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.
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