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Neoadjuvant gemcitabine–cisplatin plus tislelizumab in persons with resectable muscle-invasive bladder cancer: a multicenter, single-arm, phase 2 trial

Nature Cancer volume 5, pages 1465–1478 (2024)Cite this article

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Abstract

Programmed death 1 blockade (tislelizumab) has been approved for metastatic urothelial carcinoma but not as part of neoadjuvant therapy for muscle-invasive bladder cancer (MIBC). In this multicenter single-arm trial (ChiCTR2000037670), 65 participants with cT2-4aN0M0 MIBC received neoadjuvant gemcitabine–cisplatin plus tislelizumab; 57 of them underwent radical cystectomy (RC). The primary endpoint of pathologic complete response (pCR) rate was 50.9% (29/57, 95% confidence interval (CI) 37.3–64.4%) and the pathologic downstaging (secondary endpoint) rate was 75.4% (43/57, 95% CI 62.2–85.9%) in participants undergoing RC. Genomic and transcriptomic analyses revealed three MIBC molecular subtypes (S): S1 (immune-desert) with activated cell-cycle pathway, S2 (immune-excluded) with activated transforming growth factor-β pathway and S3 (immune-inflamed) with upregulated interferon-α and interferon-γ response. Post hoc analysis showed pCR rates of 16% (3/19, S1), 77% (10/13, S2) and 80% (12/15, S3) (P = 0.006). In conclusion, neoadjuvant gemcitabine–cisplatin plus tislelizumab for MIBC was compatible with an enhanced pCR rate.

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Fig. 1: Kaplan–Meier curves of EFS, OS and RFS.
Fig. 2: Somatic mutations and copy number variations in pretreatment tumors from participants with pCR versus non-pCR.
Fig. 3: Molecular characteristics and immune profiles in pretreatment tumors from participants with pCR versus non-pCR.
Fig. 4: MIBC subtypes in pretreatment tumors.
Fig. 5: Comparison of paired pretreatment and posttreatment tumors.
Fig. 6: Summarized characteristics of three MIBC subtypes.

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Data availability

RNA and DNA sequencing data that support the findings of this study were deposited to the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation and Beijing Institute of Genomics, Chinese Academy of Sciences under accession code HRA006086. The dataset derived from this resource that supports the findings of this study is available at https://bigd.big.ac.cn/gsa-human/browse/HRA006086. RNA and DNA sequencing data generated for this study are subjected to the regulations by the Ministry of Science and Technology of the People’s Republic of China. The hg19 human genome can be found at https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000001405.13/. All other data supporting the findings of this study are available from T.L. (lintx@mail.sysu.edu.cn) or K.L. (likw6@mail.sysu.edu.cn) on reasonable request. Individual deidentified participant data (including data dictionaries, text and tables) that underlie the results reported in this article will be eligible for data sharing requests after January 1, 2027. The study protocol can be found in the Supplementary Information. Researchers should send methodologically sound proposals directly to T.L. (lintx@mail.sysu.edu.cn) or K.L. (likw6@mail.sysu.edu.cn) for data requests. The reuse of the individual participant data is permitted only for revalidation of the results or for meta-analysis. Source data are provided with this paper.

Code availability

All relevant package and software information is provided in the Methods. No custom code was generated in the course of this study.

References

  1. Kamat, A. M. et al. Bladder cancer. Lancet 388, 2796–2810 (2016).

    Article  PubMed  Google Scholar 

  2. Alfred Witjes, J. et al. European association of urology guidelines on muscle-invasive and metastatic bladder cancer: summary of the 2023 guidelines. Eur. Urol. 85, 17–31 (2024).

    Article  CAS  PubMed  Google Scholar 

  3. Flaig, T. W. et al. A randomized phase II study of coexpression extrapolation (COXEN) with neoadjuvant chemotherapy for bladder cancer (SWOG S1314; NCT02177695). Clin. Cancer Res. 27, 2435–2441 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Zargar, H. et al. Multicenter assessment of neoadjuvant chemotherapy for muscle-invasive bladder cancer. Eur. Urol. 67, 241–249 (2015).

