The role of glucose, lipid, and amino acid metabolism in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) ranks among the leading causes of cancer-related death worldwide, and its rising incidence parallels the global epidemic of obesity, type 2 diabetes, and metabolic dysfunction-associated steatotic liver disease (MASLD). At the center of this convergence lies metabolic reprogramming, in which HCC cells couple accelerated aerobic glycolysis (the Warburg effect) to sustained de novo lipogenesis and rewired amino-acid handling. Glucose, lipid, and amino acid metabolism therefore constitute a single, interconnected network whose dysregulation supplies the energy and biosynthetic precursors that drive tumor proliferation, metastasis, and immune evasion. In this review we move beyond a pathway-by-pathway account to emphasize three integrative perspectives. First, the metabolic intermediates themselves (lactate, acetyl-CoA, succinyl-CoA, and α-ketoglutarate) operate as signaling molecules and epigenetic substrates, so that metabolic reprogramming feeds back onto chromatin and transcription to stabilize the malignant state. Second, a superimposed layer of non-coding RNAs and epigenetic machinery co-regulates the glycolytic, lipogenic, and amino-acid programs, and its perturbation, rather than any single enzyme, dictates the metabolic phenotype. Third, this rewiring is a principal driver of resistance to multikinase inhibitors, positioning metabolic enzymes as actionable co-targets. A central thesis emerges from this synthesis: the amino-acid metabolic state of an HCC is not merely a downstream supply of carbon and nitrogen but a determinant of its immune phenotype, an idea crystallized by the finding that the amino-acid metabolic cluster of HCC is enriched for PD-1 + cells and may preferentially respond to immune-checkpoint blockade. We further integrate the contribution of liver-lineage transcription factors and of CTNNB1, whose recurrent activating mutations imprint a fatty-acid-oxidation-dependent subtype, together with omics-driven molecular classification. By synthesizing these mechanisms, we provide a coherent framework that links metabolic reprogramming to tumor heterogeneity, immune evasion, and therapeutic resistance, and outline concrete avenues for metabolism-directed diagnosis and treatment of HCC.