The m6A methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics.

Abstract

Objective:Epigenetic aberration plays an important role in the development and progression of hepatocellular carcinoma (HCC). However, the alteration of RNA N6-methyladenosine (m6A) modifications and its role in HCC progression remain unclear. We therefore aimed to provide evidence using bioinformatics analysis.Methods:We comprehensively analyzed the m6A regulator modification patterns of 605 HCC samples and correlated them with metabolic alteration characteristics. We elucidated 390 gene-based m6A-related signatures and defined an m6Ascore to quantify m6A modifications. We then assessed their values for predicting prognoses and therapeutic responses in HCC patients.Results:We identified 3 distinct m6A modification patterns in HCC, and each pattern had distinct metabolic characteristics. The evaluation of m6A modification patterns using m6Ascores could predict the prognoses, tumor stages, and responses to sorafenib treatments of HCC patients. A nomogram based on m6Ascores showed high accuracy in predicting the overall survival of patients. The area under the receiver operating characteristic curve of predictions of 1, 3, and 5-year overall survivals were 0.71, 0.69, and 0.70 in the training cohort, and in the test cohort it was 0.74, 0.75, and 0.71, respectively. M6Acluster C1, which corresponded to hypoactive mRNA methylation, lower expression of m6A regulators, and a lower m6Ascore, was characterized by metabolic hyperactivity, lower tumor stage, better prognosis, and lower response to sorafenib treatment. In contrast, m6Acluster C3 was distinct in its hyperactive mRNA methylations, higher expression of m6A regulators, and higher m6Ascores, and was characterized by hypoactive metabolism, advanced tumor stage, poorer prognosis, and a better response to sorafenib. The m6Acluster, C2, was intermediate between C1 and C3.Conclusions:HCCs harbored distinct m6A regulator modification patterns that contributed to the metabolic heterogeneity and diversity of HCC. Development of m6A gene signatures and the m6Ascore provides a more comprehensive understanding of m6A modifications in HCC, and helps predict the prognosis and treatment response.