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. 2022 Mar;10(3):e004316.
doi: 10.1136/jitc-2021-004316.

Biomarker analysis from CheckMate 214: nivolumab plus ipilimumab versus sunitinib in renal cell carcinoma

Robert J Motzer #  1 , Toni K Choueiri #  2 , David F McDermott  3 , Thomas Powles  4 , Yann-Alexandre Vano  5   6 , Saurabh Gupta  7 , Jin Yao  7 , Celine Han  7 , Ron Ammar  7 , Simon Papillon-Cavanagh  7 , Shruti S Saggi  7 , M Brent McHenry  7 , Petra Ross-Macdonald  7 , Megan Wind-Rotolo  7
Affiliations

Biomarker analysis from CheckMate 214: nivolumab plus ipilimumab versus sunitinib in renal cell carcinoma

Robert J Motzer et al. J Immunother Cancer. 2022 Mar.

Abstract

Background: The phase 3 CheckMate 214 trial demonstrated higher response rates and improved overall survival with nivolumab plus ipilimumab versus sunitinib in first-line therapy for advanced clear-cell renal cell carcinoma (RCC). An unmet need exists to identify patients with RCC who are most likely to benefit from treatment with nivolumab plus ipilimumab.

Methods: In exploratory analyses, pretreatment levels of programmed death ligand 1 were assessed by immunohistochemistry. Genomic and transcriptomic biomarkers (including tumor mutational burden and gene expression signatures) were also investigated.

Results: Biomarkers previously associated with benefit from immune checkpoint inhibitor-containing regimens in RCC were not predictive for survival in patients with RCC treated with nivolumab plus ipilimumab. Analysis of gene expression identified an association between an inflammatory response and progression-free survival with nivolumab plus ipilimumab.

Conclusions: The exploratory analyses reveal relationships between molecular biomarkers and provide supportive data on how the inflammation status of the tumor microenvironment may be important for identifying predictive biomarkers of response and survival with combination immunotherapy in patients with RCC. Further validation may help to provide biomarker-driven precision treatment for patients with RCC.

Keywords: gene expression profiling; immunotherapy; inflammation; kidney neoplasms; tumor biomarkers.

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Conflict of interest statement

Competing interests: RJM reports consulting fees from Aveo, Calithera, Eisai, Eli Lilly, EMD Serono, Genentech, Merck, Novartis AG, Pfizer, and Roche, and contracted research to employer MSKCC for Bristol Myers Squibb, Eisai, Exelixis, Genentech, Merck, Pfizer, and Roche. TC reports personal and institutional research undertaken for Alexion, Analysis Group, AstraZeneca, Aveo, Bayer, Bristol Myers Squibb/ER Squibb & Sons LLC, Calithera, Cerulean, Corvus, Eisai, Exelixis, F. Hoffmann-La Roche, Foundation Medicine, Genentech, GlaxoSmithKline, Ipsen, Lilly, Merck, Novartis, Peloton, Pfizer, Prometheus Labs, Roche, Roche Products Limited, Sanofi/Aventis, Takeda, and Tracon; consulting/honoraria or advisory roles from Alexion, Analysis Group, AstraZeneca, Aveo, Bayer, Bristol Myers Squibb/ER Squibb & Sons LLC, Cerulean, Corvus, Eisai, EMD Serono, Exelixis, Foundation Medicine Inc, Genentech, GlaxoSmithKline, Heron Therapeutics, Infinity Pharma, Ipsen, Jansen Oncology, IQVIA, Lilly, Merck, NCCN, NiKang, Novartis, Peloton, Pfizer, Pionyr, Prometheus Labs, Roche, Sanofi/Aventis, Surface Oncology, Tempest, and Up-to-Date; travel, accommodations, expenses, and medical writing in relation to consulting, advisory roles, or honoraria; participation in CME-related events by OncLive, PVI, MJH Life Sciences, and in the NCI GU steering committee; owning Pionyr and Tempest stock; and patents filed, royalties, and other intellectual properties related to biomarkers of immune checkpoint inhibitors and ctDNA. TC is also supported in part by the Dana-Farber/Harvard Cancer Center Kidney SPORE and Program, the Kohlberg Chair at Harvard Medical School and the Trust Family, Michael Brigham, and Loker Pinard Funds for Kidney Cancer Research at DFCI. DM reports honoraria from Alkermes, Bristol Myers Squibb, Calithera Biosciences, Eisai, Eli Lilly, EMD Serono, Iovance, Merck, Pfizer, and Werewolf Therapeutics; and research support from Alkermes Inc, Bristol Myers Squibb, Exelixis, Genentech, Merck, Pfizer, and X4 Pharma. TP reports honoraria for advisory/research boards from Astellas, AstraZeneca, Bristol Myers Squibb, Eisai, Exelixis, Incyte, Ipsen, Johnson & Johnson, Merck, Merck Serono, MSD, Novartis, Pfizer, Roche, and Seattle Genetics; institutional grants and funding from Astellas, AstraZeneca, Bristol Myers Squibb, Eisai, Exelixis, Ipsen, Johnson & Johnson, Merck, Merck Serono, MSD, Novartis, Pfizer, Roche, and Seattle Genetics; and fees for travel and accommodation expenses from AstraZeneca, Ipsen, MSD, Roche, and Pfizer. YV reports no conflicts of interest. SG is employed by, and owns stock in, Bristol Myers Squibb. JY is employed by, and owns stock in, Bristol Myers Squibb. CH is employed by Bristol Myers Squibb. RA is employed by, and owns stock in, Bristol Myers Squibb. SP-C is employed by, and a shareholder of, Bristol Myers Squibb. SSS is employed by, and owns stock in, Bristol Myers Squibb. MBM is currently employed by BeiGene and owns stock in Bristol Myers Squibb. MW-R is currently employed by Agios Pharmaceuticals and owns stock in Agios Pharmaceuticals and Bristol Myers Squibb. MBM, MW-R, and PR-M were employees of Bristol Myers Squibb at the time this work was conducted.

