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pmid:32701935
Identification of Biomarkers for Sarcoidosis and Tuberculosis of the Lung Using Systematic and Integrated Analysis.
Min Zhao · Xin Di · Xin Jin · Chang Tian · Shan Cong · Jiaying Liu · Ke Wang
Medical science monitor : international medical journal of experimental and clinical research · 2020 doi:10.12659/MSM.925438
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Complete file
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Both of these diseases affect lungs and lymph nodes and share similar clinical manifestations. However, the underlying mechanisms for the similarities and differences in genetic characteristics of SARC and PTB remain unclear. MATERIAL AND METHODS Three datasets (GSE16538, GSE20050, and GSE19314) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in SARC and PTB were identified using GEO2R online analyzer and Venn diagram software. Functional enrichment analysis was performed using Database for Annotation, Visualization and Integrated Discovery (DAVID) and R packages. Two protein-protein interaction (PPI) networks were constructed using Search Tool for the Retrieval of Interacting Genes database, and module analysis was performed using Cytoscape. Hub genes were identified using area under the receiver operating characteristic curve analysis. RESULTS We identified 228 DEGs, including 56 common SARC-PTB DEGs (enriched in interferon-gamma-mediated signaling, response to gamma radiation, and immune response) and 172 SARC-only DEGs (enriched in immune response, cellular calcium ion homeostasis, and dendritic cell chemotaxis). Potential biomarkers for SARC included CBX5, BCL11B, and GPR18. CONCLUSIONS We identified potential biomarkers that can be used as candidates for diagnosis and/or treatment of patients with SARC.", "claims": [{"id": "claim-method", "statement": "We used the expression data of GSE19314 database to generate the receiver operating characteristic (ROC) curves of the hub genes by R/Bioconductor. 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