Expression And Prognostic Value Of Cuproptosis-related Long Noncoding RNA In Glioma

Objective:This study aims to investigate the expression and prognostic value of cuproptosis-related long non-coding RNA involved in constructing a risk prognosis model in glioma.Methods:In this study,data on glioma patients were downloaded from three databases:TCGA,GTEx and CGGA databases.We screened the 47 cuproptosis-related genes from the latest literature and confirmed the lnc RNAs related to them.Lnc RNAs associated with glioma prognosis were screened by uni-/multi-variate Cox and Lasso regression algorithms,identified cuproptosis-related lncRNAs for constructing prognosis prediction model in glioma.Glioma patients were divided into high-and low-risk groups based on the median risk score in the training group,and the ability of the model to distinguish the high-and low-risk groups were verified by PCA analysis.The predicative efficacy of the model were verified by uni-and multi-variate independent prognostic analysis,ROC analysis,Kaplan-Meier survival curves analysis,progression-free survival curve analysis,nomogram for individual survival prediction and C-index analysis.Differential gene expression,gene function enrichment,cibersort analyis of immune infiltration,tumour mutation burden and drug sensitivity differences were analyzed between the high-and low-risk groups to predict the pathways,gene,immune therapy response and sensitivity drug.Results:Using the uni-/multi-variate Cox and Lasso regression algorithms to construct and optimize the model,which identified 11 cuproptosis-related lnc RNAs(ARHGEF26-AS1、DICER1-AS1、PARD3-AS1、SLC25A21-AS1、SNAI3-AS1、DGCR5、TTC28-AS1、DLGAP1-AS1、LINC01023、DBH-AS1、UBA6-AS1)were determined to construction the prognostic model.The prognostic model was validated to effectively distinguish between high-and low-risk groups and accurately predicts the prognosis of glioma patients.Differential genes were enriched in immune-related pathways,and the high-risk group was more closely related to immune-related pathways.Immune checkpoint and immune infiltration analyses suggest that the high-risk group is more likely to benefit from immunotherapy.In addition,the semi-inhibitory concentrations of Ispinesib Mesylate,KIN001-135,NPK76-Ⅱ-72-1,OSI-027,PHA-793887,TPCA-1,VX-11,and YM201636 for glioma increased with increasing risk scores.Conclusion:A prognostic model was constructed containing 11 cuproptosis-related lncRNAs(ARHGEF26-AS1、DICER1-AS1、PARD3-AS1、SLC25A21-AS1、SNAI3-AS1、DGCR5、TTC28-AS1、DLGAP1-AS1、LINC01023、DBH-AS1、UBA6-AS1).The prognostic model effectively distinguish between high-and low-risk groups and accurately predicts the prognosis of glioma patients.It is closely related to the immune infiltration of tumor microenvironment,which provides a new idea and target of immunotherapy for glioma patients.