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

Xie,Chen; Xu,Meng; Lu,Dejuan; Zhang,Weiguang; Wang,Laizang; Wang,Hongwei; Li,Jianhua; Ren,Fubin; Wang,Chao

doi:10.3892/mmr.2018.9231

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

Authors:
- Chen Xie
- Meng Xu
- Dejuan Lu
- Weiguang Zhang
- Laizang Wang
- Hongwei Wang
- Jianhua Li
- Fubin Ren
- Chao Wang
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Affiliations: Department of Minimally Invasive Neurosurgery, Fourth Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China, Department of Neurosurgery, First People's Hospital of Heihe City, Heihe, Heilongjiang 164300, P.R. China, Department of Neurology, Fourth Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China, Department of Neurosurgery, The Cancer Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China
Published online on: June 29, 2018 https://doi.org/10.3892/mmr.2018.9231
Pages: 2715-2723
Copyright: © Xie et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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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.

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