International Wound Journal · 2023 · 23 citations · 37 references
Life SciencesBioinformaticsMolecular BiologyGene ExpressionGene Expression AnalysisInflammationDiabetes MellitusDiabetic Foot DiseaseDiabetic Foot UlcerationDifferential Gene Expression AnalysisDisease Network BiologyProtein-protein Interaction AnalysisDiabetes-associated Immune DysfunctionEnrichment AnalysisHub Gene IdentificationImmune Cell Infiltration DensityImmune Infiltration BiomarkersProtein-protein Interaction Network AlignmentProtein-protein Interaction Network AnalysisProtein-protein Interaction Network Inference
Ferroptosis is a novel form of cell death that plays a key role in several diseases, including inflammation and tumours; however, the role of ferroptosis-related genes in diabetic foot remains unclear. Herein, diabetic foot-related genes were downloaded from the Gene Expression Omnibus and the ferroptosis database (FerrDb). The least absolute shrinkage and selection operator regression algorithm was used to construct a related risk model, and differentially expressed genes were analysed through immune infiltration. Finally, we identified relevant core genes through a protein-protein interaction network, subsequently verified using immunohistochemistry. Comprehensive analysis showed 198 genes that were differentially expressed during ferroptosis. Based on functional enrichment analysis, these genes were primarily involved in cell response, chemical stimulation, and autophagy. Using the CIBERSORT algorithm, we calculated the immune infiltration of 22 different types of immune cells in diabetic foot and normal tissues. The protein-protein interaction network identified the hub gene TP53, and according to immunohistochemistry, the expression of TP53 was high in diabetic foot tissues but low in normal tissues. Accordingly, we identified the ferroptosis-related gene TP53 in the diabetic foot, which may play a key role in the pathogenesis of diabetic foot and could be used as a potential biomarker.
37
Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks
Paul Shannon, Andrew Markiel, Owen Ozier et al. · Genome Research · 2003 · 54.3K citations · Full text
Gene Ontology: tool for the unification of biology
Michael Ashburner, Catherine A. Ball, Judith A. Blake et al. · Nature Genetics · 2000 · 44.6K citations · Full text
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Guangchuang Yu, Li-Gen Wang, Yanyan Han et al. · OMICS A Journal of Integrative Biology · 2012 · 38.3K citations