Characterization of the m6A/m1A/m5C/m7G-related regulators on the prognosis and immune microenvironment of glioma by integrated analysis of scRNA-seq and bulk RNA-seq data.

Abstract

Proliferation, metabolism, tumor occurrence and development in gliomas are greatly influenced by RNA modifications. However, no research has integrated the four RNA methylation regulators of m6A, m1A, m5C and m7G in gliomas to analyze their relationship with glioma prognosis and intratumoral heterogeneity. Based on three in-house single-cell RNA-sequencing (scRNA-seq) data, the glioma heterogeneity and characteristics of m6A/m1A/m5C/m7G-related regulators were elucidated. Based on publicly available bulk RNA-sequencing (RNA-seq) data, a risk-score system for predicting the overall survival (OS) for gliomas was established by three machine learning methods and multivariate Cox regression analysis, and validated in an independent cohort. Seven cell types were identified in gliomas by three scRNA-seq data, and 22 m6A/m1A/m5C/m7G-related regulators among the marker genes of different cell subtypes were discovered. Three m6A/m1A/m5C/m7G-related regulators were selected to construct prognostic risk-score model, including EIFA, NSUN6 and TET1. The high-risk patients showed higher immune checkpoint expression, higher tumor microenvironment scores, as well as higher tumor mutation burden and poorer prognosis compared with low-risk patients. Additionally, the area under the curve values of the risk score and nomogram were 0.833 and 0.922 for 3 year survival and 0.759 and 0.885 for 5 year survival for gliomas. EIF3A was significantly highly expressed in glioma tissues in our in-house RNA-sequencing data (p < 0.05). These findings may contribute to further understanding of the role of m6A/m1A/m5C/m7G-related regulators in gliomas, and provide novel and reliable biomarkers for gliomas prognosis and treatment.