Open Access

Development of a prognostic model of glioma based on immune‑related genes

  • Authors:
    • Jing-Jing Wang
    • Han Wang
    • Bao-Long Zhu
    • Xiang Wang
    • Yong-Hong Qian
    • Lei Xie
    • Wen-Jie Wang
    • Jie Zhu
    • Xing-Yu Chen
    • Jing-Mei Wang
    • Zhi-Liang Ding
  • View Affiliations

  • Published online on: December 15, 2020     https://doi.org/10.3892/ol.2020.12377
  • Article Number: 116
  • Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Glioma is the most common type of primary brain cancer, and the prognosis of most patients with glioma, and particularly that of patients with glioblastoma, is poor. Tumor immunity serves an important role in the development of glioma. However, immunotherapy for glioma has not been completely successful, and thus, comprehensive examination of the immune‑related genes (IRGs) of glioma is required. In the present study, differentially expressed genes (DEGs) and differentially expressed IRGs (DEIRGs) were identified using the edgeR package. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used for functional enrichment analysis of DEIRGs. Survival‑associated IRGs were selected via univariate Cox regression analysis. A The Cancer Genome Atlas prognostic model and GSE43378 validation model were established using lasso‑penalized Cox regression analysis. Based on the median risk score value, patients were divided into high‑risk and low‑risk groups for clinical analysis. Receiver operating characteristic curve and nomogram analyses were used to assess the accuracy of the models. Reverse transcription‑quantitative PCR was performed to measure the expression levels of relevant genes, such as cyclin‑dependent kinase 4 (CDK4), interleukin 24 (IL24), NADPH oxidase 4 (NOX4), bone morphogenetic protein 2 (BMP2) and baculoviral IAP repeat containing 5 (BIRC5). A total of 3,238 DEGs, including 1,950 upregulated and 1,288 downregulated DEGs, and 97 DEIRGs, including 60 upregulated and 37 downregulated DEIRGs, were identified. ‘Neuroactive ligand‑receptor interaction’ and ‘Cytokine‑cytokine receptor interaction’ were the most significantly enriched pathways according to KEGG pathway analysis. A prognostic model and a validation prognostic model were created for glioma, including 15 survival‑associated IRGs (FCER1G, NOX4, TRIM5, SOCS1, APOBEC3C, BIRC5, VIM, TNC, BMP2, CMTM3, IL24, JAG1, CALCRL, HNF4G and CDK4). Furthermore, multivariate Cox regression analysis results suggested that age, high WHO Grade by histopathology, wild type isocitrate dehydrogenase 1 and high risk score were independently associated with poor overall survival. The infiltration of B cells, CD8+ T cells, dendritic cells, macrophages and neutrophils was positively associated with the prognostic risk score. In the present study, several clinically significant survival‑associated IRGs were identified, and a prognosis evaluation model of glioma was established.
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February-2021
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Spandidos Publications style
Wang J, Wang H, Zhu B, Wang X, Qian Y, Xie L, Wang W, Zhu J, Chen X, Wang J, Wang J, et al: Development of a prognostic model of glioma based on immune‑related genes. Oncol Lett 21: 116, 2021
APA
Wang, J., Wang, H., Zhu, B., Wang, X., Qian, Y., Xie, L. ... Ding, Z. (2021). Development of a prognostic model of glioma based on immune‑related genes. Oncology Letters, 21, 116. https://doi.org/10.3892/ol.2020.12377
MLA
Wang, J., Wang, H., Zhu, B., Wang, X., Qian, Y., Xie, L., Wang, W., Zhu, J., Chen, X., Wang, J., Ding, Z."Development of a prognostic model of glioma based on immune‑related genes". Oncology Letters 21.2 (2021): 116.
Chicago
Wang, J., Wang, H., Zhu, B., Wang, X., Qian, Y., Xie, L., Wang, W., Zhu, J., Chen, X., Wang, J., Ding, Z."Development of a prognostic model of glioma based on immune‑related genes". Oncology Letters 21, no. 2 (2021): 116. https://doi.org/10.3892/ol.2020.12377