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Neoadjuvant enoblituzumab in localized prostate cancer: a single-arm, phase 2 trial

Nature Medicine volume 29, pages 888–897 (2023)Cite this article

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Abstract

B7 homolog 3 (B7-H3; CD276), a tumor-associated antigen and possible immune checkpoint, is highly expressed in prostate cancer (PCa) and is associated with early recurrence and metastasis. Enoblituzumab is a humanized, Fc-engineered, B7-H3-targeting antibody that mediates antibody-dependent cellular cytotoxicity. In this phase 2, biomarker-rich neoadjuvant trial, 32 biological males with operable intermediate to high-risk localized PCa were enrolled to evaluate the safety, anti-tumor activity and immunogenicity of enoblituzumab when given before prostatectomy. The coprimary outcomes were safety and undetectable prostate-specific antigen (PSA) level (PSA0) 1 year postprostatectomy, and the aim was to obtain an estimate of PSA0 with reasonable precision. The primary safety endpoint was met with no notable unexpected surgical or medical complications, or surgical delay. Overall, 12% of patients experienced grade 3 adverse events and no grade 4 events occurred. The coprimary endpoint of the PSA0 rate 1 year postprostatectomy was 66% (95% confidence interval 47–81%). The use of B7-H3–targeted immunotherapy in PCa is feasible and generally safe and preliminary data suggest potential clinical activity. The present study validates B7-H3 as a rational target for therapy development in PCa with larger studies planned. The ClinicalTrials.gov identifier is NCT02923180.

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Fig. 1: Patient consort diagram and efficacy outcomes in the neoadjuvant treatment of patients with PCa using enoblituzumab.
Fig. 2: TCR repertoire dynamics in peripheral blood and tumor, and association with anti-tumor response.
Fig. 3: Digital spatial profiling of the TME in pretreatment biopsies and posttreatment prostatectomies stratified by clinical outcomes.
Fig. 4: Changes in circulating cytokines, chemokines and soluble protein levels from baseline to preprostatectomy (D50).

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Data availability

TRV-β-seq of tumor and peripheral T cells, as the project ‘Neoadjuvant B7H3 Trial in Prostate Cancer’, is available in the immuneACCESS free public database at https://clients.adaptivebiotech.com/immuneaccess. The authors deferred trial participant raw genomic data deposition to national or international public repositories to avoid compromising privacy of the research participants. A summary of patient whole-exome sequence alterations of clinical significance is provided in Supplementary Data Table 4. Aggregate patient-related information has been made available on ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/results/NCT02923180). Additional requests for raw and analyzed data can be referred to the corresponding author (E.S.) and will be reviewed promptly as part of a data transfer agreement per Johns Hopkins’ institutional policies, to determine whether the request is subject to any clinical trial patient confidentiality or intellectual property requirements. Source data are provided with this paper.

References

  1. Siegel, R. L., Miller, K. D., Fuchs, H. E. & Jemal, A. Cancer statistics, 2022. CA: A Cancer J. Clinicians 72, 7–33 (2022).

    Google Scholar 

  2. Shilkrut, M., McLaughlin, P. W., Merrick, G. S., Vainshtein, J. M. & Hamstra, D. A. Treatment outcomes in very high-risk prostate cancer treated by dose-escalated and combined-modality radiation therapy. Am. J. Clin. Oncol. 39, 181–188 (2016).

    Article  CAS  PubMed  Google Scholar 

  3. Sundi, D. et al. Outcomes of very high-risk prostate cancer after radical prostatectomy: validation study from 3 centers. Cancer 125, 391–397 (2019).

    Article  CAS  PubMed  Google Scholar 

  4. Antonarakis, E. S. et al. The natural history of metastatic progression in men with prostate-specific antigen recurrence after radical prostatectomy: long-term follow-up. BJU Int. 109, 32–39 (2012).

    Article  CAS  PubMed  Google Scholar 

  5. Le, D. T. et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science 357, 409–413 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Hodi, F. S. et al. Improved survival with ipilimumab in patients with metastatic melanoma. N. Engl. J. Med. 363, 711–723 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Kantoff, P. W. et al. Sipuleucel-T immunotherapy for castration-resistant prostate cancer. N. Engl. J. Med. 363, 411–422 (2010).

