Journal Article Ahead of print
PubMed: 42149133 DOI: 10.1158/1078-0432.CCR-26-0216
Dissecting the Tumor Microenvironment to Identify Biomarkers of Outcome to Anti-PD-1 Therapy in Clear Cell Renal Cell Carcinoma: analyses of the HCRN GU16-260 trial.
Clin Cancer Res
Authors: Nourhan El Ahmar, Morgan A Paul, Berkay Simsek, Sayed Matar, Opeyemi A Jegede, Yasmin Nabil Laimon, Varunika Savla, Razan Mohanna, Gabriel Roberti de Oliveira, Aseman Bagheri Sheshdeh, Thomas Denize, Destiny J West, Maxwell D Seager, Maxine Sun, Toni K Choueiri, Wanling Xie, Gordon J Freeman, Arlene H Sharpe, David A Braun, Naomi B Haas, Hans Hammers, Mehmet A Bilen, Mark Stein, Jeffrey A Sosman, Catherine J Wu, David F McDermott, Michael B Atkins, Sabina Signoretti
Affiliations
- Brigham and Women's Hospital Boston United States.
- Dana-Farber Cancer Institute Boston, MA United States.
- Yale New Haven Hospital New Haven, CT United States.
- Brigham and Women's Hospital Boston, MA United States.
- Massachusetts General Hospital Boston United States.
- Harvard University Boston United States.
- Yale University New Haven, CT United States.
- University of Pennsylvania Philadelphia, PA United States.
- The University of Texas Southwestern Medical Center Dallas, TX United States.
- Emory University Hospital Atlanta, GA United States.
- Columbia University New York, NY United States.
- Robert H. Lurie Comprehensive Cancer Center of Northwestern University Chicago, IL United States.
- Beth Israel Deaconess Medical Center, Harvard Medical School Boston, MA United States.
- Georgetown University Medical Center Washington, DC United States.
Abstract
PURPOSE
We investigated components of the immune tumor microenvironment as determinants of clinical outcome to anti-PD-1 therapy in patients with metastatic clear cell renal cell carcinoma (mccRCC) treated with frontline nivolumab in the phase 2, non-randomized HCRN GU16-260 trial.
EXPERIMENTAL DESIGN
Pre-treatment primary ccRCCs from 72 patients were analyzed by multiplex immunofluorescence and image analysis to assess non-terminally exhausted CD8+ (CD8⁺PD-1⁺TIM3⁻LAG3⁻) tumor-infiltrating lymphocytes (TILs), PD-1+ regulatory T cells (Tregs), total and peritumoral tertiary lymphoid structures (TLS), and CD163+ tumor-associated macrophages (TAMs). Clinical endpoints included objective response rate (ORR) and progression-free survival (PFS).
RESULTS
Densities of CD8⁺PD-1⁺TIM3⁻LAG3⁻ TILs, total and peritumoral TLS, and CD163⁺ TAMs, as continuous variables, were associated with improved ORR (Odds Ratio: 1.54 [1.10-2.16] for TILs; 1.18 [1.02-1.37] for total TLS; 1.10 [1.02-1.18] for peritumoral TLS; 2.21 [1.33-3.69] for TAMs) and longer PFS (Hazard Ratio: 0.79 [0.67-0.95] for TILs; 0.92 [0.85-0.99] for total TLS; 0.94 [0.90-0.98] for peritumoral TLS; 0.77 [0.61-0.97] for TAMs). Although % of PD-1+ Tregs as continuous variable was not associated with outcomes, at an optimal cut-off, high % of PD-1+ Tregs tended to be associated with lower ORR (12.5% vs 43.6%, p=0.093) and was associated with shorter PFS (3.4 vs 10.9 months, p<0.001). The biomarkers were not strongly correlated with each other and their integration in multi-biomarker models further stratified outcomes.
CONCLUSION
Individual immune cell populations within the ccRCC microenvironment are associated with response/resistance to frontline anti-PD-1 therapy. Our findings support the development of combined immune marker models to identify patients with divergent outcomes.
MeSH
Cells, Neoplasms, Multiple Chronic Conditions, Carcinoma, Renal Cell, Biomarkers, Therapeutics, Tumor Microenvironment