AUA 2017: A molecular scoring algorithm to predict survival in metastatic renal cell carcinoma

Boston, MA ( There has been rapid adoption of using molecular signatures to classify clinical outcomes by urologic researchers. Previously described prognostic models using clinicopathologic features for metastatic RCC yield imperfect results, with an average C index of 0.66. In this study from the Mayo Clinic, the gene expression profile of metastatic RCC was examined, and a score for characterizing the clinical course was described. Using specimen from 111 metastatic RCC patients with no prior systemic therapy, 124 candidate genes were found by Nanostring. From these, the panel consisting of CCA, CCB UNG2, VEGFR1/FLT1, RAN, ANGPTL4, and CDH13 were used for the characterization of disease progression. When divided into quartiles, this novel gene risk predictor outperformed the Mayo clinic predictor model based on 9 clinicopathologic features and incrementally added predictive power to the model.

Prior to clinical adoption, this 9 gene panel test needs to be independently validated in larger patient cohorts. In addition, the identified gene distinguishing aggressive from benign course after the diagnosis of metastatic RCC may lead to better understanding in the progression of RCC.

Presented by: Jeanette Eckel-Passow

Written By: Roger Li MD Urologic Oncology Fellow, UT MD Anderson Cancer Center @UrogerliMD
Ashish M. Kamat MD Wayne B. Duddlesten Professor, UT MD Anderson Cancer Center

at the 2017 AUA Annual Meeting - May 12 - 16, 2017 – Boston, Massachusetts, USA