Paper Info
Title
m6A regulator-mediated methylation modification patterns and characteristics of immunity and stemness in low-grade glioma
Abstract
m6A RNA methylation is an emerging epigenetic modification, and its potential role in immunity and sternness remains unknown. Based on 17 widely recognized m6A regulators, the m6A modification patterns and corresponding characteristics of immune infiltration and sternness of 1152 low-grade glioma samples were comprehensively analyzed. Machine-learning strategies for constructing m6AScores were trained to quantify the m6A modification patterns of individual samples. Here, we reveal a significant correlation between the multi-omics data of regulators and clinicopathological parameters. We identified two distinct m6A modification patterns (an immune-activated differentiation pattern and an immune-desert dedifferentiation pattern) and four regulatory patterns of m6A methylation on immunity and sternness. We show that the m6AScores can predict the molecular subtype of low-grade glioma, the abundance of immune infiltration, the enrichment of signaling pathways, gene variation and prognosis. The concentration of high immunogenicity and clinical benefits in the low-m6AScore group confirmed the sensitive response to radio-chemotherapy and immunotherapy in patients with high-m6AScore. The results of the pan-cancer analyses illustrate the significant correlation between m6AScore and clinical outcome, the burden of neoepitope, immune infiltration and sternness. The assessment of individual tumor m6A modification patterns will guide us in improving treatment strategies and developing objective diagnostic tools. [GRAPHICS] .
Year
DOI
Venue
2021
10.1093/bib/bbab013
BRIEFINGS IN BIOINFORMATICS
Keywords
DocType
Volume
m6A, tumor immune microenvironment, stemness, machine learning, immunotherapy, pan-cancer
Journal
22
Issue
ISSN
Citations 
5
1467-5463
0
PageRank 
References 
Authors
0.34
0
11
Name
Order
Citations
PageRank
Jianyang Du100.34
Hang Ji200.34
Shuai Ma300.34
Jiaqi Jin400.34
Shan Mi500.34
Kuiyuan Hou600.34
Jiawei Dong700.34
Fang Wang800.34
Chaochao Zhang900.34
Hao Li102511.35
Shaoshan Hu1100.34