Development of a Prognostic Model of Glioma Based on Pyroptosis-Related Genes.

Background: Glioma is the most malignant tumor of the central nervous system, with a poor prognosis. Pyroptosis is known to regulate the malignant phenotype of tumor cells, thus affecting the prognosis of patients. However, the role of pyroptosis-related genes (PRGs) in glioma remains unclear.

Methods: We used the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Rembrandt database of patients with glioma to construct a PRG-based prognostic model and analyzed the relationship between the prognostic model and tumor immune microenvironment. The Wilcox test was used to compare the expression of PRGs in glioma and normal tissues based on TCGA. Univariate Cox and LASSO regression were used to construct the prognostic model. The CGGA and Rembrandt database were used as validation sets to validate the model.

Results: Five genes were included in the model (BAX, CASP1, CASP3, CASP6, and NOD1). The survival of patients in the high-risk group was lower than that in the low-risk group. The receiver operating characteristic curve showed that the model had good prognostic evaluation ability and accuracy in all 3 cohorts of patients with glioma. The correlation analysis between the prognostic model and immune infiltration showed that the degree of immune cell infiltration, immune response process, and the expression level of immune checkpoints in the high-risk group were higher than those in the low-risk group.

Conclusions: We have constructed a reliable PRG-related prognostic model, which can provide reference for the prognostic evaluation of patients with glioma.