Identification of Tumor Biomarkers Associated with Outcome among Patients with Renal cell Carcinoma
There is a great deal of variability in the survival experience of patients diagnosed with RCC that is simply not explained by our classic clinical measures of cancer aggressiveness such as tumor stage or tumor grade. This is most likely due to the fact that indicators like tumor stage and grade are merely surrogate measures of what is actually going on at the molecular level within the tumor itself. Therefore, it stands to reason that if we can identify molecular alterations within the actual RCC tumors themselves that correlate with risk of cancer progression and ultimately patient survival we could not only improve our ability to predict outcomes and direct patient therapy but also we would be illuminating novel targets for drug development.
Our research program is also utilizing high throughput genomic and proteomic platforms and follow-up large scale epidemiological investigations to help identify molecular alterations within RCC tumors that can predict patient survival and/or disease progression. For example, we recently conducted genomic profiling to compare gene expression patterns between aggressive and non-aggressive forms of ccRCC (Kosari, Parker, et al. 2005). These gene array experiments and independent validation using real time PCR revealed that mRNA for the human protein survivin is over-expressed in aggressive ccRCC compared with non-aggressive ccRCC. As a follow-up, we used data and archived tumor samples from a large cohort of clear cell RCC patients treated surgically at Mayo Clinic from 1990 to 1994 to report that those patients whose tumors show high levels of survivin expression are at markedly increased risk of cancer progression and death from RCC compared with those patients with tumors showing low survivin expression levels (see figures 2, 3 and 4 from Parker, et al 2006). More importantly, the association of survivin expression and patient outcome remains significant even after adjustment for well-known predictors of RCC outcome (tumor stage, grade, size and presence of necrosis) (see Table 2 from Parker et al. 2006).
We are currently designing a follow up large-scale epidemiologic investigation in order to:
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