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
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Identification of hub ferroptosis-related genes and immune infiltration in lupus nephritis using bioinformatics.
Lupus nephritis (LN) is one of the most severe and more common organ manifestations of the autoimmune disease, systemic lupus erythematosus. Ferroptosis, a novel type of programmed cell death, so far its role in LN remains uncertain. In the present study, we explored the role of ferroptosis in LN and its relationship with the immune response. The GSE112943 LN dataset was downloaded from the Gene Expression Omnibus database. Ferroptosis-Related Genes (FRGs) that drive, suppress or mark ferroptosis were retrieved from the public FerrDb database. The gene expression matrix of the GSE112943 dataset was analyzed with the "limma" package in R to obtain differentially expressed genes (DEGs) between LN and healthy samples. Subsequently, the crossover genes between DEGs and FRGs were identified as differentially expressed ferroptosis-related genes (DE-FRGs). Protein-protein interaction (PPI) network analysis, visualization, and identification of hub lupus nephritis ferroptosis-related genes (LN-FRGs) were performed with STRING and Cytoscape, while their Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were determined with the clusterProfiler package. Immune cell infiltration was calculated with CIBERSORT. The relationship between hub LN-FRGs and immune-infiltrated cells in LN was determined by Pearson correlation. A total of 96 DE-FRGs and 8 hub LN-FRGs (KRAS, PIK3CA, EGFR, MAPK14, SRC, MAPK3, VEGFA, and ATM) were identified. GO and KEGG functional classification indicated these genes enrichment in apoptotic process, programmed cell death, autophagy-animal, FoxO signaling pathway, relaxin signaling pathway, and VEGF signaling pathway. Infiltration matrix analysis of immune cells showed abundant Monocytes and M0/M1/M2 macrophages in LN kidney tissues. Correlation analysis revealed 8 hub LN-FRGs associated with immune-infiltrated cells in LN. In summary, overproduction of ROS and abnormal infiltration of immune cells would be implicated in the LN caused by ferroptosis. 8 hub lupus nephritis ferroptosis-related genes (LN-FRGs) which might be good biomarkers of ferroptosis in LN were identified in this study. These findings point to the immune response playing an important role in LN caused by ferroptosis via mutual regulation between hub LN-FRGs and immune-infiltrated cells.
Hu W
，Chen X
《Scientific Reports》
Bioinformatic analysis reveals that the OAS family may play an important role in lupus nephritis.
Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. However, the molecular mechanisms of LN remain unclear. The lack of understanding hinders the development of specific targeted therapy for this progressive disease.
In the present study, we used bioinformatics analysis of gene expression profiles from the Gene Expression Omnibus to identify novel targets and potential biomarkers for LN.
A GSE32591 dataset, which included 31 LN glomerular biopsy tissues and 14 living donors' glomerular tissues, was downloaded for further analysis. Differentially expressed genes in LN were analyzed by the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for the differentially expressed genes by using the Disease Ontology Semantic and Enrichment and the clusterProfiler software. The protein-protein interaction (PPI) network was then formed using STRING online tool.
440 genes, including 310 upregulated genes and 130 downregulated genes, were found as differentially expressed genes. GO and KEGG analyses revealed that immune response is significantly enriched in such genes. The PPI network showed that ISG15, MX1, OAS1, OAS2, and OAS3 were the hub genes enriched in LN. Along with literature review, the OAS family genes were revealed to be closely associated with LN progression.
our studies provided new insight into the molecular pathogenesis of LN. The OAS family may play an important role in LN and act as a novel molecular candidate for the further study of LN.
Cao Y
，Mi X
，Wang Z
，Zhang D
，Tang W
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ResearchGate
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钛学术
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