22
views
0
recommends
+1 Recommend
2 collections
    1
    shares

          The flagship journal of the Society for Endocrinology. Learn more

      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Androgen deprivation therapy promotes an obesity-like microenvironment in periprostatic fat

      research-article

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Prostate cancer is a leading cause of morbidity and cancer-related death worldwide. Androgen deprivation therapy (ADT) is the cornerstone of management for advanced disease. The use of these therapies is associated with multiple side effects, including metabolic syndrome and truncal obesity. At the same time, obesity has been associated with both prostate cancer development and disease progression, linked to its effects on chronic inflammation at a tissue level. The connection between ADT, obesity, inflammation and prostate cancer progression is well established in clinical settings; however, an understanding of the changes in adipose tissue at the molecular level induced by castration therapies is missing. Here, we investigated the transcriptional changes in periprostatic fat tissue induced by profound ADT in a group of patients with high-risk tumours compared to a matching untreated cohort. We find that the deprivation of androgen is associated with a pro-inflammatory and obesity-like adipose tissue microenvironment. This study suggests that the beneficial effect of therapies based on androgen deprivation may be partially counteracted by metabolic and inflammatory side effects in the adipose tissue surrounding the prostate.

          Related collections

          Most cited references40

          • Record: found
          • Abstract: found
          • Article: not found

          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
            • Record: found
            • Abstract: found
            • Article: not found

            Androgen signaling negatively controls group 2 innate lymphoid cells

            At the onset of adolescence, asthma becomes less prevalent in males than in females, suggesting a protective role of male sex hormones. Here, Laffont et al. show that androgens negatively control ILC2 development and ILC2-driven lung inflammation in male mice.
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Immunoglobulin and T Cell Receptor Genes: IMGT® and the Birth and Rise of Immunoinformatics

              IMGT®, the international ImMunoGeneTics information system® 1, (CNRS and Université Montpellier 2) is the global reference in immunogenetics and immunoinformatics. By its creation in 1989, IMGT® marked the advent of immunoinformatics, which emerged at the interface between immunogenetics and bioinformatics. IMGT® is specialized in the immunoglobulins (IG) or antibodies, T cell receptors (TR), major histocompatibility (MH), and proteins of the IgSF and MhSF superfamilies. IMGT® has been built on the IMGT-ONTOLOGY axioms and concepts, which bridged the gap between genes, sequences, and three-dimensional (3D) structures. The concepts include the IMGT® standardized keywords (concepts of identification), IMGT® standardized labels (concepts of description), IMGT® standardized nomenclature (concepts of classification), IMGT unique numbering, and IMGT Colliers de Perles (concepts of numerotation). IMGT® comprises seven databases, 15,000 pages of web resources, and 17 tools, and provides a high-quality and integrated system for the analysis of the genomic and expressed IG and TR repertoire of the adaptive immune responses. Tools and databases are used in basic, veterinary, and medical research, in clinical applications (mutation analysis in leukemia and lymphoma) and in antibody engineering and humanization. They include, for example IMGT/V-QUEST and IMGT/JunctionAnalysis for nucleotide sequence analysis and their high-throughput version IMGT/HighV-QUEST for next-generation sequencing (500,000 sequences per batch), IMGT/DomainGapAlign for amino acid sequence analysis of IG and TR variable and constant domains and of MH groove domains, IMGT/3Dstructure-DB for 3D structures, contact analysis and paratope/epitope interactions of IG/antigen and TR/peptide-MH complexes and IMGT/mAb-DB interface for therapeutic antibodies and fusion proteins for immune applications (FPIA).

                Author and article information

                Journal
                Endocr Connect
                Endocr Connect
                EC
                Endocrine Connections
                Bioscientifica Ltd (Bristol )
                2049-3614
                May 2019
                04 April 2019
                : 8
                : 5
                : 547-558
                Affiliations
                [1 ]Bioinformatics Division , Walter and Eliza Hall Institute, Parkville, Victoria, Australia
                [2 ]Department of Surgery , The University of Melbourne, Parkville, Victoria, Australia
                [3 ]Department of Urology , Royal Melbourne Hospital, Parkville, Victoria, Australia
                [4 ]Australian Prostate Cancer Research Centre Epworth , Richmond, Victoria, Australia
                [5 ]Ontario Institute for Cancer Research , Toronto, Canada
                [6 ]Princess Margaret Cancer Centre , University Health Network, Toronto, Canada
                [7 ]Peter MacCallum Cancer Centre , Melbourne, Victoria, Australia
                [8 ]Department of Medical Biology , University of Melbourne, Melbourne, Victoria, Australia
                [9 ]Sir Peter MacCallum Department of Oncology , University of Melbourne, Melbourne, Victoria, Australia
                [10 ]Department of Mathematics and Statistics , University of Melbourne, Melbourne, Victoria, Australia
                [11 ]Department of Urology , Frankston Hospital, Frankston, Victoria, Australia
                Author notes
                Correspondence should be addressed to N M Corcoran: niallmcorcoran@ 123456gmail.com
                Article
                EC-19-0029
                10.1530/EC-19-0029
                6499921
                30959474
                70e4087e-db7a-45ac-8574-ab81f7f537b3
                © 2019 The authors

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 14 March 2019
                : 04 April 2019
                Categories
                Research

                prostate,cancer,obesity,adipose tissue,transcriptomics,transcriptomic econvolution

                Comments

                Comment on this article

                Related Documents Log