Computational immune synapse analysis reveals T-cell interactions in distinct tumor microenvironments

Abstract The tumor microenvironment (TME) and the cellular interactions within it can be critical to tumor progression and treatment response. Although technologies to generate multiplex images of the TME are advancing, the many ways in which TME imaging data can be mined to elucidate cellular interactions are only beginning to be realized. Here, we present a novel approach for multipronged computational immune synapse analysis (CISA) that reveals T-cell synaptic interactions from multiplex images. CISA enables automated discovery and quantification of immune synapse interactions based on the localization of proteins on cell membranes. We first demonstrate the ability of CISA to detect T-cell:APC (antigen presenting cell) synaptic interactions in two independent human melanoma imaging mass cytometry (IMC) tissue microarray datasets. We then generate melanoma histocytometry whole slide images and verify that CISA can detect similar interactions across data modalities. Interestingly, CISA histoctyometry analysis also reveals that T-cell:macrophage synapse formation is associated with T-cell proliferation. We next show the generality of CISA by extending it to breast cancer IMC images, finding that CISA quantifications of T-cell:B-cell synapses are predictive of improved patient survival. Our work demonstrates the biological and clinical significance of spatially resolving cell-cell synaptic interactions in the TME and provides a robust method to do so across imaging modalities and cancer types.

[1]  T. Sheikh,et al.  Melanoma Treatments and Mortality Rate Trends in the US, 1975 to 2019 , 2022, JAMA network open.

[2]  Nils Eling,et al.  Multiplexed imaging mass cytometry of the chemokine milieus in melanoma characterizes features of the response to immunotherapy , 2022, Science Immunology.

[3]  H. Najafabadi,et al.  Spatially mapping the immune landscape of melanoma using imaging mass cytometry , 2022, Science Immunology.

[4]  S. Tavaré,et al.  Three-dimensional imaging mass cytometry for highly multiplexed molecular and cellular mapping of tissues and the tumor microenvironment , 2021, Nature Cancer.

[5]  Ansuman T. Satpathy,et al.  Spatiotemporal co-dependency between macrophages and exhausted CD8+ T cells in cancer , 2021, bioRxiv.

[6]  Rob J. de Boer,et al.  Cytotoxic T cells are able to efficiently eliminate cancer cells by additive cytotoxicity , 2021, Nature Communications.

[7]  D. Bending,et al.  Antigen and checkpoint receptor engagement recalibrates T cell receptor signal strength , 2021, Immunity.

[8]  Jeffrey H. Chuang,et al.  Transcriptional profiling of macrophages in situ in metastatic melanoma reveals localization-dependent phenotypes and function , 2021, Cell reports. Medicine.

[9]  K. Rogers,et al.  Spatial omics and multiplexed imaging to explore cancer biology , 2021, Nature Methods.

[10]  Alyce A. Chen,et al.  The Spatial Landscape of Progression and Immunoediting in Primary Melanoma at Single-Cell Resolution , 2021, bioRxiv.

[11]  Tyler T. Risom,et al.  Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning , 2021, Nature Biotechnology.

[12]  D. Rimm,et al.  Biomarker Discovery in Patients with Immunotherapy-Treated Melanoma with Imaging Mass Cytometry , 2021, Clinical Cancer Research.

[13]  Xiongtao Ruan,et al.  PD-1 suppresses the maintenance of cell couples between cytotoxic T cells and target tumor cells within the tumor , 2020, Science Signaling.

[14]  Salil S. Bhate,et al.  Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front , 2020, Cell.

[15]  Reem Saleh,et al.  FoxP3+ T regulatory cells in cancer: Prognostic biomarkers and therapeutic targets. , 2020, Cancer letters.

[16]  M. Lenardo,et al.  A guide to cancer immunotherapy: from T cell basic science to clinical practice , 2020, Nature Reviews Immunology.

[17]  Zhaolin Hua,et al.  The role of B cell antigen presentation in the initiation of CD4+ T cell response , 2020, Immunological reviews.

[18]  Roger R. Wang,et al.  Multi-panel immunofluorescence analysis of tumor infiltrating lymphocytes in triple negative breast cancer: Evolution of tumor immune profiles and patient prognosis , 2020, PloS one.

[19]  Marius Pachitariu,et al.  Cellpose: a generalist algorithm for cellular segmentation , 2020, Nature Methods.

