Construction of m6A-Related lncRNA Prognostic Signature Model and Immunomodulatory Effect in Glioblastoma Multiforme - Xie, Pan; Yan, Han; Gao, Ying; Li, Xi; Zhou, Dong-Bo; Liu, Zhao-Qian (Frontiers in Oncology, 2022)
Background: Glioblastoma multiforme (GBM, WHO grade IV), the most prevalent and aggressive of primary malignant central nervous system tumors, has a poor clinical prognosis. This study aimed to assess and predict the survival of GBM patients by establishing an m6A-related lncRNA signalling model and to validate its validity, accuracy and applicability. Methods: RNA sequencing data and clinical data of GBM patients were obtained from TCGA data. First, m6A-associated lncRNAs were screened by Pearson correlation analysis and Univariate Cox analysis was performed to obtain lncRNAs associated with overall survival in GBM patients. Subsequently, the signal model was established using LASSO regression analysis, Principal Component Analysis was performed, and nomograms, C-index curves, and ROC curves were drawn. Finally, GO enrichment analysis was performed on the differentially expressed genes in the high-risk and low-risk groups, and the influence of this signature on the immune regulation response and anticancer drug sensitivity of GBM patients was discussed. Results: The signature constructed by four lncRNAs AC005229.3, SOX21-AS1, AL133523.1, and AC004847.1 is obtained. Furthermore, the signature proved to be effective and accurate in predicting and assessing the survival of GBM patients and could function independently of other clinical characteristics. Finally, GBM patients in the high-risk group were less sensitive to immunotherapy and multiple anti-cancer drugs than the low-risk group. Conclusion: We constructed a novel m6A-related lncRNA signalling model in GBM that can effectively predict patient prognosis closely related to immune regulation and chemotherapy sensitivity.