    Article  PubMed  Google Scholar 

  5. Iyer, G. et al. Neoadjuvant gemcitabine–cisplatin plus radical cystectomy–pelvic lymph node dissection for muscle-invasive bladder cancer: a 12-year experience. Clin. Genitourin. Cancer 18, 387–394 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Powles, T. et al. Clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial. Nat. Med. 25, 1706–1714 (2019).

    Article  CAS  PubMed  Google Scholar 

  7. Necchi, A. et al. Pembrolizumab as neoadjuvant therapy before radical cystectomy in patients with muscle-invasive urothelial bladder carcinoma (PURE-01): an open-label, single-arm, phase II study. J. Clin. Oncol. 36, 3353–3360 (2018).

    Article  CAS  PubMed  Google Scholar 

  8. de Biasi, A. R., Villena-Vargas, J. & Adusumilli, P. S. Cisplatin-induced antitumor immunomodulation: a review of preclinical and clinical evidence. Clin. Cancer Res. 20, 5384–5391 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Rose, T. L. et al. Phase II study of gemcitabine and split-dose cisplatin plus pembrolizumab as neoadjuvant therapy before radical cystectomy in patients with muscle-invasive bladder cancer. J. Clin. Oncol. 39, 3140–3148 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Funt, S. A. et al. Neoadjuvant atezolizumab with gemcitabine and cisplatin in patients with muscle-invasive bladder cancer: a multicenter, single-arm, phase II trial. J. Clin. Oncol. 40, 1312–1322 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Zhang, T. et al. The binding of an anti-PD-1 antibody to FcγRΙ has a profound impact on its biological functions. Cancer Immunol. Immunother. 67, 1079–1090 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Ye, D. et al. Tislelizumab in Asian patients with previously treated locally advanced or metastatic urothelial carcinoma. Cancer Sci. 112, 305–313 (2021).

    Article  CAS  PubMed  Google Scholar 

  13. Robertson, A. G. et al. Comprehensive molecular characterization of muscle-Invasive bladder cancer. Cell 171, 540–556 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Plimack, E. R. et al. Defects in DNA repair genes predict response to neoadjuvant cisplatin-based chemotherapy in muscle-invasive bladder cancer. Eur. Urol. 68, 959–967 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Van Allen, E. M. et al. Somatic ERCC2 mutations correlate with cisplatin sensitivity in muscle-invasive urothelial carcinoma. Cancer Discov. 4, 1140–1153 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Adib, E. et al. CDKN2A alterations and response to immunotherapy in solid tumors. Clin. Cancer Res. 27, 4025–4035 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Huang, Q. et al. Loss of TSC1/TSC2 sensitizes immune checkpoint blockade in non-small cell lung cancer. Sci. Adv. 8, eabi9533 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Lu, Q. et al. Rheb1 protects against cisplatin-induced tubular cell death and acute kidney injury via maintaining mitochondrial homeostasis. Cell Death Dis. 11, 364 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Teo, M. Y. et al. Alterations in DNA damage response and repair genes as potential marker of clinical benefit from PD-1/PD-L1 blockade in advanced urothelial cancers. J. Clin. Oncol. 36, 1685–1694 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Teo, M. Y. et al. DNA damage response and repair gene alterations are associated with improved survival in patients with platinum-treated advanced urothelial carcinoma. Clin. Cancer Res. 23, 3610–3618 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. de Visser, K. E. & Joyce, J. A. The evolving tumor microenvironment: from cancer initiation to metastatic outgrowth. Cancer Cell 41, 374–403 (2023).

    Article  PubMed  Google Scholar 

  22. Tian, B. et al. Curcumin inhibits urothelial tumor development by suppressing IGF2 and IGF2-mediated PI3K/AKT/mTOR signaling pathway. J. Drug Target. 25, 626–636 (2017).

    Article  CAS  PubMed  Google Scholar 

  23. Das, R. et al. An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer. Nat. Commun. 12, 4601 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. De Vitis, C. et al. ALDOC- and ENO2-driven glucose metabolism sustains 3D tumor spheroids growth regardless of nutrient environmental conditions: a multi-omics analysis. J. Exp. Clin. Canc. Res. 42, 69 (2023).

