Identification of Key Genes of Airway Epithelial Cells in Asthma Patients by Bioinformatics-based Analysis / 中国医科大学学报

Objective We aimed to identify key genes and pathways of airway epithelial cells involved in bronchial asthma by comparing genetic information in the databases for patients with bronchial asthma and normal people. Methods To find differentially expressed genes (DEGs), mRNA microarray dataset, GSE43696, of airway epithelial cells in asthma was analyzed by GE02R. Functional and pathway enrichment analyses were performed for DEGs using the DAVID database. The protein-protein interaction networks were established using STRING to identify key genes and important complexes. Results A total of 355 DEGs were identified; of which, 130 were up-regulated and 225, down-regulated. The genes identified were involved in cell movement, growth factor binding, and ion channel activity. Nine key genes were recognized, including BDNF, ERBB2 IL6, VEGFA, KIT, ADCY4, PRKAR2B, CCR6, and NMU. Conclusion All nine key genes identified play important roles in asthma and serve as potential targets for treatment of bronchial asthma.

Exploration of gene functions for esophageal squamous cell carcinoma using network-based guilt by association principle

Gene networks have been broadly used to predict gene functions based on guilt by association (GBA) principle. Thus, in order to better understand the molecular mechanisms of esophageal squamous cell carcinoma (ESCC), our study was designed to use a network-based GBA method to identify the optimal gene functions for ESCC. To identify genomic bio-signatures for ESCC, microarray data of GSE20347 were first downloaded from a public functional genomics data repository of Gene Expression Omnibus database. Then, differentially expressed genes (DEGs) between ESCC patients and controls were identified using the LIMMA method. Afterwards, construction of differential co-expression network (DCN) was performed relying on DEGs, followed by gene ontology (GO) enrichment analysis based on a known confirmed database and DEGs. Eventually, the optimal gene functions were predicted using GBA algorithm based on the area under the curve (AUC) for each GO term. Overall, 43 DEGs and 67 GO terms were gained for subsequent analysis. GBA predictions demonstrated that 13 GO functions with AUC>0.7 had a good classification ability. Significantly, 6 out of 13 GO terms yielded AUC>0.8, which were determined as the optimal gene functions. Interestingly, there were two GO categories with AUC>0.9, which included cell cycle checkpoint (AUC=0.91648), and mitotic sister chromatid segregation (AUC=0.91597). Our findings highlight the clinical implications of cell cycle checkpoint and mitotic sister chromatid segregation in ESCC progression and provide the molecular foundation for developing therapeutic targets.

Differential expression of circular RNA in patients with chronic HBV infection of different stages and related bioinformatic analysis / 中华临床感染病杂志

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.