Dr. Oveisi: My name is David Oveisi. I'm a second year hematology oncology fellow. I'm here with Dr. Jun Gong from Cedars-Sinai Medical Center. Today, we have a PracticeUpdate in metastatic RCC for the ESMO 2020 virtual meeting. And today we're going to talk about use of biomarkers to drive therapy. Dr. Gong, how are patients with advanced kidney cancer stratified into risk categories?
Dr. Gong: That's a very important and historical question, Dr. Oveisi, as you may know. Historically, we've used two scoring systems to kind of stratify our patients. One of them is the MSKCC, which was piloted and pioneered by Dr. Motzer's group. More recently is the IMDC, or the International Metastatic RCC Database Consortium score, developed by Dr. Heng's group. Here, it's a composite score of different clinical pathologic features and laboratory features of the patient, including the time from diagnosis to treatment, KPS performance status, calcium, hemoglobin, neutrophils and platelets.
And with these factors, you put together a composite score that is intended to be prognostic of survival in the metastatic RCC population. However, equally as importantly, is that these scoring systems, more recently IMDC, have been using clinical trials to help risk stratify the metastatic RCC patients that are enrolled in these experimental trials.
Dr. Oveisi: And how do these risk categories help select initial treatment?
Dr. Gong: Historically, the specific drugs that are investigated in these clinical trials in the risk categories that were investigated helped us select initial treatments. For example, in the CheckMate-214 study, nivolumab and ipilimumab showed benefit over sunitinib in the intermediate and poor risk categories, while in favorable risk, it was more exploratory, and there was even evidence to support that sunitinib was more efficacious than nivolumab and ipilimumab in this setting. However, the other two established combination regimens in the first-line setting in the past two years, those being axitinib and pembrolizumab and avelumab and axitinib, were investigated in all categories--favorable, intermediate and poor--and showed benefit across all three categories compared to standard of care sunitinib.
In a way, you can see that it can be argued that nivolumab and ipilimumab could be tailored for those of intermediate and poor risk, while if you needed a favorable risk in metastatic RCC therapy, the other two combination VEGF-TKI/I-Os could be favored based on the randomized phase 3 data.
Dr. Oveisi: I want to ask you about how we can refine this process because I think some features such as rhabdoid or sarcomatoid features which may respond differently to VEGF-TKIs versus immunotherapy are notably not in IMDC criteria. So, one of the important trials at this conference looks at refining the treatment selection process. How was this study designed?
Dr. Gong: So, this was a very pivotal study. The BIONIKK study was a phase 2 prospective study that actually randomized patients with metastatic RCC, who are untreated, to first-line therapies of nivolumab versus nivolumab and ipilimumab versus a VEGF-TKI, in this instance being sunitinib or pazopanib, very classical VEGF-TKI. But the uniqueness of this study was that the randomization was based on a 35-gene expression signature derived from the tumor tissues, where they stratified to four different types of signatures: ccRCC1, which can be thought of as an immune low signature; ccRCC4, which can be thought of as an immune high signature. These two signatures were determined to randomize patients to receive NIVO versus NIVO-IPI, while the other two signatures, ccRCC2, which can be thought of as a pro-angiogenic signature; and ccRCC3, which can be thought of as the normal-like signature. And patients with these types of signatures were randomized to a VEGF-TKI versus NIVO-IPI.
Dr. Oveisi: And how well does this gene expression-based approach seem to work?
Dr. Gong: Out of 154 patients in the target cohort, the signatures produced some very interesting results. In those with the ccRCC1, which is immune low, it was found that nivolumab single agent had nearly half the overall response rate of NIVO-IPI, and overall response rate was the primary endpoint of this trial. And in those with ccRCC4 subtypes, the comparative efficacy of nivolumab single agent was almost the same as that for NIVO-IPI combination. If you look at the ccRCC2, or the pro-angiogenic signature, VEGF-TKI was nearly as efficacious with response rates to NIVO-IPI. But in ccRCC3, which is the normal-like signature, the VEGF-TKIs did not fare so well versus NIVO-IPI in the overall response rate.
And I think this study points out very interestingly that, in those with ccRCC4, you can possibly tailor therapies for single agent nivolumab for the first time that was proven in, in metastatic RCC, while in those with the ccRCC2, the pro-angiogenic phenotype, VEGF-TKIs may be the preferred agent in this population.
Dr. Oveisi: Wow, so the gene expression assays that are commercially available, what further work is needed to make this approach appropriate for clinical setting?
Dr. Gong: That's a very great question. This was based on preclinical data that was published in Cancer Research in 2015. It has yet to be definitively established and piloted for routine clinical use. But nonetheless, this is a very, very important study because it proves two points. Number one, that a prospectively defined biomarker-driven study in metastatic RCC is possible, and number two is that we may finally have a signature of predictive biomarker that is better than PD-L1 or any of the other solitary single biomarkers that we've been exploring in renal cell carcinoma as a way to guide and tailor therapies based on your molecular phenotype. The investigators should be applauded for this exploration. I know that more biomarkers are being investigated, and that exploration and larger prospective cohorts of metastatic RCC are eagerly anticipated.
Dr. Oveisi: Well, thank you, Dr. Gong. This has been PracticeUpdate in RCC.
Dr. Gong: Thank you, Dr. Oveisi.