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Objective To screen key autophagy-related genes in alcoholic hepatitis (AH) and investigate potential biomarkers and therapeutic targets for AH. Methods Two AH gene chips in Gene Expression Omnibus (GEO) and autophagy-related data sets obtained from MSigDB and GeneCards databases were used, and the key genes were verified and obtained by weighted gene co-expression network analysis (WGCNA). The screened key genes were subject to gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI) and immune infiltration analyses. Messenger RNA (mRNA)- microRNA (miRNA) network was constructed to analyze the expression differences of key autophagy-related genes during different stages of AH, which were further validated by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) in the liver tissues of AH patients and mice. Results Eleven autophagy-related genes were screened in AH (EEF1A2, CFTR, SOX4, TREM2, CTHRC1, HSPB8, TUBB3, PRKAA2, RNASE1, MTCL1 and HGF), all of which were up-regulated. In the liver tissues of AH patients and mice, the relative expression levels of SOX4, TREM2, HSPB8 and PRKAA2 in the AH group were higher than those in the control group. Conclusions SOX4, TREM2, HSPB8 and PRKAA2 may be potential biomarkers and therapeutic targets for AH.
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Objective::Bioinformatic analysis was used to compare the gene expression profile between asthma patients and healthy people, and the gene characteristics of asthma were preliminarily identified and the potential mechanism and drugs were revealed. Method::The GSE74986 gene expression profile was downloaded from the gene expression omnibus (GEO) and the differentially expressed genes (DEGs) were analyzed by GEO2R. Then the gene heat map of DEGs was made by Morpheus, and their gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis were performed by DAVID 6.8. Moreover, the protein-protein interaction (PPI) network and hub genes were constructed by String 10.5. Finally, the significant modules were analyzed by MCODE in Cytoscape 3.6.1, small molecule drugs related to asthma were screened through Coremine Medical. Result::A total of 510 DEGs were screened, including 29 up-regulated genes and 481 down-regulated genes. DEGs were mainly involved in these biological processes and pathways, including chromatin silencing, transcriptional regulation of RNA polymerase Ⅱ promoter, protein transport, messenger RNA (mRNA) processing, RNA splicing, ubiquitin-mediated proteolysis, protein processing in the endoplasmic reticulum, RNA transport, and myeloid differentiation factor (MyD)-dependent Toll-like receptor signaling pathway, platelet activation, nucleotide binding oligomerization domain (NOD)-like receptor signaling pathway and so on. A total of 9 hub genes were obtained, including T-complex protein 1 subunit theta (CCT8), T-complex protein 1 subunit alpha (TCP1), 26S protease regulatory subunit S10B (PSMC6), heat shock protein 90 alpha (HSP90A)A1, cell cycle protein C (CCNC), HSP90AB1, 26S proteasome non-ATPase regulatory subunit 6 (PSMD6), ubiquitin-specific protease 14 (USP14) and eukaryotic translation initiation factor 4E (EIF4E). Two important modules were obtained. The genes in two modules mainly involved these biological process, such as splice, ubiquitin-mediated proteolysis, protein modification, RNA modification and so on. Some potential molecular drugs for the treatment of asthma, such as anisomycin and genistein, have been developed. Conclusion::DEGs and hub genes can contribute to understanding the molecular mechanism of asthma and providing potential therapeutic targets and drugs for the diagnosis and treatment of asthma.
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@# Objective: To identify the differentially expressed genes (DEGs) between hepatocellular carcinoma (HCC) tissues and normal liver tissues by bioinformatic methods, and to explore the intrinsic mechanism of these candidate genes involving in the occurrence and development of HCC from transcriptome level as well as the clinical significance of their associations with the prognosis of HCC patients. Methods: Gene expression profiles of GSE45267, GSE64041, GSE84402 and TCGA were downloaded from GEO (Gene Expression Omnibus) and TCGA(The Cancer GenomeAtlas), respectively. R software and Bioconductor packages were used to identify the DEGs between HCC tissues and para-cancer tissues, and then Gene Ontology (GO) Enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Protein-Protein Interaction (PPI) network analysis and survival analysis were performed. Results: Forty-six up-regulated genes and 154 down-regulated genes were screened out,and GO enrichment analysis showed that these DEGs were mainly related to cell division, proliferation, cycle regulation, oxidation-reduction process and certain metabolic pathways. KEGG pathway analysis revealed that DEGs were mainly involved in tryptophan metabolism, retinol metabolism and other metabolic pathways as well as p53 pathway. Over-expression of a panel of up-regulated genes (CCNA2, CDK1, DLGAP5, KIF20A, KPNA2 and MELK) was shown to be significantly negatively correlated with the prognosis of HCC patients in the TCGA dataset (all P<0.01). Conclusion: A set of up-regulated hub genes that are negatively correlated with prognosis will provide potential guiding value for the clinical research on the diagnosis and treatment of HCC.
