Identification of a pyroptosis-related prognosis gene signature and its relationship with an immune microenvironment in gliomas. Issue 28 (15th July 2022)

• Record Type: Journal Article
• Authors: Xiao, Shengying; Yan, Zhiguang; Zeng, Furen; Lu, Yichen; Qiu, Jun; Zhu, Xiaodong
• Is Part Of: Medicine. Volume 101:Issue 28(2022)
• Page Start: e29391
• Publication Date: 2022-07-15
• Subjects: pyroptosis-related genes -- prognosis -- bioinformatics -- immunity; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000029391
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Background: Glioma is the most common type of primary brain cancer, and the prognosis of most patients with glioma is poor. Pyroptosis is a newly discovered inflammatory programmed cell death. However, the expression of pyroptosis-related genes (PRGs) in glioma and its correlation with prognosis are unclear. Methods: 27 pyroptosis genes differentially expressed between glioma and adjacent normal tissues were identified. All glioma cases could be stratified into 2 subtypes based on these differentially expressed PRGs. The prognostic value of each PRG was evaluated to construct a prognostic model. Results: A novel 16-gene signature was constructed by using the least absolute shrinkage and selection operator Cox regression method. Then, patients with glioma were divided into low- and high-risk groups in the TCGA cohort. The survival rate of patients in the low-risk group was significantly higher than that in the high-risk group ( P = .001). Patients with glioma from the Gene Expression Omnibus (GEO) cohort were stratified into 2 risk groups by using the median risk score. The overall survival (OS) of the low-risk group was longer than that of the high-risk group ( P = .001). The risk score was considered an independent prognostic factor of the OS of patients with glioma. Gene ontology and Kyoto Encylopedia of Genes and Genomes analysis showed that the differentially expressed PRGs were mainly related to neutrophil activation involved in immune responses, focal adhesion, cell cycle, and p53 signaling pathway. Conclusion: PRGs could predict the prognosis of glioma and play significant roles in a tumor immune microenvironment.