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Oncolytic immunotherapy with nivolumab in muscle-invasive bladder cancer: a phase 1b trial

Nature Medicine volume 31, pages 176–188 (2025)Cite this article

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Abstract

There is a critical unmet need for safe and efficacious neoadjuvant treatment for cisplatin-ineligible patients with muscle-invasive bladder cancer. Here we launched a phase 1b study using the combination of intravesical cretostimogene grenadenorepvec (oncolytic serotype 5 adenovirus encoding granulocyte–macrophage colony-stimulating factor) with systemic nivolumab in cisplatin-ineligible patients with cT2-4aN0-1M0 muscle-invasive bladder cancer. The primary objective was to measure safety, and the secondary objective was to assess the anti-tumor efficacy as measured by pathologic complete response along with 1-year recurrence-free survival. No dose-limiting toxicity was encountered in 21 patients enrolled and treated. Combination treatment achieved a pathologic complete response rate of 42.1% and a 1-year recurrence-free survival rate of 70.4%. Pathologic response was associated with baseline free E2F activity and tumor mutational burden but not PD-L1 status. Although T cell infiltration was broadly induced after intravesical oncolytic immunotherapy, the formation, enlargement and maturation of tertiary lymphoid structures was specifically associated with complete response, supporting the importance of coordinated humoral and cellular immune responses. Together, these results highlight the potential of this combination regimen to enhance therapeutic efficacy in cisplatin-ineligible patients with muscle-invasive bladder cancer, warranting additional study as a neoadjuvant therapeutic option. ClinicalTrials.gov identifier: NCT04610671.

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Fig. 1: Study design and clinical response of cisplatin-ineligible MIBC treated with neoadjuvant cretostimogene and nivolumab.
Fig. 2: Exploratory biomarker analyses based on the mechanism of action of the study agents.
Fig. 3: T cell response associated with combined oncolytic virotherapy and ICIs.
Fig. 4: Combined OIT and ICI treatment induces the formation of mature TLSs.

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Data availability

All data supporting the findings of this study are available within the paper and its Supplementary Information. Additional data required, including individual de-identified participant clinical data or raw data from correlative studies, can be accessed by request. In accordance with the National Institutes of Health’s Genomic Data Sharing Policy, de-identified patient DNA/RNA sequencing data will be managed with institutional review board guidelines within an appropriate access-controlled repository. These data and other anonymized individual and/or study-level data will be available to be shared upon reasonable request after publication of this study and if regulatory activities and other criteria are met. Qualified scientific and medical researchers are eligible to request access to the data and can expect a response within 14 d, with a turnover of up to 90 d. Upon approval, and governed by a legal agreement, data can be accessed for a limited period of 1 year, which may be extended upon request. Data must not be used for commercial purposes but only for research purposes. Requests for data should be directed to the corresponding author, R.L. ([email protected]), and will be reviewed and approved by the first (R.L.) and senior (J.J.M. and J.R.C.-G.) authors, respectively.

Code availability

Any computer code or algorithm used to generate results and central to the main claims within this paper will be made available upon reasonable request per the methods detailed above.

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Acknowledgements

This study was funded by CG Oncology. The funders contributed to the study design but did not participate in data collection, analysis and interpretation. The primary investigator (R.L.) had full access to the data. Additional support for investigators include W81XWH-22-1-0395 (CA210846) (R.L.) and the Moffitt Cancer Center Schulze Award (R.L.) It is also supported, in part, by a generous donation from the Campbell Family Foundation. In addition, we thank the Analytical Microscopy lab and the Advanced Analytical and Digital lab as well as the Quantitative Imaging, Molecular Genomics Tissue and Pathology, Biostatistics and Bioinformatics cores at H. Lee Moffitt Cancer Center for providing support. We also thank the patients and their families for participating in this clinical trial.

Author information

Author notes

  1. These authors contributed equally: James J. Mulé, Jose R. Conejo-Garcia.

Authors and Affiliations

  1. Department of Genitourinary Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    Roger Li, Nancy Y. Villa, Denise Dorman, Wade J. Sexton, Philippe E. Spiess, Michael A. Poch, Logan Zemp, Scott M. Gilbert, Jingsong Zhang, Julio M. Pow-Sang & Rohit K. Jain

  2. Department of Immunology, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    Roger Li, Nancy Y. Villa, Gustavo Borjas, John J. Powers, Paulo C. Rodriguez, James J. Mulé & Jose R. Conejo-Garcia

  3. Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    Xiaoqing Yu, Youngchul Kim, Tingyi Li & Xuefeng Wang

  4. Analytic Microscopy Core, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    Joseph O. Johnson

  5. Department of Pathology, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    Jasreman Dhillon

  6. Advanced Analytical and Digital Laboratory, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    Carlos M. Moran-Segura

  7. Tissue Core, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    Natasha Francis

  8. Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    Alexander R. A. Anderson

