Abstract
Glioma is the most common type of primary malignant tumor in the central nervous system. Tumor recurrence and progression are common in lower-grade glioma (LGG). Immune checkpoint blockade (ICB), as an emerging immunotherapy, is expected to improve the prognosis of patients undergoing conventional treatment, but it currently performs poorly in glioma. We divided patients into genome-stable and -unstable groups according to the somatic mutation count and then found that the expression of CDC20 was positively correlated with genomic instability. We compared the differences in long non-coding RNA (lncRNA) expression and immune infiltration between the two groups. Five lncRNAs and three immune cell types were identified to construct risk models and a nomogram combing clinical features. Through internal and external validation, the models exhibited sufficient ability to predict the prognosis and the possible response to ICB therapy of patients. This study provided a potential predictive approach for the precise application of ICB and support for improving the prognosis of LGG patients.