Etiology-Driven Mouse Models of Hepatocellular Carcinoma: Paving the Way for Precision Oncology.

BACKGROUND

Hepatocellular carcinoma (HCC) is biologically heterogeneous, and its genomic alterations, inflammatory context, and tumor immune microenvironment are strongly shaped by the underlying etiology, including chronic hepatitis B virus (HBV) infection, metabolic dysfunction-associated steatotic liver disease (MASLD), and alcohol exposure. This etiological diversity complicates the selection and interpretation of preclinical models. Genetically engineered mouse models (GEMMs), particularly when combined with dietary, chemical, viral, or alcohol-related insults, provide useful systems for dissecting how defined genetic drivers interact with disease-specific liver environments in an immunocompetent host.

MAIN BODY: This review summarizes etiology-aligned GEMMs and related mouse models for HCC. In HBV-related models, we discuss how viral antigen exposure, HBV-associated genomic instability, Tert activation, and Trp53 loss support a multi-driver framework rather than a single-lesion model of carcinogenesis. In MASLD-associated HCC, we examine models involving Wnt/β-catenin activation, Acvr2a loss, Pten deficiency, and MUP-uPA driven steatohepatitis, emphasizing their value for studying immune exclusion, lactate-rich immunosuppression, IgA+ plasma-cell accumulation, and altered responses to immune checkpoint blockade. In alcohol-associated HCC, we review models centered on Aldh2 deficiency, ER stress-lysosomal lipid remodeling through the ATF4/LPLA2 axis, NF-κB-related inflammatory regulation, and neutrophil-driven tumor promotion. Across these etiologies, we compare model strengths and limitations, including tumor latency, penetrance, reproducibility, lack of cirrhotic remodeling, sex-dependent variability, microbiome-related environmental effects, and incomplete modeling of tumor-stroma co-evolution.

SHORT

CONCLUSION

Etiology-aligned GEMMs can help match biological questions to appropriate preclinical platforms and generate testable hypotheses about therapy response. However, etiology alone should not be treated as a substitute for molecular profiling or clinical validation. Future models should integrate precise genetic engineering with fibrotic or cirrhotic backgrounds, microbiome-aware environmental modulation, and complementary human-relevant systems to better capture the complex evolution of human HCC.