Epigenetic Reprogramming at Estrogen-Receptor Binding Sites Alters 3D Chromatin Landscape in Endocrine-Resistant Breast Cancer
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A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
A Clinicopathological and Molecular Genetic Analysis of Low-Grade Glioma in Adults
A CLINICOPATHOLOGICAL AND MOLECULAR GENETIC ANALYSIS OF LOW-GRADE GLIOMA IN ADULTS Presented by ANUSHREE SINGH MSc A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy Brain Tumour Research Centre Research Institute in Healthcare Sciences Faculty of Science and Engineering University of Wolverhampton November 2014 i DECLARATION This work or any part thereof has not previously been presented in any form to the University or to any other body whether for the purposes of assessment, publication or for any other purpose (unless otherwise indicated). Save for any express acknowledgments, references and/or bibliographies cited in the work, I confirm that the intellectual content of the work is the result of my own efforts and of no other person. The right of Anushree Singh to be identified as author of this work is asserted in accordance with ss.77 and 78 of the Copyright, Designs and Patents Act 1988. At this date copyright is owned by the author. Signature: Anushree Date: 30th November 2014 ii ABSTRACT The aim of the study was to identify molecular markers that can determine progression of low grade glioma. This was done using various approaches such as IDH1 and IDH2 mutation analysis, MGMT methylation analysis, copy number analysis using array comparative genomic hybridisation and identification of differentially expressed miRNAs using miRNA microarray analysis. IDH1 mutation was present at a frequency of 71% in low grade glioma and was identified as an independent marker for improved OS in a multivariate analysis, which confirms the previous findings in low grade glioma studies. -
Nursing Genetic Research: New Insights Linking Breast Cancer Genetics and Bone Density
healthcare Concept Paper Nursing Genetic Research: New Insights Linking Breast Cancer Genetics and Bone Density 1, 2, 3, Antonio Sanchez-Fernandez y, Raúl Roncero-Martin y, Jose M. Moran * , Jesus Lavado-García 2 , Luis Manuel Puerto-Parejo 2 , Fidel Lopez-Espuela 2, Ignacio Aliaga 3 and María Pedrera-Canal 2 1 Servicio de Tocoginecología, Complejo Hospitalario de Cáceres, 10004 Cáceres, Spain; [email protected] 2 Metabolic Bone Diseases Research Group, Nursing Department, Nursing and Occupational Therapy College, University of Extremadura, Avd. Universidad s/n, 10003 Cáceres, Spain; [email protected] (R.R.-M.); [email protected] (J.L.-G.); [email protected] (L.M.P.-P.); fi[email protected] (F.L.-E.); [email protected] (M.P.-C.) 3 Departamento de Estomatología II, Universidad Complutense de Madrid, 28040 Madrid, Spain; [email protected] * Correspondence: [email protected]; Tel.: +34-927-257450 Both authors contributed equally to this work. y Received: 25 April 2020; Accepted: 11 June 2020; Published: 15 June 2020 Abstract: Nursing research is expected to provide options for the primary prevention of disease and health promotion, regardless of pathology or disease. Nurses have the skills to develop and lead research that addresses the relationship between genetic factors and health. Increasing genetic knowledge and research capacity through interdisciplinary cooperation as well as the development of research resources, will accelerate the rate at which nurses contribute to the knowledge about genetics and health. There are currently different fields in which knowledge can be expanded by research developed from the nursing field. Here, we present an emerging field of research in which it is hypothesized that genetics may affect bone metabolism. -
Genes in a Refined Smith-Magenis Syndrome Critical Deletion Interval on Chromosome 17P11.2 and the Syntenic Region of the Mouse
Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Article Genes in a Refined Smith-Magenis Syndrome Critical Deletion Interval on Chromosome 17p11.2 and the Syntenic Region of the Mouse Weimin Bi,1,6 Jiong Yan,1,6 Paweł Stankiewicz,1 Sung-Sup Park,1,7 Katherina Walz,1 Cornelius F. Boerkoel,1 Lorraine Potocki,1,3 Lisa G. Shaffer,1 Koen Devriendt,4 Małgorzata J.M. Nowaczyk,5 Ken Inoue,1 and James R. Lupski1,2,3,8 Departments of 1Molecular & Human Genetics, 2Pediatrics, Baylor College of Medicine, 3Texas Children’s Hospital, Houston, Texas 77030, USA; 4Centre for Human Genetics, University Hospital Gasthuisberg, Catholic University of Leuven, B-3000 Leuven, Belgium; 5Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario