Identification of ferroptosis-related LncRNAs as potential targets for improving immunotherapy in glioblastoma

The effect of ferroptosis-related long non-coding RNAs (lncRNAs) in predicting immunotherapy response to glioblastoma (GBM) remains obscure. This study established a 11-lncRNAs prognostic signature. Differential gene expression analysis, univariate and multivariate Cox regression analyses and the least absolute shrinkage and selection operator (LASSO) regression algorithm were used to identify prognostic ferroptosis-related genes and establish a nomogram model of risk score. Kaplan-Meier survival plots and receiver operating characteristic (ROC) curve analysis were used to evaluate the prognostic accuracy of the model in the TCGA-GBM cohort. To verify the expression of these signatures, we analyzed the expression levels of three lncRNAs (AGAP2-AS1, OSMR-AS1, UNC5B-AS1) in LN229 and U87 cells. The ROC analysis showed that the area under curve (AUC) of this signature is 0.814, suggesting that it has a promising performance on GBM prognostic prediction. Kaplan-Meier analysis showed that the survival rate of GBM patients in high-risk group was significantly lower than low-risk group, and the performance of this signature on GBM prognostic prediction was superior to conventional clinicopathological factors. Further qRT-PCR experiment also confirmed our prediction of lncRNA signatures. These ferroptosis-related lncRNAs might be therapeutic targets for glioblastoma, and targeting these lncRNAs can also improve the efficacy of immunotherapy, especially immune checkpoint inhibitors. Mechanistically, these findings might attribute to N6-methyladenosine (m6A) mRNA modification on lncRNAs.