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      Lipid signalling enforces T reg cell functional specialization in tumours

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          Abstract

          Regulatory T (T reg) cells are essential for immune tolerance 1 but also drive immunosuppression in the tumour microenvironment (TME) 2. Therapeutic targeting of T reg cells in cancer requires the identification of context-specific mechanisms for T reg cell function. Here we demonstrate that inhibition of sterol regulatory element-binding protein (SREBP)-dependent lipid synthesis and metabolic signalling in T reg cells unleashes effective antitumour immune responses without autoimmune toxicity. SREBP activity is upregulated in intratumoural T reg cells, and T reg cell-specific deletion of SCAP, an obligatory factor for SREBP activity, inhibits tumour growth and boosts anti-PD-1 immunotherapy, associated with uncontrolled IFN-γ production and impaired function of intratumoural T reg cells. Mechanistically, SCAP/SREBP signalling coordinates lipid synthetic programs and inhibitory receptor signalling in T reg cells. First, de novo fatty acid synthesis mediated by fatty acid synthase (FASN) contributes to functional maturation of T reg cells, and loss of FASN in T reg cells inhibits tumour growth. Second, T reg cells show enhanced Pdcd1 expression in tumours in a process dependent on SREBP activity that further signals to mevalonate metabolism-driven protein geranylgeranylation, and blocking PD-1 or SREBP signaling results in dysregulated PI3K activation in intratumoural T reg cells. Our findings establish that metabolic reprogramming enforces T reg cell functional specialization in tumours, pointing to new avenues to target T reg cells for cancer therapy.

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          Most cited references50

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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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            Integrating single-cell transcriptomic data across different conditions, technologies, and species

            Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple data sets remains challenging. Here, we introduce an analytical strategy for integrating scRNA-seq data sets based on common sources of variation, enabling the identification of shared populations across data sets and downstream comparative analysis. We apply this approach, implemented in our R toolkit Seurat (http://satijalab.org/seurat/), to align scRNA-seq data sets of peripheral blood mononuclear cells under resting and stimulated conditions, hematopoietic progenitors sequenced using two profiling technologies, and pancreatic cell 'atlases' generated from human and mouse islets. In each case, we learn distinct or transitional cell states jointly across data sets, while boosting statistical power through integrated analysis. Our approach facilitates general comparisons of scRNA-seq data sets, potentially deepening our understanding of how distinct cell states respond to perturbation, disease, and evolution.
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              Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy.

              Cancer immunotherapy can induce long lasting responses in patients with metastatic cancers of a wide range of histologies. Broadening the clinical applicability of these treatments requires an improved understanding of the mechanisms limiting cancer immunotherapy. The interactions between the immune system and cancer cells are continuous, dynamic, and evolving from the initial establishment of a cancer cell to the development of metastatic disease, which is dependent on immune evasion. As the molecular mechanisms of resistance to immunotherapy are elucidated, actionable strategies to prevent or treat them may be derived to improve clinical outcomes for patients.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                18 February 2021
                24 February 2021
                March 2021
                24 August 2021
                : 591
                : 7849
                : 306-311
                Affiliations
                [1 ]Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA.
                [2 ]Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA.
                Author notes
                [*]

                These authors contributed equally to this work.

                Contributions

                S.A.L. and J.W. designed and performed in vitro and in vivo experiments, analyzed data, and wrote the manuscript; T.-L.M.N. designed, performed, and analyzed cellular experiments; H.S. and Y.D. performed bioinformatic analyses; W.S. and N.M.C. performed protein prenylation-related experiments; G.P. performed metabolomic tracing experiments; L.L. and J.S. helped with molecular experiments; P.V. performed immunohistochemistry analysis and provided histopathology scoring; and H.C. helped design experiments, co-wrote the manuscript, and provided overall direction.

                Correspondence should be addressed to: Hongbo Chi, Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA. Phone: 901-595-6282; Fax: 901-595-5766; hongbo.chi@ 123456stjude.org
                Article
                NIHMS1662735
                10.1038/s41586-021-03235-6
                8168716
                33627871
                204d931d-5ca6-4fcc-bc8e-26e8934b0f58

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