L8S 4J9, Canada Smith-Magenis syndrome (SMS) is a multiple congenital anomaly/mental retardation syndrome associated with behavioral abnormalities and sleep disturbance. Most patients have the same ∼4 Mb interstitial genomic deletion within chromosome 17p11.2. To investigate the molecular bases of the SMS phenotype, we constructed BAC/PAC contigs covering the SMS common deletion interval and its syntenic region on mouse chromosome 11. Comparative genome analysis reveals the absence of all three ∼200-kb SMS-REP low-copy repeats in the mouse and indicates that the evolution of SMS-REPs was accompanied by transposition of adjacent genes. Physical and genetic map comparisons in humans reveal reduced recombination in both sexes. Moreover, by examining the deleted regions in SMS patients with unusual-sized deletions, we refined the minimal Smith-Magenis critical region (SMCR) to an ∼1.1-Mb genomic interval that is syntenic to an ∼1.0-Mb region in the mouse. -
Repeated BCG Treatment of Mouse Bladder Selectively Stimulates Small
BMC Cancer BioMed Central Research article Open Access Repeated BCG treatment of mouse bladder selectively stimulates small GTPases and HLA antigens and inhibits single-spanning uroplakins Marcia R Saban1, Helen L Hellmich2, Cindy Simpson1, Carole A Davis1, Mark L Lang3, Michael A Ihnat4, Michael A O'Donnell5, Xue-Ru Wu6 and Ricardo Saban*1 Address: 1Department of Physiology, The University Oklahoma Health Sciences Center, Oklahoma City, USA, 2Department of Anesthesiology, University of Texas Medical Branch, Galveston, USA, 3Department of Microbiology and Immunology The University Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA, 4Department of Cell Biology, The University Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA, 5Department of Urology, University of Iowa, UI Hospitals and Clinics, Iowa City, Iowa 52242-1089, USA and 6Department of Urology, New York University, School of Medicine, New York, NY 10016, USA Email: Marcia R Saban - [email protected]; Helen L Hellmich - [email protected]; Cindy Simpson - [email protected]; Carole A Davis - [email protected]; Mark L Lang - [email protected]; Michael A Ihnat - [email protected]; Michael A O'Donnell - [email protected]; Xue-Ru Wu - [email protected]; Ricardo Saban* - [email protected] * Corresponding author Published: 2 November 2007 Received: 29 August 2007 Accepted: 2 November 2007 BMC Cancer 2007, 7:204 doi:10.1186/1471-2407-7-204 This article is available from: http://www.biomedcentral.com/1471-2407/7/204 © 2007 Saban et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Supplementary Material
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Page 1 / 45 SUPPLEMENTARY MATERIAL Appendix A1: Neuropsychological protocol. Appendix A2: Description of the four cases at the transitional stage. Table A1: Clinical status and center proportion in each batch. Table A2: Complete output from EdgeR. Table A3: List of the putative target genes. Table A4: Complete output from DIANA-miRPath v.3. Table A5: Comparison of studies investigating miRNAs from brain samples. Figure A1: Stratified nested cross-validation. Figure A2: Expression heatmap of miRNA signature. Figure A3: Bootstrapped ROC AUC scores. Figure A4: ROC AUC scores with 100 different fold splits. Figure A5: Presymptomatic subjects probability scores. Figure A6: Heatmap of the level of enrichment in KEGG pathways. Kmetzsch V, et al. J Neurol Neurosurg Psychiatry 2021; 92:485–493. doi: 10.1136/jnnp-2020-324647 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Appendix A1. Neuropsychological protocol The PREV-DEMALS cognitive evaluation included standardized neuropsychological tests to investigate all cognitive domains, and in particular frontal lobe functions. The scores were provided previously (Bertrand et al., 2018). Briefly, global cognitive efficiency was evaluated by means of Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Frontal executive functions were assessed with Frontal Assessment Battery (FAB), forward and backward digit spans, Trail Making Test part A and B (TMT-A and TMT-B), Wisconsin Card Sorting Test (WCST), and Symbol-Digit Modalities test. -
Binding Specificities of Human RNA Binding Proteins Towards Structured
