Objective To explore the RNAs related to the prognosis of patients with glioma, and to establish a model based on the RNAs to predict the survival status of the patients.Methods A univariate survival analysis was performed on the RNA-Seq data of 653 gliomas from The Cancer Genome Atlas (TCGA) to screen out the genes related to the survival of the patients. Using the obtained genes, a model that can predict the survival status of the patients was established through Lasso regression, and then the model was validated. Based on the risk scores derived from the model and with reference to the clinical features, a multivariate Cox regression analysis was conducted to validate whether the model was effective and independent of the clinical features.Results Totally, 31641 prognosis-related genes were screened out, and 40 expressed genes were included in the Lasso regression model; the multivariate Cox regression analysis demonstrated that the model was effective (P<0.05) and independent of the clinical features (P<0.05).Conclusions The model established with RNA-Seq data through Lasso regression can predict the survival status of patients.