Figures

Figure 1
Figure 1
PFS and OS by PD-L1 expression assessed by % TCs or CPS. (A) PFS with nivolumab plus ipilimumab vs sunitinib in patients with PD-L1 expression on <1% and ≥1% TCs. (B) PFS with nivolumab plus ipilimumab vs sunitinib in patients with PD-L1 CPS <1 and ≥1. (C) OS with nivolumab plus ipilimumab vs sunitinib in patients with PD-L1 expression on <1% and ≥1% TCs. (D) OS with nivolumab plus ipilimumab vs sunitinib in patients with PD-L1 CPS <1 and ≥1. CPS, combined positive score; IPI, ipilimumab; NIVO, nivolumab; NR, not reached; OS, overall survival; PD-L1, programmed death ligand 1; PFS, progression-free survival; SUN, sunitinib; TC, tumor cell.
Figure 2
Figure 2
Association of genomic biomarkers with survival. (A) Forest plot for PFS comparing high (≥median) vs low TMB, high (≥median) vs low TIB, and heterozygous vs homozygous HLA in the nivolumab plus ipilimumab and the sunitinib arms. (B) Forest plot for OS comparing high (≥median) vs low TMB, high (≥median) vs low TIB, and heterozygous vs homozygous HLA in the nivolumab plus ipilimumab and the sunitinib arms. (C) Representation of mutations found across both treatment arms in seven selected genes. (D) Forest plot of PFS by mutation status. (E) Forest plot of OS by mutation status. Forest plots show HRs and 95% CIs for given comparisons, and p values compare patient subgroups within each treatment arm. Het, heterozygous; HLA, human leukocyte antigen; Homo, homozygous; IPI, ipilimumab; MUT, mutant; NIVO, nivolumab; OS, overall survival; PFS, progression-free survival; SUN, sunitinib; TIB, tumor indel burden; TMB, tumor mutational burden; WES, whole-exome sequencing; WT, wild type.
Figure 3
Figure 3
Association of gene expression signatures and molecular subtypes with survival. (A) Association of gene expression signatures with PFS comparing high (≥median) vs low gene expression signature scores in the nivolumab plus ipilimumab and the sunitinib arms. P values compare patient subgroups within each treatment arm. (B) Association of gene expression signatures with OS comparing high vs low gene expression signature scores in the nivolumab plus ipilimumab and the sunitinib arms. P values compare patient subgroups within each treatment arm. PFS according to Angio signature score with (C) nivolumab plus ipilimumab and (D) sunitinib. OS according to Angio signature score with (E) nivolumab plus ipilimumab and (F) sunitinib. Association of Teffhigh/Myeloidlow and Teffhigh/Myeloidhigh with PFS with (G) nivolumab plus ipilimumab and (H) sunitinib. Association of Teffhigh/Myeloidlow and Teffhigh/Myeloidhigh with OS with (I) nivolumab plus ipilimumab and (J) sunitinib. Angio, angiogenesis; IPI, ipilimumab; MUT, mutant; NIVO, nivolumab; NR, not reached; OS, overall survival; PFS, progression-free survival; SUN, sunitinib; Teff, T-effector; TIS, tumor inflammation signature; WT, wild type.
Figure 4
Figure 4
