Molecular profiling of hepatocellular carcinoma

肝细胞癌的分子谱分析

• 批准号: 6763500
• 负责人: XIN WEI WANG
• 金额: --
• 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/6763500
• 关键词: clinical research; complementary DNA; early diagnosis; gene expression; genetic library; genetic mapping; genetic markers; genetic transcription; hepatitis B virus group; hepatitis C virus; hepatocellular carcinoma; human tissue; liver cells; liver neoplasms; metastasis; microarray technology; molecular genetics; neoplasm /cancer genetics; northern blottings; oncoproteins; protein degradation; protein structure; ribosomal proteins; serial analysis of gene expression; transfection /expression vector

Human liver cancer, with increasing occurrence in the United States, is the 5th most prevalent malignant disease in the world. It is the fourth leading cause of cancer mortality, which accounts for an estimated 1 million deaths annually. Hepatocellular carcinoma (HCC) is a major type of primary liver cancer. HCC is considered to be a terminally ill disease and currently, there is little progress toward the discovery of efficient therapies leading to regression. This is due largely to the lack of a method for early diagnosis and the lack of information on the phenotypic changes associated with the development of HCC. Our goals are to identify common gene clusters that are responsible for the genesis of HCC and to discover new genes critical for viral hepatitis-mediated HCC as well as genes necessary for metastasis. These studies will contribute to the establishment of novel markers with potential diagnostic and prognostic value, and analysis of these genes would provide further understanding of the genesis of liver cancer and provide further insights into designing strategies for HCC-directed molecular therapy. We have taken two approaches, namely, Serial Analysis of Gene Expression (SAGE) and cDNA microarray, to explore potential cellular genes that are expressed abnormally in primary human hepatocytes infected with the two viral hepatitis oncoproteins, HBx or HC-core, and in liver samples from chronic active hepatitis patients or HCC patients that differ in the status of HBV or HCV. In addition, we are comparing gene expression profiles between primary HCC and metastatic HCC. Infection of normal hepatocytes with HBx and HC-core is achieved by a replication-defective adenoviral vector. We have constructed two SAGE libraries derived from freshly isolated normal primary human hepatocytes with or without the expression of HBx(135). A total of 19,501 sequence tags (representing 1443 unique transcripts) were analyzed, which provide a distribution of a transcriptome characteristic of normal hepatocytes and a profile associated with HBx expression. Examples of the targeted genes were confirmed by the Megarray analysis with a significant correlation between quantitative SAGE and Megarray (r = 0.8, p<0.005). In HBx-expressing hepatocytes, a total of 57 transcripts (3.9%) were induced and 46 transcripts (3.3%) were repressed by more than 5-fold. There are nine novel upregulated genes (designated as XIG1-9) and 22 novel downregulated novel genes (designated as XSG1-22). Interestingly, among the known genes, most of the HBx-upregulated transcripts can be clustered into three major classes: genes that encode ribosomal proteins, transcription factors with zinc finger motifs, and proteins associated with protein degradation pathway. These results suggest that HBx may function as a major regulator in common cellular pathways that, in turn, regulate protein synthesis, gene transcription, and protein degradation. In addition, we have compared gene expression profiles in primary hepatocytes expressing HBx as well as liver samples from chronic liver diseases including HBV or HCV infection and in HCC. Clustering algorithms were used to identify the deregulation of distinctive gene expression profiles in these samples. Clustering algorithm analysis of the expression profiles indicates that there is a consistent alteration of a subset of oncogenes (such as c-myc and c-myb) and tumor suppressor genes (such as APC, p53, WAF1, and WT1). Many targeted genes were also found by the SAGE technique. Our findings are consistent with the hypothesis that the deregulation of cellular genes by oncogenic HBx may be an early event that favors hepatocyte proliferation during liver carcinogenesis. More recently, we analyzed the expression of 9,180 genes in a total of 67 HCC tumors from 40 patients without or with accompanying intra-hepatic metastases. Using a supervised machine learning algorithm to classify patients based on their gene expression profiles, we have generated for the first time a molecular signature that correctly classifies patients with or without metastases, and have identified genes that are mostly relevant to the prediction outcome including patient survival. Unexpectedly, we found that the gene expression signature of primary HCCs with accompanying metastasis was very similar to that of their corresponding metastases, implying that the genes favoring metastasis progression were likely initiated in the primary tumors. Moreover, osteopontin was overexpressed in primary HCC with intra-hepatic metastasis and a neutralizing antibody against osteopontin can block the invasion of highly metastatic HCC cells in an in vitro assay of invasion. Our studies offer a strategy to tailor HCC patients based on the gene expression profile to adjuvant therapy, and identify osteopontin both as a diagnostic marker and potential therapeutic target for metastatic HCC. We also are interested in the comparison of the molecular profiling of liver samples from many chronic liver diseases, including HBV, HCV, hemochromatosis, Wilson, alcohol, autoimmune chronic hepatitis, or primary biliary cirrhosis, with liver cancer. Our results demonstrate a unique gene expression pattern associated with these individual diseases. These results may offer insight into potential molecular mechanisms underlying precancerous conditions that are associated with HCC.

