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      Nerve growth factor interacts with CHRM4 and promotes neuroendocrine differentiation of prostate cancer and castration resistance

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          Abstract

          Nerve growth factor (NGF) contributes to the progression of malignancy. However, the functional role and regulatory mechanisms of NGF in the development of neuroendocrine prostate cancer (NEPC) are unclear. Here, we show that an androgen-deprivation therapy (ADT)-stimulated transcription factor, ZBTB46, upregulated NGF via ZBTB46 mediated-transcriptional activation of NGF. NGF regulates NEPC differentiation by physically interacting with a G-protein-coupled receptor, cholinergic receptor muscarinic 4 (CHRM4), after ADT. Pharmacologic NGF blockade and NGF knockdown markedly inhibited CHRM4-mediated NEPC differentiation and AKT-MYCN signaling activation. CHRM4 stimulation was associated with ADT resistance and was significantly correlated with increased NGF in high-grade and small-cell neuroendocrine prostate cancer (SCNC) patient samples. Our results reveal a role of the NGF in the development of NEPC that is linked to ZBTB46 upregulation and CHRM4 accumulation. Our study provides evidence that the NGF-CHRM4 axis has potential to be considered as a therapeutic target to impair NEPC progression.

          Abstract

          Here, the authors discover that NGF, upregulated by transcription factor ZBTB46 in prostate cancer exposed to androgen therapy, promotes neuroendocrine differentiation. They show that NGF interacts with the GPCR CHRM4, that both NGF and CHRM4 are upregulated in highly metastatic prostate cancer and that targeting NGF reduces therapy resistance in a mouse xenograft model.

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          Most cited references 78

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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

                Contributors
                1047@tmu.edu.tw
                liuy@tmu.edu.tw
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                4 January 2021
                4 January 2021
                2021
                : 4
                Affiliations
                [1 ]GRID grid.412896.0, ISNI 0000 0000 9337 0481, Department of Pathology, Wan Fang Hospital, , Taipei Medical University, ; Taipei, Taiwan
                [2 ]GRID grid.412896.0, ISNI 0000 0000 9337 0481, Department of Pathology, School of Medicine, College of Medicine, , Taipei Medical University, ; Taipei, Taiwan
                [3 ]GRID grid.412896.0, ISNI 0000 0000 9337 0481, Department of Urology, Wan Fang Hospital, , Taipei Medical University, ; Taipei, Taiwan
                [4 ]GRID grid.412896.0, ISNI 0000 0000 9337 0481, Department of Urology, School of Medicine, College of Medicine, , Taipei Medical University, ; Taipei, Taiwan
                [5 ]GRID grid.412896.0, ISNI 0000 0000 9337 0481, Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, , Taipei Medical University, ; Taipei, Taiwan
                [6 ]GRID grid.38348.34, ISNI 0000 0004 0532 0580, Institute of Information System and Applications, , National Tsing Hua University, ; Hsinchu, Taiwan
                [7 ]GRID grid.418414.c, ISNI 0000 0004 1804 583X, Biologics Development Department, , Institute of Biologics, Development Center for Biotechnology, ; Taipei, Taiwan
                [8 ]GRID grid.412449.e, ISNI 0000 0000 9678 1884, Department of Pathology, The First Affiliated Hospital and College of Basic Medical Sciences, , China Medical University, ; Shenyang, China
                [9 ]GRID grid.412896.0, ISNI 0000 0000 9337 0481, Department of Pathology, Shuang Ho Hospital, , Taipei Medical University, ; New Taipei City, Taiwan
                [10 ]GRID grid.412896.0, ISNI 0000 0000 9337 0481, Department of Pathology, School of Medicine, College of Medicine, , Taipei Medical University, ; Taipei, Taiwan
                [11 ]GRID grid.28665.3f, ISNI 0000 0001 2287 1366, Genomics Research Center, , Academia Sinica, ; Taipei, Taiwan
                [12 ]GRID grid.189509.c, ISNI 0000000100241216, Department of Pathology, , Duke University Medical Center, ; Durham, NC USA
                Article
                1549
                10.1038/s42003-020-01549-1
                7782543
                33398073
                © 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/.

                Funding
                Funded by: FundRef https://doi.org/10.13039/501100004663, Ministry of Science and Technology, Taiwan (Ministry of Science and Technology of Taiwan);
                Award ID: MOST108-2320-B-038-047
                Award ID: MOST108-2628-B-038-001
                Award ID: MOST109-2326-B-038-001-MY3
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100004700, Taipei Medical University (TMU);
                Award ID: 108TMU-WFH-03
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100004737, National Health Research Institutes (NHRI);
                Award ID: NHRI-EX109-10702BI
                Award Recipient :
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                © The Author(s) 2021

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