Background: The incidence and mortality rates for renal cell carcinoma (RCC) have risen steadily for more than 30 years, with a poor 5-year survival rate and a characteristically unpredictable clinical course for the most common clear cell form (ccRCC). The primary treatment for patients with localized ccRCC is surgical excision, which can be highly effective for early-stage cancers. However, due to the lack of any early detection strategies, approximately 35% to 40% of patients with no evidence of metastasis at the time of surgery will subsequently experience metastatic progression. Two key clinical issues are the need to (1) identify ways of more accurately predicting which patients will experience metastatic progression following surgery for localized ccRCC and (2) develop new treatments that can be used in combination with surgical excision to reduce progression. Objective-Hypothesis: The overall goal of our proposed study is to improve our understanding of the underlying mechanisms of clear cell RCC progression and enhance the ability to accurately predict which patients are at greatest risk of progression following surgery. We hypothesize that identification of specific tumor-associated proteins directly in histopathological specimens and their corresponding metabolite profile can be linked with our existing panel of biomarkers of clear cell RCC aggressiveness to develop a novel biomarker-based prognostic nomogram/scoring system that can significantly improve the ability to accurately identify individuals most at risk of ccRCC progression following surgery. Specific Aims: (SA1) To harness cutting-edge metabolomic and proteomic biomarker discovery technologies to identify novel biomarkers for ccRCC aggressiveness in primary tumor samples excised during surgery. (SA2) Combine novel biomarkers from SA1 with existing panel of seven previously published biomarkers of ccRCC aggressiveness to develop composite biomarker-based algorithm for predicting progression following surgery for ccRCC. (SA3) To harness cutting-edge metabolomic and proteomic biomarker discovery technologies to identify novel biomarkers that are differentially expressed in paired samples of primary and metastatic ccRCC. (SA4) To independently validate the differential expression of the candidate biomarkers identified in SA3 and estimate the association of the expression of these biomarkers in metastatic ccRCC with time to death. Study Design: Fresh-frozen tissue samples from 50 intermediate-risk ccRCC patients who experienced progression to metastasis within 3 years of surgery and 50 intermediate risk ccRCC patients who remain progression-free after 5 years of follow-up will be evaluated by MALDI mass spectrometry-based tissue imaging and metabolomic profiling. Also, the same tissue imaging and metabolomic approaches will be applied to fresh-frozen tissue samples from 15 patients with matched primary ccRCC tumor and metastatic lung ccRCC tumor pairs. A novel biomarker-based scoring algorithm for predicting ccRCC progression using a cohort of 1,500 patients undergoing nephrectomy for localized ccRCC will also be developed. An additional 250 patients who have archived tumor blocks available from both primary and metastatic ccRCC will also be evaluated for development of a biomarker panel. Impact: The identification of molecular biomarkers within tumor tissue that correlate with risk of ccRCC progression has the potential to not only improve prognostic assessment and enhance post-operative surveillance, but also to inform on the underlying biology of ccRCC aggressiveness as well as to provide rational targets and strategies for therapeutic intervention.
|Effective start/end date||1/1/09 → 4/30/14|
- Congressionally Directed Medical Research Programs: $503,664.00
- U.S. Department of Defense: $503,664.00