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OBJECTIVE: To analyze the differentially expressed genes(DEGs), and screen the key genes and signaling pathways in human lung epithelial A549 cells exposed to silica dust using bioinformatics and gene chip. METHODS: The GSE30215 gene expression profiles of A549 cells exposed to silica dust were downloaded from Public Gene Expression Omnibus database developed by the National Center for Biotechnology Information. The DEGs were screened by using GEO2 R analysis tools. Then, the DEGs were imported into the biological information annotation database for Gene Ontology(GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. The protein-protein interaction(PPI) network was constructed with the Search Tool for the Retrieval of Interacting Genes database and visualized using the software Cytoscape. Real-time quantitative polymerase chain reaction(PCR) was used to verify the expression of key DEGs in A549 cells. RESULTS: Of the 52 DEGs screened, 45 were up-regulated and 7 were down-regulated. The results of GO analysis showed that the DEGs were mainly distributed in extracellular region, associated with regulating biological functions such as chemotaxis, transcription factor activity and so on. KEGG pathway enrichment analysis showed that these DEGs were mainly involved in the tumor necrosis factor(TNF) signaling pathway and nucleotide-binding oligomerization domain like receptor signaling pathway. The top 10 key DEGs screened by PPI network were C-C motif chemokine ligand(CCL)2, prostaglandin-endoperoxide synthase 2, interleukin 6, C-X-C motif chemokine ligand(CXCL) 8, CXCL2, jun proto-oncogene, colony stimulating factor 2(CSF2), CCL20, TNF-α induced protein 3(TNFAIP3), and CXCL5. Real-time quantitative PCR results revealed that the changes of key genes were in consistent with the screening results, except the CCL2. CONCLUSION: We found 10 key DEGs that are related to the toxicity caused by exposure to silica dust in A549 cells by bioinformatics. Among them, CSF2, CCL20 and TNFAIP3 may provide new research direction for the mechanisms of the development of multiple pulmonary fibrotic diseases including pneumoconiosis.
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OBJECTIVE: To investigate the differentially expressed microRNAs(miRNAs) in human embryonic lung fibroblast MRC-5 cells stimulated by transforming growth factor-β1(TGF-β1) using microarray chip, and screen for key genes and signaling pathways of fibroblast trans-differentiation. METHODS: The miRNA expression gene chip dataset GSE43992 on TGF-β1 stimulated MRC-5 cells were downloaded from high-throughput Gene Expression Omnibus(GEO) database of National Center for Biotechnology Information of the United States. The R language Limma package was used to screen the differentially expressed miRNAs. Corresponding target genes were predicted by miRWalk database performed by Gene Ontology(GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) signaling pathway enrichment analysis. The protein-protein interaction(PPI) network was constructed by the search tool for the Retrieval of Interacting Genes database. RESULTS: A total of five differentially expressed miRNAs were identified, including four up-regulated miRNAs and one down-regulated miRNA; and 42 corresponding differentially expressed target genes were predicted. GO analysis indicated that the target genes were significantly enriched in collagen catabolic process, extracellular matrix organization, membrane organization, collagen fibril organization, and cellular response to amino acid stimulus. The results of KEGG pathway analysis showed that the signaling pathways corresponding to miRNAs and target genes were mainly concentrated in 18 signaling pathways, that were mainly related to the age-ethnic signaling pathways and protein digestion and absorption miRNAs in tumors and diabetic complications. The core genes transfected into the myofibroblasts by the three fibroblasts screened by the PPI network were threonine kinase 1, estrogen receptor 1 and β-catenin. CONCLUSION: Five differentially expressed miRNAs, 42 target genes, 18 signaling pathways, and 3 core genes related to TGF-β1-induced MRC-5 cell trans-differentiation were screened. It can provide new reference for the treatment and research of many diseases including pneumoconiosis and pulmonary fibrosis.
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Liver disorders such as hepatitis, cirrhosis and hepatocellular carcinoma are a series of the most life threatening diseases along with extensive inflammatory cellular infiltrations. Macrophage has been proved to be key regulators and initiators of inflammation, and long non-coding RNAs (lncRNAs) are recommended to play critical roles in the occurrence and development of a variety of diseases. To uncover the role of macrophage in liver disorders via lncRNA sequencing method, we first applied a lncRNA classification pipeline to identify 1247 lncRNAs represented on the Affymetrix Mouse Genome 430/430A 2.0 array. We then analyzed the lncRNA expression patterns in a set of previously published gene expression profiles of silica particle exposed macrophages and liver respectively, and identified and validated sets of differentially expressed lncRNAs shared by macrophages and liver. The functional enrichment analysis of these lncRNAs was processed on the basis of their expression signatures, three aspects including cis, trans and co-acting proteins were proposed. This is the first time to correlate macrophage with liver disorders via co-expressed lncRNAs. Our findings indicated that roles of macrophage in liver disorders were double-edged, the differentially expressed lncRNAs and their corresponding regulatory genes or proteins may serve as potential diagnostic biomarkers and therapeutic targets.
