Abstract
Glioblastoma multiforme (GBM) is categorized by rapid malignant cellular growth in the central nervous system (CNS) tumors. It is one of the most prevailing primary brain tumors, particularly in human male adults. Even though the combination therapy comprises surgery, chemotherapy, and adjuvant therapies, the survival rate is on average 14.6 months. Glioma stem cells (GSCs) have key roles in tumorigenesis, progression, and counteracting chemotherapy and radiotherapy. In our study, firstly, the gene expression dataset GSE45117 was retrieved and differentially expressed genes (DEGs) were spotted. The co-expression network analysis was employed on DEGs to find the significant modules. The most significant module resulting from co-expression analysis was the turquoise module. The turquoise module related to the tumor cells, hypoxia, normoxic treatments of glioblastoma tumor (GBT), and GSCs were screened. Sixty-one common genes in the turquoise module were selected generated through the co-expression analysis and protein–protein interaction (PPI) network. Moreover, the GO and KEGG pathway enrichment results were studied. Twenty common hub genes were screened by the NetworkAnalyst web instrument constructed on the PPI network through the STRING database. After survival analysis via the Kaplan–Meier (KM) plotter from The Cancer Genome Atlas (TCGA) database, we identified the five most significant hub genes strongly related to the progression of GBM. We further observed these five most significant hub genes also up-regulated in another GBM gene expression dataset. The protein–protein interaction (PPI) network of the turquoise module genes was constructed and a KEGG pathway enrichments study of the turquoise module genes was performed. The VEGF signaling pathway was emphasized because of the strong link with GBM. A gene–disease association network was further constructed to demonstrate the information of the progression of GBM and other related brain neoplasms. All hub genes assessed through this study would be potential markers for the prognosis and diagnosis of GBM.
Highlights
One of the most prevailing and highly deadly heterogeneous forms of brain tumors is glioblastoma multiforme (GBM) or grade-IV glioma [1]
This study identified the differentially expressed genes (DEGs) in the glioblastoma tumor (GBT)–glioblastoma stem-like cell lines (GSN), GBT–GSN_H, GBT–GSH, GBT– GSH_N, GSN-GSN_H, GSN-GSH, GSN-GSH_N, GSN_H-GSH, and GSN_H-GSH_N treatment groups
By utilizing a sequence of bioinformatics investigation, this current study demonstrated the five most significant hub genes which may be tangled in the diagnosis and prognosis and efficient concerning the characterization of GBM and treatment options
Summary
One of the most prevailing and highly deadly heterogeneous forms of brain tumors is glioblastoma multiforme (GBM) or grade-IV glioma [1]. The low efficiency of all therapeutic methods including surgery, chemotherapy, and radiotherapy [3] demands pointed to new therapeutic targets for GBM in recent years. GBM is an extremely heterogeneous tumor at the pathological and cellular level [4,5]. Gene expression and cell proliferation levels highly differ in GBM. Glioma stem cells (GSCs) take a central position regarding tumor formation of lower-grade gliomas and glioblastoma multiforme. GSCs have important characteristics including self-renewal ability, tumor initiation, progression ability, and resistance to GBM therapies. Several important roles of GSCs in GBM make GSCs new therapeutic targets [6,7]. In the wet lab conditions, glioblastoma stemlike cells efficiently disseminate in the media after being insulated from newly resected human GBM [8]
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