Abstract
Background: Hepatocellular carcinoma (HCC) is the main type of primary liver cancer, and its related death ranks third worldwide. The curative methods and progress prediction markers of HCC are not sufficient enough. Nevertheless, little progress has been made in the signature of m(1)A-, m(5)C-, m(6)A-, m(7)G-, and DNA methylation of HCC. Results: We calibrated a risk gene signature model that can be used to categorize HCC patients based on univariate, multivariate, and LASSO Cox regression analysis. This gene signature classified the patients into high- and low-risk subgroups. Patients in the high-risk group showed significantly reduced overall survival (OS) compared with patients in the low-risk group. The gene set variation analysis (GSVA), immune infiltration, and immunotherapy response were analyzed. The results demonstrated that an immunosuppressive environment was exited and the high-risk group had higher sensitivity to 5-fluorouracil, cisplatin, sorafenib, tamoxifen, and epirubicin. These results indicated personalized therapy should be taken into consideration. Conclusions: Our findings enriched our understanding of the molecular heterogeneity, tumor microenvironment (TME), and drug susceptibility of HCC. m(1)A-, m(5)C-, m(6)A-, m(7)G-, and DNA methylation-related regulators may be promising biomarkers for future research.