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Cancer Res. 2011 Apr 1;71(7):2718-27. doi: 10.1158/0008-5472.CAN-10-2705. Epub 2011 Feb 15.

Coactivation of AKT and β-catenin in mice rapidly induces formation of lipogenic liver tumors.

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  • 1Cancer and Inflammation Program, NCI-Frederick, Frederick, Maryland, USA.


Obesity is a risk factor for development of certain cancers but the basis for this risk is unclear. In this study, we developed a novel mouse model that demonstrates directly how lipogenic phenotypes commonly associated with diet-induced metabolic syndromes can influence hepatic cancer development. Activated AKT and β-catenin (AKT/CAT) genes were hydrodynamically codelivered using the Sleeping Beauty transposon to initiate liver tumorigenesis. AKT/CAT and MET/CAT combination induced microscopic tumor foci by 4 weeks, whereas no tumorigenesis resulted from delivery of AKT, MET, or CAT alone. Primary AKT/CAT tumor cells were steatotic (fatty) hepatocellular adenomas which progressed to hepatocellular carcinomas (HCC) upon in vivo passage, whereas primary MET/CAT tumors emerged directly as frank HCC. Conversion of AKT/CAT tumor cells to frank HCC during passage was associated with induction of the human HCC marker α-fetoprotein and the stem cell marker CD133. Using hierarchical clustering and gene set enrichment analysis, we compared the primary murine AKT/CAT and MET/CAT tumors to a panel of 53 human HCCs and determined that these two mouse models could be stratified as distinct subtypes associated in humans with poor clinical prognosis. The chief molecular networks identified in primary and passaged AKT/CAT tumors were steatosis and lipid metabolic pathways, respectively. Our findings show how coactivation of the AKT and CAT pathways in hepatocytes can efficiently model development of a lipogenic tumor phenotype. Furthermore, we believe that our approach could speed the dissection of microenvironmental factors responsible for driving steatotic-neoplastic transformation to frank carcinoma, through genetic modification of existing immunodefined transgenic models.

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