Integrative genomic analysis in hepatocellular carcinoma

肝细胞癌的综合基因组分析

• 批准号: 7664496
• 负责人: JOSEP M LLOVET
• 金额: $ 25.1万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-10 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7664496
• 关键词: Advanced Malignant Neoplasm; Biological Markers; Cancer Etiology; Candidate Disease Gene; Cessation of life; Characteristics; Chemopreventive Agent; Chromosome Mapping; Classification; Clinical; Clinical Data; Clinics and Hospitals; Collaborations; DNA Microarray Chip; Data; Detection; Diagnosis; Diagnostic; Diffuse; Disease; Disease Progression; Disseminated Malignant Neoplasm; Early Detection Research Network; Early Diagnosis; Ensure; Etiology; European; Excision; Gene Expression; Gene Expression Profile; Genes; Genetic; Genome; Genomics; Glioma; Health; Hepatitis C virus; Hepatocarcinogenesis; Histology; Human Genome; Incidence; Informatics; Institutes; Knowledge; Lesion; Liver; Loss of Heterozygosity; Malignant Neoplasms; Malignant neoplasm of prostate; Maps; Methods; Microarray Analysis; Molecular; Molecular Abnormality; Molecular Profiling; Mutation; National Cancer Institute; Neoplasms; New York; Nodule; Normal tissue morphology; Oncogenes; Outcome; Pathogenesis; Pathway interactions; Patients; Pattern; Population; Prevention; Primary carcinoma of the liver cells; Public Health; Recurrence; Research; Research Personnel; Reverse Transcriptase Polymerase Chain Reaction; Sampling; Scheme; Screening procedure; Single Nucleotide Polymorphism; Staging; Surveillance Program; Testing; Therapeutic; Time; Tissue Banking; Tissue Banks; Tissues; Training; Tumor Suppressor Genes; Tumor Suppressor Proteins; Universities; Validation; Western Europe; base; cancer recurrence; clinical practice; cohort; density; effective therapy; genome-wide; glypican 3; melanoma; novel; novel diagnostics; novel marker; outcome forecast; prognostic; programs; prospective; response; survivin; tumor

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).

描述（由申请人提供）：肝细胞癌（HCC）是全球与癌症相关死亡的第三个原因，在美国和西欧，癌症发病率最快。该疾病是一个主要的公共卫生问题，没有分子诊断和有限的有效治疗选择。该项目的假设是，对基因表达谱的知识和HCC的体细胞遗传改变将使抑制肿瘤抑制基因或涉及该疾病发病机理的癌基因，并将提供早期检测和新治疗靶标的标志。鉴定基因特征可以预测临床结果的基因信号，将使HCC的分子分类。为此，我们将测试230个样品[包括20个发育不良结节和100个成对的HCV相关HCC/非肿瘤性肝硬化肝]。我们已经从3个转诊HCC单位中收集了214个患者样本：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）。具体目的：目标＃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。 1a。通过基因组广泛的基因表达分析，确定肝癌发生中涉及的基因和途径。通过使用38,500个基因（Affymetrix，Genechip Human Genome-U133 Plus 2.0）的全基因组微阵列技术分析，我们已经确定了分子特征，这些分子特征将异型疾病结节，早期肿瘤和先进的癌症分类为初步的73个样本。我们将将分析扩展到230个样本。 1B。确定HCC复发和存活的分子特征。在85例接受完整临床数据的HCC的患者中，将分析能够区分良好结果的基因签名。多元方法将确保临床和分子数据的正确整合。 AIM＃2：使用高密度的单核苷酸多态性阵列询问500,000基因组基因局基因局基因局基因局基因局基因座的高密度单核苷酸多态性阵列来定义HCC基因组中的结构改变程度。将新兴的遗传图与配对的表达数据整合在一起，以鉴定候选肿瘤抑制因子和癌基因。我们将与Harvard Dana-Farber Institute的William Sellers/Matthew Meyerson博士合作，将高密度的500K SNP阵列用于HCC结构体细胞遗传变化的分析（合作者＃1）。通过使用分子分析和遗传障碍的整合基因组分析，我们将识别出新型的肿瘤抑制剂或致癌基因，这可能构成化学预防和治疗策略的新靶标。 AIM＃3：确定分子生物标志物以诊断早期HCC。 ＃3A：生物标志物的识别。我们已经通过实时RT-PCR鉴定了3个基因的基因特征（Glypican-3，Survivin，Lyve-1），能够以94％的精度区分早期癌症的发育不良病变。通过微阵列技术，我们拥有具有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：验证正在接受筛查的肝硬化患者中诊断早期HCC的分子特征。在临床实践中，将在从前瞻性HCV-Cirhotic患者（巴塞罗那大学合作者＃2）中获得的0.5-2厘米的80个样品的测试集中验证了鉴定的基因。