Identification of differentially expressed RNAs of lung cancer cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Wu Kou-Juey
PROVIDER: S-ECPF-GEOD-57756 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:BackgroundCircular RNAs (circRNAs) may function as the decoys for microRNAs (miRNAs) or proteins, the templates for translation, and the sources of pseudogene generation. The purpose of this study is to determine the diagnostic circRNAs, which are related to lung adenocarcinoma (LUAD), that adsorb miRNAs on the basis of the competing endogenous RNA (ceRNA) hypothesis.MethodsThe differentially expressed circRNAs (DEcircRNAs) in LUAD were revealed by the microarray data (GSE101586 and GSE101684) that were obtained from the Gene Expression Omnibus (GEO) database. The miRNAs that were targeted by the DEcircRNAs were predicted with the CircInteractome, and the target mRNAs of the miRNAs were found by the miRDB and the TargetScan. The ceRNA network was built by the Cytoscape. The potential biological roles and the regulatory mechanisms of the circRNAs were investigated by the Gene Ontology (GO) enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The expression of the host genes of circRNAs was examined by the Ualcan. The survival analysis was performed by the Kaplan-Meier plotter.ResultsIn comparison with normal lung tissues, LUAD tissues contained 7 overlapping cancer-specific DEcircRNAs with 294 miRNA response elements (MREs). Among the 7 DEcircRNAs, 3 circRNAs (hsa_circ_0072088, hsa_circ_0003528, and hsa_circ_0008274) were upregulated and 4 circRNAs (hsa_circ_0003162, hsa_circ_0029426, hsa_circ_0049271, and hsa_circ_0043256) were downregulated. A circRNA-miRNA-mRNA regulatory network, which included 33 differentially expressed miRNAs (DEmiRNAs) and 2007 differentially expressed mRNAs (DEmRNAs), was constructed. These mRNAs were enriched in the biological function of cell-cell adhesion, response to hypoxia, and stem cell differentiation and were involved in the PI3K-Akt signaling, HIF-1 signaling, and cAMP signaling pathways.ConclusionOur results indicated that 7 DEcircRNAs could have diagnostic value for LUAD. Additionally, the circRNAs-mediated ceRNA network might provide a novel perspective into unraveling the pathogenesis and progression of LUAD.
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Project description:Daidzein has been found to significantly inhibit the proliferation of lung cancer cells, while its potential molecular mechanisms remain unclear. To determine the molecular mechanism of daidzein on lung cancer cells, the Capital Bio Technology Human long non-coding (lnc) RNA Array v4, 4×180K chip was used to detect the gene expression profiles of 40,000 lncRNAs and 34,000 mRNAs in a human cancer cell line. Reverse transcription-quantitative (RT-q) PCR analysis was performed to detect the expression levels of target lncRNA and mRNAs in the H1299 cells treated with and without daidzein, using the lncRNA and mRNA gene chip. Bioinformatics analysis was performed to determine the differentially expressed genes from the results of the chip assays. There were 119 and 40 differentially expressed lncRNAs and mRNAs, respectively, that had a 2-fold change in expression level. A total of eight lncRNAs were upregulated in the H1299 lung cancer cells, while 111 lncRNAs were downregulated. Furthermore, five mRNAs were upregulated, and 35 mRNAs were downregulated. A total of six differentially expressed lncRNAs (ENST00000608897.1, ENST00000444196.1, ENST00000608741.1, XR_242163.1, ENST00000505196.1 and ENST00000498032.1) were randomly selected to validate the microarray data, which were consistent with the RT-qPCR analysis results. Differentially expressed mRNAs were enriched in important Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. Taken together, the results of the present study demonstrated that daidzein affected the expression level of lncRNAs in lung cancer cells, suggesting that daidzein may have potential effects on lung cancer cells.
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Project description:BackgroundMonotonically expressed genes (MEGs) are genes whose expression values increase or decrease monotonically as a disease advances or time proceeds. Non-small cell lung cancer (NSCLC) is a multistage progression process resulting from genetic sequences mutations, the identification of MEGs for NSCLC is important.ResultsWith the aid of a feature selection algorithm capable of identifying MEGs - the MFSelector method - two sets of potential MEGs were selected in this study: the MEGs across the different pathologic stages and the MEGs across the risk levels of death for the NSCLC patients at early stages. For the lung adenocarcinoma (AC) subtypes no statistically significant MEGs were identified across pathologic stages, however dozens of MEGs were identified across the risk levels of death. By contrast, for the squamous cell lung carcinoma (SCC) there were no statistically significant MEGs as either stage or risk level advanced.ConclusionsThe pathologic stage of non-small cell lung cancer patients at early stages has no prognostic value, making the identification of prognostic gene signatures for them more meaningful and highly desirable.
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