Analysis of gene expression profiles associated with glioma progression

Hu,Guozhang; Wei,Bo; Wang,Lina; Wang,Le; Kong,Daliang; Jin,Ying; Sun,Zhigang

doi:10.3892/mmr.2015.3583

Analysis of gene expression profiles associated with glioma progression

Authors:
- Guozhang Hu
- Bo Wei
- Lina Wang
- Le Wang
- Daliang Kong
- Ying Jin
- Zhigang Sun
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Affiliations: Department of Emergency Medicine, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China, Department of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China, Department of Ophthalmology, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China, Department of Opthalmology, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China, Department of Neurology, Jilin Oilfield General Hospital, Songyuan 131200, P.R. China
Published online on: April 1, 2015 https://doi.org/10.3892/mmr.2015.3583
Pages: 1884-1890
Copyright: © Hu et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 3.0].

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Abstract

The present study aimed to investigate changes at the transcript level that are associated with spontaneous astrocytoma progression, and further, to discover novel targets for glioma diagnosis and therapy. GSE4290 microarray data downloaded from Gene Expression Omnibus were used to identify the differentially expressed genes (DGEs) by significant analysis of microarray (SAM). The Short Time Series Expression Miner (STEM) method was then applied to class these DEGs based on their degrees of differentiation in the process of tumor progression. Finally, EnrichNet was used to perform the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis based on a protein‑protein interaction (PPI) network. A total of 4,506 DEGs were detected, and the number of DEGs was the highest in grade IV cells (2,580 DEGs). These DEGs were classified into nine clusters by the STEM method. In total, 11 KEGG pathways with XD‑scores larger than the threshold (0.96) were obtained. The DEGs enriched in pathways 1 (extracellular matrix‑receptor interaction), 3 (phagosome) and 6 (type I diabetes mellitus) mainly belonged to cluster 5. Pathway 2 (long‑term potentiation), 4 (Vibrio cholerae infection) and 5 (epithelial cell signaling in Helicobacter pylori infection) was involved with DEGs that belonged to different clusters. Significant changes in gene expression occurred during glioma progression. Pathways 1, 3 and 6 may be important for the deterioration of glioma into glioblastoma, and pathways 2, 4 and 5 may have a role at each stage during glioma progression. The associated DEGs, including SV2, NMDAR and mGluRs, may be suitable as biomarkers or therapeutic targets for gliomas.

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