  9. Department of Radiation Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA

    G. Daniel Grass

  10. Big Horn Basin Cancer Center, Cody, WY, USA

    James M. Burke

  11. Department of Urology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Colin P. N. Dinney

  12. Department of Integrative Immunobiology, Duke School of Medicine, Durham, NC, USA

    Jose R. Conejo-Garcia

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  1. Roger Li
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  2. Nancy Y. Villa
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  3. Xiaoqing Yu
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  13. Philippe E. Spiess
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  15. Logan Zemp
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  16. Scott M. Gilbert
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  19. Alexander R. A. Anderson
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  20. Tingyi Li
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  21. Xuefeng Wang
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  22. G. Daniel Grass
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  23. James M. Burke
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  24. Colin P. N. Dinney
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  25. Paulo C. Rodriguez
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  26. Rohit K. Jain
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  27. James J. Mulé
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  28. Jose R. Conejo-Garcia
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R.L.: conceptualization, formal analysis, supervision, investigation, original writing and writing—review and editing. N.Y.V.: formal analysis, investigations and writing—review and editing. X.Y.: formal analysis, investigations and writing—review and editing. J.O.J.: formal analysis and writing—review and editing. G.B.: investigations and writing—review and editing. J.D.: investigations and writing—review and editing. C.M.M.-S.: investigations and writing—review and editing. Y.K.: formal analysis and writing—review and editing. N.F.: investigations. D.D.: investigations. J.J.P.: investigations. W.J.S.: investigations and writing—review and editing. P.E.S.: investigations and writing—review and editing. M.A.P.: investigations and writing—review and editing. L.Z.: investigations and writing—review and editing. S.M.G.: investigations and writing—review and editing. J.Z.: conceptualization and writing—review and editing. J.M.P.-S.: conceptualization and writing—review and editing. A.R.A.A.: formal analysis and writing—review and editing. T.L.: formal analysis and writing—review and editing. X.W.: formal analysis and writing—review and editing. G.D.G.: writing—review and editing. J.M.B.: conceptualization and writing—review and editing. C.P.N.D.: conceptualization, formal analysis and writing—review and editing. P.C.R.: formal analysis and writing—review and editing. R.K.J.: conceptualization, investigations and writing—review and editing. J.J.M.: conceptualization, formal analysis, supervision, formal analysis and writing—review and editing. J.R.C.-G.: conceptualization, formal analysis, supervision, investigations, formal analysis and writing—review and editing.

Corresponding author

Correspondence to Roger Li.

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Competing interests

R.L. reports research support from Predicine, Veracyte, CG Oncology, Valar Labs, Merck and Janssen; clinical trial protocol committee participation with CG Oncology, Merck and Janssen; and is scientific advisor/consultant for Bristol Myers Quibb, Merck, Fergene, Arquer Diagnostics, Urogen Pharma, Lucence, CG Oncology, Janssen, Thericon, Iconovir, ImmunityBio and Pfizer. W.J.S. reports consultant work for Pacific Edge and Urogen Pharma. P.E.S. reports being the Vice Chair of the NCCN guidelines committee for bladder and penile cancer. J.Z. reports consultant work for Sanofi, AstraZeneca, Dendreon, Seagen, Bayer and Pfizer. G.D.G. reports consultant work for MyCareGorithm and stock options in Lantheus. J.M.B. reports consultant work for CG Oncology and Kalivir Immunotherapeutics and being a shareholder of CG Oncology and Kalivir Immunotherapeutics. C.P.N.D. reports consultant work for AstraZeneca and CG Oncology and intellectual property ownership related to the use of genetic alterations as a predictive biomarker for response to nadofaragene firadenovec. R.K.J. reports consultant work for AVEO, Bristol Myers Squibb, Sanofi, EMD Serono, Gilead Sciences, IDEOlogy Pfizer and Seattle Genetics/Astellas; speaker’s bureau for Gilead Sciences, Seagen and Seattle Genetics/Astellas; research funding from Bristol Myers Squibb, Gilead Sciences and the National Cancer Institute; and honoraria from FLASCO, Curio Science, DAVA Oncology, NCCN/Pfizer and OncLive/MJH Life Sciences. J.J.M. reports membership on the CG Oncology Board of Directors; being the Associate Center Director at Moffitt Cancer Center; ownership interest in Aleta Biotherapeutics, CG Oncology, Turnstone Biologics, Ankyra Therapeutics and AffyImmune Therapeutics; and consultant work for ONCoPEP, CG Oncology, Turnstone Biologics, Vault Pharma, Ankyra Therapeutics, AffyImmune Therapeutics, UbiVac, Vycellix and Aleta Biotherapeutics. J.R.C.-G. reports consultant work for Anixa Biosciences and Alloy Therapeutics; stock options in Compass Therapeutics, Anixa Biosciences and Alloy Therapeutics; patent licensed by Anixa Biosciences; intellectual property filed with Compass Therapeutics; and being the co-founder of Cellepus Therapeutics, a CAR T cell company. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Increases in viral replication is not associated with tumor intrinsic molecular features.

