Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33468161", "kind": "science-record", "revision": 7, "content_hash": "sha256:0edf7df11bc943d98cb596e937751540a17892a2d87588f9ec4f062442654d72", "created_at": "2026-11-01T15:41:23Z", "updated_at": "2026-11-01T22:02:58Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis.", "doi": "10.1186/s12967-020-02698-x", "pmid": "33468161", "authors": ["Xingwang Zhao", "Longlong Zhang", "Juan Wang", "Min Zhang", "Zhiqiang Song", "Bing Ni", "Yi You"], "journal": "Journal of translational medicine", "year": 2021, "abstract": "BACKGROUND: Systemic lupus erythematosus (SLE) is a multisystemic, chronic inflammatory disease characterized by destructive systemic organ involvement, which could cause the decreased functional capacity, increased morbidity and mortality. Previous studies show that SLE is characterized by autoimmune, inflammatory processes, and tissue destruction. Some seriously-ill patients could develop into lupus nephritis. However, the cause and underlying molecular events of SLE needs to be further resolved.\nMETHODS: The expression profiles of GSE144390, GSE4588, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between SLE and healthy samples. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed by metascape etc. online analyses. The protein-protein interaction (PPI) networks of the DEGs were constructed by GENEMANIA software. We performed Gene Set Enrichment Analysis (GSEA) to further understand the functions of the hub gene, Weighted gene co-expression network analysis (WGCNA) would be utilized to build a gene co-expression network, and the most significant module and hub genes was identified. CIBERSORT tools have facilitated the analysis of immune cell infiltration patterns of diseases. The receiver operating characteristic (ROC) analyses were conducted to explore the value of DEGs for SLE diagnosis.\nRESULTS: In total, 6 DEGs (IFI27, IFI44, IFI44L, IFI6, EPSTI1 and OAS1) were screened, Biological functions analysis identified key related pathways, gene modules and co-expression networks in SLE. IFI27 may be closely correlated with the occurrence of SLE. We found that an increased infiltration of moncytes, while NK cells resting infiltrated less may be related to the occurrence of SLE.\nCONCLUSION: IFI27 may be closely related pathogenesis of SLE, and represents a new candidate molecular marker of the occurrence and progression of SLE. 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