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      CD4 T cell-intrinsic STING signaling controls the differentiation and effector functions of T H1 and T H9 cells

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          Abstract

          Background

          While stimulator of interferon genes (STING) activation in innate immune cells of the tumor microenvironment can result in CD8 T cell-dependent antitumor immunity, whether STING signaling affects CD4 T-cell responses remains elusive.

          Methods

          Here, we tested whether STING activation modulated the effector functions of CD4 T cells in vivo by analyzing tumor-infiltrating CD4 T cells and evaluating the contribution of the CD4 T cell-derived cytokines in the antitumor activity of the STING ligand 2′3′-cyclic guanosine monophosphate-adenosine monophosphate (cGAMP) in two mouse tumor models. We performed ex vivo experiments to assess the impact of STING activation on CD4 T-cell differentiation and investigate the underlying molecular mechanisms. Finally, we tested whether STING activation enhances T H9 cell antitumor activity against mouse melanoma upon adoptive transfer.

          Results

          We found that activation of STING signaling cell-intrinsically enhances the differentiation and antitumor functions of T H1 and T H9 cells by increasing their respective production of interferon gamma (IFN-γ) and interleukin-9. IRF3 and type I interferon receptors (IFNARs) are required for the STING-driven enhancement of T H1 cell differentiation. However, STING activation favors T H9 cell differentiation independently of the IFNARs/IRF3 pathway but through mammalian target of rapamycin (mTOR) signaling, underscoring that STING activation differentially affects the fate of distinct CD4 T-cell subsets. The therapeutic effect of STING activation relies on T H1 and T H9-derived cytokines, and STING activation enhances the antitumor activity of T H9 cells upon adoptive transfer.

          Conclusion

          Our results reveal the STING signaling pathway as a therapeutic target to boost CD4 T-cell effector functions and antitumor immunity.

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          Most cited references63

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

              Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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                Author and article information

                Journal
                J Immunother Cancer
                J Immunother Cancer
                jitc
                jitc
                Journal for Immunotherapy of Cancer
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2051-1426
                2022
                28 January 2022
                : 10
                : 1
                : e003459
                Affiliations
                [1 ]INSERM, U1231 , Dijon, France
                [2 ]UFR Sciences de Santé, Université Bourgogne Franche-Comté , Dijon, France
                [3 ]INSERM, UMR-S 1193, Université Paris-Saclay , Châtenay-Malabry, France
                [4 ]departmentDepartment of Molecular and Integrative Physiology , University of Illinois at Urbana Champaign , Urbana, IL, USA
                [5 ]departmentINSERM UMR - S1109, Department of Clinical Immunology and Internal Medicine, National Reference Center for Systemic Autoimmune Diseases (CNR RESO), Tertiary Center for Primary Immunodeficiency , Hôpitaux Universitaires de Strasbourg, Université de Strasbourg , Strasbourg, France
                [6 ]departmentLaboratoire d'ImmunoRhumatologie Moléculaire, GENOMAX platform, INSERM UMR_S 1109 , Faculté de Médecine, Fédération Hospitalo-Universitaire OMICARE, Fédération de Médecine Translationnelle de Strasbourg (FMTS), LabEx TRANSPLANTEX , Strasbourg, France
                [7 ]departmentDepartment of Biology and Pathology of Tumors , Centre Georges François Leclerc , Dijon, France
                [8 ]departmentDepartment of Immunobiology , Yale University School of Medicine , New Heaven, CT, USA
                [9 ]departmentUMR 7355, Experimental and Molecular Immunology and Neurogenetics , CNRS , Orléans, France
                [10 ]departmentDepartment of Immunology , Institute of Infectious Disease and Molecular Medicine, University of Cape Town , Cape Town, South Africa
                [11 ]departmentAnticancer Discovery from Pets to People Theme , University of Illinois Urbana-Champaign, Cancer Center at Illinois , Urbana Champaign, Illinois, USA
                [12 ]departmentUniversity of Illinois Cancer Center , University of Illinois at Chicago , Chicago, IL, USA
                [13 ]departmentINSERM UMR-S1109, Department of Clinical Immunology and Internal Medicine, National Reference Center for Systemic Autoimmune Diseases (CNR RESO), Tertiary Center for Primary Immunodeficiency, Faculty of Pharmacy , Université de Strasbourg , Strasbourg, France
                [14 ]departmentCentre d'Immunologie de Marseille-Luminy , Université Aix-Marseille, INSERM, CNRS , Marseille, France
                [15 ]INSERM, U1100 , Tours, France
                [16 ]departmentFaculté de Médecine , Université de Tours , Tours, France
                Author notes
                [Correspondence to ] Pr Lionel Apetoh; lionel.apetoh@ 123456inserm.fr

                IB-L, EJ and TRV are joint first authors.

                Author information
                http://orcid.org/0000-0003-1187-6828
                http://orcid.org/0000-0003-0368-4113
                http://orcid.org/0000-0001-6032-7847
                http://orcid.org/0000-0002-2774-438X
                Article
                jitc-2021-003459
                10.1136/jitc-2021-003459
                8804688
                35091453
                6f59b7aa-7563-4cac-8578-d289c8e00003
                © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See https://creativecommons.org/licenses/by/4.0/.

                History
                : 02 December 2021
                Funding
                Funded by: National Cancer Institute of the National Institutes of Health;
                Award ID: R01CA234025
                Funded by: Department of Defense;
                Award ID: BC171214
                Funded by: FundRef http://dx.doi.org/10.13039/501100002915, Fondation pour la Recherche Médicale;
                Award ID: ARF20170938687
                Funded by: European Research Council (ERC);
                Award ID: 677251
                Funded by: Fondation ARC;
                Award ID: DOC20190509200
                Funded by: FEDER;
                Funded by: ANR;
                Award ID: 19-CE15-0028-01
                Funded by: LabEX MabImprove;
                Funded by: FundRef http://dx.doi.org/10.13039/501100001665, Agence Nationale de la Recherche;
                Award ID: ANR-11-LABX-0021
                Award ID: ANR-14-CE14-0026-04
                Funded by: FundRef http://dx.doi.org/10.13039/501100004431, Fondation de France;
                Categories
                Basic Tumor Immunology
                1506
                2434
                Original research
                Custom metadata
                unlocked

                cd4-positive t lymphocytes,adaptive immunity,immunomodulation,melanoma

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