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Clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

A Publisher Correction to this article was published on 21 March 2023

A Publisher Correction to this article was published on 15 May 2020

This article has been updated

Abstract

Antibodies targeting PD-1 or its ligand 1 PD-L1 such as atezolizumab, have great efficacy in a proportion of metastatic urothelial cancers1,2. Biomarkers may facilitate identification of these responding tumors3. Neoadjuvant use of these agents is associated with pathological complete response in a spectrum of tumors, including urothelial cancer4,5,6,7. Sequential tissue sampling from these studies allowed for detailed on-treatment biomarker analysis. Here, we present a single-arm phase 2 study, investigating two cycles of atezolizumab before cystectomy in 95 patients with muscle-invasive urothelial cancer (ClinicalTrials.gov identifier: NCT02662309). Pathological complete response was the primary endpoint. Secondary endpoints focused on safety, relapse-free survival and biomarker analysis. The pathological complete response rate was 31% (95% confidence interval: 21–41%), achieving the primary efficacy endpoint. Baseline biomarkers showed that the presence of preexisting activated T cells was more prominent than expected and correlated with outcome. Other established biomarkers, such as tumor mutational burden, did not predict outcome, differentiating this from the metastatic setting. Dynamic changes to gene expression signatures and protein biomarkers occurred with therapy, whereas changes in DNA alterations with treatment were uncommon. Responding tumors showed predominant expression of genes related to tissue repair after treatment, making tumor biomarker interpretation challenging in this group. Stromal factors such as transforming growth factor-β and fibroblast activation protein were linked to resistance, as was high expression of cell cycle gene signatures after treatment.

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Fig. 1: Analysis of three response biologies at baseline.
Fig. 2: Investigation of three response biologies in treated tissue.
Fig. 3: Exploratory analysis of DNA alterations and RNA and protein expression.

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Data availability

Data that support the findings of this paper are available from the corresponding author upon reasonable request. Raw data have been deposited to the European Genome-Phenome Archive under accession number ega-box-1336.

Change history

  • 15 May 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

  • 21 March 2023

    A Correction to this paper has been published: https://doi.org/10.1038/s41591-023-02312-9

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Acknowledgements

We thank the patients and their families as well as all of the investigators and their staff involved in ABACUS. The Experiment Cancer Medicine Centre at Barts Cancer Institute organized and had oversight of all aspects of the study. T.P. was the chief investigator, imCORE (Roche) and Histogenex performed aspects of the biomarker analysis. Queen Mary University of London was the Sponsor of the study. Roche granted QMUL funding for the study and supplied the study drug. J. Bull and M. Jacobson also provided financial support for aspects of the biomarker analysis. We are grateful to the members of the Data Monitoring Committee: M. Bower, Chelsea and Westminster Hospital NHS Foundation Trust; J. Peters, Barts Health NHS Trust; J. Catto and Sheffield Teaching Hospitals NHS Trust. We are grateful to the following people who helped with the study: C. Lawrence, C. Tyson and J. Bansal of the Experiment Cancer Medicine Centre at Barts Cancer Institute; S. Tabuteau and C. Gazille of Le Centre Hospitalier Universitaire de Bordeaux; the investigators and project managers of the Spanish Oncology Genitourinary Group; A. Moreno and M. De Figueora of Apices; and H. Schrijver and E. van Schaffelaar of the Netherlands Cancer Institute–Antoni van Leeuwenhoek Hospital. We acknowledge Cancer Research UK, the UK Experimental Cancer Medicine Network and La Roche-Hoffmann for funding.

Author information

Authors and Affiliations

Authors

Contributions

T.P. was the chief investigator for the trial and developed the trial. T.P., A.R., M.S.V.D.H., I.D. and K.M. were involved in the protocol development. T.P., K.M. and A.P. constituted the trial management group. T.P., A.R.-V., I.D., S.J.C., M.S.V.D.H., A.F.P., G.G., U.A.H., A.P., A.R., D.M., M.J.M., C.S., M.L. and D.C. were involved in recruitment, clinical care and data returns. A.P. performed the main analyses, overseen by T.P. and K.M. M.K., B.S., P.-J.v.D., D.S. and S.D. contributed to PD-L1 and CD8 analysis and associated data interpretation. T.P., R.B. and J.S.T. contributed to RNA and DNA analysis. T.P. and R.B. interpreted the DNA and RNA data. S.M. contributed to all data interpretation. T.P. wrote the first draft of the manuscript and all other authors contributed to subsequent revisions. All authors reviewed and approved the final version of the paper.

Corresponding author

Correspondence to Thomas Powles.

