Identifying potential pathogenesis and immune infiltration in diabetic foot ulcers using bioinformatics and in vitro analyses.

BACKGROUND: Diabetic foot ulcers (DFU) are among the fastest-growing diseases worldwide. Recent evidence has emphasized the critical role of microRNA (miRNA)-mRNA networks in various chronic wounds, including DFU. In this study, we aimed to clarify the miRNA-mRNA axes associated with the occurrence of DFU. METHODS: Expression profiles of miRNAs and mRNAs were extracted from the Gene Expression Omnibus. Differentially expressed genes and differentially expressed miRNAs were identified, and miRNA-mRNA regulatory axes were constructed through integrated bioinformatics analyses. We validated the miRNA-mRNA axes using quantitative real-time PCR (qPCR) and dual-luciferase reporter assays. We conducted an immune infiltration analysis and confirmed the bioinformatics results using immunofluorescence staining. Single-sample gene set enrichment analysis (ssGSEA) was used to analyze the metabolic mechanisms. RESULTS: miR-182-5p-CHL1/MITF and miR-338-3p-NOVA1 interactions were identified using in silico analysis. The qPCR results showed apparent dysregulation of these miRNA-mRNA axes in DFU. The dual-luciferase reporter assay confirmed that miR-182-5p targeted CHL1 and MITF, and miR-338-3p targeted NOVA1. We conducted an immune infiltration analysis and observed that key genes correlated with decreased infiltration of M1 macrophages and resting mast cells in DFU. Immunofluorescence staining verified the co-localization of CHL1 and tryptase, while MITF and CD68 showed weak positive correlations. Metabolic pathways related to these three genes were identified using ssGSEA. CONCLUSIONS: In summary, the miR-182-5p-CHL1/MITF and miR-338-3p-NOVA1 pathway interactions and decreased infiltration of M1 macrophages and resting mast cells may provide novel clues to the pathogenesis of DFU. TRIAL REGISTRATION: The clinical trial included in this study was registered in the Chinese Clinical Trial Registry ( ChiCTR2200066660 ) on December 13, 2022.

Pan-cancer analysis of the oncogenic role of the core osteosarcoma gene VCAN in human tumors.

OBJECTIVE: Versican (VCAN), a member of the multifunctional glycoprotein family, is involved in various aspects of cancer progression. However, the role of VCAN in diverse cancers remains poorly defined. This research aimed to investigate the correlation between VCAN expression and the oncogenic role, as well as visualize its prognostic landscape in pan-cancer. METHODS: Raw data in regard to VCAN expression in cancer patients were acquired from GEO GeneChip public database in NCBI. Besides, we selected microarray data GSE16088 for analysis. We retrieved the genes associated with osteosarcoma (OS) from the OMIM database and identified their intersection with the core module. VCAN was suggested to be a potential marker gene for OS. Subsequently, we conducted Gene Set Enrichment Analysis (GSEA) to explore gene functional enrichment. Moreover, we performed pan-cancer analysis on VCAN to gain a comprehensive understanding of its implications across various cancer types. RESULTS: The VCAN expression in the tumor tissue was higher than that in normal tissue. Elevated expression of VCAN was associated with high the tumor stage and poor long-term survival. There was a significant positive correlation between VCAN and cancer fibroblasts in all pan cancers. Moreover, FBN1 was the intersection gene of VCAN-related genes and linker genes. ANTXR1, COL5A2, CSGALNACT2, and SPARC were the target genes of VCAN genes. GSEA analysis showed that VCAN was mainly enriched in the extracellular matrix (ECM) signaling pathway. CONCLUSION: VCAN can be used as a marker molecule for the early diagnosis of OS and holds significance as a molecule in cases of OS with distant metastasis. The ECM signaling pathway may be a core pathway in OS development and distant metastasis. These findings shed new light on therapeutics of cancers.

Bioinformatics Analysis of ZBTB16 as a Prognostic Marker for Ewing's Sarcoma.

OBJECTIVE: The purpose of this study is to identify novel biomarkers for the prognosis of Ewing's sarcoma based on bioinformatics analysis. METHODS: The GSE63157 and GSE17679 datasets contain patient and healthy control microarray data that were downloaded from the Gene Expression Omnibus (GEO) database and analyzed through R language software to obtain differentially expressed genes (DEGs). Firstly, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment, protein-protein interaction (PPI) networks, and Cytoscape Molecular Complex Detection (MCODE) plug-in were then used to compute the highest scores of the module. After survival analysis, the hub genes were lastly obtained from the two module genes. RESULTS: A total of 1181 DEGs were identified from the two GSEs. Through MCODE and survival analysis, we obtain 53 DEGs from the module and 29 overall survival- (OS-) related genes. ZBTB16 was the only downregulated gene after Venn diagrams. Survival analysis indicates that there was a significant correlation between the high expression of ZBTB16 and the OS of Ewing's sarcoma (ES), and the low expression group had an unfavorable OS when compared to the high expression group. CONCLUSIONS: High expression of ZBTB16 may serve as a predictor biomarker of poor prognosis in ES patients.