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: The process of hepatocarcinogenesis in the diethylnitrosamine (DEN) initiation/phenobarbital (PB) promotion mouse model involves the selective clonal outgrowth of cells harboring oncogene mutations in Ctnnb1, while spontaneous or DEN-only-induced tumors are often Ha-ras- or B-raf-mutated. The molecular mechanisms and pathways underlying these different tumor sub-types are not well characterized. Their identification may help identify markers for xenobiotic promoted versus spontaneously occurring liver tumors. Here, we have characterized mouse liver tumors harboring either Ctnnb1 or Ha-ras mutations via integrated molecular profiling at the transcriptional, translational and post-translational levels. In addition, metabolites of the intermediary metabolism were quantified by high resolution 1H magic angle nuclear magnetic resonance. We have identified tumor genotype-specific differences in mRNA and miRNA expression, protein levels, post-translational modifications, and metabolite levels that facilitate the molecular and biochemical stratification of tumor phenotypes. Bioinformatic integration of these data at the pathway level led to novel insights into tumor genotype-specific aberrant cell signaling and in particular to a better understanding of alterations in pathways of the cell intermediary metabolism, which are driven by the constitutive activation of the [beta]-Catenin and Ha-ras oncoproteins in tumors of the two genotypes.

What's new?

Changes in tumor cell intermediary metabolism may offer new options in cancer therapy. This study investigated changes in the intermediary metabolism of liver cells caused by aberrant signaling through two different oncoproteins. Mouse liver tumors-either mutated in Ha-ras or in Ctnnb1, which encodes [beta]-Catenin-were analyzed for changes in global mRNA and microRNA expression, phosphoprotein levels, and metabolite spectra. The study revealed tumor genotype-specific alterations in several important pathways of the cellular intermediary metabolism, increasing knowledge about the complex interplay between oncogenic signaling and the tumor phenotype. This may help advance the diagnostic and development of biomarkers for tumors.

(C) 2014 John Wiley & Sons, Ltd