Molecular Classification of Human and Mouse Hepatocellul

肝细胞癌患者预后的差异性表明，肝细胞癌可能包括几种不同的生物学表型。这些表型可能是由于不同的致癌途径在肿瘤发生过程中被激活和/或来自不同的起源细胞。我们已经解决了肝细胞癌的转录特征是否可以提供对肿瘤的细胞起源的洞察。我们整合了来自大鼠胎肝母细胞和成年肝细胞的基因表达数据，以及来自人和小鼠模型的肝细胞癌。与胎儿肝母细胞基因表达模式相同的肝细胞癌患者预后较差。区别于其他类型的肝细胞癌的基因表达程序包括肝卵圆细胞的标记，提示该亚型的肝细胞癌可能起源于肝祖细胞。基因网络分析表明，AP-1转录因子在这一新发现的肝癌亚型中的激活可能在肿瘤的发展中起关键作用。在这项工作中，我们已经证明，通过应用两个独立的基因表达信号，我们能够将肝癌患者分为三个亚组，这些亚组具有统计学上显著的临床结果差异。这些发现支持多个分子途径决定了肝细胞癌的发展和不同的临床结局的观点。我们的发现还表明，肝细胞癌的分子特征，如预后基因表达特征，在诊断时就已经存在。因此，基因表达谱的使用有望改善肝细胞癌的分子分类和预后预测。此外，将肝细胞癌患者的分子分层划分为同质亚组可能为新的治疗方式的发展提供机会。

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.