Glioma is the most common primary intracranial tumour and has a very poor prognosis. Pyroptosis, also known as inflammatory necrosis, is a type of programmed cell death that was discovered in recent years. The expression and role of pyroptosis-related genes in gliomas are still unclear. | Zhang et al. BMC Cancer 2021 21 1311 https s12885-021-09046-2 RESEARCH Open Access A novel pyroptosis-related gene signature predicts the prognosis of glioma through immune infiltration Moxuan Zhang1 Yanhao Cheng1 Zhengchun Xue2 Qiang Sun2 and Jian Zhang1 Abstract Background Glioma is the most common primary intracranial tumour and has a very poor prognosis. Pyroptosis also known as inflammatory necrosis is a type of programmed cell death that was discovered in recent years. The expression and role of pyroptosis-related genes in gliomas are still unclear. Methods In this study we analysed the RNA-seq and clinical information of glioma patients from The Cancer Genome Atlas TCGA database and Chinese Glioma Genome Atlas CGGA database. To investigate the prognosis and immune microenvironment of pyroptosis-related genes in gliomas we constructed a risk model based on the TCGA cohort. The patients in the CGGA cohort were used as the validation cohort. Results In this study we identified 34 pyroptosis-related differentially expressed genes DEGs in glioma. By cluster- ing these DEGs all glioma cases can be divided into two clusters. Survival analysis showed that the overall survival time of Cluster 1 was significantly higher than that of Cluster 2. Using the TCGA cohort as the training set a 10-gene risk model was constructed through univariate Cox regression analysis and LASSO Cox regression analysis. According to the risk score gliomas were divided into high-risk and low-risk groups. Survival analysis showed that the low-risk group had a longer survival time than the high-risk group. The above results were verified in the CGGA validation cohort. To verify that the risk model was independent of other clinical features the distribution and the Kaplan-Meier survival curves associated with risk scores were performed. Combined with the characteristics of the clinical cases the risk score was found to be an independent factor predicting the overall survival of
