An m6A-Related lncRNA Signature Predicts the Prognosis of Hepatocellular Carcinoma
Zhenyu Zhang, Fangkai Wang, Jianlin Zhang, Wenjing Zhan, Gaosong Zhang, Chong Li, Tongyuan Zhang, Qianqian Yuan, Jia Chen, Manyu Guo, Honghai Xu, Feng Yu, Hengyi Wang, Xingyu Wang, Weihao Kong
Abstract
Objective: The purpose of this study was to establish an N6-methylandenosine (m6A)-related long non-coding RNA (lncRNA) signature to predict the prognosis of hepatocellular carcinoma (HCC). Methods: Pearson correlation analysis was used to identify m6A-related lncRNAs. We then performed univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct an m6A-related lncRNA signature. Based on the cutoff value of the risk score determined by the X-title software, we divided the HCC patients into high -and low-risk groups. A time-dependent ROC curve was used to evaluate the predictive value of the model. Finally, we constructed a nomogram based on the m6A-related lncRNA signature. Results: ZEB1-AS1, MIR210HG, BACE1-AS, and SNHG3 were identified to comprise an m6A-related lncRNA signature. These four lncRNAs were upregulated in HCC tissues compared to normal tissues. The prognosis of patients with HCC in the low-risk group was significantly longer than that in the high-risk group. The M6A-related lncRNA signature was significantly associated with clinicopathological features and was established as a risk factor for the prognosis of patients with HCC. The nomogram based on the m6A-related lncRNA signature had a good distinguishing ability and consistency. Conclusion: We identified an m6A-related lncRNA signature and constructed a nomogram model to evaluate the prognosis of patients with HCC.