Predicting Outcomes in Renal Cell Cancer: the Role of Single Nucleotide Polymorphisms (Snps).

e16074 Background: Despite major advances in the knowledge of the molecular basis of RCC, prognosis is still defined mostly using clinical and pathological parameters. Moreover, no valid predictive biomarkers exist to help us selecting the best treatment for each patient. The aim of this work is analyzing the expression and determining the prognostic and predictive value of 64 key SNPs in 18 genes related with angiogenesis or metabolism of antiangiogenics in two cohorts of RCC patients (pts) [localized and advanced] RCC treated at our institution. Methods: DNA from formalin fixed paraffin embedded tumor and non-tumor samples from 99 pts with RCC (26 advanced/ 73 localized) was extracted with QiAGEN Kit and amplified with a specific primers pool for every SNP as determined by the manufacturer (Lifetech). Sixty-four SNPs were chosen based on their Minor Allele Frequency by HapMap, linkage disequilibrium by Haploview and information from SNP data base (dSNP) and were studied by TaqMan OpenArray (Lifetech). Statistically significant SNPs were validated in an external cohort by individual assays. The presence of the selected SNPs was correlated with clinical features, disease free survival (DFS), overall survival (OS) and response to treatment (RR). SPSS v20 was utilized for statistical analyses. Results: In pts with localized RCC, 2 SNPs in 2 genes involved in angiogenesis showed a protective effect (VEGFR2: rs2071559, PDGFRA: rs4358459) and others SNPs predicted for worse DFS (VEGFR2: rs10013228, rs1870377, PDGFRA: rs2228230) and shorter OS (VEGFR2: rs2305948, rs10013228; VEGFR3: rs6877011, rs307826) (p < 0.05). In the advanced setting, 6 SNPs in genes related to both angiogenesis and metabolism of antiangiogenics were statistically implicated in OS (IL8: rs2227543, PDGFA: rs9800958, PDGFRB: rs2302273 (p≤0.05)) and RR (VEGFA: rs699947, rs3025010, VEGFB: rs594942 (p < 0.03)). These 14 SNPs are currently being validated in an external cohort of 80 patients with RCC and this data will be presented. Conclusions: These SNPs in genes critical to angiogenesis and metabolism of antiangiogenics might be used as potential prognostic/predictive biomarkers. Prospective validation is ongoing.