ASCO GU 2019: Risk Stratification After Resection of Localized Disease: Which Model to Use, and Why?
Historically, prognostication of recurrence was solely based on clinicopathologic features after RCC resection. These factors include pathologic T stage, N stage, tumor size, and grade, as well as some more subjective factors including the presence of tumor necrosis, lymphovascular invasion, and patient performance status. Based on these factors, several models have been developed, including the Memorial Sloan Kettering (MSK) Postoperative nomogram, the Leibovich score, the UISS model, and the SIGN model. He believes that while these models have been validated, and are predictive of recurrence, they do not take into account the individual tumor biology of each patient. He believes that by incorporating genomic data, we may be able to more accurately prognosticate the likelihood of recurrence in individual patients.
Dr. Rini then went on to discuss the multigene assays that have recently been developed to provide improved prognostic information beyond the traditional histopathologic factors. He helped to develop a 16 gene panel that was created by screening 732 genes with known biologic pathways that are functionally important in clear cell RCC. The 16 genes that were eventually selected as the most likely to confer a better or worse outcome included gene families involved in neovascularization, the immune response, cell growth/division, and inflammation. Up- or down-regulation of these genes was then correlated with risk of recurrence after surgical resection to determine a Recurrence Score (RS). RS is calculated on a scale of 0 – 100, and for each 25-point increase in the recurrence score, it confers a hazard ratio of 4.20 (2.76 – 6.40 95% CI) for local or distant recurrence on multivariate analysis. He additionally presented data showing that the RS also predicts RCC-specific survival, disease-free survival, and overall survival with statistical significance.
He additionally discussed the data regarding two other gene panels, ClearCode 34, and the cell cycle progression (CCP) score. Both assays have also been shown to add additional prognostic information by themselves, and when combined with histopathologic factors. Rini believes that soon, we will begin to incorporate this genomic data when risk-stratifying patients with clinically localized RCC. It will also become important to help predict response to treatment, particularly as ongoing trials are evaluating the efficacy of adjuvant immunologic agents in patients who are at higher risk of recurrence. He notes that future trials should help to solidify the role that these gene panel tests will play in the future.
Presenter: Brian Rini, MD, Cleveland Clinic Taussig Cancer Institute
Written by: Brian Kadow, MD. Society of Urologic Oncology Fellow, Fox Chase Cancer Center at the 2019 American Society of Clinical Oncology Genitourinary Cancers Symposium, (ASCO GU) #GU19, February 14-16, 2019 - San Francisco, CA