Screening recurrent glioblastoma-related genes and analyzing their gene expressions in association with clinicopathological parameters and prognosis

Yi Lin, Ce Wang, Xun Kang, Zhuang Kang, Feng Chen, Bo Jiang, Wenbin Li

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Article number1007-3639(2022)01-0013-11
Pages (from-to)13-23
Number of pages11
JournalChina Oncology
Issue number1
StatePublished - Jan 30 2022


  • Bioinformatics
  • Glioma
  • Histidine metabolism
  • Recurrence
  • Survival

ASJC Scopus subject areas

  • Oncology


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