ArticleMedicine2022
Identification of a pyroptosis-related prognosis gene signature and its relationship with an immune microenvironment in gliomas.
Article in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- A novel golgi related genes based correlation prognostic index can better predict the prognosis of glioma and responses to immunotherapy.Discover oncology · 2025Article
- Comprehensive machine learning-based integration develops a novel prognostic model for glioblastoma.Molecular therapy. Oncology · 2024Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGlioma 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.
methods27 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.
resultsA 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.
conclusionPRGs could predict the prognosis of glioma and play significant roles in a tumor immune microenvironment.
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Registered trials
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