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Bioinformatics analysis to determine the prognostic value and prospective pathway signaling of miR-126 in non-small cell lung cancer
Author(s) -
Zichen Jiao,
Ao Yu,
Xiaofeng He,
Yulong Xuan,
He Zhang,
Guojun Wang,
Minke Shi,
Tao Wang
Publication year - 2020
Publication title -
annals of translational medicine
Language(s) - English
Resource type - Journals
eISSN - 2305-5847
pISSN - 2305-5839
DOI - 10.21037/atm-20-7520
Subject(s) - lung cancer , pathway analysis , bioinformatics , microrna , signal transduction , value (mathematics) , oncology , medicine , cancer research , prospective cohort study , cancer , computational biology , biology , genetics , gene , computer science , gene expression , machine learning
BackgroundMicroRNAs (miRNAs) have been demonstrated to play crucial roles in the initiation and development of non-small cell lung cancer (NSCLC). However, further investigation of the specific role of miR-126 in NSCLC is still required.MethodsAn analysis of miR-126 expression in NSCLC was carried out using the Gene Expression Omnibus (GEO) database, and a literature review was also performed. The differentially expressed genes (DEGs) in three mRNA datasets, GSE18842, GSE19804, and GSE101929, from GEO were identified. Following the prediction of hsa-miR-126-5p target genes by TargetScan, the overlap of miR-126 target genes with DEGs in NSCLC was examined. After that, Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed. Finally, an analysis to identify the impact of hub genes on the prognosis of NSCLC was carried out on the basis of a protein-protein interaction (PPI) network constructed using STRING and Cytoscape.ResultsThe data in the literature review revealed a trend that miR126 was downregulated in NSCLC. The number of both NSCLC-related and miR-126-related DEGs was 187. Dozens of DEGs were significantly enriched in biological regulation, cell membrane binding, and signal receptor binding. In the PPI network analysis, 3 of 10 identified hub genes, namely NCAPG, MELK, and KIAA0101, were obviously related to poor prognosis in NSCLC; the survival rate was low among patients with high expression levels of these genes. Furthermore, through network analysis, TPX2, HMMR, and ANLN were identified as recessive miR-126-related genes that may be involved in NSCLC.ConclusionsMiR-126 plays an essential role in the biological processes of NSCLC through binding to target genes and influences the prognosis of patients with the disease.

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