Molecular signatures for liver cancer diagnosis and treatment stratification

我们正在使用全球基因组方法来分析与肝脏疾病不同阶段相关的临床标本。我们已经确定了早期肝癌患者的独特诊断特征，并基于转移性原发性肝细胞癌（HCC）标本的mRNA基因表达开发了独特的分子特征，以预测HCC患者的预后和转移。我们发现，这种分子标记可以识别那些复发风险最高的患者，即使是早期疾病患者。最近，我们整合了基因组和转录组谱来寻找转移驱动基因。我们发现原发肿瘤病变及其匹配的远处转移相似，但在伴有或不伴有转移的原发肿瘤之间可以识别出显着差异。此外，转移基因主要是肿瘤类型和器官部位特异性的，进一步巩固了转移倾向是原发肿瘤固有的。我们还开发了一种基于HCC患者肝脏微环境mRNA基因表达的独特分子预后标记。我们发现，在转移性肝脏微环境中存在主要的体液细胞因子谱，并且向抗炎/免疫抑制反应的转变可能促进HCC转移。有趣的是，肿瘤的特征与肝脏微环境的特征主要不同。我们最近研究了激活的肝星状细胞（a - hsc）是否直接导致HCC复发。我们在HCC患者的非肿瘤组织中鉴定并验证了与HCC复发和生存相关的a - hsc特异性基因表达特征。进一步的研究表明，a -造血干细胞优先改变单核细胞群体，通过将其基因表达从炎症特征转变为免疫抑制特征，诱导成瘤和进展特征。这些发现表明，破坏炎症细胞与微环境成分之间的相互作用和信号事件可能是预防HCC复发的有用治疗策略。我们还发现，小的非编码rna，称为microrna，与转移有关，甚至在早期疾病中也能显著预测患者的生存和复发，而某些microrna（如microRNA-26）与性别有关。microRNA-26低表达的患者生存率较低，对干扰素治疗的反应优于正常表达的患者。我们开发了一种基于qrt - pcr的基质模板和评分算法（MIR26-DX），将患者分为低或高microRNA-26组。模板选择的低microRNA-26水平的患者对干扰素- α治疗反应良好。基于这些发现（NCT01681446），我们已经在中国启动了一项多中心随机对照临床试验。我们还发现，miR-29家族成员在AFP+肿瘤中显著下调，与DNMT3A基因表达呈显著负相关，DNA甲基化增加。AFP还通过c-MYC抑制miR-29a/b-1位点的转录，促进裸小鼠AFP- HCC细胞的肿瘤生长。因此，AFP+ HCC和AFP- HCC之间的肿瘤生物学差异很大，并且AFP是miR-29的功能性拮抗剂，这可能导致HCC的整体表观遗传改变和预后不良。我们还使用综合方法来鉴定HCC驱动基因。我们结合了高分辨率，基于阵列的比较基因组杂交和HCC样本的转录组分析，以鉴定和验证与染色体8p丢失和不良预后相关的10个基因特征。功能研究表明，三个基因产物具有肿瘤抑制特性，其中两个基因SORBS3和SH2D4A在HCC细胞中相互连接并抑制stat3介导的IL-6信号传导。我们还整合了代谢物和mRNA谱来定义HCC癌症干细胞的关键信号事件。我们的分析显示，硬脂酰辅酶a去饱和酶（SCD），一种参与脂肪酸生物合成的关键酶，及其相关代谢物在干细胞样HCC中高度升高，并与HCC的生存和侵袭性相关。在肝脏、乳腺癌和胰腺癌组织的全球代谢谱比较中，我们发现代谢物主要是每种组织和癌症类型所特有的。因此，代谢谱分析可以作为癌症分类工具，根据肿瘤的起源组织来区分肿瘤。我们最近还分析了从乳腺癌和HCC患者中收集的代谢组学和转录组学资料，以探索代谢酶表达和参与其催化反应的代谢物水平之间的关联并建立预测因子。广泛的代谢物可以成功地从转录组预测。我们还开发了一种综合子图挖掘方法，issubgraph，以发现mirna -基因网络的模式，以对HCC患者进行分层。该算法可以检测出mirna和基因的协同调控，并具有高度稳定的分类预测。因此，我们的方法可以整合来自不同平台和不同动态尺度的各种组学数据，更好地定义分子肿瘤亚型。通过最近对HCC的分析，我们发现大量RNA结合蛋白（RBP）失调，RBP失调与预后不良有关。我们进一步发现，通过体细胞拷贝数改变，一种顶级候选RBP——负伸长因子E （NELFE）的致癌激活增强了MYC信号传导并促进了HCC的进展。有趣的是，NELFE通过选择性调节myc相关基因诱导独特的肿瘤转录组。因此，我们的研究结果表明，NELFE是一种致癌蛋白，可能通过调节MYC信号传导导致HCC中转录组失衡。胆管癌（CCA）是一种与胆管相关的癌症，也是第二常见的原发性肝癌（PLC），其发病率非常普遍，尤其是在泰国东北部地区。我们发起了泰国肝癌基因组学和表达研究计划（TIGER-LC），以提供与泰国肝癌患者原发性肝癌类型相关的基因组改变的全面全球分析。最近，我们通过基因组学、转录组学和代谢组学的系统整合，在199名泰国CCA和HCC患者中发现了与类似预后相关的关键驱动因素的共同分子亚型。我们的研究结果表明，虽然ICC和HCC在临床上被视为不同的实体，但它们具有共同的分子决定因素，这表明需要统一的肝癌分子景观来提高诊断和治疗。肝癌的肿瘤内分子异质性部分归因于肝癌干细胞（CSCs）的存在。由不同细胞表面标记定义的不同CSC群体可能包含不同的致癌驱动因素，这对确定分子靶向治疗提出了挑战。我们在单细胞水平上结合肝癌细胞的转录组学和功能分析来评估CSC的异质性程度。我们发现肝脏CSCs在单细胞水平上具有表型、功能和转录组异质性。CSC亚群包含不同的分子特征。有趣的是，不同CSC亚群中的不同基因与肝细胞癌预后独立相关，这表明不同的肝CSC转录组影响肿瘤内异质性和肿瘤进展。

We are using global genomic approaches to profile clinical specimens that are associated with different stages of liver diseases. We have identified a unique diagnostic signature for patients with early onset of liver cancer and have also developed a unique molecular signature based on the mRNA gene expression of metastatic primary hepatocellular carcinoma (HCC) specimens to predict prognosis and metastasis of HCC patients. We found that this molecular signature could identify those patients who were most at risk for recurrence even in patients with early stage disease. More recently, we integrated genomic and transcriptomic profiles to search for metastasis driver genes. We found that primary tumor lesions and their match distant metastasis were similar, however significant differences could be identified between primary tumors with or without accompanying metastasis. Moreover, metastasis genes were principally tumor type and organ-site-specific, further solidifying that metastatic propensity is inherent to