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Liver cancer, or hepatic cancer, is a malignant tumour that grows on the surface or inside the liver. The leading cause is a viral infection with hepatitis B or C virus. The most frequent liver cancers are hepatocellular carcinoma and hepatoblastoma (formed by immature liver cells).
Sun et al. identify fatty acid binding protein 5 (FABP5) as a driver of obesity-induced hepatocellular carcinoma in mice. FABP5 inhibition is found to predispose transformed cells to death by ferroptosis and to induce a pro-inflammatory tumour microenvironment.
Artificial intelligence (AI) is advancing rapidly and is already starting to transform cancer research and care. Here, the authors outline how AI could be incorporated into liver cancer management, highlighting areas with academic, commercial and clinical potential, as well as ongoing progress and pitfalls.
A recent study reported the development and validation of the Liver Artificial Intelligence Diagnosis System (LiAIDS), a fully automated system that integrates deep learning for the diagnosis of liver lesions on the basis of contrast-enhanced CT scans and clinical information. This tool improved diagnostic precision, surpassed the accuracy of junior radiologists (and equalled that of senior radiologists) and streamlined patient triage. These advances underscore the potential of artificial intelligence to enhance hepatology care, although challenges to widespread clinical implementation remain.
Recently published in Nature, Fan et al. demonstrate that accumulation of advanced glycation end-products in the extracellular matrix of the liver increases viscoelasticity to promote hepatocellular carcinoma growth, independent of stiffness.