在美国，人类肝癌的发生越来越大，是世界上第五大最普遍的恶性疾病。这是癌症死亡率的第四个主要原因，每年估计死亡100万。肝细胞癌（HCC）是原发性肝癌的主要类型。 HCC被认为是一种疾病，目前，在发现有效疗法导致回归方面几乎没有进展。这主要是由于缺乏早期诊断方法以及缺乏与HCC发展相关的表型变化的信息。我们的目标是确定负责HCC起源的常见基因簇，并发现对病毒肝炎介导的HCC至关重要的新基因以及转移所需的基因。这些研究将有助于建立具有潜在诊断和预后价值的新型标记物，对这些基因的分析将提供对肝癌起源的进一步了解，并为HCC指导分子治疗的设计策略提供进一步的见解。 我们采用了两种方法，即对基因表达（SAGE）和cDNA微阵列的序列分析，探索潜在的细胞基因，这些基因在原发性人肝细胞中异常表达，感染了两个病毒肝炎肝炎癌蛋白，HBX或HC核，HBX或HC核，以及在慢性活性异常患者或HCC中的状态与HCC的状态相差。此外，我们正在比较一级HCC和转移性HCC之间的基因表达谱。通过复制缺陷型腺病毒载体来实现HBX和HC核的正常肝细胞的感染。我们已经构建了两个鼠尾草文库，这些文库来自新鲜分离的正常原代人肝细胞，有或没有HBX的表达（135）。总共分析了19,501个序列标签（代表1443个独特的转录本），这些序列标签提供了正常肝细胞的转录组特征的分布和与HBX表达相关的轮廓。通过大型分析证实了靶向基因的示例，并在定量鼠尾草和大型象征之间具有显着相关性（r = 0.8，p <0.005）。在表达HBX的肝细胞中，诱导了总共57次转录本（3.9％），并抑制了46个转录本（3.3％）。有九种新颖的上调基因（指定为Xig1-9）和22种新型新颖基因（称为XSG1-22）。有趣的是，在已知的基因中，大多数HBX上调的转录本可以聚集在三个主要类中：编码核糖体蛋白质的基因，具有锌指基序的转录因子以及与蛋白质降解途径相关的蛋白质。这些结果表明，HBX可能在常见的细胞途径中起主要调节剂的作用，进而调节蛋白质合成，基因转录和蛋白质降解。此外，我们还比较了表达HBX的原发性肝细胞中的基因表达谱以及来自慢性肝病（包括HBV或HCV感染）和HCC中的肝脏样品。聚类算法用于确定这些样品中独特基因表达谱的放松管制。表达曲线的聚类算法分析表明，癌基因（例如C-MYC和C-MYB）和肿瘤抑制基因（例如APC，P53，WAF1和WT1）的一部分持续改变。 SAGE技术也发现了许多靶向基因。我们的发现与以下假设一致：通过致癌性HBX对细胞基因的失调可能是一个早期事件，它有利于肝癌期间有利于肝细胞增殖。 最近，我们分析了40例没有或伴有肝内转移酶的40例患者的67例HCC肿瘤中9,180个基因的表达。使用监督的机器学习算法根据患者的基因表达谱进行分类，我们首次生成了一个分子特征，该分子特征正确地对患有或没有转移的患者进行了正确分类，并且已经鉴定出与包括患者生存在内的预测结果相关的基因。出乎意料的是，我们发现伴有转移的原代HCC的基因表达特征与它们相应的转移酶的基因表达特征非常相似，这意味着有利于转移进展的基因可能是在原发性肿瘤中启动的。此外，骨桥蛋白在肝内转移的一级HCC中过表达，针对骨桥蛋白的中和抗体可以阻止在体外浸润测定法中高度转移性HCC细胞的侵袭。我们的研究提供了一种策略，以根据辅助治疗的基因表达谱量量身定制HCC患者，并将骨桥蛋白视为转移性HCC的诊断标记和潜在的治疗靶标。 我们还对来自许多慢性肝病的肝样品的分子分析感兴趣，包括HBV，HCV，血色素沉着症，威尔逊，酒精，自身免疫性慢性肝炎或原发性胆汁肝硬化和肝癌。我们的结果证明了与这些个体疾病相关的独特基因表达模式。这些结果可能会深入了解与HCC相关的癌前条件下的潜在分子机制。