Differential Gene Expression in Renal Cancers

肾癌的差异基因表达

• 批准号: 6879414
• 负责人: ALEXANDER S PARKER
• 金额: $ 7.5万
• 依托单位: MAYO CLINIC JACKSONVILLE
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-03 至 2005-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6879414
• 关键词: body composition; cancer registry /resource; clinical research; gene environment interaction; gene expression; genetic susceptibility; high throughput technology; human tissue; laser capture microdissection; microarray technology; neoplasm /cancer epidemiology; neoplasm /cancer genetics; obesity; renal cell carcinoma

DESCRIPTION (provided by applicant): Incidence and mortality rates for renal cell carcinoma (RCC) have increased steadily over the past three decades, and these trends are largely unexplained. While it is widely acknowledged that a history of obesity increases the risk of developing RCC, little is known regarding the actual biologic mechanisms that underlie this association. Indeed, the Kidney Cancer Progress Review Group recently recommended that investigators focus efforts on illuminating the "biological mechanisms underlying the known risk factors for kidney cancers". A logical first approach to identifying specific molecular alterations that link obesity and RCC would be to compare the somatic gene expression profiles in tumors from RCC patients with and without a history of obesity. In this application, we propose to employ the high throughput capabilities of commercially available DNA microarray technology in order to scan the genome for genes that are differentially expressed in RCC tumors that develop in obese and non-obese individuals. To do this, we will use the Mayo Nephrectomy Registry to identify all patients treated surgically for stage I, clear cell RCC at the Mayo Clinic Rochester during a one year period who report no history of smoking. From this list, we will sample 10 individuals with and 10 individuals without a history of obesity. We will then request fresh-frozen tissue samples (both tumor and normal) on each individual and use laser capture microdissection to obtain samples for RNA extraction. The Mayo Clinic DNA Microarray Core Facility will conduct measurements of gene expression in the sampled tissues using the Affymetrix U133 GeneChip platform. Members of our investigative team with experience in microarray analysis and bioinformatics will then conduct analysis to determine differential gene expression patterns between the two study groups. Explicitly, we wish to test the hypothesis that specific gene expression profiles can be identified that will distinguish between RCC tumors that develop in obese and nonobese individuals. Results from this study will provide direction and support for larger, more candidate-specific investigations of the biologic mechanisms behind the obesity/RCC association. In summary, this application represents an effort to harness an innovative, high throughput laboratory technology in order to improve our understanding of RCC etiology by broadening the search for risk-factor-specific molecular heterogeneity in human RCC. The long-term goal of the proposed study is to potentially inform novel prevention and treatment strategies for RCC at both the individual and population level.

描述(由申请人提供)： 肾细胞癌(RCC)的发病率和死亡率在过去三十年中稳步上升，这些趋势在很大程度上是无法解释的。虽然人们普遍认为，肥胖史会增加发生肾癌的风险，但人们对这种联系背后的实际生物机制知之甚少。事实上，肾癌进展回顾小组最近建议研究人员将重点放在阐明“肾癌已知风险因素潜在的生物学机制”上。确定肥胖和肾癌之间联系的特定分子改变的第一个合乎逻辑的方法是比较有和没有肥胖史的肾癌患者肿瘤中的体细胞基因表达谱。在这项应用中，我们建议利用商用DNA微阵列技术的高通量能力来扫描基因组，以寻找在肥胖和非肥胖个体发生的肾癌肿瘤中差异表达的基因。为此，我们将使用梅奥肾脏切除登记系统来识别在一年内在梅奥诊所罗切斯特接受手术治疗的I期Clear cell RCC的所有患者，这些患者报告没有吸烟史。从这份名单中，我们将抽取10名有肥胖史的人和10名没有肥胖史的人作为样本。然后，我们将要求每个人的新鲜冰冻组织样本(包括肿瘤和正常组织)，并使用激光捕获显微切割获得样本以提取RNA。梅奥诊所DNA微阵列核心设备将使用Affymetrix U133基因芯片平台测量样本组织中的基因表达。我们的调查团队成员具有微阵列分析和生物信息学方面的经验，然后将进行分析，以确定两个研究小组之间的差异基因表达模式。明确地说，我们希望测试这一假设，即可以识别特定的基因表达谱，以区分在肥胖和非肥胖者中发展的肾癌肿瘤。这项研究的结果将为更大规模、更具候选人特异性的肥胖/肾细胞癌关联背后的生物机制研究提供方向和支持。总之，这项应用代表了一种利用创新的高通量实验室技术的努力，以通过扩大对人类肾癌风险因子特异性分子异质性的搜索来提高我们对肾癌病因学的理解。这项拟议研究的长期目标是潜在地在个人和人群层面为肾癌提供新的预防和治疗策略。