Dataset Information

Bioinformatics analysis and verification of gene targets for benign tracheal stenosis.

ABSTRACT: BACKGROUND:Tracheal injury could cause intratracheal scar hyperplasia which in turn causes benign tracheal stenosis (TS). With the increasing use of mechanical ventilation and ventilator, the incidence of TS is increasing. However, the molecular mechanisms of TS have not been elucidated. It is significant to further explore the molecular mechanisms of TS. METHODS:The repeatability of public data was verified. Differently expressed genes (DEGs) and most significant genes were identified between TS and normal samples. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed. The comparative toxicogenomics database were analyzed. TS patients were recruited and RT-qPCR were performed to verify the most significant genes. RESULTS:There exist strong correlations among samples of TS and normal group. There was a total of 194 DEGs, including 61 downregulated DEGs and 133 upregulated DEGs. GO were significantly enriched in mitotic nuclear division, cell cycle, and cell division. Analysis of KEGG indicated that the top pathways were cell cycle, and p53 pathway. MKI67(OMIM:176741), CCNB1(OMIM:123836), and CCNB2(OMIM:602755) were identified as the most significant genes of TS, and validated by the clinical samples. CONCLUSION:Bioinformatics methods might be useful method to explore the mechanisms of TS. In addition, MKI67, CCNB1, and CCNB2 might be the most significant genes of TS.

SUBMITTER: Li XZ

PROVIDER: S-EPMC7284051 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Bioinformatics analysis and verification of gene targets for benign tracheal stenosis.

Li Xu-Ze XZ Wang Zi-Chen ZC Qiu Yong Y Ma Shu-Xian SX Meng Ling-Bing LB Wu Wen-Hao WH Zhang Pei P Yang Wei W Song Wen-Ping WP Huang Lining L

Molecular genetics & genomic medicine 20200420 6

<h4>Background</h4>Tracheal injury could cause intratracheal scar hyperplasia which in turn causes benign tracheal stenosis (TS). With the increasing use of mechanical ventilation and ventilator, the incidence of TS is increasing. However, the molecular mechanisms of TS have not been elucidated. It is significant to further explore the molecular mechanisms of TS.<h4>Methods</h4>The repeatability of public data was verified. Differently expressed genes (DEGs) and most significant genes were ident ...[more]

PMID: 32309912

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Project description:Objective: To explore the possible biological functions of the differentially expressed genes in patients with benign tracheal stenosis, and to provide a valuable molecular basis for investigating the pathogenesis of benign tracheal stenosis. Method: Whole transcriptome sequencing was performed on blood samples collected from patients with benign tracheal stenosis and normal controls. Differentially expressed mRNA, lncRNA, and circRNA were analyzed using the DESeq2 package. The protein interaction networks for differentially expressed mRNAs were constructed by STRING. The results of gene co-expression network analysis, Starbase database prediction, and differential gene expression were combined to construct a competing endogenous RNA network. The transcription factors of key genes were predicted using the Network Analyst database and a transcription factor-mRNA regulatory network was constructed. The classical pathways, intermolecular interaction networks, and upstream regulatory components of key genes were analyzed using Ingenuity Pathway Analysis (IPA). Finally, the DGIDB database was used to predict the potential therapeutic drugs to target the identified key genes. Result: Based on mRNA, lncRNA and circRNA expression data, we found that differentially expressed mRNAs were enriched in oxygen transport, neutrophil activation, immune response, and oxygen binding. Then the pearson correlation between mRNAs of 46 key genes and lncRNAs and cricRNAs were calculated, and the correlation greater than 0.9 were selected to construct the co-expression network of "mRNA-lncRA" and "mRNA-cricRNA." Moreover, a "lncRNA-miRNA-mRNA" network and a "circRNA-miRNA-mRNA" network were constructed. IPA analysis showed that the 46 key genes were significantly associated with inflammatory activation and acute respiratory distress syndrome. The constructed TF-mRNA regulatory network was composed of 274 nodes and 573 interacting pairs. 251 potential therapeutic drugs were identified from the DGIDB database. Conclusion: This study analyzed the differential genes associated with benign tracheal stenosis and explored the potential regulatory mechanisms, providing a scientific reference for further studies on the pathogenesis of benign tracheal stenosis.

Project description:BackgroundEpithelial ovarian cancer (EOC) is a lethal and aggressive gynecological malignancy. Despite recent advances, existing therapies are challenged by a high relapse rate, eventually resulting in disease recurrence and chemoresistance. Emerging evidence indicates that a subpopulation of cells known as cancer stem-like cells (CSLCs) exists with non-tumorigenic cancer cells (non-CSCs) within a bulk tumor and is thought to be responsible for tumor recurrence and drug-resistance. Therefore, identifying the molecular drivers for cancer stem cells (CSCs) is critical for the development of novel therapeutic strategies for the treatment of EOC.MethodsTwo gene datasets were downloaded from the Gene Expression Omnibus (GEO) database based on our search criteria. Differentially expressed genes (DEGs) in both datasets were obtained by the GEO2R web tool. Based on log2 (fold change) >2, the top thirteen up-regulated genes and log2 (fold change) < -1.5 top thirteen down-regulated genes were selected, and the association between their expressions and overall survival was analyzed by OncoLnc web tool. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathways analysis, and protein-protein interaction (PPI) networks were performed for all the common DEGs found in both datasets. SK-OV-3 cells were cultured in an adherent culture medium and spheroids were generated in suspension culture with CSCs specific medium. RNA from both cell population was extracted to validate the selected DEGs expression by q-PCR. Growth inhibition assay was performed in SK-OV-3 cells after carboplatin treatment.ResultsA total of 200 DEGs, 117 up-regulated and 83 down-regulated genes were commonly identified in both datasets. Analysis of pathways and enrichment tests indicated that the extracellular matrix part, cell proliferation, tissue development, and molecular function regulation were enriched in CSCs. Biological pathways such as interferon-alpha/beta signaling, molecules associated with elastic fibers, and synthesis of bile acids and bile salts were significantly enriched in CSCs. Among the top 13 up-regulated and down-regulated genes, MMP1 and PPFIBP1 expression were associated with overall survival. Higher expression of ADM, CXCR4, LGR5, and PTGS2 in carboplatin treated SK-OV-3 cells indicate a potential role in drug resistance.ConclusionsThe molecular signature and signaling pathways enriched in ovarian CSCs were identified by bioinformatics analysis. This analysis could provide further research ideas to find the new mechanism and novel potential therapeutic targets for ovarian CSCs.

Dataset Information

Bioinformatics analysis and verification of gene targets for benign tracheal stenosis.

Publications

Bioinformatics analysis and verification of gene targets for benign tracheal stenosis.

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