Fold change in GM-CSF, used as a surrogate marker for viral replication, was associated with neither baseline E2F target expression levels (n = 18; Pearson correlation R2 = 0.019; p = 0.58) (a), nor with molecular subtypes (n = 17; p = 0.228) (b).

Extended Data Fig. 2 Increase in T lymphocyte infiltration is not associated with baseline tumor/immune features nor treatment response.

Fold changes in infiltrating T lymphocyte levels were not associated with baseline tumor mutational burden (n = 19; CD3+ p = 0.33; CD4+ p = 0.23; CD8+ p = 0.81) (a); pre-treatment CD3+ lymphocytic infiltration (n = 19; CD3+ p = 0.27; CD4+ p = 0.44; CD8+ p = 0.43) (b); baseline tumor molecular subtypes (n = 17; CD3+ p = 0.11; CD4+ p = 0.305; CD8+ p = 0.16) (c); nor with treatment response (n = 19; CD3+ p = 0.97; CD4+ p = 0.9; CD8+ p = 0.5) (d). For dot-plots in a-c, correlation coefficients and P values were calculated using Pearson Correlation. For boxplots in d, boxes represent median (center) and first/third quartile (bottom and top, respectively) values; Tukey whiskers represent the ± 1.5 interquartile range (IQR); individual data points are shown in dots; Two-sided P values were calculated by Wilcoxon’s signed-rank test.

Extended Data Fig. 3 Phenotypic changes in T cell markers from pre- to post-treatment.

a, Gene expression levels of PDCD1 (PD-1), TNFRSF4 (b); LAG3 (c); and HAVCR2 (TIM3) (d) on bulk RNA sequencing were not different from pre- to post-treatment in pathologic complete responders vs. non-responders. Two-sided P values were calculated by Wilcoxon signed-rank test. Boxes represent median (center) and first/third quartile (bottom and top, respectively) values; Tukey whiskers represent the ± 1.5 interquartile range (IQR); individual data points are shown in dots colored by CR (blue) or NR (gray).

Extended Data Fig. 4 Enzyme-linked immunosorbent spot (ELISpot) analysis indicates heightened cell-mediated anti-tumor systemic reactivity in patients with pathologic complete response.

a, Representative plots showing fold changes in interferon-γ (IFN-γ) spot-forming units at weeks 2 and/or 6 compared to baseline in clinical responders and b, clinical non-responders. Significance increases were seen at the following timepoints in the following patients: Due to sample limitations, co-culture using neopeptide-primed monocyte-derived DCs with autologous T cells from each patient at each time point was conducted once without replicates.

Extended Data Fig. 5 No change was found in the tertiary lymphoid structure (TLS) density from pre- to post-treatment in non-responding patients following treatment.

a, Representative whole slide multiplex immunofluorescence images from a patient who did not respond to treatment, demonstrating lack of increase of TLS in the post-treatment samples. b, TLS density at baseline did not predict pathologic response to combined oncolytic immunotherapy and immune checkpoint inhibitor (n = 16; p = 0.594). Two-sided p values were calculated by Wilcoxon’s signed-rank test. Boxes represent median (center) and first/third quartile (bottom and top, respectively) values; Tukey whiskers represent the ± 1.5 interquartile range (IQR); individual data points are shown in dots colored by the response (responder = blue; non-responder = gray).

Extended Data Fig. 6 Features of mature vs. immature tertiary lymphoid structure (TLS).

a, TLS were scored according to morphological features on multiplex immunofluorescence. Immature TLS consisted of general clustering of CD20 + B cells with unclear shape and structure. Mature TLS consisted of large, oval or circular shaped conglomeration of CD20 + B cells. As expected, mature TLS were marked by higher surface areas (***p < 0.001) (b) and cellular density (**p = 0.00652) (c). Two-sided p values were calculated by Wilcoxon’s signed-rank test. Boxes represent median (center) and first/third quartile (bottom and top, respectively) values; Tukey whiskers represent the ± 1.5 interquartile range (IQR).

Extended Data Fig. 7 Heightened antibody response post-treatment is directed against tumor cells.

Of all pathologic complete responders, one patient exhibited downstaging of disease (cTis) on the post-treatment biopsy prior to attaining pathologic complete response at the time of radical cystectomy. On multiplex immunofluorescence staining of the post-treatment biopsy specimen, IgG was observed to coat tumor cells, suggesting specific anti-tumor humoral response.

Supplementary information

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Supplemental Tables 1–3 and study protocol.

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Li, R., Villa, N.Y., Yu, X. et al. Oncolytic immunotherapy with nivolumab in muscle-invasive bladder cancer: a phase 1b trial. Nat Med 31, 176–188 (2025). https://doi.org/10.1038/s41591-024-03324-9

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