    Article  Google Scholar 

  25. Januchowski, R. et al. Drug transporter expression profiling in chemoresistant variants of the A2780 ovarian cancer cell line. Biomed. Pharmacother. 68, 447–453 (2014).

    Article  CAS  PubMed  Google Scholar 

  26. Maddika, S. et al. Cell survival, cell death and cell cycle pathways are interconnected: implications for cancer therapy. Drug Resist. Updat. 10, 13–29 (2007).

    Article  CAS  PubMed  Google Scholar 

  27. Rooney, M. S., Shukla, S. A., Wu, C. J., Getz, G. & Hacohen, N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell 160, 48–61 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Kamoun, A. et al. A consensus molecular classification of muscle-invasive bladder cancer. Eur. Urol. 77, 420–433 (2020).

    Article  PubMed  Google Scholar 

  29. Mariathasan, S. et al. TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature 554, 544–548 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Liu, Z. et al. TTN/OBSCN ‘double‐hit’ predicts favourable prognosis, ‘immune‐hot’ subtype and potentially better immunotherapeutic efficacy in colorectal cancer. J. Cell. Mol. Med. 25, 3239–3251 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Zhang, L., Han, X. & Shi, Y. Association of MUC16 mutation with response to immune checkpoint inhibitors in solid tumors. JAMA Netw. Open 3, e2013201 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Subramanian, A. et al. A next generation connectivity map: L1000 platform and the first 1,000,000 profiles. Cell 171, 1437–1452 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Carneiro, B. A. et al. Phase I study of elraglusib (9-ING-41), a glycogen synthase kinase-3β inhibitor, as monotherapy or combined with chemotherapy in patients with advanced malignancies. Clin. Cancer Res. 30, 522–531 (2024).

    Article  CAS  PubMed  Google Scholar 

  34. Song, Y. et al. Fibroblast growth factor receptor 3 mutation attenuates response to immune checkpoint blockade in metastatic urothelial carcinoma by driving immunosuppressive microenvironment. J. Immunother. Cancer 11, e006643 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Cathomas, R. et al. Perioperative chemoimmunotherapy with durvalumab for muscle-invasive urothelial carcinoma: primary analysis of the single-arm phase II trial SAKK 06/17. J. Clin. Oncol. 41, 5131–5139 (2023).

    Article  CAS  PubMed  Google Scholar 

  36. Brown, J. et al. HCRN GU14-188: phase Ib/II study of neoadjuvant pembrolizumab and chemotherapy for T2-4aN0M0 urothelial cancer. J. Clin. Oncol. 41, 448–448 (2023).

    Article  Google Scholar 

  37. Gupta, S. et al. Results from BLASST-1 (Bladder Cancer Signal Seeking Trial) of nivolumab, gemcitabine, and cisplatin in muscle invasive bladder cancer (MIBC) undergoing cystectomy. J. Clin. Oncol. 38, 439–439 (2020).

    Article  Google Scholar 

  38. Powles, T. et al. Pembrolizumab alone or combined with chemotherapy versus chemotherapy as first-line therapy for advanced urothelial carcinoma (KEYNOTE-361): a randomised, open-label, phase 3 trial. Lancet Oncol. 22, 931–945 (2021).

    Article  CAS  PubMed  Google Scholar 

  39. Bamias, A. et al. Atezolizumab monotherapy versus chemotherapy in untreated locally advanced or metastatic urothelial carcinoma (IMvigor130): final overall survival analysis from a randomised, controlled, phase 3 study. Lancet Oncol. 25, 46–61 (2024).

    Article  CAS  PubMed  Google Scholar 

  40. Van Der Heijden, M. S. et al. Nivolumab plus gemcitabine–cisplatin in advanced urothelial carcinoma. N. Engl. J. Med. 389, 1778–1789 (2023).

    Article  PubMed  Google Scholar 

  41. Bajorin, D. F. et al. Adjuvant nivolumab versus placebo in muscle-invasive urothelial carcinoma. N. Engl. J. Med. 384, 2102–2114 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Szabados, B. et al. Final results of neoadjuvant atezolizumab in cisplatin-ineligible patients with muscle-invasive urothelial cancer of the bladder. Eur. Urol. 82, 212–222 (2022).