[20]  I. A. Adejumobi,et al.  Dissecting the role of crosstalk between glioblastoma subpopulations in tumor cell spreading , 2020, Oncogenesis.

[21]  Carlos Caldas,et al.  Imaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer , 2020, Nature Cancer.

[22]  H. Moch,et al.  The single-cell pathology landscape of breast cancer , 2020, Nature.

[23]  Jeffrey E. Lee,et al.  B cells and tertiary lymphoid structures promote immunotherapy response , 2020, Nature.

[24]  D. Schadendorf,et al.  Tertiary lymphoid structures improve immunotherapy and survival in melanoma , 2020, Nature.

[25]  Shixiang Wang,et al.  Antigen presentation and tumor immunogenicity in cancer immunotherapy response prediction , 2019, eLife.

[26]  S. Hilsenbeck,et al.  Evaluation of the Predictive Role of Tumor Immune Infiltrate in Patients with HER2-Positive Breast Cancer Treated with Neoadjuvant Anti-HER2 Therapy without Chemotherapy , 2019, Clinical Cancer Research.

[27]  Maxim N. Artyomov,et al.  MHC-II neoantigens shape tumor immunity and response to immunotherapy , 2019, Nature.

[28]  D. Pe’er,et al.  Combination anti–CTLA-4 plus anti–PD-1 checkpoint blockade utilizes cellular mechanisms partially distinct from monotherapies , 2019, Proceedings of the National Academy of Sciences.

[29]  J. Wilmott,et al.  Close proximity of immune and tumor cells underlies response to anti-PD-1 based therapies in metastatic melanoma patients , 2019, Oncoimmunology.

[30]  Fred A. Hamprecht,et al.  ilastik: interactive machine learning for (bio)image analysis , 2019, Nature Methods.

[31]  Salil S. Bhate,et al.  Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front , 2019, Cell.

[32]  J. Madore,et al.  Distinct Immune Cell Populations Define Response to Anti-PD-1 Monotherapy and Anti-PD-1/Anti-CTLA-4 Combined Therapy. , 2019, Cancer cell.

[33]  Aviv Regev,et al.  Checkpoint Blockade Immunotherapy Induces Dynamic Changes in PD‐1−CD8+ Tumor‐Infiltrating T Cells , 2019, Immunity.

[34]  Johannes Griss,et al.  B cells sustain inflammation and predict response to immune checkpoint blockade in human melanoma , 2019, Nature Communications.

[35]  Timothy A. Chan,et al.  The hallmarks of successful anticancer immunotherapy , 2018, Science Translational Medicine.

[36]  Sean C. Bendall,et al.  A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging , 2018, Cell.

[37]  P. Darcy,et al.  Multiplex immunohistochemistry accurately defines the immune context of metastatic melanoma , 2018, Scientific Reports.

[38]  V. Pascual,et al.  IL1 Receptor Antagonist Controls Transcriptional Signature of Inflammation in Patients with Metastatic Breast Cancer. , 2018, Cancer research.

[39]  Eugene W. Myers,et al.  Cell Detection with Star-convex Polygons , 2018, MICCAI.

[40]  Sandro Santagata,et al.  Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes , 2018, eLife.

[41]  Steven J. M. Jones,et al.  The Immune Landscape of Cancer , 2018, Immunity.

[42]  C. Baldari,et al.  Signals Controlling Lytic Granule Polarization at the Cytotoxic Immune Synapse , 2018, Front. Immunol..

[43]  J. Banchereau,et al.  Humanized mice in studying efficacy and mechanisms of PD-1-targeted cancer immunotherapy , 2017, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[44]  Sarah A. Teichmann,et al.  Faculty Opinions recommendation of histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data. , 2017 .

[45]  J. Madrigal,et al.  B cell regulation in cancer and anti-tumor immunity , 2017, Cellular &Molecular Immunology.

[46]  Theresa A. Storm,et al.  Disrupting the CD47-SIRPα anti-phagocytic axis by a humanized anti-CD47 antibody is an efficacious treatment for malignant pediatric brain tumors , 2017, Science Translational Medicine.

[47]  I. Mellman,et al.  Elements of cancer immunity and the cancer–immune set point , 2017, Nature.

