Molecular Classification of Human and Mouse Hepatocellul

肝细胞癌（HCC）个体预后的变异性表明HCC可能包括几种不同的生物学表型。这些表型可能是由肿瘤发生过程中不同致癌途径的激活和/或不同来源的细胞引起的。我们已经解决了肝癌的转录特征是否可以提供深入了解肿瘤的细胞起源。我们整合了来自大鼠胚胎肝母细胞和成人肝细胞的基因表达数据与来自人类和小鼠模型的HCC。与胎儿成肝细胞基因表达模式相同的HCC患者预后差。区分该亚型与其他类型HCC的基因表达程序包括肝卵圆细胞的标志物，表明该亚型的HCC可能起源于肝祖细胞。基因网络的分析表明，AP-1转录因子的激活在这个新发现的HCC亚型可能有关键作用，在肿瘤development.In这项工作中，我们已经表明，通过应用两个独立的基因表达的签名，我们能够与HCC的个人分为三个亚组，其特点是在临床结果的统计学显着差异。这些发现支持了多个分子途径决定HCC的发展和不同临床结果的观点。我们的发现还表明，肝癌的分子特征（例如预后基因表达特征）在诊断时就存在。因此，基因表达谱的使用有望改善HCC的分子分类和预后预测。此外，将HCC个体分子分层为同质亚组可能为开发新的治疗方式提供机会。

The variability in the prognosis of individuals with hepatocellular carcinoma (HCC) suggests that HCC may comprise several distinct biological phenotypes. These phenotypes may result from activation of different oncogenic pathways during tumorigenesis and/or from a different cell of origin. We have address whether the transcriptional characteristics of HCC can provide insight into the cellular origin of the tumor. We integrated gene expression data from rat fetal hepatoblasts and adult hepatocytes with HCC from human and mouse models. Individuals with HCC who shared a gene expression pattern with fetal hepatoblasts had a poor prognosis. The gene expression program that distinguished this subtype from other types of HCC included markers of hepatic oval cells, suggesting that HCC of this subtype may arise from hepatic progenitor cells. Analyses of gene networks showed that activation of AP-1 transcription factors in this newly identified HCC subtype might have key roles in tumor development.In this work we have shown that by applying two independent gene expression signatures, we were able to divide individuals with HCC into three subgroups characterized by statistically significant differences in clinical outcome. These findings support the notion that multiple molecular pathways dictate the development and different clinical outcomes of HCC. Our finding also indicates that the molecular features of HCC such as prognostic gene expression signatures are present at the time of diagnosis. Therefore, the use of gene expression profiling promises to improve molecular classification and prediction of outcomes in HCC. Furthermore, molecular stratification of individuals with HCC into homogeneous subgroups may provide opportunities for the development of new treatment modalities.