Genetic Changes in Early Stage Ovarian Cancer

早期卵巢癌的基因变化

• 批准号: 6991019
• 负责人: SAMUEL C MOK
• 金额: $ 14万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6991019
• 关键词: bioinformatics; comparative genomic hybridization; enzyme linked immunosorbent assay; female; fluorescent in situ hybridization; gene expression profiling; high throughput technology; human genetic material tag; human tissue; immunocytochemistry; loss of heterozygosity; microarray technology; neoplasm /cancer genetics; ovary neoplasms; patient oriented research; prognosis; single nucleotide polymorphism

Understanding the cascade of genetic changes that leads to the formation of cancer promises a revolution in the prevention, early detection, and treatment of cancer by approaches that are innovative and specific. In addition, molecular profiling of tumors is likely to have far greater prognostic ability than traditional staging and grading. Advances in understanding early molecular genetic changes for ovarian cancer have been slow likely due to: a relative paucity of early-staged cancers for study of this disease, infrequent availability of fresh tissue for early-stage lesions, and histologic diversity of the disease which may confound efforts to identify common pathways. For this study, we will utilize innovative high throughput technologies for DNA and RNA analyses of early stage ovarian cancers obtained from two sources: 272 well-annotated formalin fixed specimens from the Gynecologic Oncology Group protocol 157 and 100 specimens collected from Partners Hospital with snap frozen tissue available. These specimens will be evaluated using the NCI eDNA array platform for comparative genomic hybridization analysis to detect DNA copy number abnormalities and by single nucleotide polymorphisms (SNP)-array-based loss of heterozygosity analysis on the 1OK SNP array platform to detect allelic loss profiles. Candidate genes will be first selected by performing expression profiling with the eDNA array platform and then further validated by fluorescent in situ hybridization (FISH), quantitative PCR, immunohistochemistry and enzyme linked immunosorbant assay (ELISA). All analyses will be histology-specific and use bioinformatics techniques suitable for assay based data to identify genetic changes correlated with clinical outcomes. Our hypothesis is that the identification of histologyspecific molecular genetic changes will suggest potential targets for prevention, early detection, or treatment strategies, and that the molecular genetic profiles will provide important predictors.

了解导致癌症形成的遗传变化级联，有望通过创新和特异性的方法在预防，早期检测和治疗癌症方面带来革命。此外，肿瘤的分子谱可能比传统的分期和分级具有更大的预后能力。了解卵巢癌早期分子遗传变化的进展缓慢，可能是由于：用于研究这种疾病的早期癌症相对较少，早期病变的新鲜组织很少，以及可能混淆识别共同途径的努力的疾病的组织学多样性。在这项研究中，我们将利用创新的高通量DNA技术， 早期卵巢癌的RNA分析来自两个来源：来自妇科肿瘤组方案157的272个注释良好的福尔马林固定标本和从Partners医院收集的100个标本，其中快速冷冻组织可用。将使用NCI eDNA阵列平台进行比较基因组杂交分析，以检测DNA拷贝数异常，并在1OK SNP阵列平台上通过基于单核苷酸多态性（SNP）阵列的杂合性缺失分析，以检测等位基因缺失谱，对这些标本进行评价。候选基因将首先通过使用eDNA阵列平台进行表达谱分析来选择，然后通过荧光原位杂交（FISH）、定量PCR、免疫组织化学和酶联免疫吸附测定（ELISA）来进一步验证。所有 分析将是组织学特异性的，并使用适合于基于分析的数据的生物信息学技术来识别与临床结果相关的遗传变化。我们的假设是，组织学特异性分子遗传学变化的鉴定将为预防、早期检测或治疗策略提供潜在的靶点，并且分子遗传学特征将提供重要的预测因子。