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      TNF is a potential therapeutic target to suppress prostatic inflammation and hyperplasia in autoimmune disease

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          Abstract

          Autoimmune (AI) diseases can affect many organs; however, the prostate has not been considered to be a primary target of these systemic inflammatory processes. Here, we utilize medical record data, patient samples, and in vivo models to evaluate the impact of inflammation, as seen in AI diseases, on prostate tissue. Human and mouse tissues are used to examine whether systemic targeting of inflammation limits prostatic inflammation and hyperplasia. Evaluation of 112,152 medical records indicates that benign prostatic hyperplasia (BPH) prevalence is significantly higher among patients with AI diseases. Furthermore, treating these patients with tumor necrosis factor (TNF)-antagonists significantly decreases BPH incidence. Single-cell RNA-seq and in vitro assays suggest that macrophage-derived TNF stimulates BPH-derived fibroblast proliferation. TNF blockade significantly reduces epithelial hyperplasia, NFκB activation, and macrophage-mediated inflammation within prostate tissues. Together, these studies show that patients with AI diseases have a heightened susceptibility to BPH and that reducing inflammation with a therapeutic agent can suppress BPH.

          Abstract

          Reduction of systemic autoimmunity using TNF blockers may also reduce inflammatory diseases in other organs. Here, the authors use a patient database and scRNA-seq to link autoimmune diseases to benign prostatic hyperplasia (BPH), and demonstrate that prostatic hyperplasia is reduced by TNF blockers in humans and mice.

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          Most cited references78

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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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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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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                Author and article information

                Contributors
                shayward@northshore.org
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                19 April 2022
                19 April 2022
                2022
                : 13
                : 2133
                Affiliations
                [1 ]GRID grid.170205.1, ISNI 0000 0004 1936 7822, Department of Surgery, NorthShore University HealthSystem, , an Academic Affiliate of the University of Chicago Pritzker School of Medicine, ; Evanston, IL 60201 USA
                [2 ]GRID grid.259870.1, ISNI 0000 0001 0286 752X, Department of Cancer Biology, Meharry Medical College, ; Nashville, TN 37208 USA
                [3 ]GRID grid.240614.5, ISNI 0000 0001 2181 8635, Department of Cancer Genetics and Genomics, Roswell Park Comprehensive Cancer Center, ; Buffalo, NY 14263 USA
                [4 ]GRID grid.169077.e, ISNI 0000 0004 1937 2197, Department of Comparative Pathobiology, , Purdue University, ; West Lafayette, IN 47907 USA
                [5 ]GRID grid.169077.e, ISNI 0000 0004 1937 2197, Purdue Center for Cancer Research, , Purdue University, ; West Lafayette, IN 47907 USA
                [6 ]GRID grid.240372.0, ISNI 0000 0004 0400 4439, Biostatistics and Research Informatics, , NorthShore University HealthSystem, ; Evanston, IL 60201 USA
                [7 ]GRID grid.169077.e, ISNI 0000 0004 1937 2197, Department of Medicinal Chemistry and Molecular Pharmacology, , Purdue University, ; West Lafayette, IN 47907 USA
                [8 ]GRID grid.240614.5, ISNI 0000 0001 2181 8635, Department of Urology, Roswell Park Comprehensive Cancer Center, ; Buffalo, NY 14263 USA
                [9 ]GRID grid.239578.2, ISNI 0000 0001 0675 4725, Present Address: Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, ; Cleveland, OH 44195 USA
                [10 ]GRID grid.260026.0, ISNI 0000 0004 0372 555X, Present Address: Department of Nephro-Urologic Surgery and Andrology, , Mie University Graduate School of Medicine, ; Mie, Japan
                [11 ]GRID grid.253615.6, ISNI 0000 0004 1936 9510, Present Address: GW Cancer Center, , The George Washington University, ; Washington, DC 20052 USA
                Author information
                http://orcid.org/0000-0002-5614-9221
                http://orcid.org/0000-0003-1435-5075
                http://orcid.org/0000-0002-1819-7070
                http://orcid.org/0000-0002-4314-2282
                http://orcid.org/0000-0002-2569-4163
                http://orcid.org/0000-0002-0065-1474
                http://orcid.org/0000-0003-1781-9023
                http://orcid.org/0000-0003-4221-5416
                http://orcid.org/0000-0002-6059-6550
                Article
                29719
                10.1038/s41467-022-29719-1
                9018703
                35440548
                064989de-0d27-4f15-912a-b6c6ad44a546
                © The Author(s) 2022

                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
                : 19 March 2021
                : 24 March 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000062, U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases);
                Award ID: 1P20DK116185
                Award ID: 1P20DK116185
                Award ID: R01DK117906
                Award Recipient :
                Funded by: Walther Cancer Foundation
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases)
                Funded by: Collaborative Core for Cancer Bioinformatics Rob Brooks Fund for Precision Prostate Cancer Care
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                chronic inflammation,autoimmune diseases,translational immunology,prostate,tumour-necrosis factors

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