N6-methyladenine-related genes affect biological behavior and the prognosis of glioma

Abstract

Background: Although aberrant expression of N6-methyladenine (m⁶ A) methylation-related genes contribute to tumorigenesis in many solid tumors, the prognostic value of the m⁶ A-related genes and their correlation with clinicopathological features in gliomas need advanced study.

Methods: The clinical and sequencing data of 288 patients with glioma were extracted from Chinese Glioma Genome Atlas database. By univariate and multivariable Cox regression analysis, the m⁶ A-related prognostic genes were identified, and their correlation with clinicopathological features was further analysis. A nomogram was constructed by R software and the performance of it was assessed by calibration and time-dependent receiver operating characteristic curve.

Results: Nine m⁶ A-related genes were identified as independent prognostic factors, which were mostly enriched in RNA splicing, regulation of immune response and vesicle-mediated transport. By expression value and regression coefficient of these genes, we constructed risk score of each patient, which was highly associated with clinicopathological features. Kaplan-Meier curve showed that the prognosis of patients with high-risk scores was significantly worse than that with low-risk scores (HR = 4.30, 95% CI = 3.16-5.85, p < 0.0001). A nomogram was constructed based on the nine m⁶ A-related genes signature and clinicopathological features with well-fitted calibration curves (c-index = 0.82), showing high specificity and sensitivity (area under the curve for 1-, 3-, and 5-years survival probability = 0.874, 0.918, and 0.934).

Conclusions: A nine m⁶ A-related genes signature was identified in gliomas. The m⁶ A-related risk score is a novel prognostic factor for patients with glioma, and is associated with clinicopathological features. Moreover, the nomogram based on the nine m⁶ A-related genes signature and clinicopathological features had good efficacy in predicting the survival probability.

Keywords: neoplasms; nomograms; prognosis.