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Treatment options for renal cell carcinoma (RCC) have evolved dramatically in recent years, significantly improving patient outcomes. Immune checkpoint inhibitors (ICIs), tyrosine kinase inhibitors (TKIs), and doublet therapies have all become new standards. But these changes have also brought new uncertainties, noted the authors of a recent clinical commentary in .

For example, said Nataliya Mar, MD, and colleagues at the University of California, Irvine, are current risk-stratification algorithms, based on older therapies, still optimal? And how does the choice of first-line therapy affect subsequent treatments? In their commentary, the authors explored the most recent efforts to answer the questions, which Mar also discussed in the following interview.

One challenge you point out is that current risk-stratification algorithms predate TKI and ICI therapies, rendering prognosis based on their risk groups potentially inaccurate. What can you advise oncologists about this? Is there a more up-to-date risk-stratification model available?

Mar: The two most frequently used risk-stratification algorithms are the IMDC [International Metastatic RCC Database Consortium] and MSKCC [Memorial Sloan Kettering Cancer Center] models, which were developed prior to the availability of modern therapies for RCC. These models contain an element of subjectivity and do not incorporate factors such as location of metastasis, volume of disease, tumor histology (i.e., presence of sarcomatoid differentiation), tumor WHO [World Health Organization] grade, and molecular tumor characteristics.

Attempts to modernize these algorithms are underway, such as by (presented at ASCO GU 2020), who found that risk grouping using monocyte-to-lymphocyte ratio, body mass index, and metastatic sites in patients treated with immune checkpoint inhibitors may predict survival. However, this is still a work in progress and an area of need.

Although I still use the IMDC and MSKCC models to assess the general prognosis of my patients, I do not use any specific algorithm to influence my treatment decisions. One reason is that all currently available first-line advanced ICI/TKI regimens are FDA-approved for all risk groups. Instead, I use a combination of patient characteristics (i.e., age, performance status, degree of symptoms, preference), pace of their disease, tumor volume, location of metastasis, tumor WHO grade and histologic features, as well as treatment cost to dictate the choice of first-line therapy.

You also mention that favorable risk-group patients, according to current algorithms, may have a different underlying tumor biology and respond differently to available therapies. Can you tell us about some of the evidence for this?

Mar: The main evidence to support this concept comes from the which assessed the efficacy of ipilimumab and nivolumab versus sunitinib in patients with previously untreated advanced RCC. In this study, 249 patients, representing 23% of the total study population, had favorable-risk group RCC. The baseline characteristics of these patients were similar to those of the intermediate- and high-risk groups, except that their baseline PD-L1 expression was lower.

In the subgroup analysis of this study, the survival benefit with ipilimumab and nivolumab was only noted in patients with IMDC intermediate- and high-risk groups, with hazard ratios of 0.66 and 0.57, respectively. In the favorable-risk group, the hazard ratio for survival was 1.45. Further, the objective response rate was 29% with ipilimumab and nivolumab versus 52% with sunitinib (P<0.001), while the median progression-free survival was 15.3 months versus 25.1 months (P<0.001), respectively.

Although these results should be interpreted with caution due to the small sample size of the favorable risk group in this study, it is possible that these patients have a different underlying disease biology with more VEGF [vascular endothelial growth factor receptor]-driven disease and better responses to TKI-based therapies.

Another outstanding question is whether the choice of first-line therapy influences the effectiveness of subsequent therapies. What do we know about this so far?

Mar: The currently available data to answer this question is sparse and there is no definitive algorithm regarding optimal sequencing of agents. The choice of second- and later-line systemic therapies is largely dependent on the agents used in the frontline setting. Published evidence supporting use of TKIs following immunotherapy arise from small prospective cohorts and retrospective series, but shows activity with these agents.

Meanwhile, re-treatment with a second immune checkpoint inhibitor combination (i.e., salvage ipilimumab/nivolumab after progression on a PD-1/PD-L1 agent with or without TKI) appears to have activity, although efficacy of this approach compared to that of VEGF monotherapy is unclear.

Overall, my approach to patients with advanced clear-cell RCC is to select the "most aggressive" combination therapy regimen in the first-line setting that will have the highest chance of achieving a strong and durable treatment response. My hope with this approach is that these patients will go into a complete or deep partial response and will not need second-line therapy for a prolonged period of time.

Clinical trials are evaluating novel therapies with new mechanisms of action. Can you tell us about one or two of these?

Mar: One class of drugs with a novel mechanism of action is the hypoxia-inducible factor 2 alpha (HIF-2α) inhibitors. The vast majority of clear-cell RCC is characterized by inactivation of the von Hippel-Lindau (VHL) tumor suppressor gene and consequent loss of the VHL protein, which is a key oncogenic event leading to accumulation of HIF-2α and its dimerization with HIF-1β.

The HIF-2α/HIF-1β complex transcriptionally activates hundreds of genes promoting the adaptation to hypoxia that is implicated in tumor development. HIF-2α inhibitors are orally bioavailable, small molecule inhibitors that selectively disrupt the heterodimerization of HIF-2α with HIF-1β, thereby blocking cancer cell growth, proliferation, and tumor angiogenesis.

Belzutifan is the first-in-class agent that was FDA-approved in 2021 for patients with VHL disease who require therapy for associated RCC, CNS [central nervous system] hemangioblastomas, or pNETs [primitive neuroectodermal tumors]. Belzutifan and other similar molecules are currently being investigated in clinical trials as single-agents or in combination with other therapies for patients with clear-cell RCC without VHL disease.

Early data with single-agent belzutifan in patients with advanced clear-cell RCC who received one or more prior therapies from a was presented at ASCO GU 2021. In this study, overall response rate (ORR) was 25%, disease control rate (DCR) was 80%, and 77% of patients had a response of 6 months or more. Median progression free survival (PFS) was 14.5 months.

In a of belzutifan in combination with cabozantinib in a similar patient population, also presented at ASCO GU 2021, ORR was 22.0% and DCR was 92.7%, while median PFS was 16.8 months.

Longer follow-up data from these studies is eagerly awaited.

Read the clinical commentary here and additional expert perspective here.