Frontiers in Pharmacology (Mar 2022)

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

DOI
https://doi.org/10.3389/fphar.2022.854851
Journal volume & issue
Vol. 13

Abstract

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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.

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