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      Immune suppressive activity of myeloid-derived suppressor cells in cancer requires inactivation of the type I interferon pathway

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          Abstract

          Myeloid-derived suppressor cells (MDSC) are pathologically activated neutrophils and monocytes with potent immune suppressive activity. These cells play an important role in accelerating tumor progression and undermining the efficacy of anti-cancer therapies. The natural mechanisms limiting MDSC activity are not well understood. Here, we present evidence that type I interferons (IFN1) receptor signaling serves as a universal mechanism that restricts acquisition of suppressive activity by these cells. Downregulation of the IFNAR1 chain of this receptor is found in MDSC from cancer patients and mouse tumor models. The decrease in IFNAR1 depends on the activation of the p38 protein kinase and is required for activation of the immune suppressive phenotype. Whereas deletion of IFNAR1 is not sufficient to convert neutrophils and monocytes to MDSC, genetic stabilization of IFNAR1 in tumor bearing mice undermines suppressive activity of MDSC and has potent antitumor effect. Stabilizing IFNAR1 using inhibitor of p38 combined with the interferon induction therapy elicits a robust anti-tumor effect. Thus, negative regulatory mechanisms of MDSC function can be exploited therapeutically.

          Abstract

          The role of type I interferon signalling in the control of myeloid derived suppressor cells (MDSC) activity remains controversial. Here the authors show that downregulation of type I interferon receptor is observed in MDSC from cancer patients and tumor-bearing mice and is required for the activation of their immune suppressive properties.

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          Most cited references79

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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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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              Statistical significance for genomewide studies.

              With the increase in genomewide experiments and the sequencing of multiple genomes, the analysis of large data sets has become commonplace in biology. It is often the case that thousands of features in a genomewide data set are tested against some null hypothesis, where a number of features are expected to be significant. Here we propose an approach to measuring statistical significance in these genomewide studies based on the concept of the false discovery rate. This approach offers a sensible balance between the number of true and false positives that is automatically calibrated and easily interpreted. In doing so, a measure of statistical significance called the q value is associated with each tested feature. The q value is similar to the well known p value, except it is a measure of significance in terms of the false discovery rate rather than the false positive rate. Our approach avoids a flood of false positive results, while offering a more liberal criterion than what has been used in genome scans for linkage.
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                Author and article information

                Contributors
                dmitry.gabrilovich@astrazeneca.com
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                19 March 2021
                19 March 2021
                2021
                : 12
                : 1717
                Affiliations
                [1 ]GRID grid.251075.4, ISNI 0000 0001 1956 6678, The Wistar Institute, ; Philadelphia, PA USA
                [2 ]GRID grid.418152.b, AstraZeneca, ; Gaithersburg, MD USA
                [3 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Department of Biomedical Sciences, , School of Veterinary Medicine University of Pennsylvania, ; Philadelphia, PA USA
                [4 ]GRID grid.414316.5, ISNI 0000 0004 0444 1241, Helen F. Graham Cancer Center and Research Institute, ; Newark, DE USA
                [5 ]GRID grid.41891.35, ISNI 0000 0001 2156 6108, Department of Microbiology and Immunology, Montana State University, ; Bozeman, MT USA
                [6 ]GRID grid.16821.3c, ISNI 0000 0004 0368 8293, Present Address: State Key Laboratory of Oncogenes and Related Genes, Stem Cell Research Center, Renji Hospital, , School of Medicine Shanghai Jiao Tong University, ; Shanghai, China
                [7 ]GRID grid.468198.a, ISNI 0000 0000 9891 5233, Present Address: H. Lee Moffitt Cancer Center, ; Tampa, FL USA
                Author information
                http://orcid.org/0000-0001-8021-2967
                http://orcid.org/0000-0002-0136-5103
                http://orcid.org/0000-0001-9913-6407
                Article
                22033
                10.1038/s41467-021-22033-2
                7979850
                33741967
                cec734fe-b2b3-4dc1-87af-64b5e009c6e1
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 4 May 2020
                : 24 February 2021
                Categories
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                © The Author(s) 2021

                Uncategorized
                immune evasion,tumour immunology
                Uncategorized
                immune evasion, tumour immunology

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