Predictive biomarkers for RCC urgently needed, difficult to uncover
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With new targeted and immune-based treatments coming out for renal cell carcinoma, predictive biomarkers are needed more than ever. The many different tumor entities of RCC, their genetic and mutational alterations and different clinical behaviors all contribute to a complex disease that requires personalized treatment.
Researchers continue to search for biomarkers that will unlock a deeper understanding of RCC and enable customized treatment, but many factors can complicate study results, according to Pooja Ghatalia, MD, a medical oncologist specializing in genitourinary cancers and assistant professor in the department of hematology/oncology at Temple Health’s Fox Chase Cancer Center in Philadelphia.
“Predictive biomarkers help guide treatment selection and help minimize use of unnecessary treatment in patients. However, several limitations need to be considered when designing [clinical trials for] biomarkers,” she said. “These include intratumoral heterogeneity, unclear cutoffs to define positivity, variability in expression arising from specimen age, prior treatments, assay choice and cells analyzed.”
Current biomarker landscape
In the United States, the International mRCC Database Consortium’s (IMDC) prognostic risk model uses six clinical parameters to classify patient disease by risk level as favorable, immediate or poor risk.
“This classification is prognostic but is also predictive based on the results of the CheckMate-214 study,” Ghatalia said. “This study showed better clinical outcomes with [ipilimumab (Yervoy, Bristol-Myers Squibb) and nivolumab (Opdivo, Bristol-Myers Squibb)] combination compared to sunitinib [Sutent, Pfizer] in patients with intermediate/poor risk disease. In favorable risk patients, the [overall response rate] was higher in the sunitinib compared to the [ipilimumab/nivolumab] arm.”
Beyond this stratification, a few biomarkers have shown encouraging predictive results but need further study, Ghatalia said.
“Angiogenic and immune gene signatures appear to show promise and I anticipate further development of these signatures in guiding use of immune checkpoint inhibitors,” she said. For example, the phase 3 IMmotion150 clinical trial showed a combination of atezolizumab [Tecentriq, Genentech/Roche] and bevacizumab [Avastin, Genentech] conferred longer PFS than sunitinib as first-line treatment for mRCC. Additionally, she noted, the researchers found “tumors with T effector/IFN-gamma-high or angiogenesis-low signatures exhibited better outcomes with combination therapy versus sunitinib.”
Ghatalia said obesity is another potential area of interest for research.
“Several studies have shown interesting results suggesting an interaction between obesity and treatment effect. Patients with higher body mass index have been shown to have better survival outcomes when treated with VEGF-targeted agents. These findings may be related to the adiponectin-adipoR1 axis and warrant further investigation,” she explained.
While PD-L1 initially showed promise as a biomarker in metastatic RCC, Ghatalia said it has since shown to be unreliable and thus is not used in clinic to guide treatment.
“For example in KEYNOTE427, high PD-L1 associated with higher ORR and in CheckMate-214 high PD-L1 associated with high PFS but this association of high PD-L1 and response to immunotherapy was not seen in CheckMate-025 and JAVELIN Renal 101 studies. While not predictive for IO response, PDL1+ disease, in general, has been associated with poor prognosis in advanced RCC.”
PD-L1 is also limited by disagreement around the best definition among the range of 1% to 50% for PD-L1 positivity.
PBRM1 mutation has shown similar results.
“A study by Miao Science in 2018 indicated an association between PBRM1 mutation and response to immunotherapy in RCC. However, this association has not been validated by several other groups, including evaluation of the association in IMmotion150 study, which was negative,” Ghatalia said.
Personalized therapy on the horizon
Ghatalia noted because clear cell RCC contributes to about 80% of cases, “most of the research pertaining to predictive markers has been conducted in clear cell RCC. Most certainly, novel predictive biomarkers will guide therapy in non cc-RCC.”
Ghatalia said several paths remain open to investigation for additional and more reliable biomarkers for clear cell RCC.
“Evaluation of other immune cell types, epigenetic modifiers and metabolic correlates and their role in regulating IO response will likely surface over the next few years. For example, presence of CD8-positive PD1-positive T-cells and high endogenous retroviruses have been associated with immunotherapy response. Assessing pre- and post-therapy tumor and blood samples will help shed more light on mechanisms of response and resistance to therapy and will help identify biomarkers.”
References:
- Farber NJ, et al. Transl Cancer Res. 2017;doi:10.21037/tcr.2017.05.19.
- Lopez-Beltran A, et al. Front Oncol. 2018;doi:10.3389/fonc.2018.00456.
- Motzer RJ, et al. J Clin Oncol. 2009;doi:10.1200/JCO.2008.20.1293.
- Rini BI, et al. J Immunother Cancer. 2019;doi:10.1186/s40425-019-0813-8.
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