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J Pathol. 2011 Sep;225(1):19-28. doi: 10.1002/path.2936. Epub 2011 Jul 8.

A ΔRaf1-ER-inducible oncogenic zebrafish liver cell model identifies hepatocellular carcinoma signatures.

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Institute of Biology, Leiden University, The Netherlands.


Although the underlying molecular mechanism of hepatocellular carcinoma remains unclear, signalling pathways essential in cell survival and growth are altered, including the Raf-MEK-MAPK pathway. This pathway can be activated by hepatitis B or C virus infections and the ectopic expression of the Raf-1 oncogene is frequently seen in hepatocellular carcinomas. In addition, the Raf-MEK-MAPK pathway was also shown to be deregulated in zebrafish liver tumours. Based on the genetic conservation between zebrafish and human liver tumours, the zebrafish was used as an animal model to better understand the molecular basis of hepatocellular carcinoma. Here we establish an inducible oncogenic zebrafish cell model, in which oncogenic human Raf-1(ΔRaf1) can be post-transcriptionally activated in zebrafish liver cells by administration of 4-hydroxytamoxifen (4HT). The ΔRaf1 activation resulted in the hyperactivation of the zebrafish MEK-ERK cascade, promoted cell growth and proliferation, and inhibited apoptosis. The mitogenic transformation of the ZFL-ΔRaf1-ER cells was confirmed by in vivo allo-transplantation and in silico microarray analyses. Gene expression profiling of cells treated with 4HT and a MEK-inhibitor identified a Raf-MEK-dependent signature set. This transcriptome response was compared to zebrafish and human liver cancer transcriptomes. We identified, and validated by quantitative PCR, a set of genes transcriptionally regulated by hyperactive MAPK signalling in ZFL-ΔRaf1-ER cells, zebrafish liver tumours and human liver tumours, suggesting that the in vitro zebrafish liver cell model can be used for further study of the molecular basis of human hepatocellular carcinoma. The molecular targeting of the commonly regulated hepatocellular carcinoma genes using the ZFL-ΔRaf1-ER cell model can be applied for high-throughput preclinical target discovery.

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