Low-Grade Dysplastic Nodules Revealed as the Tipping Point during Multistep Hepatocarcinogenesis by Dynamic Network Biomarkers.
Low-Grade Dysplastic Nodules Revealed as the Tipping Point during Multistep Hepatocarcinogenesis by Dynamic Network Biomarkers.
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动态网络生物标志物揭示低度发育不良结节是多步肝癌发生过程中的临界点
DOI：
10.3390/genes8100268
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发表时间：
2017-10-13
期刊：
影响因子：
3.5
通讯作者：
Chen L
中科院分区：
文献类型：
--
作者：
Lu L;Jiang Z;Dai Y;Chen L
肝细胞癌（HCC）是一种复杂的疾病，具有从肿瘤前病变(包括肝硬化、低级别发育不良结节（lgdn）和高级别发育不良结节（HGDNs）到HCC的多步骤癌变过程。目前对其分子发病机制只有基本的了解，关键问题是在分子水平上确定HCC起始期的关键转变发生的时间和方式。在这项工作中，我们首次揭示了lgdn是肝癌发生的临界点（即HCC前状态，而不是HCC状态），这是基于一系列基因表达谱的新数学模型，称为动态网络生物标志物(DNB) -一组主导过渡的基因或分子。与传统的基于观察到的基因（或分子）差异表达来诊断疾病状态的生物标志物不同，DNB模型利用观察到的基因的集体波动和相关性，从而预测即将发生的疾病状态或诊断临界状态。我们的研究结果表明，由59个基因组成的DNB标志着HCC的引爆点（即lgdn）。另一方面，肝硬化和hgdn之间存在大量差异表达的基因，这突出了在临界点或lgdn前后的明显差异或剧烈变化，这意味着59个DNB成员是HCC即将急剧恶化的预警信号。我们进一步确定了负责这一转变的生物学途径，如I型干扰素信号通路、Janus激酶信号转导和转录激活因子（JAK-STAT）信号通路、转化生长因子(TGF)-β信号通路、视黄酸诱导基因I （RIG-I）样受体信号通路、细胞粘附分子和细胞周期。特别是，与免疫系统反应和细胞粘附相关的通路下调，与细胞生长和死亡相关的通路上调。此外，通过独立数据的生存分析，DNB被证实是hcv诱导的HCC患者预后的有效预测因子，提示DNB具有潜在的临床应用价值。这项工作为多步骤肝癌发生过程中关键转变的动态调控提供了生物学见解。
Hepatocellular carcinoma (HCC) is a complex disease with a multi-step carcinogenic process from preneoplastic lesions, including cirrhosis, low-grade dysplastic nodules (LGDNs), and high-grade dysplastic nodules (HGDNs) to HCC. There is only an elemental understanding of its molecular pathogenesis, for which a key problem is to identify when and how the critical transition happens during the HCC initiation period at a molecular level. In this work, for the first time, we revealed that LGDNs is the tipping point (i.e., pre-HCC state rather than HCC state) of hepatocarcinogenesis based on a series of gene expression profiles by a new mathematical model termed dynamic network biomarkers (DNB)—a group of dominant genes or molecules for the transition. Different from the conventional biomarkers based on the differential expressions of the observed genes (or molecules) for diagnosing a disease state, the DNB model exploits collective fluctuations and correlations of the observed genes, thereby predicting the imminent disease state or diagnosing the critical state. Our results show that DNB composed of 59 genes signals the tipping point of HCC (i.e., LGDNs). On the other hand, there are a large number of differentially expressed genes between cirrhosis and HGDNs, which highlighted the stark differences or drastic changes before and after the tipping point or LGDNs, implying the 59 DNB members serving as the early-warning signals of the upcoming drastic deterioration for HCC. We further identified the biological pathways responsible for this transition, such as the type I interferon signaling pathway, Janus kinase–signal transducers and activators of transcription (JAK–STAT) signaling pathway, transforming growth factor (TGF)-β signaling pathway, retinoic acid-inducible gene I (RIG-I)-like receptor signaling pathway, cell adhesion molecules, and cell cycle. In particular, pathways related to immune system reactions and cell adhesion were downregulated, and pathways related to cell growth and death were upregulated. Furthermore, DNB was validated as an effective predictor of prognosis for HCV-induced HCC patients by survival analysis on independent data, suggesting a potential clinical application of DNB. This work provides biological insights into the dynamic regulations of the critical transitions during multistep hepatocarcinogenesis.
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