In Search of Clinical Biomarkers of Response to Checkpoint Inhibitor Therapy in Renal Cell Carcinoma | Cancer Biomarkers | JAMA Network Open | JAMA Network
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Invited Commentary
Oncology
January 26, 2021

In Search of Clinical Biomarkers of Response to Checkpoint Inhibitor Therapy in Renal Cell Carcinoma

Author Affiliations
  • 1Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California
  • 2Department of Urology, Stanford University School of Medicine, Stanford, California
JAMA Netw Open. 2021;4(1):e2035120. doi:10.1001/jamanetworkopen.2020.35120

Sati et al1 present an analysis of factors that may be associated with response to and survival after therapy with programmed death 1/programmed death ligand 1 (PD-1/PD-L1) checkpoint inhibitors (CPIs) for patients with metastatic clear cell renal cell carcinoma (ccRCC). There is a tremendous clinical need to identify factors associated with response to CPI therapy. The treatment landscape for patients with metastatic ccRCC is rapidly evolving. Because there are currently 15 US Food and Drug Administration–approved therapies for metastatic ccRCC, patients often cycle through multiple regimens.2 Without biomarker-informed strategies, this empirical sequential treatment selection exposes patients to maximal toxic effects but does not optimize clinical benefit. Especially for PD-1/PD-L1–directed therapies, which can require many months to achieve maximal response, biomarkers are being sought to estimate clinical benefit.

A meta-analysis typically combines data from multiple studies to generate the average association between an exposure and an outcome (eg, receipt of a PD-1/PD-L1–based CPI and overall survival). Sati et al1 used a meta-analysis approach combining data from 6 clinical trials to evaluate the average association of relevant covariates (eg, age and PD-L1 expression) with response to PD-1/PD-L1–based CPI therapies. The authors found that overall survival was better among younger patients and that progression-free survival was better among patients with tumors demonstrating more PDL-1 expression, those with poor Memorial Sloan Kettering Cancer Center risk scores, and those with sarcomatoid features. Because 3 of the studies in this analysis investigated CPI monotherapy and 3 included combinations of antiangiogenesis agents plus CPIs, the findings may be applicable to patients who receive immune CPIs alone or together with antiangiogenesis agents.

Strikingly, in the study by Sati et al,1 age was the sole clinical factor associated with improved overall survival: Patients younger than 65 years had improved overall survival compared with patients aged 75 years or older. It is important to note that younger age did not meet statistical significance thresholds in any of the 3 included trials, and the relative effect in this meta-analysis was modest. Moreover, younger age was associated with improved overall survival, but not progression-free survival. Thus, it is not clear whether age is an effect modifier of response to PD-1/PD-L1–based CPI therapies, because it could also be functioning as a measure of overall health. Unfortunately, decreased benefit from systemic treatment for older patients may be a general phenomenon in metastatic ccRCC.3 Together, these concerns highlight the need for research that focuses on factors associated with therapeutic efficacy in an older patient population.

Sati et al1 also identified additional clinical factors that, although not associated with improved overall survival, were associated with progression-free survival. Surprisingly, neither the presence of lung or bone metastases nor sex was associated with overall survival. Although patients with a poor International Metastatic Renal Cell Carcinoma Database Consortium risk score lacked an overall survival benefit in this analysis, patients with a poor Memorial Sloan Kettering Cancer Center risk score did have improved progression-free survival compared with favorable risk patients. Similarly, elevated PD-L1 and presence of sarcomatoid differentiation were found to be associated with improved progression-free survival.

This meta-analysis likelihood ratio approach has limitations. Clinical decision-making requires information to help clinicians choose the best treatment for an individual patient, rather than the relative likelihood of a patient to respond to PD-1/PD-L1–based CPI therapies. These data should be interpreted with caution and not used to suggest that older patients should not receive PD-1/PD-L1 based CPI therapies. Older patients do show benefit from using CPI-based treatment and can exhibit dramatic responses. Similarly, patients with tumors that do not demonstrate sarcomatoid differentiation also derive benefit from CPI, and clinical trials have demonstrated that PD-L1 expression is not always associated with response for patients with metastatic ccRCC.4 Also, although randomized clinical trials have internal validity, using data from these 6 clinical trials that used different inclusion criteria, studied different CPIs or combinations of CPIs with other treatments, and contributed subanalyses data for only some of these clinical factors is challenging.

The current state of biomarkers to estimate response to PD-1/PD-L1–based CPI therapy is wanting. Sati et al1 have identified candidate cohorts that may be preferentially selected for receipt of PD-1/PD-L1–based CPI therapy. Research efforts will continue to focus on ways to personalize treatment selection for individual patients by identifying which treatments are associated with improved overall survival, result in complete responses, and are associated with immune-related adverse events, as well as strategies that inform appropriate sequencing of individual agents or combinations of therapies.4,5 We remain optimistic that a combination of clinical characteristics, molecular biomarkers, and imaging approaches will yield biomarkers to identify treatments and significantly improve outcomes for patients with metastatic ccRCC.

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Article Information

Published: January 26, 2021. doi:10.1001/jamanetworkopen.2020.35120

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Fan AC et al. JAMA Network Open.

Corresponding Author: John T. Leppert, MD, MS, Department of Urology, Stanford University School of Medicine, 300 Pasteur Dr, Grant S-287, Stanford, CA 94305 (jleppert@stanford.edu).

Conflict of Interest Disclosures: None reported.

References
1.
Sati  N, Boyne  D, Cheung  WY, Cash  SB, Arora  P.  Factors modifying the associations of single or combination programmed cell death 1 and programmed cell death ligand 1 inhibitor therapies with survival outcomes in patients with metastatic clear cell renal cell carcinoma: a systematic review and meta-analysis.   JAMA Netw Open. 2021;4(1):e2034201. doi:10.1001/jamanetworkopen.2020.34201Google Scholar
2.
Chen  VJ, Hernandez-Meza  G, Agrawal  P,  et al.  Time on therapy for at least three months correlates with overall survival in metastatic renal cell carcinoma.   Cancers (Basel). 2019;11(7):E1000. doi:10.3390/cancers11071000PubMedGoogle Scholar
3.
van den Brom  RRH, van Es  SC, Leliveld  AM,  et al.  Balancing treatment efficacy, toxicity and complication risk in elderly patients with metastatic renal cell carcinoma.   Cancer Treat Rev. 2016;46:63-72. doi:10.1016/j.ctrv.2016.04.002PubMedGoogle ScholarCrossref
4.
Motzer  RJ, Robbins  PB, Powles  T,  et al.  Avelumab plus axitinib versus sunitinib in advanced renal cell carcinoma: biomarker analysis of the phase 3 JAVELIN Renal 101 trial.   Nat Med. 2020;26(11):1733-1741. doi:10.1038/s41591-020-1044-8PubMedGoogle ScholarCrossref
5.
Braun  DA, Hou  Y, Bakouny  Z,  et al.  Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma.   Nat Med. 2020;26(6):909-918. doi:10.1038/s41591-020-0839-yPubMedGoogle ScholarCrossref
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