Dataset Information

Identification of microRNA differentially expressed in three subtypes of non-small cell lung cancer and in silico functional analysis.

ABSTRACT: Emerging studies demonstrated that miRNAs played fundamental roles in lung cancer. In this study, we attempted to explore the clinical significance of the miRNA signature in different histological subtypes of non-small cell lung cancer (NSCLC). Three miRNome profiling datasets (GSE19945, GSE25508 and GSE51853) containing lung squamous cell carcinoma (SCC), lung adenocarcinoma (ADC) and large cell lung cancer (LCLC) samples were obtained for bioinformatics and survival analysis. Moreover, pathway enrichment and coexpression network were performed to explore underlying molecular mechanism. MicroRNA-375 (miR-375), miR-203 and miR-205 were identified as differentially expressed miRNAs (DEmiRNAs) which distinguished SCC from other NSCLC subtypes. Pathway enrichment analysis suggested that Hippo signaling pathway was combinatorically affected by above mentioned three miRNAs. Coexpression analysis of three miRNAs and the Hippo signaling pathway related genes were conducted based on another dataset, GSE51852. Four hub genes (TP63, RERE, TJP1 and YWHAE) were identified as the candidate targets of three miRNAs, and three of them (TP63, TJP1 and YWHAE) were validated to be downregulated by miR-203 and miR-375, respectively. Finally, survival analysis further suggested the prognostic value of three-miRNA signature in SCC patients. Taken together, our study compared the miRNA profiles among three histological subtypes of NSCLC, and suggested that a three-miRNA signature might be potential diagnostic and prognostic biomarkers for SCC patients.

SUBMITTER: Hu Y

PROVIDER: S-EPMC5650362 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Identification of microRNA differentially expressed in three subtypes of non-small cell lung cancer and in silico functional analysis.

Hu Yanjun Y Wang Luqing L Gu Jingxian J Qu Kai K Wang Yunxia Y

Oncotarget 20170812 43

Emerging studies demonstrated that miRNAs played fundamental roles in lung cancer. In this study, we attempted to explore the clinical significance of the miRNA signature in different histological subtypes of non-small cell lung cancer (NSCLC). Three miRNome profiling datasets (GSE19945, GSE25508 and GSE51853) containing lung squamous cell carcinoma (SCC), lung adenocarcinoma (ADC) and large cell lung cancer (LCLC) samples were obtained for bioinformatics and survival analysis. Moreover, pathway ...[more]

PMID: 29088807

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Project description:Non-small cell lung cancer (NSCLC) is a leading cause of mortality worldwide. However, the pathogenesis of NSCLC remains to be fully elucidated. Therefore, the present study aimed to explore the differential expression of mRNAs and microRNAs (miRNAs/miRs) in NSCLC and to determine how these RNA molecules interact with one another to affect disease progression. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were identified from the GSE18842, GSE32863 and GSE29250 datasets downloaded from the Gene Expression Omnibus (GEO database). Functional and pathway enrichment analysis were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. STRING, Cytoscape and MCODE were applied to construct a protein-protein interaction (PPI) network and to screen hub genes. The interactions between miRNAs and mRNAs were predicted using miRWalk 3.0 and a miRNA-mRNA regulatory network was constructed. The prognostic value of the identified hub genes was then evaluated via Kaplan-Meier survival analyses using datasets from The Cancer Genome Atlas. A total of 782 DEGs and 46 DEMs were identified from the 3 GEO datasets. The enriched pathways and functions of the DEGs and target genes of the DEMs included osteoclast differentiation, cell adhesion, response to a drug, plasma membrane, extracellular exosome and protein binding. A subnetwork composed of 11 genes was extracted from the PPI network and the genes in this subnetwork were mainly involved in the cell cycle, cell division and DNA replication. A miRNA-gene regulatory network was constructed with 247 miRNA-gene pairs based on 6 DEMs and 210 DEGs. Kaplan-Meier survival analysis indicated that the expression of ubiquitin E2 ligase C, cell division cycle protein 20, DNA topoisomerase II?, aurora kinase A and B, cyclin B2, maternal embryonic leucine zipper kinase, slit guidance ligand 3, phosphoglucomutase 5, endomucin, cysteine dioxygenase type 1, dihydropyrimidinase-like 2, miR-130b, miR-1181 and miR-127 was significantly associated with overall survival of patients with lung adenocarcinoma. In the present study, a miRNA-mRNA regulatory network in NSCLC was established, which may provide future avenues for scientific exploration and therapeutic targeting of NSCLC.

Dataset Information

Identification of microRNA differentially expressed in three subtypes of non-small cell lung cancer and in silico functional analysis.

Publications

Identification of microRNA differentially expressed in three subtypes of non-small cell lung cancer and in silico functional analysis.

Similar Datasets

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