AUTHOR=Shao Dongqi , Li Yu , Wu Junyong , Zhang Binbin , Xie Shan , Zheng Xialin , Jiang Zhiquan 

TITLE=An m6A/m5C/m1A/m7G-Related Long Non-coding RNA Signature to Predict Prognosis and Immune Features of Glioma

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.903117

DOI=10.3389/fgene.2022.903117

ISSN=1664-8021

ABSTRACT=Background: Gliomas are the most common and fatal malignant type of tumor in the central nervous system. RNA post-transcriptional modifications, as a frontier and hotspot in the field of epigenetics, have attracted increased attention in recent years. Among such modifications, methylation is most abundant, encompassing N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1 methyladenosine (m1A), and 7-methylguanosine (m7G) methylation. 
Methods: We downloaded normal and low-grade glioma samples from RNA-sequencing data of the Cancer Genome Atlas database. Using clinical information and mutation data of glioblastoma tumor samples, 49 m6A/m5C/m1A/m7G-related genes were summarized. Then, m6A/m5C/m1A/m7G- lncRNA signature(LS) co-expressing long non-coding RNAs were searched. We used least absolute shrink and selection operator Cox expression to obtain 13 m6A/m5C/m1A/m7G-related lncRNAs to construct the prognostic characteristics of a glioma and verify its immune correlation and drug sensitivity.
Results: A total of 13 m6A/m5C/m1A/m7G-related genes (AL080276.2, AC092111.1, SOX21-AS1, DNAJC9-AS1, AC025171.1, AL356019.2, AC017104.1, AC099850.3, UNC5B-AS1, AC006064.2, AC010319.4, and AC016822.1) were used to construct a survival and prognosis model, which had a good independent prediction ability for glioma patients. According to m6A/m5C/m1A/m7G-LS, the patients were divided into a low m6A/m5C/m1A/m7G-LS group and a high m6A/m5C/m1A/m7G-LS group, the latter of which had a poor prognosis. In addition, m6A/m5C/m1A/m7G-LS enabled us to better distinguish the results of enrichment analysis, immunotherapy response, and drug sensitivity of glioma patients in different subgroups.
Conclusions: Our study constructed an m6A/m5C/m1A/m7G-LS and established a nomogram model, which can accurately predict the prognosis of glioma patients and provide promising immunotherapy strategies for the future.