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Objective:To analyze the known mechanism of toxicology and predict the unknown toxicity in Asari Radix et Rhizoma sinensis by establishing the network relationship of compound, protein, gene and toxicant reaction. Method:After comparing the Asari Radix et Rhizoma candidate compounds obtained from the traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) database and the toxicological information obtained from the Comparative Toxicogenomics Database(CTD) database, we screened out 13 toxic components from Asari Radix et Rhizoma. And use the Pharm Mapper Server website to find the detailed information of target proteins of the 13 components. The network structure of these 13 chemical components and their corresponding target proteins were drawn by using Cytospace software, and several target proteins with the highest degree of association were found. ClueGO+CluePedia plug-in of Cytospace software was applied in gene ontology(GO) enrichment analysis of genes and kyoto encyclopedia of genes and genomes(KEGG) pathway enrichment analysis, so as to determine the pathways through which toxic substances in Asari Radix et Rhizoma might be harmful to human body. Result:The toxic substances in Asari Radix et Rhizoma may induce tumor and cancer formation through p53 signaling pathway, interleukin(IL)-17 signaling pathway, nuclear factor(NF)-kappa B signaling pathway, tumor necrosis factor(TNF)-signaling pathway. Asari Radix et Rhizoma could inhibit the central nervous system by regulating apoptosis pathways and neurons, and may also cause other autoimmune diseases by IL-17, TNF-α pathway and apoptosis regulation. Conclusion:This study preliminarily explores related mechanisms of toxicity of Asari Radix et Rhizoma,this method can be used to predict toxicity and explain toxicity mechanism of traditional Chinese medicine.
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Objective To investigate the differential expression of circular RNA ( circRNA ) in patients with chronic HBV infection of different stages.Methods Seven patients with chronic HBV infection admitted in Taizhou People's Hospital from October 2014 to October 2015 were enrolled, including 4 with chronic hepatitis B ( CHB ) and 3 chronic HBV carriers;3 healthy subjects served as controls. Peripheral blood mononuclear cells (PBMCs) were separated,and the expression of circRNA molecules in PBMCs were detected by new generation of circRNA microarray and validated by fluorescent quantitative PCR.The interaction sites between circRNA and miRNA were predicted with Arraystar miRNA target prediction software.Target genes regulated by the circRNA related to miRNA were analyzed by Gene oncology (Go) and Kyoto encyclopedia of genes and genomes (KEGG) analysis.SPSS 17.0 software was used for statistical analysis.Results Compared with the healthy controls , 137 circRNA molecules of differential expression were found in patients with chronic hepatitis B , of which 89 were up-regulated and 48 were down-regulated; while 444 circRNA molecules of differential expression , of which 130 were up-regulated (>5 fold in 34 ) and 314 down-regulated , were found in chronic HBV carriers.Compared with chronic HBV carriers , 1041 circRNA molecules of differential expression were found in CHB patients , including 663 up-regulated and 378 down-regulated (>5 fold in 54).There were many miRNA responsive elements which complementary with seed regions on miRNA in different circRNA molecules.Target gene analysis demonstrated that 533 target genes regulated by hsa_circ_0038646 were related to miRNAs , 249 target genes found in hsa_circ_0087354 were related to microRNAs.GO analysis showed that function of target genes regulated by hsa_circ_0038646 related to miRNA mainly enriched in activin binding.Function of target genes regulated by hsa_circ_0087354 related to miRNA mainly enriched in armadillo repeat domain binding.KEGG analysis showed that hsa_circ_0038646 molecules related to miRNA mainly involved in T cell receptor , estrogen receptor signaling pathway and so on.Hsa_circ_0087354 molecules related to miRNA mainly involved in adherens junction , MAPK signaling pathway and so on. Conclusion There are differential expressions of circRNA in patients at different clinical stages of chronic HBV infection , which might be involved in immune regulation of chronic HBV infection through the regulation of multiple target genes and signaling pathways.