Identification of the Role and Clinical Prognostic Value of Target Genes of m6A RNA Methylation Regulators in Glioma

Abstract

m6A RNA methylation regulators can regulate the growth, progression, and invasion of glioma cells by regulating their target genes, which provides a reliable support for the m6A regulator–target axes as the novel therapeutic targets and clinical prognostic signature in glioma. This study aimed to explore the role and prognostic value of m6A RNA methylation regulators and their targets. Expression profiles and clinicopathological data were obtained from the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Clinical Proteome Tumor Analysis Consortium (CPTAC) datasets. Differential expression and correlation analyses were performed between normal and glioma tissues at mRNA and protein levels. Univariate Cox regression, survival, and Lasso Cox regression analyses were conducted to identify and establish the prognostic gene signature. Kaplan–Meier curve, multivariate Cox regression analysis, and ROC were utilized to evaluate the prognostic capacity of the prognostic gene signature. The correlation analysis, systematic bioinformatics analysis, and cell experiment were performed to further understand the potential underlying molecular mechanisms and drug sensitivity. Our results suggested that IGF2BP2, KIAA1429, METTL16, and METTL3, as well as 208 targets are involved in the occurrence of glioma, GBM, and LGG. YTHDF1 and 78 targets involved the occurrence of glioma and GBM, not LGG, among which 181 genes were associated with overall survival. From other findings and our cell experiment results, we demonstrated that METTL3 can activate Notch pathway and facilitate glioma occurrence through regulating its direct targets NOTCH3, DLL3, and HES1, and Notch pathway genes may serve as the potential treatment targets for glioma. Our study established and validated a seven-gene signature comprising METTL3, COL18A1, NASP, PHLPP2, TIMP1, U2AF2, and VEGFA, with a good capability for predicting glioma survival, which may guide therapeutic customization and clinical decision-making. These genes were identified to influence 81 anticancer drug responses, which further contributes to the early phase clinical trials of drug development.

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma

“…Furthermore, we compared the prognostic predictive abilities of 20 different risk signatures of gliomas in TCGA from published articles, including inflammatory response-related gene (IRRG) signature ( Yan et al, 2022 ), DNA damage and repair-related gene (DDRRG) signature ( Li et al, 2022c ), CXCR members signature ( He et al, 2022 ), pyroptosis-related gene signature ( Zhang M. et al, 2021b ; Chao et al, 2022 ; Yang et al, 2022 ; Zhang et al, 2022 ), ECM-related gene (ECMRG) signature ( Li et al, 2022b ), tripartite motif (TRIM) family gene signature ( Xiao et al, 2022 ), antigen presentation machinery (APM) signature ( Chen et al, 2022 ), natural killer cell-related gene (NKRG) signature ( Li C. et al, 2022a ), IL-4-related gene (IL4RG) signature ( Qi et al, 2022 ), hypoxia-related gene (HRG) signature ( Gao et al, 2021 ), S100 family-based signature ( Hu et al, 2021 ), TIME signature ( Zhang C. et al, 2021a ), focal adhesion-related gene (FARG) signature ( Li et al, 2021 ), m6A RNA methylation regulator signature ( Cong et al, 2021 ), HDAC1-related signature ( Fan et al, 2021 ), RNA-binding protein (RBP)-based signature ( Chen et al, 2021a ) and ferroptosis-related gene (FRG) signature ( Chen et al, 2021b ). The results of univariate and multivariate Cox analyses showed that our ARG signature had independent predictive ability ( p < 0.001, Table 1 ).…”

CLP1 is a Prognosis-Related Biomarker and Correlates With Immune Infiltrates in Rheumatoid Arthritis

“…We preprocessed the downloaded expression matrix, including data background adjustment, normalization, and summarization. The 5 gene sets of RNA modification writer genes (including m6A,m1A,m5C, APA, A-1) were obtained by Chen H et al( Chen et al, 2021 ) and Cong P et al( Cong et al, 2021 ): In order to analyze the changes in the expression values of 5 RNA modification writer genes in the synovial tissues of rheumatoid arthritis relative to the normal tissues, we further screened the differentially expressed genes in RA and normal synovium. DEG is recognized and integrated by the Limma package ( Ritchie et al, 2015 ) and FunRich software ( Pathan et al, 2015 ) in R, we set the genes with logFC>1 and adjPvalue<0.05 as up-regulated genes.…”

Post-Transcriptional Modifications of RNA as Regulators of Apoptosis in Glioblastoma

“…Knockdown of METTL3 inhibits the proliferation of glioblastoma cell lines. These data show that m6A methylation influences the NOTCH pathway, which is a potential target for glioblastoma treatment [ 141 ]. It is known that the NOTCH pathway influences many vital cell processes including apoptosis, so activation of this pathway by m6A-mediated stabilization of NOTCH3, DLL3 and HES1 mRNA, and increased expression of corresponding proteins, leads to the inhibition of apoptosis.…”