The pattern of expression and prognostic value of key regulators for m7G RNA methylation in hepatocellular carcinoma - Chen, Jianxing; Yao, Shibin; Sun, Zhijuan; Wang, Yanjun; Yue, Jili; Cui, Yongkang; Yu, Chengping; Xu, Haozhi; Li, Linqiang (Frontiers in Genetics, 2022)
N7-methylguanosine (m7G) modification on internal RNA positions plays an important role in various biological processes. Recent studies have indicated that m7G modification is associated with multiple cancers. However, in hepatocellular carcinoma (HCC), its implications remain to be determined. Herein, we sought to investigate the expression patterns of 29 key regulators of m7G RNA modification and to assess their prognostic value in HCC. First, the data from The Cancer Genome Atlas (TCGA) database concerning patient clinical information and mRNA gene expression data was analyzed systematically. Second, two subgroups (clusters 1 and 2) were identified via consensus clustering according to the expression of 29 m7G RNA methylation regulators. Furthermore, a robust risk signature for seven m7G RNA modification regulators was constructed. Last, the prognostic associations of the seven-gene risk signature were validated using the Gene Expression Omnibus (GEO) dataset. We found that 24 out of the 29 key regulators of m7G RNA modification varied significantly in their expression levels between the HCC and the adjacent tumor control tissues. Cluster 1 had a worse prognosis compared with cluster 2 and was also positively correlated with T classification (T), pathological stage, and vital status (fustat) significantly. Consensus clustering results suggested the expression pattern of m7G RNA modification regulators was correlated with the malignancy of HCC strongly. In addition, cluster 1 was extensively enriched in metabolic-related pathways. Seven optimal genes (METTL1, WDR4, NSUN2, EIF4E, EIF4E2, NCBP1, and NCBP2) were selected to establish the risk model for HCC. Indicating by further analyses and validation, the prognostic model has good predictive power and this risk signature might be an independent prognostic factor for HCC. Finally, a new prognostic nomogram based on age, gender, pathological stage, histological grade, and risk score was established to accurately predict the prognosis of HCC patients. In summary, we uncovered the association of HCC severity and expression levels of m7G RNA modification regulators, and developed a risk score model for predicting prognosis of HCC patients’ progression.