Analyses of cell populations in the TME estimated in RNA-seq data. (A) HRs for the association of high (≥median) vs low cell abundance scores with PFS. P values compare patient subgroups within each treatment arm and were corrected for multiple hypothesis testing using Benjamini-Hochberg procedure. (B) HRs for the association of cell abundance scores with OS. P values compare patient subgroups within each treatment arm. (C) RNA-seq–evaluable samples grouped into five clusters (C1–C5) by unsupervised clustering. (D) Heatmap showing abundance scores for the 10 cell types in each evaluable sample. Sample annotation tracks show the MCP-counter cluster assignment and sarcomatoid status. DC, dendritic cell; IPI, ipilimumab; MCP, microenvironment cell population; NIVO, nivolumab; NK, natural killer; OS, overall survival; PC, principal component; PFS, progression-free survival; SUN, sunitinib; TME, tumor microenvironment.
Figure 5
Figure 5
HALLMARK gene sets with significant enrichment (FDR <0.05) in the transcripts associated with PFS or OS by a Cox proportional-hazards analysis. Gene sets enriched in transcripts associated with longer PFS in the (A) nivolumab plus ipilimumab or (B) sunitinib arms. Bold typeset indicates gene sets with opposing association in the two arms (ie, transcripts associated with longer PFS in patients treated with nivolumab plus ipilimumab but shorter PFS in those treated with sunitinib). Gene sets enriched in transcripts associated with longer OS in the (C) nivolumab plus ipilimumab and (D) sunitinib arms. FDR, false discovery rate; IPI, ipilimumab; NES, normalized enrichment score; NIVO, nivolumab; OS, overall survival; PFS, progression-free survival; SUN, sunitinib.
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References

    1. Motzer RJ, Tannir NM, McDermott DF, et al. . Nivolumab plus ipilimumab versus sunitinib in advanced renal-cell carcinoma. N Engl J Med 2018;378:1277–90. 10.1056/NEJMoa1712126 - DOI - PMC - PubMed
    1. Rini BI, Plimack ER, Stus V, et al. . Pembrolizumab plus axitinib versus sunitinib for advanced renal-cell carcinoma. N Engl J Med 2019;380:1116–27. 10.1056/NEJMoa1816714 - DOI - PubMed
    1. Mori K, Mostafaei H, Miura N, et al. . Systemic therapy for metastatic renal cell carcinoma in the first-line setting: a systematic review and network meta-analysis. Cancer Immunol Immunother 2021;70:265–73. 10.1007/s00262-020-02684-8 - DOI - PMC - PubMed
    1. McFarlane JJ, Kochenderfer MD, Olsen MR, et al. . Safety and efficacy of nivolumab in patients with advanced clear cell renal cell carcinoma: results from the phase IIIb/IV CheckMate 374 study. Clin Genitourin Cancer 2020;18:469–76. 10.1016/j.clgc.2020.06.002 - DOI - PubMed
    1. Choueiri TK, Motzer RJ. Systemic therapy for metastatic renal-cell carcinoma. N Engl J Med 2017;376:354–66. 10.1056/NEJMra1601333 - DOI - PubMed

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