Objective To screen the differentially expressed ubiquitination-related long non-coding RNAs(lncRNAs)in glioblastoma(GBM)patients by bioinformatics methods based on two databases and to construct a prognostic risk assessment model.Methods The sequencing data and corresponding clinical data of GBM patients were downloaded from The Cancer Genome Atlas database and Chinese Glioma Genome Atlas database.The ubiquitination-related lncRNAs shared between the two databases were screened by Pearson correlation analysis.Furthermore,univariate Cox regression analysis and least absolute shrinkage and selection operator regression analysis were used to screen ubiquitination-related lncRNAs associated with survival and construct prognostic models.The validity of the model prediction was verified in an internal cohort and an external cohort,and survival analysis,gene function enrichment analysis,immune microenvironment analysis and drug response prediction were performed in the high-risk and low-risk groups of the model.Results A total of 409 shared ubiquitination-related lncRNAs were screened from the two databases.After rigorous screening,nine key ubiquitination-related lncRNAs significantly associated with GBM prognosis were finally analyzed,and a prognostic risk scoring model was constructed.All patients were divided into high-risk group and low-risk group on the basis of the prognostic risk score.The survival curve revealed that the overall survival of the high-risk group was significantly lower than that of the low-risk group in the training cohort,test cohort and external cohort(P＜0.05).Receiver operating characteristic curve revealed that the model had a good predictive value for 1-,3-and 5-year overall survival(P＜0.05).In the risk model,there were significant differences in immune-related pathways and immune microenvironment between high-risk group and low-risk group,and the response level of patients in high-risk group to drug therapy was lower(P＜0.05).Conclusion In this paper,a prognostic risk assessment model of ubiquitination-related lncRNAs for patients with GBM is successfully constructed using public databases.Then,the efficacy is verified by different cohorts,and the results show that the model has good predictive value for GBM prognosis and may be closely related to immune microenvironment.This model may help to determine the prognostic biomarkers for GBM patients and provide new ideas for future treatment of GBM.
维普
万方数据