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      T cells armed with the C-X-C chemokine receptor type 6 enhance adoptive cell therapy for pancreatic tumours

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      1 , 1 , 2 , 1 , 1 , 1 , 1 , 3 , 1 , 1 , 1 , 1 , 1 , 1 , 4 , 1 , 1 , 1 , 1 , 2 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 5 , 6 , 5 , 6 , 6 , 7 , 8 , 8 , 1 , 9 , 10 , 11 , 12 , 12 , 13 , 14 , 14 , 15 , 16 , 15 , 17 , 2 , 9 , 6 , 7 , 18 , 5 , 6 , 1 , 19 , 20 , 1 , 1 , 2 , 8 , 21 , 3 , 22 , 23 , 14 , 1 , 19 , 23 , 1 , 19 , 23 , *
      Nature biomedical engineering

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          Abstract

          The efficacy of adoptive cell therapy for solid tumours is hampered by the poor accumulation of the transferred T cells in tumour tissue. Here, we show that the forced expression of the C-X-C chemokine receptor type 6 (CXCR6, whose ligand is highly expressed by human and murine pancreatic cancer cells and by tumour-infiltrating immune cells) in antigen-specific T cells enhanced the recognition and lysis of pancreatic cancer cells and the efficacy of adoptive cell therapy for pancreatic cancer. In mice with subcutaneous pancreatic tumours treated with T cells with either a transgenic T-cell receptor or a murine chimeric antigen receptor targeting the tumour-associated antigen epithelial cell-adhesion molecule, and in mice with orthotopic pancreatic tumours or patient-derived xenografts treated with T cells expressing a chimeric antigen receptor targeting mesothelin, the T cells exhibited enhanced intratumoral accumulation, exerted sustained antitumoral activity and prolonged animal survival only when co-expressing CXCR6. Arming tumour-specific T cells with tumour-specific chemokine receptors may represent a promising strategy for the realization of adoptive cell therapy for solid tumours.

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          Is Open Access

          SCANPY : large-scale single-cell gene expression data analysis

          Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks. Its Python-based implementation efficiently deals with data sets of more than one million cells (https://github.com/theislab/Scanpy). Along with Scanpy, we present AnnData, a generic class for handling annotated data matrices (https://github.com/theislab/anndata).
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            Massively parallel digital transcriptional profiling of single cells

            Characterizing the transcriptome of individual cells is fundamental to understanding complex biological systems. We describe a droplet-based system that enables 3′ mRNA counting of tens of thousands of single cells per sample. Cell encapsulation, of up to 8 samples at a time, takes place in ∼6 min, with ∼50% cell capture efficiency. To demonstrate the system's technical performance, we collected transcriptome data from ∼250k single cells across 29 samples. We validated the sensitivity of the system and its ability to detect rare populations using cell lines and synthetic RNAs. We profiled 68k peripheral blood mononuclear cells to demonstrate the system's ability to characterize large immune populations. Finally, we used sequence variation in the transcriptome data to determine host and donor chimerism at single-cell resolution from bone marrow mononuclear cells isolated from transplant patients.
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              Visualizing and interpreting cancer genomics data via the Xena platform

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                Author and article information

                Journal
                101696896
                Nat Biomed Eng
                Nat Biomed Eng
                Nature biomedical engineering
                2157-846X
                27 April 2021
                01 November 2021
                03 June 2021
                03 December 2021
                : 5
                : 11
                : 1246-1260
                Affiliations
                [1 ]Center of Integrated Protein Science Munich (CIPS-M) and Division of Clinical Pharmacology, Department of Medicine IV, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany, Member of the German Center for Lung Research (DZL)
                [2 ]Department of Medicine III, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
                [3 ]Klinik und Poliklinik für Innere Medizin II, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany
                [4 ]Center for Precision Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA
                [5 ]Université de Paris, Institute Cochin, INSERM, CNRS, F-75014 Paris, France
                [6 ]Equipe labellisée Ligue Contre le Cancer, Toulouse, France
                [7 ]Université de Paris, PARCC, INSERM U970, F-75006 Paris
                [8 ]Department of Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA
                [9 ]Institute for Cardiovascular Prevention (IPEK), University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
                [10 ]Cardiovascular Research Institute Maastricht (CARIM), Department of BME, Maastricht University, Maastricht, Netherlands
                [11 ]Department of Surgery, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany
                [12 ]Helmholtz Diabetes Center and German Diabetes Center (DZD), Helmholtz Zentrum München, Neuherberg, Germany
                [13 ]LMU Biocenter, Department Biology II, Ludwig Maximilians-Universität (LMU Munich), Martinsried, Germany
                [14 ]Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA
                [15 ]Institute of Computational Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
                [16 ]Technical University of Munich, School of Life Science Weihenstephan, Freising, Germany
                [17 ]Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany
                [18 ]Service d’Immunologie Biologique, APHP, Hôpital Européen Georges Pompidou. F-75015 Paris
                [19 ]Einheit für Klinische Pharmakologie (EKLiP), Helmholtz Zentrum München, Research Center for Environmental Health (HMGU), Neuherberg, Germany
                [20 ]Institute of Innate Immunity, University of Bonn, Bonn, Germany
                [21 ]Department of Translational Immunotherapy, German Cancer Research Center (DKFZ), Heidelberg, Germany
                [22 ]Center for Protein Assemblies (CPA), Technische Universität München, Ernst-Otto-Fischer Str. 8, 85747 Garching, Germany
                [23 ]German Center for Translational Cancer Research (DKTK), partner site Munich, Germany
                Author notes
                [* ] Correspondence and requests for materials should be addressed to S.K. Sebastian.kobold@ 123456med.uni-muenchen.de
                Article
                EMS123298
                10.1038/s41551-021-00737-6
                7611996
                34083764
                94f35f6b-71df-4a3c-a111-9016d3568726

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