Literature DB >> 33264518

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

Shanqiang Qu1,2, Zhixin Chen3, Bin Liu4, Jin Liu5, Huafu Wang6.   

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.
© 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Entities:  

Keywords:  neoplasms; nomograms; prognosis

Mesh:

Substances:

Year:  2020        PMID: 33264518      PMCID: PMC7826482          DOI: 10.1002/cam4.3574

Source DB:  PubMed          Journal:  Cancer Med        ISSN: 2045-7634            Impact factor:   4.452


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