To better assess the clinical outcomes of HCC patients, in this study, we applied machine learning approaches to explore the prognostic significance of AE-DEGs in HCC and established a prognostic model based on a panel of six AE-DEGs, including PLOD2, HOXD9, BOP1, RAB26, KLRK1, and RGL4. Our identified AE-DEG-based signature outperformed clinical characteristics such as the TNM stage and seven previously established similar prognostic models in terms of predictive accuracy, suggesting that those six AE-DEGs might play important roles in HCC. This evidence concerns the gene RGL4 and hepatocellular carcinoma.