Molecular signatures for liver cancer diagnosis and treatment stratification

肝癌诊断和治疗分层的分子特征

• 批准号: 10702334
• 负责人: Xin Wei Wang
• 金额: $ 200.12万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10702334
• 关键词: AFP gene; Algorithms; Anti-Inflammatory Agents; Area; Biology; Cancer Etiology; Cell surface; Cells; Cellular Structures; Cessation of life; China; Cholangiocarcinoma; Clinical; DNA Methylation; DNA Sequence Alteration; Data; Diagnosis; Disease; Distant Metastasis; Early Diagnosis; Enzymes; Epigenetic Process; Etiology; Event; Family member; Gender; Gene Cluster; Gene Expression; Gene Expression Profile; Genes; Genetic Transcription; Genomic approach; Genomics; Goals; Hepatic; Hepatic Stellate Cell; Heterogeneity; Human; Immune; Incidence; Inflammatory; Interferon-alpha; Interleukin-6; Lesion; Link; Liver; Liver diseases; Malignant - descriptor; Malignant Epithelial Cell; Malignant Neoplasms; Malignant neoplasm of liver; Malignant neoplasm of pancreas; Mediating; Messenger RNA; Metabolic; Metastatic Neoplasm to the Liver; Methods; MicroRNAs; Mining; Molecular; Molecular Profiling; Neoplasm Metastasis; Nude Mice; Oncogenic; Operative Surgical Procedures; Organ; Outcome; Patients; Pattern; Phenotype; Population; Population Study; Primary Malignant Neoplasm of Liver; Primary Neoplasm; Primary carcinoma of the liver cells; Prognosis; Property; Proteins; Quantitative Reverse Transcriptase PCR; RNA-Binding Proteins; Randomized Controlled Clinical Trials; Reaction; Recurrence; Regulation; Relapse; Research; Resolution; Risk; Role; STAT3 gene; Sampling; Signal Transduction; Site; Specimen; Stearoyl-CoA Desaturase; Systems Integration; Terminal Disease; Thailand; Therapeutic; Tissues; Tumor Biology; Tumor Subtype; United States; Untranslated RNA; Viral hepatitis; antagonist; base; bile duct; c-myc Genes; cancer classification; cancer diagnosis; cancer stem cell; cancer therapy; cancer type; chromosome 8p loss; comparative genomic hybridization; cytokine; detection method; diagnostic signature; early onset; fatty acid biosynthesis; gender disparity; gene network; gene product; genetic signature; genome-wide; genomic data; improved; interferon therapy; liver cancer patient; malignant breast neoplasm; men; metabolic profile; metabolomics; molecular marker; molecular subtypes; molecular targeted therapies; monocyte; mortality; negative elongation factor; personalized medicine; predictive modeling; prevent; prognostic signature; response; stem cell population; stem-like cell; survival disparity; tool; transcriptome; transcriptomics; treatment stratification; tumor; tumor growth

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. *TRUNCATED*

我们正在使用全球基因组方法来分析与肝病不同阶段相关的临床标本。我们为早期肝癌患者确定了独特的诊断特征，并根据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，这种分子特征可以识别那些最有复发风险的患者，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灶与其相匹配的远处转移相似，但是在有或没有伴随转移的原发肿瘤之间可以发现显着差异。此外，转移基因主要是肿瘤类型和器官部位特异性的，进一步证实了转移倾向是原发肿瘤所固有的。我们还根据 HCC 患者肝脏微环境的 mRNA 基因表达开发了独特的分子预后特征。我们发现，主要的体液细胞因子谱发生在转移性肝脏微环境中，并且抗炎/免疫抑制反应的转变可能会促进 HCC 转移。有趣的是，肿瘤特征主要不同于肝脏微环境。我们最近探讨了活化的肝星状细胞 (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-HSC 优先改变单核细胞群，通过将其基因表达从炎症特征转变为免疫抑制特征来诱导促肿瘤和进展特征。这些发现表明，破坏炎症细胞和微环境成分之间的相互作用和信号传导事件可能是预防 HCC 复发的有用治疗策略。我们还发现，称为 microRNA 的小非编码 RNA 与转移相关，即使在疾病早期也可以显着预测患者的生存和复发，而某些 microRNA（例如 microRNA-26）与性别相关。与表达正常的患者相比，microRNA-26 表达低的患者生存率较差，并且对干扰素治疗的反应更好。我们开发了一种基于 qRT-PCR 的矩阵模板和评分算法 (MIR26-DX)，将患者分为低或高 microRNA-26 组。模板选择的 microRNA-26 水平低的患者是那些对干扰素 α 治疗有良好反应的患者。我们现已根据这些发现在中国启动了一项多中心随机对照临床试验（NCT01681446）。我们还发现，miR-29 家族成员在 AFP+ 肿瘤中显着下调，与 DNMT3A 基因表达和 DNA 甲基化增加呈显着负相关。 AFP 还通过 c-MYC 抑制 miR-29a/b-1 位点的转录，并促进裸鼠 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 的功能拮抗剂，这可能导致 HCC 的整体表观遗传改变和不良预后。我们还使用综合方法来识别 HCC 驱动基因。 我们将 HCC 样本的高分辨率、基于芯片的比较基因组杂交和转录组分析结合起来，以识别和验证与染色体 8p 丢失和不良预后相关的 10 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 相互关联并抑制 HCC 细胞中 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传导事件。我们的分析表明，硬脂酰辅酶A去饱和酶（SCD）是一种参与脂肪酸生物合成的关键酶，其相关代谢物在干细胞样肝癌中高度升高，并且与肝癌的存活和侵袭性相关。在比较肝癌、乳腺癌和胰腺癌组织之间的整体代谢特征时，我们发现代谢物对于每种组织和癌症类型来说基本上都是独特的。因此，代谢分析可以用作癌症分类工具，以根据起源组织区分肿瘤。我们最近还分析了从乳腺癌和肝癌患者联合收集的代谢组学和转录组学概况，以探索代谢酶的表达与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。从转录组中可以成功预测多种代谢物。我们还开发了一种综合子图挖掘方法 iSubgraph，以发现 miRNA 基因网络模式，从而对 HCC 患者进行分层。该算法可以检测 miRNA 和基因的协同调控，并具有高度稳定的类别预测。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，以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，并且 RBP 失调与不良预后相关。我们进一步发现，首要候选 RBP 负延伸因子 E (NELFE) 的致癌激活通过体细胞拷贝数改变增强了 MYC 信号传导并促进了 HCC 进展。有趣的是，NELFE 通过选择性调节 MYC 相关基因来诱导独特的肿瘤转录组。因此，我们的结果表明 NELFE 作为一种致癌蛋白，可能通过调节 MYC 信号传导导致 HCC 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），其发病率很高，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)，旨在对泰国肝癌患者中与原发性肝癌类型相关的基因组改变进行全面的全球分析。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 患者中确定了与相似预后相关的常见分子亚型。我们的结果表明，ICC 和 HCC 虽然在临床上被视为独立的实体，但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改善诊断和治疗。肝细胞癌的瘤内分子异质性部分归因于肝癌干细胞（CSC）的存在。由不同细胞表面标志物定义的不同CSC群体可能包含不同的致癌驱动因素，这对定义分子靶向治疗提出了挑战。我们在单细胞水平上结合肝细胞癌细胞的转录组学和功能分析来评估 CSC 异质性程度。我们发现单细胞水平的肝CSC在表型、功能和转录组上是异质的。 CSC 亚群包含独特的分子特征。 *截断*