Bioinformatic analysis of key biomarkers and immune filtration of skin biopsy in discoid lupus erythematosus

Abstract

Objective: Discoid lupus erythematosus (DLE) is the most common category of chronic cutaneous lupus erythematosus, where the pathological process is proved to be closely associated with immunity. This bioinformatic analysis sought to identify key biomarkers and to perform immune infiltration analysis in the skin biopsy samples of DLE. Methods: GSE120809, GSE100093, GSE72535, GSE81071 were used as the data source of gene expression profiles, altogether containing 79 DLE samples and 47 normal controls (NC). Limma package was applied to identify differentially expressed genes (DEGs) and additional Gene Ontology (GO) together with The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were done. Protein-protein interaction network (PPI) was constructed using STRING and Cytoscape. Hub genes were selected by CytoHubba. Finally, immune filtration analysis was finished by the CIBERSORT algorithm, and comparisons between the two groups were accomplished. Results: A total of 391 DEGs were identified, which were composed of 57 up-regulated genes and 334 down-regulated genes. GO and KEGG enrichment analyses revealed that DEGs were closely related with different steps in the immune response. Top 10 hub genes included GBP2, HLA-F, IFIT2, RSAD2, ISG15, IFIT1, IFIT3, MX1, XAF1 and IFI6. Immune filtration analysis from CIBERSORT had found that compared with NC, DLE samples had higher percentages of CD8+ T cells, T cells CD4 memory activated, T cells gamma delta, macrophages M1 and lower percentages of T cells regulatory, macrophages M2, dendritic cells resting, mast cells resting, mast cells activated. Conclusion: This bioinformatic study selected key biomarkers from the contrast between DLE and NC skin samples and is the first research to analyze immune cell filtration in DLE.