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      A Single-Cell Atlas of the Tumor and Immune Ecosystem of Human Breast Cancer

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          Summary

          Breast cancer is a heterogeneous disease. Tumor cells and associated healthy cells form ecosystems that determine disease progression and response to therapy. To characterize features of breast cancer ecosystems and their associations with clinical data, we analyzed 144 human breast tumor and 50 non-tumor tissue samples using mass cytometry. The expression of 73 proteins in 26 million cells was evaluated using tumor and immune cell-centric antibody panels. Tumors displayed individuality in tumor cell composition, including phenotypic abnormalities and phenotype dominance. Relationship analyses between tumor and immune cells revealed characteristics of ecosystems related to immunosuppression and poor prognosis. High frequencies of PD-L1 + tumor-associated macrophages and exhausted T cells were found in high-grade ER + and ER tumors. This large-scale, single-cell atlas deepens our understanding of breast tumor ecosystems and suggests that ecosystem-based patient classification will facilitate identification of individuals for precision medicine approaches targeting the tumor and its immunoenvironment.

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          Highlights

          • Single-cell proteomics reveals tumor and immune cell diversity in tumor ecosystems

          • Breast cancer exhibits tumor cell phenotypic abnormalities and tumor individuality

          • PD-L1 + TAMs and exhausted T cells are abundant in high-grade ER and ER + tumors

          • Tumor-immune relationships in the tumor ecosystem are patient-stratifying

          Abstract

          A single-cell atlas of cancer and immune cells reveals distinct tumor ecosystems across breast cancer patients, informing prognosis and, potentially, therapy selection.

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          Most cited references30

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          ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

          Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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            Tailoring therapies—improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015

            The 14th St Gallen International Breast Cancer Conference (2015) reviewed new evidence on locoregional and systemic therapies for early breast cancer. This manuscript presents news and progress since the 2013 meeting, provides expert opinion on almost 200 questions posed to Consensus Panel members, and summarizes treatment-oriented classification of subgroups and treatment recommendations.
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              Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses

              To guide the design of immunotherapy strategies for patients with early stage lung tumors, we developed a multiscale immune profiling strategy to map the immune landscape of early lung adenocarcinoma lesions to search for tumor-driven immune changes. Utilizing a barcoding method that allows a simultaneous single cell analysis of the tumor, non-involved lung and blood cells together with multiplex tissue imaging to assess spatial cell distribution, we provide a detailed immune cell atlas of early lung tumors. We show that stage I lung adenocarcinoma lesions already harbor significantly altered T cell and NK cell compartments. Moreover, we identified changes in tumor infiltrating myeloid cell (TIM) subsets that likely compromise anti-tumor T cell immunity. Paired single cell analyses thus offer valuable knowledge of tumor-driven immune changes, providing a powerful tool for the rational design of immune therapies. Comparing single tumor cells with adjacent normal tissue and blood from patients with lung adenocarcinoma charts early changes in tumor immunity and provides insights to guide immunotherapy design.
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                Author and article information

                Contributors
                Journal
                Cell
                Cell
                Cell
                Cell Press
                0092-8674
                1097-4172
                16 May 2019
                16 May 2019
                : 177
                : 5
                : 1330-1345.e18
                Affiliations
                [1 ]Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
                [2 ]Molecular Life Sciences Ph.D. Program, Life Science Zurich Graduate School, ETH Zurich and University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
                [3 ]IBM Research Zurich, Saeumerstrasse 4, 8803 Rueschlikon, Switzerland
                [4 ]Patients’ Tumor Bank of Hope (PATH) Biobank, PO 750729, 81337 Munich, Germany
                [5 ]Institute of Pathology at Josefshaus, Amalienstrasse 21, 44137 Dortmund, Germany
                [6 ]Institute of Pathology, University Hospital Giessen and Marburg, Baldingerstrasse, 35043 Marburg, Germany
                [7 ]Institute of Pathology, University Hospital Basel and University of Basel, Schoenbeinstrasse 40, 4031 Basel, Switzerland
                [8 ]Clarunis, University Hospital Basel and University of Basel, Spitalstrasse 21, 4031 Basel, Switzerland
                [9 ]Breast Cancer Center, University Hospital Basel and University of Basel, Spitalstrasse 21, 4031 Basel, Switzerland
                [10 ]Systems Biology Ph.D. Program, Life Science Zurich Graduate School, ETH Zurich and University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
                [11 ]Institute of Experimental Immunology, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
                [12 ]Breast Cancer Center, University Hospital Zurich, Frauenklinikstrasse 10, 8091 Zurich, Switzerland
                [13 ]Department of Surgery, University Hospital Basel and University of Basel, Spitalstrasse 21, 4031 Basel, Switzerland
                Author notes
                []Corresponding author bernd.bodenmiller@ 123456imls.uzh.ch
                [14]

                Present address: Department of Quantitative Biomedicine, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland

                [15]

                These authors contributed equally

                [16]

                Lead Contact

                Article
                S0092-8674(19)30267-3
                10.1016/j.cell.2019.03.005
                6526772
                30982598
                50557c33-533a-414f-bb02-081b5a6d49b5
                © 2019 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 6 September 2018
                : 16 January 2019
                : 1 March 2019
                Categories
                Article

                Cell biology
                breast cancer,tumor ecosystem,tumor heterogeneity,immunosuppression,t cell,macrophage,single-cell analysis,mass cytometry

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