Role of quantitative gene expression using RT-PCR in the prediction of recurrence risk in resected T1 clear cell renal cell carcinoma (ccRCC).

Abstract

338 Background: Current pathology and clinical methods do not accurately estimate risk of recurrence in all patients with pT1 ccRCC. Quantitative RT-PCR (qPCR) analysis was performed on resected ccRCC tumors to identify genes associated with recurrence that significantly augment current prognostic tools. Methods: A retrospective observational cohort consisting of 931 patients (434 T1a, 201 T1b, 296 T2/3) with ccRCC was evaluated. All patients underwent nephrectomy between 1985 and 2003 at Cleveland Clinic and had paraffin-embedded tumor blocks. Patients with inherited ccRCC or inadequate follow-up (< 6 months or no recurrence data) were excluded. qPCR analysis of 732 genes was performed on all patients. Cox Proportional Hazards regression models were used to evaluate the association between gene expression and recurrence-free interval (RFI). Results: 448 genes were significantly (unadj. p < 0.05) associated with RFI, from which 72 genes were carried forward for further study (Rini, ASCO 2010, #4501). Angiogenesis is the strongest among the pathways represented, from which 3 genes (AQP1, NOS3, PPAP2B) were selected for this analysis. Incorporating these 3 genes, a subset of higher risk patients among those classified as low risk by Leibovich criteria was identified. By Leibovich criteria, 85% of the patients in the cohort with pT1 tumors (< 7.0 cm) were identified as low risk - 7% recurrence at 5 years (95% CI: 5%, 9%). Incorporating these 3 genes, 9% of these patients were found to be at increased risk for recurrence - 19% at 5 years (95% CI: 7%, 21%). For the subset of T1a patients (< 4.0 cm), 98.6% were low risk according to the Leibovich criteria - 7% recurrence at 5 years (95% CI: 4%, 10%). Incorporating the 3 genes, 11% of these patients were found to be at increased risk - 20% at 5 years (95% CI: 7%, 31%). Conclusions: Addition of 3 angiogenesis-related genes to the Leibovich criteria in patients with pT1 tumors refines stratification of patient risk in a subset of patients. More precise estimation of recurrence risk will help to tailor surveillance and refine inclusion into clinical trials. These genes will be incorporated into an algorithm that requires validation in an external data set. [Table: see text]