    Article  CAS  PubMed  Google Scholar 

  8. Kwon, E. D. et al. Ipilimumab versus placebo after radiotherapy in patients with metastatic castration-resistant prostate cancer that had progressed after docetaxel chemotherapy (CA184-043): a multicentre, randomised, double-blind, phase 3 trial. Lancet Oncol. 15, 700–712 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Shenderov, E. et al. Nivolumab plus ipilimumab, with or without enzalutamide, in AR-V7-expressing metastatic castration-resistant prostate cancer: a phase-2 nonrandomized clinical trial. Prostate 81, 326–338 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Sharma, P. et al. Nivolumab plus ipilimumab for metastatic castration-resistant prostate cancer: preliminary analysis of patients in the checkMate 650 trial. Cancer Cell 38, 489–499.e483 (2020).

    Article  CAS  PubMed  Google Scholar 

  11. Chapoval, A. I. et al. B7-H3: a costimulatory molecule for T cell activation and IFN-gamma production. Nat. Immunol. 2, 269–274 (2001).

    Article  CAS  PubMed  Google Scholar 

  12. Benzon, B. et al. Correlation of B7-H3 with androgen receptor, immune pathways and poor outcome in prostate cancer: an expression-based analysis. Prostate Cancer Prostatic Dis. 20, 28–35 (2017).

    Article  CAS  PubMed  Google Scholar 

  13. Loo, D. et al. Development of an Fc-enhanced anti-B7-H3 monoclonal antibody with potent antitumor activity. Clin. Cancer Res. 18, 3834–3845 (2012).

    Article  CAS  PubMed  Google Scholar 

  14. Musolino, A. et al. Immunoglobulin G fragment C receptor polymorphisms and clinical efficacy of trastuzumab-based therapy in patients with HER-2/neu-positive metastatic breast cancer. J. Clin. Oncol. 26, 1789–1796 (2008).

    Article  CAS  PubMed  Google Scholar 

  15. Obradovic, A. Z. et al. T-cell infiltration and adaptive treg resistance in response to androgen deprivation with or without vaccination in localized prostate cancer. Clin. Cancer Res. 26, 3182–3192 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Fong, L. et al. Activated lymphocyte recruitment into the tumor microenvironment following preoperative sipuleucel-T for localized prostate cancer. J. Natl Cancer Inst. 106, dju268 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Clynes, R. A., Towers, T. L., Presta, L. G. & Ravetch, J. V. Inhibitory Fc receptors modulate in vivo cytoxicity against tumor targets. Nat. Med. 6, 443–446 (2000).

    Article  CAS  PubMed  Google Scholar 

  18. Tobinai, K., Klein, C., Oya, N. & Fingerle-Rowson, G. A review of obinutuzumab (GA101), a novel type II anti-CD20 monoclonal antibody, for the treatment of patients with B-cell malignancies. Adv. Ther. 34, 324–356 (2017).

    Article  CAS  PubMed  Google Scholar 

  19. Lee, Y. H. et al. Inhibition of the B7-H3 immune checkpoint limits tumor growth by enhancing cytotoxic lymphocyte function. Cell Res. 27, 1034–1045 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Yonesaka, K. et al. B7-H3 negatively modulates CTL-mediated cancer immunity. Clin. Cancer Res. 24, 2653–2664 (2018).

    Article  CAS  PubMed  Google Scholar 

  21. Mendes, A. A. et al. Association of B7-H3 expression with racial ancestry, immune cell density, and androgen receptor activation in prostate cancer. Cancer 128, 2269–2280 (2022).

    Article  CAS  PubMed  Google Scholar 

  22. Hogan, S. A. et al. Peripheral blood TCR repertoire profiling may facilitate patient stratification for immunotherapy against melanoma. Cancer Immunol. Res. 7, 77–85 (2019).

    Article  CAS  PubMed  Google Scholar 

  23. Han, J. et al. TCR repertoire diversity of peripheral PD-1+CD8+ T cells predicts clinical outcomes after immunotherapy in patients with non–small cell lung cancer. Cancer Immunol. Res. 8, 146–154 (2020).

    Article  CAS  PubMed  Google Scholar 

  24. Thorsson, V. et al. The immune landscape of cancer. Immunity 48, 812–830.e814 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Haffner, M. C. et al. Comprehensive evaluation of programmed death-ligand 1 expression in primary and metastatic prostate cancer. Am. J. Pathol. 188, 1478–1485 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Antonarakis, E. S. et al. Pembrolizumab for treatment-refractory metastatic castration-resistant prostate cancer: multicohort, open-label phase II KEYNOTE-199 study. J. Clin. Oncol. 38, 395–405 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Graff, J. N. et al. A phase II single-arm study of pembrolizumab with enzalutamide in men with metastatic castration-resistant prostate cancer progressing on enzalutamide alone. J. Immunother. Cancer 8, e000642 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Mengus, C. et al. Elevated levels of circulating IL-7 and IL-15 in patients with early stage prostate cancer. J. Transl. Med. 9, 162 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Dorff, T. B. et al. Clinical and correlative results of SWOG S0354: a phase II trial of CNTO328 (siltuximab), a monoclonal antibody against interleukin-6, in chemotherapy-pretreated patients with castration-resistant prostate cancer. Clin. Cancer Res. 16, 3028–3034 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Waldmann, T. A. Cytokines in cancer immunotherapy. Cold Spring Harb. Perspect. Biol. 10, a028472 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Vigne, S. et al. IL-36 signaling amplifies Th1 responses by enhancing proliferation and Th1 polarization of naive CD4+ T cells. Blood 120, 3478–3487 (2012).

