Dataset Information

Candidate genes and microRNAs for glioma pathogenesis and prognosis based on gene expression profiles.

ABSTRACT: Glioma is the most common malignant brain tumor, and the incidence of glioma demonstrates an upward trend. It is vital to elucidate the pathogenesis of glioma and seek effective therapies. The aim of the present study was to identify the potential gene markers associated with glioma based on GSE31262 gene expression profiles, and to explore the underlying mechanism of glioma progression by analyzing the gene markers. The microarray dataset GSE31262 was downloaded and neural stem cell samples (control group) and glioma samples (glioma group) were analyzed to identify the differentially expressed genes (DEGs) between the two groups. Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using DAVID software. Subsequently, a protein?protein interaction (PPI) network was constructed and important modules were extracted from this network. Additionally, the miRNA?target regulatory network was established. In total, 1377 DEGs with P<0.01 and |log2 fold change| ?2 were identified between the control and glioma groups. The DEGs that were upregulated in glioma samples compared with controls were primarily associated with functions such as the M phase and cell cycle pathway, while the downregulated genes were associated with functions such as nerve impulse and the axon guidance pathway. The results also indicated that certain DEGs, including cyclin?dependent kinase 1 (CDK1) and cadherin 1 (CDH1), had important roles in the PPI network. The MCODE tool in Cytoscape software was used to identify upregulated and downregulated modules in the PPI network, and 5 upregulated and 2 downregulated modules were extracted. Furthermore, the WebGestal online tool was used to identify potential interactions of the upregulated and downregulated genes with microRNAs (miRNA/miR), and miR?135A/B and its two targets, discs large MAGUK scaffold protein 2 and forkhead box O1 (FOXO1), had the highest number of connections in the miRNA?target regulatory network. In addition, cell division cycle 20 and FOXO1 were confirmed to be upregulated in U87 glioma cells compared with normal human astrocytes (HA1800) by reverse transcription?quantitative polymerase chain reaction. In conclusion, M phase function and the axon guidance pathway may be vital for glioma progression. In addition, CDK1 and CDH1 may be associated with the process of glioma. Furthermore, miR?135A/B, and the target FOXO1, may be potential therapy targets for glioma treatment.

SUBMITTER: Xie C

PROVIDER: S-EPMC6102685 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Candidate genes and microRNAs for glioma pathogenesis and prognosis based on gene expression profiles.

Xie Chen C Xu Meng M Lu Dejuan D Zhang Weiguang W Wang Laizang L Wang Hongwei H Li Jianhua J Ren Fubin F Wang Chao C

Molecular medicine reports 20180629 3

Glioma is the most common malignant brain tumor, and the incidence of glioma demonstrates an upward trend. It is vital to elucidate the pathogenesis of glioma and seek effective therapies. The aim of the present study was to identify the potential gene markers associated with glioma based on GSE31262 gene expression profiles, and to explore the underlying mechanism of glioma progression by analyzing the gene markers. The microarray dataset GSE31262 was downloaded and neural stem cell samples (co ...[more]

PMID: 30015885

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Project description:ObjectiveTo explore the mechanism of osteoarthritis (OA) and provide valid biological information for further investigation.MethodsGene expression profile of GSE46750 was downloaded from Gene Expression Omnibus database. The Linear Models for Microarray Data (limma) package (Bioconductor project, http://www.bioconductor.org/packages/release/bioc/html/limma.html) was used to identify differentially expressed genes (DEGs) in inflamed OA samples. Gene Ontology function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were performed based on Database for Annotation, Visualization and Integrated Discovery data, and protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins database. Regulatory network was screened based on Encyclopedia of DNA Elements. Molecular Complex Detection was used for sub-network screening. Two sub-networks with highest node degree were integrated with transcriptional regulatory network and KEGG functional enrichment analysis was processed for 2 modules.ResultsIn total, 401 up- and 196 down-regulated DEGs were obtained. Up-regulated DEGs were involved in inflammatory response, while down-regulated DEGs were involved in cell cycle. PPI network with 2392 protein interactions was constructed. Moreover, 10 genes including Interleukin 6 (IL6) and Aurora B kinase (AURKB) were found to be outstanding in PPI network. There are 214 up- and 8 down-regulated transcription factor (TF)-target pairs in the TF regulatory network. Module 1 had TFs including SPI1, PRDM1, and FOS, while module 2 contained FOSL1. The nodes in module 1 were enriched in chemokine signaling pathway, while the nodes in module 2 were mainly enriched in cell cycle.ConclusionThe screened DEGs including IL6, AGT, and AURKB might be potential biomarkers for gene therapy for OA by being regulated by TFs such as FOS and SPI1, and participating in the cell cycle and cytokine-cytokine receptor interaction pathway.

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Dataset Information

Candidate genes and microRNAs for glioma pathogenesis and prognosis based on gene expression profiles.

Publications

Candidate genes and microRNAs for glioma pathogenesis and prognosis based on gene expression profiles.

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