How to cite item

MiR-195 restrains lung adenocarcinoma by regulating CD4+ T cell activation via the CCDC88C/Wnt signaling pathway: a study based on the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and bioinformatic analysis

  
@article{ATM26384,
	author = {Cheng Yuan and Liyang Xiang and Rui Bai and Kuo Cao and Yanping Gao and Xueping Jiang and Nannan Zhang and Yan Gong and Conghua Xie},
	title = {MiR-195 restrains lung adenocarcinoma by regulating CD4+ T cell activation via the CCDC88C/Wnt signaling pathway: a study based on the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and bioinformatic analysis},
	journal = {Annals of Translational Medicine},
	volume = {7},
	number = {12},
	year = {2019},
	keywords = {},
	abstract = {Background: To systematically identity microRNA signatures, as well as miRNA-gene axes, for lung adenocarcinoma (LUAD) and to explore the potential biomarkers and mechanisms associated with the LUAD immune responses.
Methods: LUAD-related data were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), and these data were then used to identify the differentially expressed miRNAs that were downregulated in tumor tissues. Summary receiver operating characteristic curve analysis, survival analysis and meta-analysis were applied to evaluate the clinical significance and diagnostic value of the identified miRNAs. The presumed targets of the integrated-signature miRNAs were identified via 3 different target prediction algorithms: TargetScan, miRDB and DIANA-TarBase. Immunologic signature gene sets were enriched by gene set enrichment analysis (GSEA). Tumor-infiltrating lymphocytes were profiled by the Tumor IMmune Estimation Resource (TIMER). After pathway enrichment analysis using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, pathway-gene networks were constructed using Cytoscape software.
Results: After integrated analysis of 4 GEO data sets (GSE48414, GSE51853, GSE63805 and GSE74190) and TCGA databases, miR-195 was identified as a potential clinical diagnostic marker. A total of 287 miR-195 target genes were screened, and 3 functional gene sets (GSE13485, GSE21379 and GSE29164) were enriched. GSE21379 was associated with the upregulation of CD4+ T cells in tumors, and the core genes were validated via the TIMER database. The CCDC88C expression level was significantly correlated with CD4+ T cell activation (partial.cor =0.437, P},
	issn = {2305-5847},	url = {http://atm.amegroups.com/article/view/26384}
}