Frontiers in Neurology (May 2021)

Development of an Immune-Related Prognostic Index Associated With Glioblastoma

  • Zhengye Jiang,
  • Zhengye Jiang,
  • Yanxi Shi,
  • Wenpeng Zhao,
  • Wenpeng Zhao,
  • Yaya Zhang,
  • Yaya Zhang,
  • Yuanyuan Xie,
  • Yuanyuan Xie,
  • Bingchang Zhang,
  • Bingchang Zhang,
  • Guowei Tan,
  • Guowei Tan,
  • Zhanxiang Wang,
  • Zhanxiang Wang

DOI
https://doi.org/10.3389/fneur.2021.610797
Journal volume & issue
Vol. 12

Abstract

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Background: Although the tumor microenvironment (TME) is known to influence the prognosis of glioblastoma (GBM), the underlying mechanisms are not clear. This study aims to identify hub genes in the TME that affect the prognosis of GBM.Methods: The transcriptome profiles of the central nervous systems of GBM patients were downloaded from The Cancer Genome Atlas (TCGA). The ESTIMATE scoring algorithm was used to calculate immune and stromal scores. The application of these scores in histology classification was tested. Univariate Cox regression analysis was conducted to identify genes with prognostic value. Subsequently, functional enrichment analysis and protein–protein interaction (PPI) network analysis were performed to reveal the pathways and biological functions associated with the genes. Next, these prognosis genes were validated in an independent GBM cohort from the Chinese Glioma Genome Atlas (CGGA). Finally, the efficacy of current antitumor drugs targeting these genes against glioma was evaluated.Results: Gene expression profiles and clinical data of 309 GBM samples were obtained from TCGA database. Higher immune and stromal scores were found to be significantly correlated with tissue type and poor overall survival (OS) (p = 0.15 and 0.77, respectively). Functional enrichment analysis identified 860 upregulated and 162 downregulated cross genes, which were mainly linked to immune response, inflammatory response, cell membrane, and receptor activity. Survival analysis identified 228 differentially expressed genes associated with the prognosis of GBM (p ≤ 0.05). A total of 48 hub genes were identified by the Cytoscape tool, and pathway enrichment analysis of the genes was performed using Database for Annotation, Visualization and Integrated Discovery (DAVID). The 228 genes were validated in an independent GBM cohort from the CGGA. In total, 10 genes were found to be significantly associated with prognosis of GBM. Finally, 14 antitumor drugs were identified by drug–gene interaction analysis.Conclusions: Here, 10 TME-related genes and 14 corresponding antitumor agents were found to be associated with the prognosis and OS of GBM.

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