Somatic mutations as preoperative predictors of metastases in patients with localized clear cell renal cell carcinoma - An exploratory analysis.

Abstract

Recurrent genomic alterations in clear cell renal cell carcinoma (ccRCC) have been associated with treatment outcomes; however, current preoperative predictive models do not include known genetic predictors. We aimed to explore the value of common somatic mutations in the preoperative prediction of metastatic disease among patients treated for localized ccRCC. After obtaining institutional review board approval, data of 254 patients with localized ccRCC treated between 2005 and 2015 who underwent genetic sequencing was collected. The mutation status of VHL, PBRM1, SETD2, BAP1 and KDM5C were evaluated in the nephrectomy tumor specimen, which served as a proxy for biopsy mutation status. The Raj et al. preoperative nomogram was used to predict the 12-year metastatic free probability (MFP). The study outcome was MFP; the relationship between MFP and mutation status was evaluated with Cox-regression models adjusting for the preoperative nomogram variables (age, gender, incidental presentation, lymphadenopathy, necrosis, and size). The study cohort included 188 males (74%) and 66 females (26%) with a median age of 58 years. VHL mutations were present in 152/254 patients (60%), PBRM1 in 91/254 (36%), SETD2 in 32/254 (13%), BAP1 in 19/254 (8%), and KDM5C in 19/254 (8%). Median follow-up for survivors was 8.1 years. Estimated 12-year MFP was 70% (95% CI: 63%-75%). On univariable analysis SETD2 (HR: 3.30), BAP1 (HR: 2.44) and PBRM1 (HR: 1.78) were significantly associated with a higher risk of metastases. After adjusting for known preoperative predictors in the existing nomogram, SETD2 mutations remained associated with a higher rate of metastases after nephrectomy (HR: 2.09, 95% CI: 1.19-3.67, P = 0.011). In the current exploratory analysis, SETD2 mutations were significant predictors of MFP among patients treated for localized ccRCC. Our findings support future studies evaluating genetic alterations in preoperative renal biopsy samples as potential predictors of treatment outcome.