    Article  CAS  PubMed  Google Scholar 

  43. Galsky, M. D. et al. Determinants of survival with combined HER2 and PD-1 blockade in metastatic esophagogastric cancer. Clin. Cancer Res. 29, 3633–3640 (2023).

    Article  Google Scholar 

  44. Kitamura, H. et al. Randomised phase III study of neoadjuvant chemotherapy with methotrexate, doxorubicin, vinblastine and cisplatin followed by radical cystectomy compared with radical cystectomy alone for muscle-invasive bladder cancer: Japan Clinical Oncology Group Study JCOG0209. Ann. Oncol. 25, 1192–1198 (2014).

    Article  CAS  PubMed  Google Scholar 

  45. Grossman, H. B. et al. Neoadjuvant chemotherapy plus cystectomy compared with cystectomy alone for locally advanced bladder cancer. N. Engl. J. Med. 349, 859–866 (2003).

    Article  CAS  PubMed  Google Scholar 

  46. Strandgaard, T. et al. Field cancerization is associated with tumor development, T-cell exhaustion, and clinical outcomes in bladder cancer. Eur. Urol. 85, 82–92 (2024).

    Article  CAS  PubMed  Google Scholar 

  47. Robertson, A. G. et al. Expression-based subtypes define pathologic response to neoadjuvant immune-checkpoint inhibitors in muscle-invasive bladder cancer. Nat. Commun. 14, 2126 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Kortlever, R. M. et al. Myc cooperates with Ras by programming inflammation and immune suppression. Cell 171, 1301–1315 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Fang, X. et al. Sintilimab plus bevacizumab, oxaliplatin and capecitabine as first-line therapy in RAS-mutant, microsatellite stable, unresectable metastatic colorectal cancer: an open-label, single-arm, phase II trial. EClinicalMedicine 62, 102123 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Kent, L. N. & Leone, G. The broken cycle: E2F dysfunction in cancer. Nat. Rev. Cancer 19, 326–338 (2019).

    Article  CAS  PubMed  Google Scholar 

  51. Baldominos, P. et al. Quiescent cancer cells resist T cell attack by forming an immunosuppressive niche. Cell 185, 1694–1708 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Seiler, R. et al. Divergent biological response to neoadjuvant chemotherapy in muscle-invasive bladder cancer. Clin. Cancer Res. 25, 5082–5093 (2019).

    Article  CAS  PubMed  Google Scholar 

  53. Schulz, K. F., Altman, D. G., Moher, D. & CONSORT Group CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. BMJ 340, c332–c332 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Landrum, M. J. et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 46, D1062–D1067 (2018).

    Article  CAS  PubMed  Google Scholar 

  55. Adzhubei, I. A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Liberzon, A. et al. The molecular signatures database hallmark gene set collection. Cell Syst. 1, 417–425 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Aran, D., Hu, Z. & Butte, A. J. xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 18, 220 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Yoshihara, K. et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat. Commun. 4, 2612 (2013).

    Article  PubMed  Google Scholar 

  59. Li, S. et al. Molecular signatures of antibody responses derived from a systems biology study of five human vaccines. Nat. Immunol. 15, 195–204 (2014).

    Article  PubMed  Google Scholar 

  60. Chaussabel, D. et al. A modular analysis framework for blood genomics studies: application to systemic lupus erythematosus. Immunity 29, 150–164 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Zyla, J. et al. Gene set enrichment for reproducible science: comparison of CERNO and eight other algorithms. Bioinformatics 35, 5146–5154 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Simon, R. Optimal two-stage designs for phase II clinical trials. Controlled Clin. Trials 10, 1–10 (1989).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This trial was supported by the National Key Research and Development Program of China (2018YFA0902800), the National Natural Science Foundation of China (81825016, 82341018 and U21A20383) and Sun Yat-Sen Memorial Hospital Clinical Research 5010 Program (SYS-5010Z-202401) to T.L., the National Natural Science Foundation of China (82173230 and 81961128027) to J.H., the National Natural Science Foundation of China (82173088), the Natural Science Foundation of Guangdong (2022A1515012383) and research funding of Sun Yat-sen University (23ptpy168) to K.L., the National Natural Science Foundation of China (82373254) to W.Z. and the Guangdong Provincial Clinical Research Center for Urological Diseases (2020B1111170006). BeiGene (Beijing, China) provided tislelizumab free of charge and financial support for the procurement of gemcitabine and cisplatin, as well as biomarker analysis. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. L. Ling from the Department of Medical Statistics, School of Public Health, Sun Yat-Sen University provided statistical assistance. K. Zhang from the Ivy Medical Editing (Shanghai, China) provided writing and editing assistance.

