Interaction network of immune‑associated genes affecting the prognosis of patients with glioblastoma

Abstract

Glioblastoma multiforme (GBM) is a common malignant tumor type of the nervous system. The purpose of the present study was to establish a regulatory network of immune-associated genes affecting the prognosis of patients with GBM. The GSE4290, GSE50161 and GSE2223 datasets from the Gene Expression Omnibus database were screened to identify common differentially expressed genes (co-DEGs). A functional enrichment analysis indicated that the co-DEGs were mainly enriched in cell communication, regulation of enzyme activity, immune response, nervous system, cytokine signaling in immune system and the AKT signaling pathway. The co-DEGs accumulated in immune response were then further investigated. For this, the intersection of those co-DEGs and currently known immune-regulatory genes was obtained and a differential expression analysis of these overlapping immune-associated genes was performed. A risk model was established using immune-regulatory genes that affect the prognosis of patients with GBM. The risk score was significantly associated with the prognosis of patients with GBM and had a significant independent predictive value. The risk model had high accuracy in predicting the prognosis of patients with GBM [area under the receiver operating characteristic curve (AUC)=0.764], which was higher than that of a previously reported model of prognosis-associated biomarkers (AUC=0.667). Furthermore, an interaction network was constructed by using immune-regulatory genes and transcription factors affecting the prognosis of patients with GBM and the University of California Santa Cruz database was used to perform a preliminary analysis of the transcription factors and immune genes of interest. The interaction network of immune-regulatory genes constructed in the present study enhances the current understanding of mechanisms associated with poor prognosis of patients with GBM. The risk score model established in the present study may be used to evaluate the prognosis of patients with GBM.

Identification, and Experimental and Bioinformatics Validation of an Immune-Related Prognosis Gene Signature for Low-Grade Glioma Based on mRNAsi

“…Immunotherapy is a significant and popular approach in preventing and treating tumors [ 30 ]. Presently, increasingly more studies have been exploring new prognostic biomarkers associated with the tumor immune microenvironment, including LGG.…”

Immune‐related interaction perturbation networks unravel biological peculiars and clinical significance of glioblastoma

“…Cancer cells in GBM generated a proangiogenic and inflamed microenvironment, which recruited immune cells and molecules to infiltrate the tumor mass, leading to intricate immune networks in GBM [ 39 ]. Emerging evidence has demonstrated that immune networks consisting of multiple immune components in the tumor microenvironment could characterize the immune phenotypes of tumors and impact the clinical outcomes of GBM patients [ 17 , 18 ]. Due to the essential role of immune networks and their diverse presence in GBM, this study performed clustering analysis based on IRGs, which may contribute to the understanding of GBM heterogeneity and facilitate individualized treatment.…”

“…Previous studies have demonstrated that immune networks are inextricably linked to cancer initiation and progression, with the ability to predict prognosis and guide treatment for tumor patients [ 15 , 16 ]. Hou et al have demonstrated that the immune‐regulatory interaction networks were tightly associated with unfavorable prognosis of GBM patients [ 17 ]. The interplay between tumor cells and the immune microenvironment in GBM ultimately suppresses the beneficial pattern of molecular pathways, improving its malignancy and elevated resistance to cancer therapy [ 18 ].…”