Temporal and spatial composition of the tumor microenvironment predicts response to immune checkpoint inhibition

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Immune checkpoint inhibition (ICI) has fundamentally changed cancer treatment. However, only a minority of patients with metastatic triple negative breast cancer (TNBC) benefit from ICI, and the determinants of response remain largely unknown. To better understand the factors influencing patient outcome, we assembled a longitudinal cohort with tissue from multiple timepoints, including primary tumor, pre-treatment metastatic tumor, and on-treatment metastatic tumor from 117 patients treated with ICI (nivolumab) in the phase II TONIC trial. We used highly multiplexed imaging to quantify the subcellular localization of 37 proteins in each tumor. To extract meaningful information from the imaging data, we developed SpaceCat, a computational pipeline that quantifies features from imaging data such as cell density, cell diversity, spatial structure, and functional marker expression. We applied SpaceCat to 678 images from 294 tumors, generating more than 800 distinct features per tumor. Spatial features were more predictive of patient outcome, including features like the degree of mixing between cancer and immune cells, the diversity of the neighboring immune cells surrounding cancer cells, and the degree of T cell infiltration at the tumor border. Non-spatial features, including the ratio between T cell subsets and cancer cells and PD-L1 levels on myeloid cells, were also associated with patient outcome. Surprisingly, we did not identify robust predictors of response in the primary tumors. In contrast, the metastatic tumors had numerous features which predicted response. Some of these features, such as the cellular diversity at the tumor border, were shared across timepoints, but many of the features, such as T cell infiltration at the tumor border, were predictive of response at only a single timepoint. We trained multivariate models on all of the features in the dataset, finding that we could accurately predict patient outcome from the pre-treatment metastatic tumors, with improved performance using the on-treatment tumors. We validated our findings in matched bulk RNA-seq data, finding the most informative features from the on-treatment samples. Our study highlights the importance of profiling sequential tumor biopsies to understand the evolution of the tumor microenvironment, elucidating the temporal and spatial dynamics underlying patient responses and underscoring the need for further research on the prognostic role of metastatic tissue and its utility in stratifying patients for ICI.

Authors 35

1. Noah F. Greenwald

   Stanford Medicine · Stanford University

   Affiliation as printed

   Cancer Biology Program, Stanford University School of Medicine, Stanford, CA, USA

   Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

2. Iris Nederlof

   The Netherlands Cancer Institute

   Affiliation as printed

   Division of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands

3. Daisy Yi Ding

   Stanford Medicine · Stanford University

   Affiliation as printed

   Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA

4. Seongyeol Park

   Stanford Medicine · Stanford Cancer Institute · Stanford University

   Affiliation as printed

   Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

5. Alex Kong

   Stanford Medicine · Stanford University

   Affiliation as printed

   Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

6. Kathleen E. Houlahan

   Stanford Medicine · Stanford Cancer Institute · Stanford University

   Affiliation as printed

   Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

7. Sricharan Reddy Varra

   Stanford Medicine · Stanford University

   Affiliation as printed

   Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

8. Manon de Graaf

   The Netherlands Cancer Institute

   Affiliation as printed

   Division of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, Netherlands

9. Veerle C. M. Geurts

   The Netherlands Cancer Institute

   Affiliation as printed

   Division of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, Netherlands

10. Candace C. Liu

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

11. Jolene S. Ranek

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

12. Leonie Voorwerk

    The Netherlands Cancer Institute

    Affiliation as printed

    Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, Netherlands

13. Michiel de Maaker

    The Netherlands Cancer Institute

    Affiliation as printed

    Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, Netherlands

14. Adam Kagel

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

15. Erin McCaffrey

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

16. Aziz Khan

    Stanford Medicine · Stanford Cancer Institute · Stanford University

    Affiliation as printed

    Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

17. Christine Y. Yeh

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA

    Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA

    Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

18. Christine Camacho Fullaway

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

19. Zumana Khair

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

20. Yunhao Bai

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Chemistry, Stanford University School of Humanities and Sciences, Stanford, CA, USA, Stanford University School of Humanities and Sciences, Stanford, CA, USA

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

21. Hadeesha Piyadasa

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

22. Tyler Risom

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

23. Alea C. Delmastro

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

24. Felix J. Hartmann

    German Cancer Research Center · Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

    German Cancer Research Center (DKFZ), Heidelberg, Systems Immunology & Single-Cell Biology, Germany

25. Lise Mangiante

    Stanford Medicine · Stanford Cancer Institute · Stanford University

    Affiliation as printed

    Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

26. Cristina Sotomayor-Vivas

    Stanford Medicine · Stanford Cancer Institute · Stanford University

    Affiliation as printed

    Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

27. Ton N. Schumacher Aachen Department of Hematology, Leiden University Medical Center

    Leiden University Medical Center · The Netherlands Cancer Institute

    Affiliation as printed

    Department of Hematology, Leiden University Medical Center, Leiden, The Netherlands

    Division of Molecular Oncology & Immunology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands

28. Zhicheng Ma

    Stanford Medicine · Stanford Cancer Institute · Stanford University

    Affiliation as printed

    Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

29. Marc MB Bosse

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

30. Marc J. van de Vijver

    University of Amsterdam

    Affiliation as printed

    Department of Pathology, University of Amsterdam, Amsterdam, the Netherlands

31. Robert Tibshirani

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA

    Department of Statistics, Stanford University, Stanford, CA, USA

32. Hugo M. Horlings

    The Netherlands Cancer Institute

    Affiliation as printed

    Department of Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands

33. Christina N. Curtis corresponding

    Chan Zuckerberg Biohub San Francisco · Stanford Medicine · Stanford Cancer Institute · Stanford University

    Affiliation as printed

    Chan Zuckerberg Biohub, San Francisco, CA, USA

    Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA

    Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA

    Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

34. Marleen Kok corresponding

    The Netherlands Cancer Institute

    Affiliation as printed

    Division of Medical Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands

    Division of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, the Netherlands

35. Michael R. Angelo corresponding

    Stanford Medicine · Stanford University

    Affiliation as printed

    Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA