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Updated: Jun 14, 2025
Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy
Published on: October 4, 2019
Identification and Prognostic Value of m6A-Related Genes in Glioblastoma
Ping Zheng1,2, Xiaoxue Zhang2, Dabin Ren1
1Department of Neurosurgery, Shanghai Pudong New area People's Hospital, Shanghai, China.
Background:
N6-methyladenosine (m6A) is one of the most common forms of mRNA modification, which is dynamically regulated by the m6A-related genes; however, its effect in glioblastoma (GBM) is still unknown.
Objective:
We sought to investigate the association between m6A-related genes (m6A-RGs) and GBM.
Methods:
Transcriptome data and the relevant clinical data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The m6A-RGs were identified from differently expressed genes, and COX and lasso regression models were applied to locate the prognosis-related genes.
Results:
We identified 15 out of 19 m6A-RGs differentially expressed between GBM and nontumor tissues. We identified two subgroups of GBM (clusters 1 and 2) by applying consensus clustering. Compared with the cluster 1 subgroup, the cluster 1 subgroup correlates with a poorer prognosis, and most of the 19 m6A-RGs are higher expressed in cluster 1. Through univariate Cox and lasso regression model, we identified three m6A-RGs, namely HNRNPC, ALKBH5, and FTO, which were used to construct a Cox regression risk model to predict the prognosis of GBM patients.
Conclusion:
We identified a valuable m6A model for predicting the prognosis of GBM patients, which can provide useful epigenetic biomarkers.
