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Screening recurrent glioblastoma-related genes and analyzing their gene expressions in association with clinicopathological parameters and prognosis
China Oncology
2022, 32 (1):
13-23.
DOI: 10.19401/j.cnki.1007-3639.2022.01.002
Background and purpose: Glioma is the most common and malignant primary brain tumor in the central nervous system (CNS). Glioblastoma is highly malignant and aggressive, and the prognosis of patients with recurrent glioblastoma is very poor. This study aimed to screen the genes related to the recurrent glioblastoma, and analyze the relationship between their expressions, clinicopathological parameters and prognosis in glioma. Methods: By mining the relevant datasets of the primary and recurrent cases of glioblastoma in the GEO database, the differentially expressed gene (DEG) in the samples of primary and recurrent glioblastomas were screened and analyzed. All DEGs analyses were carried out in ontology function and pathway enrichment. Protein-protein interaction (PPI) network was constructed and used for screening Hub gene. Key genes were intersected by PPI network and Venn diagram, and the Gene Expression Profiling Interactive Analysis (GEPIA) and Chinese Glioma Genome Atlas (CGGA) database were analyzed for association of key gene expressions and survival status. Key genes were furtherly analyzed to determine the relationship between their expressions and clinicopathological parameters of glioma. Results: There were 40 DEG screened in the dataset GSE62153, including 34 up-regulated genes and 6 down-regulated genes. There were 19 DEG screened in the dataset GSE58399, including 16 up-regulated genes and 3 down-regulated genes. Go functional analyses showed that the DEG of GSE62153 were mainly involved in 11 physiological processes, such as central nervous system development, myelin sheath, actin binding, central nervous system myelination. The DEG of GSE58399 were mainly enriched in the positive regulation of epithelial cell migration. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment showed that the datasets GSE62153 and GSE58399 were both enriched in histidine metabolism. By using the STRING database, the core of PPI network was constructed with 20 protein molecules. A total of 10 hub genes were screened, including MOBP, OPALIN, ERMN, PLP1, MOG, CLDN11, ASPA, TMEM125, KLK6 and NKX6-2 gene. The key genes for recurrent glioblastoma were ERMN, MOG and MOBP gene. Based on analyses using The Cancer Genome Atlas (TCGA) and CGGA databases, the prognosis of patients with high expressions of ERMN, MOG and MOBP was favorable compared with the low expression group. The expression levels of key genes in glioblastoma were lower compared with the control tissues (P<0.001). There were significant differences in the expressions of ERMN, MOG and MOBP gene among different World Health Organization (WHO) grades (WHO Ⅱ, Ⅲ and Ⅳ) (P<0.001). As the grade of glioblastoma increased, the expressions of ERMN, MOG and MOBP were decreased gradually. The expressions of ERMN, MOG and MOBP gene were correlated with WHO classification, isocitrate dehydrogenase (IDH) status and clinicopathological characteristics (P<0.001). The expression of MOBP gene was correlated with age (P<0.001) and MGMT methylation status (P=0.022). Conclusion: ERMN, MOG and MOBP gene may function as tumor suppressor genes and participate in the recurrence of glioblastoma. The histidine metabolism pathway may be related to the sensitivity of methotrexate treatment. ![]()
Fig. 6
mRNA expression of ERMN, MOG and MOBP genes in control tissues and glioma tissues
N: Control tissues; T: Glioma tissues. A: mRNA expression of ERMN gene in control tissues and glioma tissues; B: mRNA expression of MOG gene in control tissues and glioma tissues; C: mRNA expression of MOBP gene in control tissues and glioma tissues; D: mRNA expression of ERMN gene in different WHO grades of glioma; E: mRNA expression of MOG gene in different WHO grades of glioma; F: mRNA expression of MOBP gene in different WHO grades of glioma. *: P<0.05, compared with control tissues.
Extracts from the Article
通过GEPIA分析ERMN、MOG和MOBP基因在胶质瘤中的表达情况。ERMN、MOG和MOBP基因在低级别胶质瘤和对照组织之间的表达水平差异无统计学意义,而在胶质母细胞瘤和对照组织之间差异有统计学意义(图6)。ERMN、MOG和MOBP基因在胶质母细胞瘤组织内的表达水平低于对照组织。研究进一步通过CGGA数据库分析ERMN、MOG和MOBP基因在肿瘤不同分级(WHOⅡ、Ⅲ和Ⅳ级)组织间的表达情况,结果显示,ERMN、MOG和MOBP基因在不同分级组织内的表达差异有统计学意义(P<0.001),且随着胶质母细胞瘤的级别升高,ERMN、MOG和MOBP基因的表达逐渐降低(图6)。
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