    Article  CAS  PubMed  Google Scholar 

  32. Williams, J. B. et al. The EGR2 targets LAG-3 and 4-1BB describe and regulate dysfunctional antigen-specific CD8+ T cells in the tumor microenvironment. J. Exp. Med. 214, 381–400 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Glez-Vaz, J. et al. Soluble CD137 as a dynamic biomarker to monitor agonist CD137 immunotherapies. J. Immunother. Cancer 10, e003532 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Landrum, M. J. et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 44, D862–D868 (2016).

    Article  CAS  PubMed  Google Scholar 

  35. Robins, H. S. et al. Comprehensive assessment of T-cell receptor beta-chain diversity in alphabeta T cells. Blood 114, 4099–4107 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Carlson, C. S. et al. Using synthetic templates to design an unbiased multiplex PCR assay. Nat. Commun. 4, 2680 (2013).

    Article  PubMed  Google Scholar 

  37. DeWitt, W. S. et al. Dynamics of the cytotoxic T cell response to a model of acute viral infection. J. Virol. 89, 4517–4526 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Merritt, C. R. et al. Multiplex digital spatial profiling of proteins and RNA in fixed tissue. Nat. Biotechnol. 38, 586–599 (2020).

    Article  CAS  PubMed  Google Scholar 

  39. Jeong, J. S. et al. Rapid Identification of monospecific monoclonal antibodies using a human proteome microarray*. Mol. Cell. Proteom. 11, O111.016253 (2012).

    Article  Google Scholar 

Download references

Acknowledgements

We thank patients and their families for participation in this ClinicalTrials.gov-registered clinical trial (NCT02923180). This investigator-initiated trial at Johns Hopkins was funded by MacroGenics, Inc. which also provided study drug free of cost. The sponsor was involved in data collection and analysis, but was not involved in study design, decision to publish or preparation of the manuscript. The authors retain full responsibility for the content. This work was partially supported by the National Institutes of Health Cancer Center Support (grant no. P30 CA006973 to E.S., E.S.A. and A.M.D.M.); NCI SPORE in Prostate Cancer (grant/award no. P50CA58236 to A.M.D.M.); Prostate Cancer Foundation Young Investigator Award (to E.S.); Department of Defense grant (nos. W81XWH-16-PCRP-CCRSA and W81XWH-19-1-0511 to E.S., and W81XWH ‐18‐2‐0015 to A.M.D.M.); and the Bloomberg–Kimmel Institute for Cancer Immunotherapy (E.S., D.M.P. and E.S.A.). We thank M. Caldwell for his assistance with the Tempus xE assay bioinformatics pipeline preparation.

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Author notes

  1. Emmanuel S. Antonarakis

    Present address: University of Minnesota Masonic Cancer Center, Minneapolis, MN, USA

Authors and Affiliations

  1. Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Eugene Shenderov, Angelo M. De Marzo, Tamara L. Lotan, Sin Chan, Carolyn Chapman, Samuel R. Denmeade, Kenneth J. Pienta, Drew M. Pardoll & Emmanuel S. Antonarakis

  2. The Bloomberg–Kimmel Institute for Cancer Immunotherapy, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Eugene Shenderov, Drew M. Pardoll & Emmanuel S. Antonarakis

  3. Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Angelo M. De Marzo & Tamara L. Lotan

  4. Department of Urology, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Angelo M. De Marzo, Tamara L. Lotan, Mohamad E. Allaf & Christian P. Pavlovich

  5. Department of Oncology Biostatistics and Bioinformatics, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Hao Wang & Su Jin Lim