Author information

Author notes

  1. These authors contributed equally: Kaiwen Li, Wenlong Zhong.

Authors and Affiliations

  1. Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China

    Kaiwen Li, Wenlong Zhong, Shaoxu Wu, Longhao Xu, Jian Huang & Tianxin Lin

  2. Guangdong Provincial Clinical Research Center for Urological Diseases, Guangzhou, China

    Kaiwen Li, Wenlong Zhong, Shaoxu Wu, Jian Huang & Tianxin Lin

  3. Department of Urology, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China

    Jinhai Fan & Kaijie Wu

  4. Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

    Shaogang Wang, Zheng Liu, Zhiquan Hu & Fan Li

  5. Department of Urology, The Second Hospital of Anhui Medical University, Hefei, China

    Dexin Yu, Jinyou Wang, Qi Wang, Jie Min & Zhiqiang Zhang

  6. Department of Urology, Peking University People’s Hospital, Beijing, China

    Tao Xu & Luping Yu

  7. Department of Urology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Ji’nan, China

    Jiaju Lyu & Sentai Ding

  8. Department of Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China

    Tao Qin

  9. Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China

    Zhuo Wu

  10. Research Institute, GloriousMed Clinical Laboratory Co., Ltd., Shanghai, China

    Longfei Huang & Tingting Zhao

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  1. Kaiwen Li
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Contributions

Conceptualization and design, T.L., J.H., K.L. and W.Z. Administrative support: T.L. and J.H. Provision of study materials, K.L., J.F., S.Wang, D.Y., T.X., J.L., Z.L., K.W., J.W., Q.W., J.M., Z.H., F.L., Z.Z., L.Y., S.D., J.H. and T.L. Collection and assembly of data, K.L., J.F., S. Wang, D.Y., T.X., J.L., T.Q., Z.L., K.W., J.W., Q.W., J.M., Z.H., F.L., Z.Z., L.Y., S.D., J.H. and T.L. Data analysis and interpretation, K.L., W.Z., J.F., S.Wang, D.Y., T.X., J.L., S.Wu, T.Q., Z.W., L.X., Z.L., K.W., J.W., Q.W., J.M., Z.H., F.L., Z.Z., L.Y., S.D., L.H., T.Z., J.H. and T.L. Manuscript writing, K.L., W.Z., J.H. and T.L. Accountable for all aspects of the work: T.L. and J.H. All authors read and approved the final version of the manuscript. T.L. and J.H. supervised all aspects of this work.

Corresponding authors

Correspondence to Jian Huang or Tianxin Lin.

Ethics declarations

Competing interests

L.H. and T.Z. were employees of GloriousMed at the time of the study. The other authors declare no competing interests.

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Nature Cancer thanks Joaquim Bellmunt and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Trial design and participant enrollment.

a, The design of this trial; b, Flow of participants enrolled in this trial.

Extended Data Fig. 2 Comparison of response to neoadjuvant treatment by radiologic and pathologic assessment.

a, Representative magnetic resonance imaging (MRI) images showing bladder tumor status in a cT3N0M0 patient, at the time of prior-cycle 1 and cycle 3 of neoadjuvant treatment, and prior-radical cystectomy, respectively. This patient was evaluated as radiologic complete response (rCR) after neoadjuvant treatment and confirmed as pathologic complete response (pCR) after radical cystectomy. b, Comparison between rCR and pCR. ADC: apparent diffusion coefficient; DCE: dynamic contrast enhanced; DWI: diffusion weighted imaging; PD: progressive disease; T2WI: T2 weighted imaging.