the primary tumor. We have also developed a unique molecular prognostic signature based on mRNA gene expression of the liver microenvironment of HCC patients. We found that a predominant humoral cytokine profile occurs in the metastatic liver microenvironment and that a shift toward anti-inflammatory/immune-suppressive responses may promote HCC metastases. Interestingly, the tumor signature is principally different from that of liver microenvironment. We have recently explored whether activated hepatic stellate cells (A-HSCs) contribute directly to HCC recurrence. We identified and validated an A-HSC-specific gene expression signature among nontumor tissues of HCC patients that was associated with HCC recurrence and survival. Further studies showed that A-HSCs preferentially alter monocyte populations to induce protumorigenic and progressive features by shifting their gene expression from an inflammatory to an immune suppressive signature. These findings indicate that disruption of the interactions and signaling events between inflammatory cells and components of the microenvironment may be useful therapeutic strategies for preventing HCC relapse. We have also found that small non-coding RNAs, termed microRNAs are associated with metastasis and could significantly predict patient survival and relapse even in early stage disease, while certain microRNAs (e.g. microRNA-26) are gender-related. Patients with low microRNA-26 expression had poor survival and were better responders to interferon therapy than those with normal expression. We developed a qRT-PCR-based matrix template and scoring algorithm (MIR26-DX) to assign patients into either low or high microRNA-26 groups. Patients with low microRNA-26 levels selected by the template were those that responded favorably to interferon-alpha therapy. We have now initiated a multi-center randomized control clinical trial in China based on these findings (NCT01681446). We also found that miR-29 family members were significantly down-regulated in AFP+ tumors with significant inverse correlation of DNMT3A gene expression and an increase in DNA methylation. AFP also inhibited transcription of the miR-29a/b-1 locus via c-MYC and promotes tumor growth of AFP- HCC cells in nude mice. Thus, tumor biology differs considerably between AFP+ HCC and AFP- HCC and that AFP is a functional antagonist of miR-29, which may contribute to global epigenetic alterations and poor prognosis in HCC. We have also used integrative approaches to identify HCC driver genes. We have combined high-resolution, array-based comparative genomic hybridization and transcriptome analysis of HCC samples to identify and validate a 10-gene signature associated with chromosome 8p loss and poor outcome. Functional studies demonstrated that three gene products have tumor suppressive properties and two of these genes, SORBS3 and SH2D4A, are linked and inhibit STAT3-mediated IL-6 signaling in HCC cells. We have also integrated metabolite and mRNA profiles to define key signaling events of HCC cancer stem cells. Our analysis revealed that stearoyl CoA desaturase (SCD), a key enzyme involved in fatty acid biosynthesis, and its related metabolites were highly elevated in stem cell-like HCC and are associated with HCC survival and aggressiveness. In a comparison of global metabolic profiles between liver, breast and pancreatic cancer