Identification of Core Genes and Screening of Potential Targets in Glioblastoma Multiforme by Integrated Bioinformatic Analysis.

Ji’An Yang,Qian Yang

doi:10.3389/fonc.2020.615976

Abstract

Glioblastoma multiforme is the most common primary intracranial malignancy, but its etiology and pathogenesis are still unclear. With the deepening of human genome research, the research of glioma subtype screening based on core molecules has become more in-depth. In the present study, we screened out differentially expressed genes (DEGs) through reanalyzing the glioblastoma multiforme (GBM) datasets GSE90598 from the Gene Expression Omnibus (GEO), the GBM dataset TCGA-GBM and the low-grade glioma (LGG) dataset TCGA-LGG from the Cancer Genome Atlas (TCGA). A total of 150 intersecting DEGs were found, of which 48 were upregulated and 102 were downregulated. These DEGs from GSE90598 dataset were enriched using the overrepresentation method, and multiple enriched gene ontology (GO) function terms were significantly correlated with neural cell signal transduction. DEGs between GBM and LGG were analyzed by gene set enrichment analysis (GSEA), and the significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in synapse signaling and oxytocin signaling pathways. Then, a protein-protein interaction (PPI) network was constructed to assess the interaction of proteins encoded by the DEGs. MCODE identified 2 modules from the PPI network. The 11 genes with the highest degrees in module 1 were designated as core molecules, namely, GABRD, KCNC1, KCNA1, SYT1, CACNG3, OPALIN, CD163, HPCAL4, ANK3, KIF5A, and MS4A6A, which were mainly enriched in ionic signaling-related pathways. Survival analysis of the GSE83300 dataset verified the significant relationship between expression levels of the 11 core genes and survival. Finally, the core molecules of GBM and the DrugBank database were assessed by a hypergeometric test to identify 10 drugs included tetrachlorodecaoxide related to cancer and neuropsychiatric diseases. Further studies are required to explore these core genes for their potentiality in diagnosis, prognosis, and targeted therapy and explain the relationship among ionic signaling-related pathways, neuropsychiatric diseases and neurological tumors.

Highlights

Neuroepithelial tumors are collectively referred to as gliomas, which represent approximately 30% of all primary brain and other central nervous system (CNS) tumors and are the most common intracranial malignancies
As early as 2002, some researchers developed a classification system based on DNA microarray gene expression data
According to gene expression characteristics, childhood medulloblastoma can be distinguished from other brain tumors, including primitive neuroectodermal tumors (PNETs), atypical teratoid/rhabdoid tumors (AT/RTs) and malignant gliomas [17]

Summary

Introduction

Neuroepithelial tumors are collectively referred to as gliomas, which represent approximately 30% of all primary brain and other central nervous system (CNS) tumors and are the most common intracranial malignancies. Gliomas are generally graded by cell activity and aggressiveness on a scale of I to IV. HGGs, including glioblastoma multiforme (GBM), are poorly differentiated gliomas. Such tumors are malignant tumors with a poor prognosis. GBM is the most commonly occurring type of glioma, with a 5-year survival rate of approximately 5.6% [1]. This classification system has high interobserver variability, and the survival rate varies greatly between patients with different disease grades [2].

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