Most neoplasms, including bladder cancer, are thought to progress through a series of clinical histopathological stages. This progression is accompanied by specific genetic changes which include activation of protooncogenes and loss of tumor suppressor genes. Recently, we defined two critical events that occur early in bladder progression: (1) a high incidence of loss on chromosome 9p21 and less often (2) instability of microsatellite repeats. A novel tumor suppressor gene, p16, is often deleted in the 9p21 region. However, other areas of chromosomal deletion and other critical genes in known regions of high frequency loss remain to be identified. Studies in this proposal are aimed at the development of a genetic model of bladder cancer progression and ultimately in developing new molecular detection strategies. First, a variety of lesions including, preinvasive and invasive tumor will be tested to identify new regions of loss (and verify established regions of loss) and microsatellite alterations to develop a molecular progression model for bladder cancer. Second, mapping studies will continue to identify the precise location of putative tumor suppressor gene loci on 14q and other chromosomal arms with a high frequency of loss. Finally, we will continue development of assays that can detect microsattelite alterations in urine. Initial feasibility projects demonstrate that these studies will be greatly accelerated with the advent of high throughput fluorescent capillary and chip arrays. A combination of the above studies should provide important insight into the specific genetic changes associated with bladder tumor progression and eventually lead to the isolation of novel tumor suppressor genes. Additionally, establishment of highly susceptible microsatellite repeats in bladder tumors will allow identification of critical targets for further development of molecular detection approaches.
|Effective start/end date||1/1/01 → 7/31/11|
- Molecular Biology
- Cancer Research
- Cell Biology
- Statistics and Probability
- Statistics, Probability and Uncertainty
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