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Article Abstract

Background & Aims: One-third of hepatocellular carcinomas (HCCs) harbor mutations activating the β-catenin pathway, predominantly via mutations in the CTNNB1 gene itself. Mouse models of Apc loss-of-function are widely used to mimic β-catenin-dependent tumorigenesis. Given the low prevalence of APC mutations in human HCCs, we aimed to generate liver tumors through CTNNB1 exon 3 deletion (βcat). We then compared βcat liver tumors with liver tumors generated via frameshift in exon 15 of Apc (Apc).

Methods: We used hepatocyte-specific and inducible mouse models generated through either a Cre-Lox or a CRISPR/Cas9 approach using adeno-associated virus vectors. Tumors generated by the Cre-Lox models were phenotypically analyzed using immunohistochemistry and were selected for transcriptomic analysis by RNA-sequencing (RNAseq). Mouse RNAseq data were compared to human RNAseq data (8 normal tissues, 48 HCCs, 9 hepatoblastomas) in an integrative analysis. Tumors generated via CRISPR were analyzed using DNA sequencing and immuno-histochemistry.

Results: Mice with CTNNB1 exon 3 deletion in hepatocytes developed liver tumors indistinguishable from Apc liver tumors. Both Apc and βcat mouse models induced growth of phenotypically distinct tumors (differentiated or undifferentiated). Integrative analysis of human and mouse tumors showed that differentiated mouse tumors cluster with well-differentiated human CTNNB1-mutated tumors. Conversely, undifferentiated mouse tumors cluster with human mesenchymal hepatoblastomas and harbor activated YAP signaling.

Conclusion: Apc and βcat mouse models both induce growth of tumors that are transcriptionally similar to either well-differentiated and β-catenin-activated human HCCs or mesenchymal hepatoblastomas.

Lay Summary: New and easy-to-use transgenic mouse models of primary liver cancers have been generated, with mutations in the gene encoding beta-catenin, which are frequent in both adult and pediatric primary liver cancers. The mice develop both types of cancer, constituting a strong preclinical model.

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http://dx.doi.org/10.1016/j.jhep.2022.02.023DOI Listing

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