The Role Of Cuproptosis-associated LncRNA In The Tumor Microenvironment Of Glioblastoma Based On Bioinformatics Analysis

Background:Multiple lncRNAs have been identified to play important roles in glioblastoma multiforme(GBM).However,studies on lncRNA associated with cuproptosis in GBM are still lacking.Therefore,in this study,a cuproptosis-related lncRNA model was constructed by bioinformatics analysis,and whether this model could well predict the prognosis of GBM and some drugs related to the clinical treatment of GBM was evaluated.Methods:RNA sequence analysis data from GBM patients were obtained from the UCSC Xena database,The Cancer Genome Atlas(TCGA),Gene Expression Synthesis(GEO),and Chinese glioma Genome Atlas(CGGA).R language software was used to collate the data,and co-expression analysis and univariate Cox regression analysis were used to identify prognostic lncRNAs associated with cuproptosis.Then,the minimum absolute shrinkage and selection operator(LASSO)and multi-Cox regression analysis were used to select the optimal value to construct the cuproptosis-associated lncRNA model.Median risk scores were divided into high and low-risk groups.The model was then validated and evaluated by Kaplan-Meier analysis,time-dependent receiver operating characteristics(ROC),independent prognostic analysis,and histogram analysis.Pathway enrichment analysis and gene set enrichment analysis(GSEA)were also analyzed in the risk group,and the expression and distribution of model lncRNAs in the GBM tumor microenvironment were found in the Single Cell Center for Tumor Immunity(TISCH).Finally,the relationship between the risk model and tumor mutation,immune cell infiltration,and tumor microenvironment was verified,as well as the prediction of drugs that may be effective in the clinical treatment of GBM.Results:1.Through univariate Cox regression analysis,19 lncRNAs associated with cuproptosis were found to be significantly correlated with the prognosis of GBM patients.The model was constructed by lasso and multivariate Cox regression analysis,and six models(H19,AC007686.3,AL157392.3,AC037450.1,LINC01637,AGAP2-AS1)were identified.Among them,H19,AGAP2-AS1 and LINC01637 were risk related genes(HR>1),AC007686.3,AL157392.3 and AC037450.1 were protective genes(HR<1).2.Survival curve,ROC curve,independent prognostic analysis,and column chart verified the accuracy of the model prediction;In addition,compared with other models,this model has higher advantages.The results of differential gene enrichment analysis showed that some cancer pathways related to metabolism,including the high-risk group related to oxidative phosphorylation and pentose phosphate pathway,while the low-risk group related to NOTCH,MTOR pathway,glioma,non-small cell lung cancer,endometrial cancer,and other diseases.3.In tumor immune analysis,there was a significant difference in immune infiltration between high-risk and low-risk patients.In the tumor microenvironment,significant differences were found in the immune score,stroma score,and microenvironment score between high and low-risk patients.In addition,based on the risk score,some drugs are predicted to be therapeutic for patients with GBM.In summary,cuproptosis-associated lncRNAs have vital functions in the tumor microenvironment of GBM and may be prognostic biomarkers and therapeutic targets for GBM.Conclusion:1.A prognosis model composed of lncRNAs associated with copper death(H19,AC007686.3,AL157392.3,AC037450.1,LINC01637,AGAP2-AS1)was constructed.2.This model has a good predictive ability for the prognosis of GBM patients and plays an important role in the GBM tumor microenvironment.3.12 clinical drugs(BAY.61.3606,BI.2536,Embelin,FH535,PF.562271,PLX4720)were found,QS11,Bortezomib,GNF.2,Mitomycin,NVP.BEZ235,and PF.4708671)may have therapeutic effects on GBM in the future.