We previously showed that the hepatoblast-like (HB) signature is driven by the downstream targets of AP-1.19 Furthermore, the increase in JUN expression was attributed to an increase in JUB (Ajuba, LIM domain protein)/Ajuba, which is known to promote activation of murine c-Jun27 and the phoshorylation of β-catenin.28 Based on the list of homologous rat and human genes, we matched the expression profile unique to CK19+ foci with the human HCC data set. We then assessed the enrichment of the CK19+ gene signature in HCC subtypes A and B by using the nonparametric gene set enrichment analysis29 (Fig. 5A). The CK19+ gene signature was
significantly enriched (P = 0.002) and positively correlated with the poor survival subclass A and progenitor-derived Natural Product Library HCCs. An enrichment analysis of the CK19+ gene signature with the Molecular Signatures Database demonstrated a
significant overlap with several stem cell–related genes sets (Supporting Table 2). Notably, among the top 10 gene sets, an overlap was found with several liver-specific gene sets. Also, assessment of the human stem cell module map30 revealed a significant overlap between the gene expression signature unique to CK19+ foci and genes associated with stem cell derivation (Fig. 5B). Together, these data show that CK19+/GSTP+ persistent nodules selleck kinase inhibitor exhibit an HPC-like expression profile. Next, we examined the functional connectivity among the significant genes specific for the CK19-negative focal lesions. The most predominant feature was the overexpression of KLF10/transforming growth factor beta (TGF-β)–inducible early growth response gene, previously described as a tumor suppressor gene in breast cancer.31 KLF10 expression has been shown to be sufficient to Cyclin-dependent kinase 3 induce apoptosis in Hep3B cells.32 Moreover, loss of KLF10 interfered with TGF-β–induced apoptosis and promoted carcinogenesis.32 Thus,
KLF10 may be an early response gene responsible for TGF-β–dependent apoptosis, thereby contributing to the remodeling phenotype. We next examined the potential usefulness of the RH model to gain insight into the relevance of HPC for human HCC. For this purpose, we used a comparative functional genomics approach.33, 34 This approach is based on the hypothesis that because regulatory elements of evolutionarily related species are conserved, gene expression signatures reflecting similar phenotypes in different species could be also conserved. The hypothesis has been supported by numerous studies demonstrating that cross-compared gene expression data from human HCC and rodent HCC models can identify the aberrant phenotypes reflecting the evolutionarily conserved molecular pathways.35, 36 Here, we applied the signature of 276 orthologous genes found between human and rat, to integrate the rat lesions with a data set of 53 human HCCs (Fig. 6 and Supporting Table 1).