Comprehensive analysis of ferroptosis-related hub gene signatures as a potential pathogenesis and therapeutic target for systemic sclerosis: A bioinformatics analysis.

Introduction: The molecular mechanism of systemic sclerosis (SSc) remains unclear. Ferroptosis participates in a series of cell activities, such as inflammatory progression, by regulating cell death; unfortunately, there aren't many research that discuss the connection between ferroptosis and SSc.Objectives: This study used bioinformatics analysis to report a potential relationship between ferroptosis and SSc.Methods: The SSc and control datasets GSE125362 and GSE76807 were obtained from the gene expression omnibus database. The differentially expressed genes (DEGs) were identified using the R software. By the Venn diagram, ferroptosis DEGs were detected. The chosen candidate genes were then subjected to analyses of protein-protein interactions, gene ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment. With the Molecular Complex Detection plugin program, the hub genes were investigated. A multifactor regulatory network was constructed depending on key hub genes, and immune infiltration was also evaluated. Finally, quantitative real-time polymerase chain reaction (RT-PCR) and enzyme linked immunosorbent assay were used to validate the bioinformatic results.Results: Twenty-four ferroptosis-related differentially expressed genes were detected in patients with SSc versus the normal controls. The biological processes of FRGs in patients with SSc focused on the negative regulation of cell proliferation and inflammatory response. The signaling pathways were enriched in necroptosis. The core genes of SSc were CYBB, IL-6, NOX4,TLR4, CXCL2, JUN, and LY96. Three miRNAs, two lncRNAs, and five transcription factors were predicted. The evaluation of immune infiltration showed that the number of activated natural killer (NK) cells increased in SSc skin tissues, whereas the number of resting dendritic, NK, and mast cells decreased. The bioinformatics prediction results from the mRNA chip were in line with the expression levels of IL-6 and CYBB.Conclusions: Necroptosis and ferroptosis were upregulated in patients with SSc and involved in modulating cell proliferation, differentiation, and migration. IL-6 and CYBB are key ferroptosis-related genes in SSc. Ferroptosis and related genes might be promising targets in the treatment of SSc.

Identification of a circRNA-miRNA-mRNA network to explore the effects of circRNAs on pathogenesis and treatment of systemic lupus erythematosus.

OBJECTIVES: Systemic lupus erythematosus (SLE) is an autoimmune disease characterised by immune inflammation. It involves multiple organs. Many studies have demonstrated that circRNAs are closely associated with SLE. Nonetheless, the potential mechanism by which circRNAs impacts SLE is not fully understood. The aim of this study was to explore the regulatory roles of circRNAs, the key genes and pathways governing the pathophysiological processes of SLE, and to screen therapeutic agents. METHODS: The sequencing data of circRNA, miRNA and mRNA were obtained from Gene Expression Omnibus (GEO) datasets. Candidates were identified to construct a circRNA-miRNA-mRNA network based on circRNA-miRNA interactions and miRNA-mRNA interactions. Gene functional enrichments were performed on the DAVID database. Protein-protein interaction (PPI) network was constructed by STRING database and visualised in Cytoscape software. The hub genes were explored by the MCODE plugin app. The Connectivity Map L1000 platform was used to identify potential agents. RESULTS: A total of 1093 differentially expressed circRNAs (DEcircRNAs), 42 differentially expressed miRNAs (DEmiRNAs) and 1431 differentially expressed mRNAs (DEmRNAs) were identified. We integrated 3 overlapped circRNAs, 13 miRNAs and 352 target mRNAs into a circRNA-miRNA-mRNA network. We next identified 44 hub genes based on the PPI network. KEGG pathway analysis revealed that the DEGs were mainly associated with MAPK signalling pathway. In addition, we discovered several chemicals as potential treatment options for SLE. CONCLUSIONS: Through this bioinformatics analysis, we suggest a regulatory role for circRNAs in the pathogenesis and treatment of SLE from the view of a competitive endogenous RNA (ceRNA) network.