tissues, we found that metabolites are principally unique to each tissue and cancer type. Thus, metabolic profiling could be applied as cancer classification tools to differentiate tumors based on tissue of origin. We have also recently analyzed metabolomic and transcriptomic profiles jointly collected from breast cancer and HCC patients to explore the associations between and build predictors of the expression of metabolic enzymes and the levels of the metabolites participating in the reactions they catalyze. A wide range of metabolites can be successfully predicted from the transcriptome. We also developed an integrative subgraph mining approach, iSubgraph, to discover patterns of miRNA-gene networks to stratify HCC patients. This algorithm could detect cooperative regulation of miRNAs and genes with highly stable class predictions. Thus, our methods can integrate various omics data derived from different platforms and with different dynamic scales to better define molecular tumor subtypes. Through recent analyses of HCC, we revealed that a large number of RNA binding proteins (RBPs) are dysregulated and that RBP dysregulation is associated with poor prognosis. We further identified that oncogenic activation of a top candidate RBP, negative elongation factor E (NELFE), via somatic copy-number alterations enhanced MYC signaling and promoted HCC progression. Interestingly, NELFE induces a unique tumor transcriptome by selectively regulating MYC-associated genes. Thus, our results revealed NELFE as an oncogenic protein that may contribute to transcriptome imbalance in HCC through the regulation of MYC signaling. The incidence of cholangiocarcinoma (CCA), a bile-duct-related cancer and second most frequent primary liver cancer (PLC), is prevalent, especially in the north-east area of Thailand. We initiated the Thailand Initiative for Genomics and Expression Research in Liver Cancer (TIGER-LC) to provide a comprehensive global analysis of genomic alterations related to the primary liver cancer types in Thai liver cancer patients. Recently, we have identified common molecular subtypes with key drivers linked to similar prognosis among 199 Thai CCA and HCC patients through systems integration of genomics, transcriptomics, and metabolomics. Our results indicate that ICC and HCC, while clinically treated as separate entities, share common molecular determinants, suggesting that a unified molecular landscape of liver cancer is required to improve diagnosis and therapy. Intratumor molecular heterogeneity of hepatocellular carcinoma is partly attributed to the presence of hepatic cancer stem cells (CSCs). Different CSC populations defined by various cell surface markers may contain different oncogenic drivers, posing a challenge in defining molecularly targeted therapeutics. We combined transcriptomic and functional analyses of hepatocellular carcinoma cells at the single-cell level to assess the degree of CSC heterogeneity. We found that hepatic CSCs at the single-cell level are phenotypically, functionally, and transcriptomically heterogeneous. CSC subpopulations contain distinct molecular signatures. Interestingly, distinct genes within different CSC subpopulations are independently associated with hepatocellular carcinoma prognosis, suggesting that a diverse hepatic CSC transcriptome affects intratumor heterogeneity and tumor progression.