Differential Gene Expression in Renal Cancers

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无法解释。虽然人们普遍认为肥胖史会增加患RCC的风险，但对这种关联背后的实际生物学机制知之甚少。事实上，肾癌进展审查小组最近建议研究人员集中精力阐明“肾癌已知风险因素的生物学机制”。确定肥胖和RCC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RCC患者肿瘤中的体细胞基因表达谱。在本申请中，我们建议利用市售DNA微阵列技术的高通量能力，扫描基因组中肥胖和非肥胖个体中发生的RCC肿瘤中差异表达的基因。为此，我们将使用马约肾切除术登记，以确定所有在马约诊所罗切斯特接受手术治疗的I期透明细胞肾细胞癌患者，这些患者在一年内没有吸烟史。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。然后，我们将要求每个个体的新鲜冷冻组织样本（肿瘤和正常组织），并使用激光捕获显微切割获得RNA提取样本。马约诊所DNA微阵列核心机构将使用Affytek U133 GeneChip平台测量采样组织中的基因表达。我们的研究小组成员在微阵列分析和生物信息学的经验，然后将进行分析，以确定两个研究组之间的差异基因表达模式。因此，我们希望验证这样一个假设，即可以鉴定出特异性基因表达谱，从而区分肥胖和非肥胖个体中发生的RCC肿瘤。这项研究的结果将为肥胖/RCC相关性背后的生物学机制的更大、更针对候选人的研究提供方向和支持。总之，该应用代表了利用创新的高通量实验室技术的努力，以便通过扩大对人类RCC中风险因素特异性分子异质性的研究来提高我们对RCC病因的了解。拟议研究的长期目标是在个体和群体水平上为RCC提供新的预防和治疗策略。

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.