[48]  I. Weissman,et al.  First-in-Human, First-in-Class Phase I Trial of the Anti-CD47 Antibody Hu5F9-G4 in Patients With Advanced Cancers. , 2016, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[49]  G. Nolan,et al.  Automated Mapping of Phenotype Space with Single-Cell Data , 2016, Nature Methods.

[50]  M. Vicente-Manzanares,et al.  Concerning immune synapses: a spatiotemporal timeline , 2016, F1000Research.

[51]  Lisa M. Coussens,et al.  The Basis of Oncoimmunology , 2016, Cell.

[52]  yang-xin fu,et al.  CD47 Blockade Triggers T cell-mediated Destruction of Immunogenic Tumors , 2015, Nature Medicine.

[53]  D. Fearon,et al.  T cell exclusion, immune privilege, and the tumor microenvironment , 2015, Science.

[54]  Emmanuelle Gouillart,et al.  scikit-image: image processing in Python , 2014, PeerJ.

[55]  F. Schuetz,et al.  B cell-regulated immune responses in tumor models and cancer patients , 2013, Oncoimmunology.

[56]  Michael Y. Gerner,et al.  Histo-cytometry: a method for highly multiplex quantitative tissue imaging analysis applied to dendritic cell subset microanatomy in lymph nodes. , 2012, Immunity.

[57]  Takashi Saito,et al.  Programmed cell death 1 forms negative costimulatory microclusters that directly inhibit T cell receptor signaling by recruiting phosphatase SHP2 , 2012, The Journal of experimental medicine.

[58]  I. Weissman,et al.  Anti-CD47 antibodies promote phagocytosis and inhibit the growth of human myeloma cells , 2012, Leukemia.

[59]  I. Ellis,et al.  The prognostic significance of B lymphocytes in invasive carcinoma of the breast , 2012, Breast Cancer Research and Treatment.

[60]  C. Sautès-Fridman,et al.  The immune contexture in human tumours: impact on clinical outcome , 2012, Nature Reviews Cancer.

[61]  P. Sharma,et al.  The ICOS/ICOSL pathway is required for optimal antitumor responses mediated by anti-CTLA-4 therapy. , 2011, Cancer research.

[62]  J. Tímár,et al.  Prognostic impact of B-cell density in cutaneous melanoma , 2011, Cancer Immunology, Immunotherapy.

[63]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[64]  Ash A. Alizadeh,et al.  Anti-CD47 Antibody Synergizes with Rituximab to Promote Phagocytosis and Eradicate Non-Hodgkin Lymphoma , 2010, Cell.

[65]  T. Tedder,et al.  B Cells Are Required for Optimal CD4+ and CD8+ T Cell Tumor Immunity: Therapeutic B Cell Depletion Enhances B16 Melanoma Growth in Mice , 2010, The Journal of Immunology.

[66]  Jian Yu,et al.  Otsu Method and K-means , 2009, 2009 Ninth International Conference on Hybrid Intelligent Systems.

[67]  M. Herrero,et al.  Infiltrating CTLs in human glioblastoma establish immunological synapses with tumorigenic cells. , 2009, The American journal of pathology.

[68]  Michael Loran Dustin T‐cell activation through immunological synapses and kinapses , 2008, Immunological reviews.

[69]  J. Houghton,et al.  Tumor microenvironment: The role of the tumor stroma in cancer , 2007, Journal of cellular biochemistry.

[70]  Anne E Carpenter,et al.  CellProfiler: image analysis software for identifying and quantifying cell phenotypes , 2006, Genome Biology.

[71]  J. Joyce,et al.  Therapeutic Targeting of the Tumor Microenvironment. , 2021, Cancer discovery.

[72]  Mark M. Davis,et al.  T-cell-antigen recognition and the immunological synapse , 2003, Nature Reviews Immunology.

[73]  G. Griffiths,et al.  The immunological synapse of CTL contains a secretory domain and membrane bridges. , 2001, Immunity.

[74]  M. Sadelain,et al.  Antigen-dependent CD28 Signaling Selectively Enhances Survival and Proliferation in Genetically Modified Activated Human Primary T Lymphocytes , 1998, The Journal of experimental medicine.

[75]  E. M.,et al.  Statistical Mechanics , 2021, Manual for Theoretical Chemistry.

[76]  Sebastian Amigorena,et al.  Dissecting the Tumor Myeloid Compartment Reveals Rare Activating Antigen-Presenting Cells Critical for T Cell Immunity. , 2014, Cancer cell.