Source data

Extended Data Fig. 3 Swimmer plot with treatment, response and follow-up details for 57 patients undergoing radical cystectomy.

Duration is relative to the date of first-dose neoadjuvant treatment. Clinical T/N stage is shown on the left side of the plot and displayed by bars with colors (green for T2N0M0, red for T3N0M0, and blue for T4aN0M0, respectively). Pathologic T/N stage after radical cystectomy is shown on the right side. Time points are marked by different shapes, including inverted triangle (last-dose of neoadjuvant treatment), triangle (last radiologic evaluation), diamond (radical cystectomy), circle (recurrence), cross (death), and arrow (continued follow-up).

Source data

Extended Data Fig. 4 Kaplan–Meier curves of event-free, overall survival (EFS and OS) and recurrence-free survival (RFS) stratified by different pathologic responses to neoadjuvant treatment.

a, b, c, Patients with (n = 14) or without pDS (n = 43). The cutoff of landmark analysis was 6 months for EFS and OS, and 3 months for RFS. Hazard ratio (HR) was calculated by comparing patients with vs without pDS. d, e, f, Patients with pCR (n = 29), paR (n = 14) and non-pDS (n = 14). CI, confidence interval; ns: non-significant; paR, partial response, Tis/Ta/T1N0M0; pCR, pathologic complete response; pDS, pathologic downstaging. p-values were calculated by using two-sided log-rank test.

Source data

Extended Data Fig. 5 Baseline urine tumor DNA (utDNA) assessment.

Estimated variant allele frequency (eVAF%) in baseline urine from patients with a, bladder-pCR (pT0Nx, n = 32) vs non-pT0 (n = 25); b, pCR (n = 29) vs non-pCR (n = 28), and c, pDS (n = 43) vs non-pDS (n = 14). pCR, pathologic complete response; pDS, pathologic downstaging. Two-sided Mann-Whitney U test was used.

Source data

Extended Data Fig. 6 Immune checkpoint gene expression and hallmark pathways in three subtypes.

a, Expression level of PDCD1, CD274, CTLA4, TIM3, and LAG3 gene; and b, Single-sample Gene set enrichment analysis showing pathways (based on the MSigDB v6.2 Hallmarks gene sets) with significant differences among three subtypes (subtype [S]1 [n = 19], S2 [n = 13] and S3 [n = 15]). Two-side Kruskal-Wallis test was used.

Source data

Extended Data Fig. 7 Somatic mutations and copy number variations (CNVs) in three subtypes.

a, Oncoprints for somatic mutations and CNVs in subtype 1 (S1, n = 18), S2 (n = 13) and S3 (n = 15) tumors. Horizontal bars to the right indicate the number of samples with an alteration and the types of alterations in indicated gene. Bar plots at the top show the total number of genetic alterations in the oncoprint genes. Horizontal bars and bar plots are colored by the alteration type. b, Percentage of subtypes (S1, n = 18; S2, n = 13; and S3, n = 15) tumors in patients with mutation in 13 selected genes. c, Pathways (based on the MSigDB v6.2 Hallmarks gene sets) with significant difference in patients (n = 46) with vs without mutation in 13 selected genes. Red (vs blue) discs represent for enriched (vs repressed) gene sets with disc areas for the areas-under-the-curve (AUCs) by the CERNO test.

Source data

Extended Data Table 1 Pathologic outcomes stratified by clinical T (cT) stage (N = 57)
Full size table
Extended Data Table 2 Summary of treatment-related adverse event (TRAE) with ≥10% frequency or any grade 3-5 (N = 65)
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Extended Data Table. 3 Summary of immune-related adverse event (irAE) (N = 65)
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Li, K., Zhong, W., Fan, J. et al. Neoadjuvant gemcitabine–cisplatin plus tislelizumab in persons with resectable muscle-invasive bladder cancer: a multicenter, single-arm, phase 2 trial. Nat Cancer 5, 1465–1478 (2024). https://doi.org/10.1038/s43018-024-00822-0

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