A Multigene Signature Based on Cell Cycle Proliferation Improves Prediction of Mortality Within 5 Yr of Radical Nephrectomy for Renal Cell Carcinoma

Abstract

Background: There is a critical need for improved prognostic discrimination in patients with renal cell carcinoma (RCC) given the increasing awareness that some patients may be managed with active surveillance, while others with higher-risk disease might benefit from adjuvant therapy following surgery.

Objective: To determine whether a multigene proliferation signature predicts long-term oncologic outcomes in surgically resected RCC.

Design, setting, and participants: The cell cycle proliferation (CCP) score was determined after radical nephrectomy for localized clear cell, papillary, or chromophobe RCC in 565 patients.

Outcome measurements and statistical analysis: The primary end point was disease-specific mortality (DSM), and disease recurrence was a secondary end point. Association with outcomes was evaluated by Cox proportional hazards survival analysis. The CCP score was compared with the Karakiewicz nomogram, and a composite (R-CCP) score was developed.

Results and limitations: A total of 68 patients (12%) recurred and 32 (6%) died of disease within 5 yr of nephrectomy. The CCP score was an independent predictor of recurrence (hazard ratio [HR] 1.50, 95% confidence interval [CI] 1.07-2.09) and DSM (HR 2.49, 95% CI 1.53-4.04) after adjusting for clinical variables using the baseline nomogram. The composite R-CCP score gave a Harrell's concordance index of 0.87 and stratified patients into low- (n=338) and high-risk (n=202) categories with 99% and 84% cancer-specific survival probabilities, respectively (p<0.001).

Conclusions: The CCP score is a significant, independent predictor of long-term oncologic outcomes in patients who have undergone nephrectomy for RCC. Combining the molecular classifier with baseline clinical variables allows for accurate, patient-specific risk assessment for use in guiding clinical management.

Patient summary: In this study, we sought to understand how well gene expression information from individual kidney tumors can predict cancer recurrence and death following surgical removal. We found that the combination of the gene expression test and clinical characteristics provides an accurate prognostic assessment to help inform clinical decisions.

Keywords: Biomarkers; Kidney cancer; Molecular classifier; Predictive models; Renal cell carcinoma.