Gene expression analysis of biopsy samples reveals critical limitations of transcriptome-based molecular classifications of hepatocellular carcinoma.
Gene expression analysis of biopsy samples reveals critical limitations of transcriptome-based molecular classifications of hepatocellular carcinoma.
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DOI：
10.1002/cjp2.37
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发表时间：
2016-04
期刊：
影响因子：
--
通讯作者：
Heim MH
中科院分区：
文献类型：
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作者：
Makowska Z;Boldanova T;Adametz D;Quagliata L;Vogt JE;Dill MT;Matter MS;Roth V;Terracciano L;Heim MH
肝细胞癌（HCC）的分子分类可以指导患者分层，以针对亚类特异性癌症“驱动途径”进行个性化治疗。目前，HCC 有几种基于转录组的分子分类，具有不同的亚类数量，从 2 到 6 个不等。它们是使用切除的肿瘤建立的，这对没有肝硬化和早期 HCC 的患者产生了选择偏差。我们生成并分析了 60 名患者的配对 HCC 和非癌性肝组织活检以及 5 个正常肝脏样本的基因表达数据。 HCC 活检概况的无偏共识聚类确定了 3 个稳健的类别。类别成员资格与生存率、肿瘤大小以及埃德蒙森和巴塞罗那临床肝癌 (BCLC) 分期相关。当仅关注 HCC 活检的基因表达时，我们可以根据特征基因的表达模式验证先前报告的 HCC 分类。然而，当使用相对于正常组织的倍数变化时，亚类特异性基因表达模式不再保留。大多数被认为是亚类特异性的基因被证明是所有 HCC 患者中差异调节的癌症相关基因，分子亚类之间存在定量而非定性差异。除了具有明确的β-连环蛋白基因特征的样本子集之外，生物途径分析无法识别反映不同致癌程序激活的类特异性途径。总之，我们发现 HCC 活检的基因表达谱在指导针对特定驱动途径的治疗方面的潜力有限，但可以识别具有不同预后的患者亚组。
Molecular classification of hepatocellular carcinomas (HCC) could guide patient stratification for personalized therapies targeting subclass‐specific cancer ‘driver pathways’. Currently, there are several transcriptome‐based molecular classifications of HCC with different subclass numbers, ranging from two to six. They were established using resected tumours that introduce a selection bias towards patients without liver cirrhosis and with early stage HCCs. We generated and analyzed gene expression data from paired HCC and non‐cancerous liver tissue biopsies from 60 patients as well as five normal liver samples. Unbiased consensus clustering of HCC biopsy profiles identified 3 robust classes. Class membership correlated with survival, tumour size and with Edmondson and Barcelona Clinical Liver Cancer (BCLC) stage. When focusing only on the gene expression of the HCC biopsies, we could validate previously reported classifications of HCC based on expression patterns of signature genes. However, the subclass‐specific gene expression patterns were no longer preserved when the fold‐change relative to the normal tissue was used. The majority of genes believed to be subclass‐specific turned out to be cancer‐related genes differentially regulated in all HCC patients, with quantitative rather than qualitative differences between the molecular subclasses. With the exception of a subset of samples with a definitive β‐catenin gene signature, biological pathway analysis could not identify class‐specific pathways reflecting the activation of distinct oncogenic programs. In conclusion, we have found that gene expression profiling of HCC biopsies has limited potential to direct therapies that target specific driver pathways, but can identify subgroups of patients with different prognosis.