Integrative genomic analysis in hepatocellular carcinoma

描述（由申请人提供）：肝细胞癌（HCC）是全球癌症相关死亡的第三大原因，在美国和西欧的癌症发病率上升最快。该病是一个重大的公共卫生问题，目前尚无分子诊断方法，有效的治疗方案也有限。该项目的假设是，了解HCC的基因表达谱和体细胞遗传改变，将有助于识别参与该疾病发病机制的抑癌基因或癌基因，并为早期发现和新的治疗靶点提供标记。预测临床结果的基因特征的鉴定将使HCC的分子分类成为可能。为此，我们将测试230个样本[包括20个发育不良结节和100对HCV相关的HCC/非肿瘤性肝硬化肝脏]。我们已经从3个转诊HCC单位的患者中收集了214个样本：纽约西奈山；巴塞罗那医院诊所（合作者#2）；米兰国家癌症研究所（合作者#3）。目的1：表征HCV感染患者中发育不良病变和肝细胞癌的基因表达谱。1一个。通过全基因组基因表达分析，确定参与肝癌发生的基因和途径。通过使用38,500个基因的全基因组微阵列技术分析（Affymetrix, Genechip Human Genome-U133 Plus 2.0），我们已经在73个初步样本中确定了分类发育不良结节，早期肿瘤和晚期癌症的分子特征。我们将把分析范围扩大到230个样本。1 b。确定预测HCC复发和生存的分子特征。我们将分析85例接受肝细胞癌切除术的患者的基因特征，这些患者有完整的临床数据记录。多变量方法将确保临床和分子数据的适当整合。目的2：利用高密度单核苷酸多态性阵列分析50万个基因组位点，确定HCC基因组结构改变的程度。整合新出现的基因图谱与配对表达数据，以确定候选肿瘤抑制因子和癌基因。我们将与哈佛大学丹娜-法伯研究所的William Sellers博士/Matthew Meyerson小组（合作者1号）合作，将高密度500K SNP阵列应用于HCC的结构体细胞遗传改变分析。通过对分子谱和遗传干扰的综合基因组分析，我们将发现新的肿瘤抑制基因或致癌基因，这可能成为化学预防和治疗策略的新靶点。目的3：确定早期HCC诊断的分子生物标志物。#3a：生物标志物的鉴定。我们已经通过Real-Time RT-PCR鉴定出3个基因（Glypican-3, Survivin, LYVE-1）的基因标记能够区分发育不良病变和早期癌症，准确率为94%。通过微阵列技术，我们获得了一组93个潜在候选基因的初步数据，用于鉴定新的生物标志物。#3b：验证接受筛查的肝硬化患者早期HCC诊断的分子特征。所确定的基因标记将在临床实践中进行验证，该测试集来自一组hcv -肝硬化患者（合作者#2，巴塞罗那大学）的80个0.5-2cm结节样本。

DESCRIPTION (provided by applicant): Hepatocellular carcinoma (HCC) is the third cause of cancer-related death worldwide with the most rapidly rising cancer incidence in the US and Western Europe. The disease is a major public health problem, for which there are no molecular diagnostics and limited effective treatment options. The hypothesis of the project is that knowledge of the gene expression profiles and the somatic genetic alterations of HCC will enable the identification of tumor suppressor genes or oncogenes involved in the pathogenesis of the disease, and will provide markers of early detection and new treatment targets. The identification of gene signatures predictive of clinical outcomes will enable a molecular classification of HCC. For that purpose we will test 230 samples [including 20 dysplastic nodules and 100 paired HCV- related HCC/non-tumoral cirrhotic liver]. We already have collected 214 samples from patients in 3 referral HCC Units: Mount Sinai, New York; Hospital Clinic Barcelona (Collaborator #2); National Cancer Institute, Milan (Collaborator #3). Specific aims: Aim #1: Characterize the gene expression profiles of dysplastic lesions and hepatocellular carcinoma in HCV infected patients. 1a. Determine the genes and pathways involved in hepatocarcinogenesis, by genome- wide gene expression analysis. By using genome-wide microarray technology profiling of 38,500 genes, (Affymetrix, Genechip Human Genome-U133 Plus 2.0), we have identified molecular signatures that classify dysplastic nodules, early tumors and advanced cancers in a preliminary set of 73 samples. We will expand the analysis to 230 samples. 1b. Identify a molecular signature predictive of HCC recurrence and survival. A gene signature able to discriminate good and poor outcomes will be analyzed in 85 patients undergoing resection for HCC in which complete clinical data has been recorded. Multivariate approaches will ensure a proper integration of the clinical and molecular data. Aim #2: To define the extent of structural alterations in the HCC genome using high-density single nucleotide polymorphisms arrays interrogating 500,000 genomic loci. To integrate emerging genetic maps with paired expression data to identify candidate tumor suppressors and oncogenes. We will apply high-density 500K SNP arrays to the analysis of structural somatic genetic alterations in HCC, in collaboration with the Dr. William Sellers/Matthew Meyerson's group in Dana-Farber Institute, Harvard (Collaborator #1). By using integrative genomic analysis of the molecular profiling and genetic disturbances we'll identify novel tumor suppressors or oncogenes, which may constitute new targets for chemopreventive and therapeutic strategies. Aim #3: Identify molecular biomarkers for the diagnosis of early HCC. #3a: Identification of biomarkers. We have identified by Real-Time RT-PCR a gene signature of 3 genes (Glypican-3, Survivin, LYVE-1) able to discriminate between dysplastic lesions from early cancer with an accuracy of 94%. By microarray technology, we have preliminary data with a set of 93 potential candidate genes for the identification of new biomarkers. #3b: To validate the molecular signature for the diagnosis of early HCC in cirrhotic patients undergoing screening. The gene- signature identified will be validated in the clinical practice in a testing set of 80 samples from nodules between 0.5-2cm obtained from a prospective cohort of HCV-cirrhotic patients (Collaborator #2, University of Barcelona).