Bioinformatics analyses of gene expression profile identify key genes and functional pathways involved in cutaneous lupus erythematosus.

Lupus erythematosus is an autoimmune disease that causes damage to multiple organs ranging from skin lesions to systemic manifestations. Cutaneous lupus erythematosus (CLE) is a common type of lupus erythematosus (LE), but its molecular mechanisms are currently unknown. The study aimed to explore changes in the gene expression profiles and identify key genes involved in CLE, hoping to uncover its molecular mechanism and identify new targets for CLE. We analyzed the microarray dataset (GSE109248) derived from the Gene Expression Omnibus (GEO) database, which was a transcriptome profiling of CLE cutaneous lesions. The differentially expressed genes (DEGs) were identified, and the functional annotation of DEGs was performed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein-protein interaction (PPI) network was also constructed to identify hub genes involved in CLE. A total of 755 up-regulated DEGs and 405 down-regulated DEGs were identified. GO enrichment analysis showed that defense response to virus, immune response, and type I interferon signaling pathway were the most significant enrichment items in DEGs. The KEGG pathway analysis identified 51 significant enrichment pathways, which mainly included systemic lupus erythematosus, osteoclast differentiation, cytokine-cytokine receptor interaction, and primary immunodeficiency. Based on the PPI network, the study identified the top 10 hub genes involved in CLE, which were CXCL10, CCR7, FPR3, PPARGC1A, MMP9, IRF7, IL2RG, SOCS1, ISG15, and GSTM3. By comparison between subtypes, the results showed that ACLE had the least DEGs, while CCLE showed the most gene and functional changes. The identified hub genes and functional pathways found in this study may expand our understanding on the underlying pathogenesis of CLE and provide new insights into potential biomarkers or targets for the diagnosis and treatment of CLE. Key Points • The bioinformatics analysis based on CLE patients and healthy controls was performed and 1160 DEGs were identified • The 1160 DEGs were mainly enriched in biological processes related to immune responses, including innate immune response, type I interferon signaling pathway, interferon-γ-mediated signaling pathway, positive regulation of T cell proliferation, regulation of immune response, antigen processing, and presentation via MHC class Ib and so on • KEGG pathway enrichment analysis indicated that DEGs were mainly enriched in several immune-related diseases and virus infection, including systemic lupus erythematosus, primary immunodeficiency, herpes simplex infection, measles, influenza A, and so on • The hub genes such as CXCL10, IRF7, MMP9, CCR7, and SOCS1 may become new markers or targets for the diagnosis and treatment of CLE.

Gao ZY ，Su LC ，Wu QC ，Sheng JE ，Wang YL ，Dai YF ，Chen AP ，He SS ，Huang X ，Yan GQ ... -  《-》

Identification of Significant Genes and Pathways for the Chronic and Subacute Cutaneous Lupus Erythematosus via Bioinformatics Analysis.

Chronic cutaneous lupus erythematosus (CCLE) and subacute cutaneous lupus erythematosus (SCLE) are both common variants of cutaneous lupus erythematosus (CLE) that mainly involve the skin and mucous membrane. Oral mucosal involvement is frequently observed in patients of CLE. Despite that they have different clinicopathological features, whether there is a significant difference in pathogenesis between them remains unclear. Herein, we investigated specific genes and pathways of SCLE and CCLE via bioinformatics analysis. Microarray expression datasets of GSE109248 and GSE112943 were both retrieved from the GEO database. Differentially expressed genes (DEGs) between CCLE or SCLE skin tissues and health controls were selected by GEO2R. Common DEGs were picked out via the Venn diagram software. Then, functional enrichment and PPI network analysis were conducted, and the top 10 key genes were identified via Cytohubba. Totally, 176 DEGs of SCLE and 287 DEGs of CCLE were identified. The GO enrichment and KEGG analysis of DEGs of SCLE is significantly enriched in the response to virus, defense response to virus, response to IFN-gamma, cellular response to IFN-γ, type I IFN signaling pathway, chemokine activity, chemokine receptor binding, NOD-like receptor signaling pathway, etc. The GO enrichment and KEGG analysis of DEGs of CCLE is significantly enriched in the response to virus, regulation of multiorganism process, negative regulation of viral process, regulation of lymphocyte activation, chemokine receptor binding, CCR chemokine receptor binding, NOD-like receptor signaling pathway, etc. The top 10 hub genes of SCLE and CCLE, respectively, include STAT1, CXCL10, IRF7, ISG15, and RSAD2 and CXCL10, IRF7, IFIT3, CTLA4, and ISG15. Our finding suggests that SCLE and CCLE have the similar potential key genes and pathways and majority of them belong to IFN signatures and IFN signaling pathway. Besides, the NOD-like receptor signaling pathway might also have an essential role in the pathogenesis of SCLE and CCLE. Together, the identified genes and signaling pathways have enhanced our understanding of the mechanism underlying the occurrence and development of both SCLE and CCLE.

Teng Y ，Li S ，Ding Y ，Fan Y ，He M ，Li H ，Tao X ，Huang Y ... -  《-》

Bioinformatics identification of key candidate genes and pathways associated with systemic lupus erythematosus.

Yang F ，Zhai Z ，Luo X ，Luo G ，Zhuang L ，Zhang Y ，Li Y ，Sun E ，He Y ... -  《-》

Bioinformatics analysis of differentially expressed gene profiles associated with systemic lupus erythematosus.

Wu C ，Zhao Y ，Lin Y ，Yang X ，Yan M ，Min Y ，Pan Z ，Xia S ，Shao Q ... -  《-》

Bioinformatics analysis of fibroblasts exposed to TGF‑β at the early proliferation phase of wound repair.

Mi B ，Liu G ，Zhou W ，Lv H ，Zha K ，Liu Y ，Wu Q ，Liu J ... -  《-》