirmed the close and stable binding of DB07045 and cathepsin B. This work identified diagnostic molecules and potential therapeutic drugs of AD by scRNA-seq combined with a systematic computing framework of network pharmacology, which may provide valuable clues for drug design.

Systematic characterization of cancer transcriptome at transcript resolution

Transcribed RNAs undergo various regulation and modification to become functional transcripts. Notably, cancer transcriptome has not been fully characterized at transcript resolution. Herein, we carry out a reference-based transcript assembly across >1000 cancer cell lines. We identify 498,255 transcripts, approximately half of which are unannotated. Unannotated transcripts are closely associated with cancer-related hallmarks and show clinical significance. We build a high-confidence RNA binding protein (RBP)-transcript regulatory network, wherein most RBPs tend to regulate transcripts involved in cell proliferation. We identify numerous transcripts that are highly associated with anti-cancer drug sensitivity. Furthermore, we establish RBP-transcript-drug axes, wherein PTBP1 is experimentally validated to affect the sensitivity to decitabine by regulating KIAA1522-a6 transcript. Finally, we establish a user-friendly data portal to serve as a valuable resource for understanding cancer transcriptome diversity and its potential clinical utility at transcript level. Our study substantially extends cancer RNA repository and will facilitate anti-cancer drug discovery.

Construction of a focal adhesion signaling pathway-related ceRNA network in pelvic organ prolapse by transcriptome analysis

Objective: Pelvic organ prolapse (POP) affects a large proportion of adult women, but the pathogenesis of POP remains unclear. The increase in global population aging will impose a substantial medical burden. Herein, we aimed to explore the related RNAs regulating the occurrence of POP and provide potential therapeutic targets.

Method: Tissue biopsies were collected from the anterior vaginal wall of six women with POP and six matched subjects without POP. The profiles of mRNAs, circRNAs, lncRNAs, and miRNAs were obtained by whole transcriptome RNA sequencing.

Result: The findings revealed that 71 circRNAs, 76 known lncRNAs, 84 miRNAs, and 931 mRNAs were significantly altered (p < 0.05 and |log2FC| > 1). GO and KEGG enrichment analyses indicated that the differentially expressed genes (DEGs) were mainly enriched in the focal adhesion signaling pathway. FLT, ITGA9, VEGFD, PPP1R12B, and ROCK2 were identified as focal adhesion signaling pathway-related hub genes by protein–protein interaction network analysis. Based on the relationships between the DEGs and miRNA, lncRNA and circRNA targets, we constructed a focal adhesion signaling pathway-related ceRNA network. The ceRNA network includes hsa_circ_0002190/hsa_circ_0046843/lnc-CARMN -miR-23a-3p - ROCK2 and hsa_circ_0001326/hsa_circ_0007733/lnc-AC107959/lnc-TPM1-AS - miR-205-5p - ROCK2/PPP1R12B/VEGFD. Moreover, abnormalities in the cytoskeleton in fibroblasts from individuals with POP were observed.

Conclusion: In this study, a focal adhesion signaling pathway-related ceRNA network was constructed, and this network may serve as a target for finding suitable drugs for the treatment of POP.

Interrogation of RDEB Epidermal Allografts after BMT Reveals Coexpression of Collagen VII and Keratin 15 with Proinflammatory Immune Cells and Fibroblasts

Recessive dystrophic epidermolysis bullosa (RDEB) is a devastating genodermatosis characterized by dysfunctional collagen VII protein resulting in epithelial blistering of the skin, mucosa, and gastrointestinal tract. There is no cure for RDEB, but improvement of clinical phenotype has been achieved with bone marrow transplantation and subsequent epidermal allografting from the bone marrow transplant donor. Epidermal allografting of these patients has decreased wound surface area for up to 3 years after treatment. This study aimed to determine the phenotype of the epidermal allograft cells responsible for durable persistence of wound healing and skin integrity. We found that epidermal allografts provide basal keratinocytes coexpressing collagen VII and basal stem cell marker keratin 15. Characterization of RDEB full-thickness skin biopsies with single-cell RNA sequencing uncovered proinflammatory immune and fibroblast phenotypes potentially driven by the local environment of RDEB skin. This is further highlighted by the presence of a myofibroblast population, which has not been described in healthy control human skin. Finally, we found inflammatory fibroblasts expressing profibrotic gene POSTN, which may have implications in the development of squamous cell carcinoma, a common, lethal complication of RDEB that lacks curative treatment. In conclusion, this study provides insights into and targets for future RDEB studies and treatments.