Hepatocellular carcinoma (HCC) is the most common histological subtype of primary liver cancer, accounting for nearly 80-90 % of all liver cancer cases. While 'liver cancer' refers broadly to all malignant tumors arising in the liver (including HCC, cholangiocarcinoma, and others), HCC specifically originates from hepatocytes. HCC is characterized by extensive metabolic reprogramming, including not only higher levels of aerobic glycolysis, de novo lipogenesis, and altered glutamine metabolism but also altered one-carbon metabolism. Enhanced metabolic adaptation markers, therefore, serve as key indicators of malignant transformation but also contribute to cancer progression by promoting cell proliferation, metastasis, immune modulation, and therapy evasion. Emerging evidence suggests microRNAs (miRNAs) can coordinate these metabolic adaptations by targeting key enzymes, transporters, transcription factors, signaling molecules, or pathways involved in metabolism. For instance, miR-122, miR-27a, miR-148a, and miR-4310 inhibit lipid accumulation and mitochondrial dysfunction, while miR-21, miR-103a, and miR-30b-5p promote glycolysis, lipogenesis, and anabolic metabolism. Long non-coding RNAs (lncRNAs) and exosomal miRNAs interact with these upstream regulators to form a heterogeneous network of non-coding RNAs. These networks participate in remodeling the tumor microenvironment, modulating the immune response, and facilitating metabolic adaptation in HCC. miRNAs are ideal for the potential stratification of HCC risk, prognosis, and therapeutic response, as they occupy key upstream positions in regulatory hierarchies and have been described as both biomarkers and potential metabolic switches. This study aims to elucidate the role of microRNAs in regulating metabolic pathways in HCC by delineating numerous miRNA-target interactions involved in glycolysis, lipid, amino acid, and nucleotide metabolism. This knowledge will enable us to identify novel diagnostic biomarkers and therapeutic targets for prognosis and to explore effective novel precision treatment strategies.
Alrawi et al. (2025) studied this question.