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.

人类肝癌在美国的发病率越来越高，是世界上第五大流行的恶性疾病。它是癌症死亡率的第四大原因，估计每年有100万人死于癌症。肝细胞癌（HCC）是原发性肝癌的主要类型。HCC被认为是一种绝症，目前，在发现导致消退的有效疗法方面几乎没有进展。这在很大程度上是由于缺乏早期诊断的方法和缺乏与HCC发展相关的表型变化的信息。我们的目标是确定共同的基因簇，负责肝细胞癌的发生，并发现新的病毒性肝炎介导的肝细胞癌的关键基因，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标志物，对这些基因的分析将进一步了解肝癌的发生，并为设计HCC定向分子治疗策略提供进一步的见解。 我们已经采取了两种方法，即，基因表达系列分析（SAGE）和cDNA微阵列，以探索潜在的细胞基因，表达异常的原代人肝细胞感染的两种病毒性肝炎癌蛋白，HBx或HC核心，并在肝脏样本中的慢性活动性肝炎患者或肝癌患者的HBV或HCV的状态不同。此外，我们正在比较原发性肝癌和转移性肝癌的基因表达谱。通过复制缺陷型腺病毒载体实现用HBx和HC核心感染正常肝细胞。我们已经构建了两个SAGE文库，它们来源于新鲜分离的正常原代人肝细胞，表达或不表达HBx（135）。共分析了19，501个序列标签（代表1443个独特的转录物），其提供了正常肝细胞的转录组特征分布和与HBx表达相关的谱。通过Megarray分析证实靶向基因的实例，其中定量SAGE和Megarray之间具有显著相关性（r = 0.8，p<0.005）。在表达HBx的肝细胞中，共57个转录本（3.9%）被诱导，46个转录本（3.3%）被抑制超过5倍。有9个新的上调基因（命名为XIG 1 -9）和22个新的下调基因（命名为XSG 1 -22）。有趣的是，在已知的基因中，大多数HBx上调的转录物可以被聚类为三个主要类别：编码核糖体蛋白的基因，具有锌指基序的转录因子，和与蛋白质降解途径相关的蛋白质。这些结果表明，HBx可能作为一个主要的调节器在共同的细胞途径，反过来，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的原代肝细胞以及慢性肝病（包括HBV或HCV感染）和HCC的肝脏样本中的基因表达谱。聚类算法被用来确定这些样品中独特的基因表达谱的失调。表达谱的聚类算法分析表明，癌基因（如c-myc和c-myb）和肿瘤抑制基因（如APC，p53，WAF 1和WT 1）的子集存在一致的改变。SAGE技术也发现了许多靶基因。我们的研究结果是一致的假设，细胞基因的失调，致癌HBx可能是一个早期事件，有利于肝细胞增殖过程中的肝癌。 最近，我们分析了来自40名无或伴有肝内转移的患者的总共67个肝癌肿瘤中9，180个基因的表达。使用有监督的机器学习算法根据基因表达谱对患者进行分类，我们首次生成了一个分子特征，可以正确分类有或无转移的患者，并确定了与预测结果（包括患者生存率）最相关的基因。出乎意料的是，我们发现伴有转移的原发性HCC的基因表达特征与其相应的转移非常相似，这意味着有利于转移进展的基因可能在原发性肿瘤中启动。此外，骨桥蛋白在原发性肝细胞癌肝内转移中过表达，在体外侵袭试验中，骨桥蛋白的中和抗体可以阻断高转移性肝细胞癌细胞的侵袭。我们的研究提供了一种策略，根据基因表达谱来定制HCC患者的辅助治疗，并确定骨桥蛋白作为转移性HCC的诊断标志物和潜在的治疗靶点。 我们还对许多慢性肝病肝脏样本的分子谱比较感兴趣，包括HBV，HCV，血色病，Wilson，酒精，自身免疫性慢性肝炎或原发性胆汁性肝硬化，肝癌。我们的研究结果证明了与这些个体疾病相关的独特基因表达模式。这些结果可能为深入了解与HCC相关的癌前病变的潜在分子机制提供帮助。