  6. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Hongkai Ji

  7. MacroGenics, Inc., Rockville, MD, USA

    Paul A. Moore & Francine Chen

  8. NanoString Technologies Inc., Seattle, WA, USA

    Kristina Sorg, Andrew M. White, Sarah E. Church & Briana Hudson

  9. Adaptive Biotechnologies, Seattle, WA, USA

    Paul A. Fields

  10. CDI Labs, Baltimore, MD, USA

    Shaohui Hu

  11. Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

    Ashley E. Ross

  12. Immuno-Oncology, Janssen, Horsham, PA, USA

    Charles G. Drake

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Contributions

E.S., E.S.A., D.M.P., C.G.D. and A.E.R. conceived and designed the study. E.S.A., D.P. and C.G.D. supervised the study. E.S., M.E.A., C.C., S.R.D., K.J.P. and C.P.P. recruited and coordinated the participants. E.S., A.M.D.M., T.L.L., C.C., P.M., H.W., S.C., S.J.L., H.J., F.C., K.S., A.M.W., S.E.C., B.H., P.F., S.H. and E.S.A. collected, processed and analyzed the data. E.S. and E.S.A. prepared the manuscript, with all the authors contributing to its review and editing.

Corresponding author

Correspondence to Eugene Shenderov.

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Competing interests

E.S. is a paid consultant to GT Biopharma, Guidepoint Global, FirstThought and GLG, and receives institutional research funding from MacroGenics, Inc. E.S.A. is a paid consultant/advisor to and/or received institutional research funding from Janssen, Astellas, Sanofi, Dendreon, Genentech, Pfizer, Amgen, Lilly, Bayer, Tokai, Clovis, AstraZeneca, Novartis and BMS; and patent and royalty rights from QIAGEN for AR-V7 in prostate cancer. P.M. and F.C. are employees of MacroGenics, Inc. and receive stock options. K.S., A.M.W., S.E.C. and B.H. are employees of NanoString Technologies Inc. and receive stock options. P.F. is an employee of Adaptive Biotechnologies and receives stock options. S.H. is an employee of CDI Labs and receives stock options. C.G.D. is an employee of Janssen and receives stock options. A.M.D.M. is a paid consultant to Merck and Cepheid and received institutional research funding from Janssen. The remaining authors report no competing interests.

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Extended data

Extended Data Fig. 1 Clinical trial flow chart showing biospecimen collection time schema.

Created with BioRender.com.

Extended Data Fig. 2 B7-H3 Expression vs. Enoblituzumab Drug Distribution in post-enoblituzumab treated prostatectomy tissue.

a, Two illustrative patients. Small malignant glands (M) showed obvious membrane staining by both SP206 anti-B7-H3 and anti-enoblituzumab antibody IHC staining. However, the adjacent non-malignant ducts (NM) showed relative negative membrane staining for both test articles. b, Frequency table of enoblituzumab positive or negative staining on post-enoblituzumab treated prostatectomy frozen sections, as well as SP206 anti-B7-H3 H-score on adjacent treated prostatectomy frozen sections. Image acquired using 20× magnification.

Extended Data Fig. 3 B7-H3 Expression vs. Enoblituzumab Drug Distribution in post-enoblituzumab treated prostatectomy tissue.

Orange bars show enoblituzumab treated patients and gray bars show untreated control 1:1 matched prostatectomies from patients matched by grade group, stage, margins, block age [within 2 years], age [within 2 years], and self-reported race. No bar shown if no change in Gleason between biopsy and prostatectomy.

Extended Data Fig. 4 TCR repertoire characterization in peripheral blood and tumor by PSA0 at 1-year.

(a, b) Total T-cells expanded in tumor (a) or peripheral blood at prostatectomy (b, D50) versus fraction of peripheral clones expanded and detected intratumorally. (c, d) Total unique T-cell clonotypes expanded in tumor (c) or peripheral blood at prostatectomy (d, D50) versus fraction of peripheral clones expanded and detected intratumorally. Each point on the scatter plots represents a patient. Blue dots indicate responders for a given outcome and red dots indicate non-responders.

Extended Data Fig. 5 Volcano plot of tumor region mRNA expression changes of matched untreated control prostatectomies versus post-treatment prostatectomies by Nanostring PanCancer IO 360 analysis.

Genes that remained significant after Benjamini and Yekutieli False Discovery Rate (FDR, adjusted p < 0.01) are in blue and labeled. Matched 1:1 untreated controls by grade group, stage, margins, block age [within 2 years], age [within 2 years], and self-reported race. Tumor regions isolated by macrodissection.

Source data

Extended Data Fig. 6 Grouped boxplots of difference in mean log2 marker level of upregulated proteins by clinical outcome using DSP of the TME in pretreatment biopsies and post-treatment prostatectomies following B7-H3 monoclonal antibody treatment.

a, protein marker status by PSA response (PSA < 0.1 ng/mL) at 12 months after prostatectomy versus PSA recurrence. Protein expression was assessed in n = 27 tissue samples from n = 32 patients (n = 18 responders and n = 9 non-responders). b, protein marker status by Gleason grade group change from biopsy to prostatectomy. Protein expression was assessed in n = 27 tissue samples from n = 32 patients (n = 14 decline in Gleason and n = 13 no decline in Gleason). Median (IQR) data is presented and whiskers indicate the minimum and maximum values.

