Expression Pattern and Prognostic Value of Key Regulators for m6A RNA Modification in Hepatocellular Carcinoma

Front Med (Lausanne). 2020 Sep 16:7:556. doi: 10.3389/fmed.2020.00556. eCollection 2020.

Abstract

As the most prevalent type of mRNA modification in mammals, N6-methyladenosine (m6A) is involved in various biological processes. Accumulating studies have indicated that the deregulation of m6A RNA modification is linked to cancer and other diseases. However, its implications in hepatocellular carcinoma (HCC) remain poorly characterized. Herein, we sought to investigate the expression pattern of 13 key regulators for m6A RNA modification and to evaluate their prognostic value in HCC. First, we systematically analyzed data from The Cancer Genome Atlas (TCGA) database pertaining to patient clinical information and mRNA gene expression data. We found that 11 out of 13 key regulators for m6A RNA modification showed significantly higher expression levels in HCC. Subsequently, we identified two subgroups (clusters 1 and 2) via consensus clustering based on the expression of 13 m6A RNA methylation regulators. Cluster 2 had a worse prognosis and was also significantly correlated with higher histological grade and pathological stage when compared with cluster 1. Moreover, cluster 2 was remarkedly enriched for cancer-related pathways. We further constructed a robust risk signature of five regulators for m6A RNA modification. Further analysis indicated that this risk signature could be an independent prognostic factor for HCC, and the prognostic relevance of this five-gene risk signature was successfully validated using the Gene Expression Omnibus (GEO) dataset. Finally, we established a novel prognostic nomogram on the basis of age, gender, histological grade, pathological stage, and risk score to precisely predict the prognosis of patients with HCC. In summary, we herein uncovered the vital role of regulators for m6A RNA modification in HCC and developed a risk signature as a promising prognostic marker in HCC patients.

Keywords: bioinformatics; hepatocellular carcinoma; m6A; nomogram; prognostic signature.