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Competing interests

Employment by Roche: S.M., J.S.T. and R.B.; employment by Histogenex: M.K., P.-J.v.D., D.S. and S.D.; research funding/honoraria (BMS): T.P., A.R., I.D., M.S.V.D.H., A.P. and M.L.; research funding/honoraria (Roche): T.P., A.R., I.D., M.S.V.D.H., G.G., U.A.H., M.K., A.P., A.R., M.J.M. and C.S.; research funding/honoraria (AZ): T.P., I.D., M.S.V.D.H., A.P., G.G., U.A.H., M.K. and C.S.; research funding/honoraria (MSD): T.P., I.D., S.J.C., M.S.V.D.H., M.K., D.M., C.S. and M.L.; research funding/honoraria (Pfizer): T.P., S.J.C., G.G., A.P., A.R., M.J.M. and C.S.; research funding/honoraria (Novartis): I.D., U.A.H., A.P., A.R. and C.S.; research funding/honoraria (Exelixis): T.P. and C.S.; research funding/honoraria (Astellas): T.P., S.J.C., G.G., A.P., A.R. and M.L.; research funding/honoraria (Johnson & Johnson): T.P.

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Peer review information: Javier Carmona was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 Consort diagram.

95 patients were recruited to this study and received treatment. 75 received the full treatment regime with 2 cycles of atezolizumab and 20 patients were treated with only one cycle. In total, 87 patients underwent radical cystectomy, 7 patients did not undergo surgery and one patient withdrew consent from the study. 88 patients were assessable for the primary efficacy endpoint analysis, including one patient who experienced progression of disease.

Extended Data Fig. 2 Change in T and N stage associated with therapy.

T and N stage at baseline was assessed with pathology samples from TURBT and cross-sectional imaging. T and N stage at surgery was assessed with pathology results from cystectomy and lymphadenectomy (n = 88). Direct comparisons between time points should be avoided due to differences in methodologies of assessment. Baseline nodal staging was radiological while it was pathological at surgery which may account for discrepancies.

Extended Data Fig. 3 Change in the size of bladder mass on imaging.

Imaging occurred at baseline and after completion of treatment prior to planned surgery. All patients were included irrespective if they were fit for surgery. Due to definitions of measurable disease not all bladder tumors were measurable at baseline. RECIST v1.1 was used to define response. A positive change denotes an increase in tumor size over time and conversely a negative change denotes a decrease in tumor size over time. Reference lines have been added for response (-30% reduction in tumor size) and progression (20% increase in tumor size). 58 of the 95 treated patients had sequential imaging and radiologically measurable disease at baseline. Radiological progression = 9/58 = 16% (7–27). Radiological response 13/58 = 22% (13–35). 12 patients exhibited no change in their tumor, were not evaluable at pre-cystectomy scan, handled as <10 mm at baseline, and therefore not included in this plot.

Extended Data Fig. 4 Bar charts representing PD-L1 expression in tumor cells, in all samples or by outcome group.

Only patients with measurable pre / post biopsies were considered in this analysis.

Extended Data Fig. 5 Association between clinical outcome and the cell cycle signature at baseline.

The cell cycle signature is calculated as the mean Z-score of the following genes: MKI67, CCNE1, BUB1, BUB1B, CCNB2, CDC25C, CDK2, MCM4, MCM6, MCM2. Median IQRs and ranges are shown. There was no significant difference between response and relapse samples (two-sided Wilcoxon rank sum test, p=0.34). No adjustments were made for multiple comparisons. Number of samples given in parenthesis.

Extended Data Fig. 6 Correlation between biomarkers.

The expression of 4 biomarkers were correlated with one another. Correlations were measured using Pearson’s product moment correlation coefficient. Light blue on the grid shows correlation in baseline samples and orange shaded data shows correlation in treated samples. Most biomarkers correlated positively with one another except for FAP and CD8. Strongest correlation was between and PD-L1.

Extended Data Fig. 7 Association between immune phenotypes and response to treatment.

The frequency of immune phenotypes pre (left panel) and post (right panel) therapy by clinical outcome group. Immune phenotypes were assessed centrally by two pathologists using established methods11. 78 baseline and 57 cystectomy samples were assessed. A higher than expected proportion displayed inflamed phenotype compared to patients with metastatic disease3. Deserts were not present in responding patients. Analysis of pCR samples was not possible because of lack of tumor cells.

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Powles, T., Kockx, M., Rodriguez-Vida, A. et al. Clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial. Nat Med 25, 1706–1714 (2019). https://doi.org/10.1038/s41591-019-0628-7

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