Extended Data Fig. 7 Treatment-induced antibody reactivity assessment.

a, A HuProt array probed with a representative patient serum (baseline, D1) and detected with anti-human IgG (red) and anti-human IgM (green) secondary antibodies. Each protein is printed in duplicate diagonally. b, Serum samples of the representative patient collected immediately prior to prostatectomy (D50) and 30-days post-prostatectomy (P30) showed significantly higher IgG signals than baseline (D1) on C1R. c, The mean C1R IgG signals of all 32 patients at D50 and P30 are significantly higher than D1 (p < 0.05). The mean PRB1 IgM signal of all 32 patients at P30 is significantly higher than D1 (p < 0.05). Two-sided, unpaired, student t-test utilized and standard deviation bars shown.

Extended Data Fig. 8 Univariate and multivariate analysis of lower tertile versus upper 2 tertiles of serum biomarker alterations by Gleason grade group decline ≥2 or by PSA0 response at 1 year.

Serum biomarkers assessed in n = 64 blood samples from n = 32 patients. (a-c) By Gleason grade group decline ≥2: (a) Gleason grade group ≥ 2 decline by biomarker and percentile. (b) Unadjusted hazard ratio and 95% confidence interval shown for each biomarker. (c) Adjusted hazard ratio and 95% confidence interval by age. (d-f) By PSA0 response at 1 year: (d) PSA0 responders at 1 year by biomarker and percentile. (e) Unadjusted hazard ratio and 95% confidence interval shown for each biomarker. (f) Adjusted hazard ratio and 95% confidence interval by age.

Extended Data Fig. 9 Kaplan-Meier curves for PSA recurrence-free survival by mutation status post radical prostatectomy.

(a) SPOP/FOXA1 mutation: the median survival was 10.2 months (95% CI: [3.1, NA]) for the SPOP/FOXA1 mutation group, but it was not reached for the other group, NR months (95% CI: [NR, NR]). The HR of PSA recurrence-free survival for the SPOP/FOXA1 mutation group compared with the other group is 2.48 (0.65–9.44, p = 0.181). (b) PTEN/TP53/RB1 inactivation: the median survival was 7.4 months (95% CI: [6, NR]) for the PTEN/TP53/RB1 inactivation group, but it was not reached for the other group, NR months (95% CI: [32.7, NR]). The HR of PSA recurrence-free survival for the PTEN/TP53/RB1 inactivation group compared with the other group is 1.97 (0.57–6.76, p = 0.281). (c) HRR gene inactivation: median survival was not reached for both groups, NR months (95% CI: [9.6, NR]) for the HRR gene inactivation group and NR months (95% CI: [32.7, NR]) for the other group. The HR of PSA recurrence-free survival for the HRR gene inactivation group compared with the other group is 1.08 (0.23–5.01, p = 0.921). (d) KMT2D/ARID2D inactivation: median survival was not reached for both groups, NR months (95% CI: [10.2, NR]) for the KMT2D/ARID2D inactivation group and NR months (95% CI: [NR, NR]) for the other group. The HR of PSA recurrence-free survival for the KMT2D/ARID2D inactivation group compared with the other group is 3.01 (0.38–23.51, p = 0.294). (e) TMB below or above median: median survival was not reached for both groups, NR months (95% CI: [10.2, NA]) for the TMB 5 mutations/Mb group and NR months (95% CI: [32.7, NR]) for the TMB < 0.5 mutations/Mb group. The HR of PSA recurrence-free survival for the TMB 5 ng/ml group compared with the TMB < 0.5 mutations/Mb group is 1.01 (0.31–3.30, p = 0.990).

Extended Data Table 1 Pathology outcomes post-treatment
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Supplementary information

Supplementary Information

Supplementary Information.

Reporting Summary

Supplementary Table

Study protocol and statistical analysis plan.

Source data

Source Data Fig. 3

Nanostring DSP-normalized data.

Source Data Extended Data Fig. 5

Nanostring IO360 mRNA expression-normalized data.

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Shenderov, E., De Marzo, A.M., Lotan, T.L. et al. Neoadjuvant enoblituzumab in localized prostate cancer: a single-arm, phase 2 trial. Nat Med 29, 888–897 (2023). https://doi.org/10.1038/s41591-023-02284-w

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