A new signature based on alternative polyadenylation for prognostic prediction and therapeutic responses in low-grade glioma

Background: Evidence from research supports the significant role of alternative polyadenylation (APA) in the development of cancer. The aim of this study is to explore the prognostic and therapeutic value of APA events for patients with low-grade gliomas (LGG). Methods: The gene expression and APA profiles of patients with low-grade gliomas were obtained from The Cancer Genome Atlas database. All patients were sorted randomly into training and test sets. The prognostic-associated events of alternative splicing were screened by univariate Cox regression. Subsequently, Least Absolute Shrinkage and Selection Operator and multivariate Cox analysis were performed to construct a prognostic signature. The patients were sorted into the high and low-risk groups based on their median risk score. Bioinformatics methods were used to identify genetic variation, pathway activation, immune heterogeneity, and drug response differences between the two groups. Results: A prognostic signature was constructed shown to be capable of accurately predicting prognosis of patients with LGG. Notable variations were observed in the tumor mutation burden and copy number variations between the high-risk and low-risk patients. Besides, the high-risk group had enhanced immune cell abundance and immune checkpoint gene expression. In terms of drug response, we further found that the patients of high-risk group were more sensitive to immunotherapy, but chemotherapy was suggestively more appropriate for the low-risk group patients. Conclusion: Our findings give new insights and methods related to prognosis prediction and treatment methods for LGG patients, and expand the understanding regarding the role of alternative splicing in LGG.