Development of a novel angiogenesis-related lncRNA signature to predict the prognosis and immunotherapy of glioblastoma multiforme.

Background: Long noncoding RNA (lncRNA) can regulate tumorigenesis, angiogenesis, proliferation, and other tumor biological behaviors, and is closely related to the growth and progression of glioma. The purpose of this research was to investigate the role of angiogenesis-related lncRNA in the prognosis and immunotherapy of glioblastoma multiforme (GBM). Methods: Differential analysis was carried out to acquire angiogenesis-related differentially expressed lncRNAs (AR-DElncRNAs). The AR-DElncRNAs were then subjected to univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses to construct a prognostic model. Based on the median risk score, patients were classified into high-risk and low-risk groups. Kaplan-Meier survival analysis was conducted to estimate the prognostic value of the prognostic model. In addition, a nomogram was built to predict individual survival probabilities by combining clinicopathological characteristics and a prognostic model. Furthermore, immune infiltration, immunotherapy, and drug sensitivity analyses were administered to investigate the differences between the high- and low-risk groups. Results: We identified 3 lncRNAs (DGCR5, PRKAG2-AS1, and ACAP2-IT1) that were significantly associated with the survival of GBM patients from the 255 AR-DElncRNAs based on univariate Cox and LASSO analyses. Then, a prognostic model was structured according to these 3 lncRNAs, from which we found that high-risk GBM patients had a worse prognosis than that of low-risk patients. Moreover, the risk score was determined to be an independent prognostic factor [hazard ratio (HR) =1.444; 95% confidence interval (CI): 1.014-2.057; P<0.05]. The immune microenvironment analysis revealed that the immune score, stromal score, and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) score were significantly higher in the high-risk group than in the low-risk group. Neutrophils, macrophages, immature dendritic cells (iDCs), natural killer (NK) CD56dim cells, activated DCs (aDCs), and uncharacterized cells were different in the high- and low-risk groups. In addition, the high-risk group had a stronger sensitivity to immunotherapy. Furthermore, the sensitivity of 28 potential chemotherapeutic drugs differed significantly between the high- and low-risk groups. Conclusions: A novel angiogenesis-related lncRNA signature could be used to predict the prognosis and treatment of GBM.