N6-methyladenosine RNA methylation regulator-related alternative splicing gene signature as prognostic predictor and in immune microenvironment characterization of patients with low-grade glioma

• DOI: 10.3389/fgene.2022.872186
• Publication Date: 2022-07-22T16:18:06Z
• Authors: Aierpati Maimaiti; Abudireheman Tuer...; Xianghong Meng; Yinan Pei; Wenyu Ji; Zhaohai Feng; Lei Jiang; Zengliang Wang; Maimaitijiang Kasimu; Yongxin Wang; Xin Shi
• Keywords: KEGG; N6-Methyladenosine; RNA methylation

Background: N6-methyladenosine (m6A) RNA methylation is an important epigenetic modification affecting alternative splicing (AS) patterns of genes to regulate gene expression. AS drives protein diversity and its imbalance may be factor in tumorigenesis. However, the clinical significance m6A regulator-related tumor microenvironment has not been investigated low-grade glioma (LGG). Methods: We used 12 modulatory (WTAP, FTO, HNRNPC, YTHDF2, YTHDF1, YTHDC2, ALKBH5, YTHDC1, ZC3H13, RBM15, METTL14, METTL3) from The Cancer Genome Atlas (TCGA) database as well TCGA-LGG (n = 502) dataset events transcriptome data. These data were downloaded subjected machine learning, bioinformatics, statistical analyses, including ontology (GO) Kyoto Encyclopedia Genes Genomes (KEGG) pathway enrichment analysis. Univariate Cox, Least Absolute Shrinkage Selection Operator (LASSO), multivariable Cox regression develop prognostic characteristics. Prognostic values validated using Kaplan-Maier survival analysis, proportional risk models, ROC curves, nomograms. ESTIMATE package, TIMER database, CIBERSORT method, ssGSEA algorithm R package utilized explore role immune LGG. Lastly, AS-splicing (SF) regulatory network was examined case considering SFs regulating events. Results: An aggregate 3,272 patients with LGG screened six learning algorithms. developed eight characteristics based on splice subtypes, which showed excellent prediction performance. Furthermore, quantitative nomograms strong validity prediction. In addition, signatures substantially associated diversity, ICB-related genes, infiltration status cell subtypes. Specifically, UGP2 better promise a for Finally, networks revealed potential functions SFs. Conclusion: present research offers novel perspective methylation. reveal that can mediate progression through immune-microenvironment, could serve viable biological marker stratification so optimize treatment regimens.