Hepatocellular carcinoma (HCC) remains a global challenge as it is the sixth most common neoplasm worldwide and the third leading cause of cancer-related death. A key feature of HCC is abnormal metabolism, which promotes cancer cell proliferation, survival, invasion, and metastasis. However, the significance of metabolism-related genes (MRGs) in HCC remains to be elucidated. Here, we aim to establish a novel metabolism-related prognostic signature for the prediction of patient outcomes and to investigate the value of MRG expression in the prognostic prediction of HCC. In our research, a Metabolism-Related Risk Score (MRRS) model was constructed using 14 MRGs (DLAT, SEPHS1, ACADS, UCK2, GOT2, ADH4, LDHA, ME1, TXNRD1, B4GALT2, AK2, PTDSS2, CSAD, and AMD1). The Kaplan-Meier curve confirmed that the MRRS has a high accuracy in predicting the prognosis of HCC patients (p<0.001). According to the MRRS model, the area under the curve (AUC) values for predicting the prognosis of patients with hepatocellular carcinoma at 1, 3, and 5 years reached 0.829, 0.760, and 0.739, respectively. Functional analyses revealed that signaling pathways associated with the cell cycle were largely enriched by differential genes between high and low-risk groups. In addition, dendritic cells (DCs) (p<0.001), CD4+ T cells (p<0.01), CD8+ T cells (p<0.001), B cells (p<0.001), neutrophils (p<0.001), macrophages (p<0.001) had a higher proportion of infiltrates in high-risk populations. Low GOT2 expression is associated with poor prognosis in patients with hepatocellular carcinoma. Knockdown of GOT2 significantly increased the migration capacity of the Huh7 and MHCC97H hepatocellular carcinoma lines. Our research reveals that GOT2 is negatively related to the survival of patients with hepatocellular carcinoma and GOT2 may contribute to tumor progression by inhibiting the ability of tumor cells to migrate.