bioRxiv preprint doi: https://doi.org/10.1101/317909; this version posted March 1, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Binding specificities of human RNA binding proteins towards structured and linear 2 RNA sequences 3 4 Arttu Jolma1,#, Jilin Zhang1,#, Estefania Mondragón4,#, Teemu Kivioja2, Yimeng Yin1, 5 Fangjie Zhu1, Quaid Morris5,6,7,8, Timothy R. Hughes5,6, Louis James Maher III4 and Jussi 6 Taipale1,2,3,* 7 8 9 AUTHOR AFFILIATIONS 10 11 1Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden 12 2Genome-Scale Biology Program, University of Helsinki, Helsinki, Finland 13 3Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom 14 4Department of Biochemistry and Molecular Biology and Mayo Clinic Graduate School of 15 Biomedical Sciences, Mayo Clinic College of Medicine and Science, Rochester, USA 16 5Department of Molecular Genetics, University of Toronto, Toronto, Canada 17 6Donnelly Centre, University of Toronto, Toronto, Canada 18 7Edward S Rogers Sr Department of Electrical and Computer Engineering, University of 19 Toronto, Toronto, Canada 20 8Department of Computer Science, University of Toronto, Toronto, Canada 21 #Authors contributed equally 22 *Correspondence: [email protected] 23 24 25 SUMMARY 26 27 Sequence specific RNA-binding proteins (RBPs) control many important 28 processes affecting gene expression. They regulate RNA metabolism at multiple 29 levels, by affecting splicing of nascent transcripts, RNA folding, base modification, 30 transport, localization, translation and stability. Despite their central role in most 31 aspects of RNA metabolism and function, most RBP binding specificities remain 32 unknown or incompletely defined. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Greb1is a Novel Androgen-Regulated Gene Required for Prostate Cancer Growth
The Prostate GREB1is a Novel Androgen-Regulated Gene Required for Prostate Cancer Growth James M. Rae,1* Michael D. Johnson,2 Kevin E. Cordero,1 Joshua O. Scheys,1 Jose´ M. Larios,1 Marco M. Gottardis,3 Kenneth J. Pienta,1 and Marc E. Lippman1 1Division of Hematology Oncology,Department of Internal Medicine, University of Michigan Medical Center, Ann Arbor,Michigan 2Department of Oncology,Georgetown University,Washington, District of Columbia 3Department of Discovery Biology,Bristol^ Myers Squibb Pharmaceutical Research Institute, Princeton, New Jersey BACKGROUND. Gene regulated in breast cancer 1 (GREB1) is a novel estrogen-regulated gene shown to play a pivotal role in hormone-stimulated breast cancer growth. GREB1 is expressed in the prostate and its putative promoter contains potential androgen receptor (AR) response elements. METHODS. We investigated the effects of androgens on GREB1 expression and its role in androgen-dependent prostate cancer growth. RESULTS. Real-time PCR demonstrated high level GREB1 expression in benign prostatic hypertrophy (BPH), localized prostate cancer (L-PCa), and hormone refractory prostate cancer (HR-PCa). Androgen treatment of AR-positive prostate cancer cells induced dose-dependent GREB1 expression, which was blocked by anti-androgens. AR binding to the GREB1 promoter was confirmed by chromatin immunoprecipitation (ChIP) assays. Suppression of GREB1 by RNA interference blocked androgen-stimulated LNCaP cell proliferation. CONCLUSIONS. GREB1 is expressed in proliferating prostatic tissue and prostate -
PREX1 Polyclonal Antibody
PREX1 Polyclonal Antibody Catalog No : YN1041 Reactivity : Human,Mouse Applications : WB,ELISA Gene Name : PREX1 KIAA1415 Protein Name : Phosphatidylinositol 3,4,5-trisphosphate-dependent Rac exchanger 1 protein (P- Rex1) (PtdIns(3,4,5)-dependent Rac exchanger 1) Human Gene Id : 57580 Human Swiss Prot Q8TCU6 No : Mouse Swiss Prot Q69ZK0 No : Immunogen : Synthesized peptide derived from human protein . at AA range: 340-420 Specificity : PREX1 Polyclonal Antibody detects endogenous levels of protein. Formulation : Liquid in PBS containing 50% glycerol, and 0.02% sodium azide. Source : Rabbit Dilution : WB 1:500-2000 ELISA 1:5000-20000 Purification : The antibody was affinity-purified from rabbit antiserum by affinity- chromatography using epitope-specific immunogen. Concentration : 1 mg/ml Storage Stability : -20°C/1 year Observed Band : 182 Cell Pathway : Chemokine, 1 / 2 Background : phosphatidylinositol-3,4,5-trisphosphate dependent Rac exchange factor 1(PREX1) Homo sapiens The protein encoded by this gene acts as a guanine nucleotide exchange factor for the RHO family of small GTP-binding proteins (RACs). It has been shown to bind to and activate RAC1 by exchanging bound GDP for free GTP. The encoded protein, which is found mainly in the cytoplasm, is activated by phosphatidylinositol-3,4,5-trisphosphate and the beta-gamma subunits of heterotrimeric G proteins. [provided by RefSeq, Jul 2008], Function : function:Functions as a RAC guanine nucleotide exchange factor (GEF), which activates the Rac proteins by exchanging bound GDP for free GTP. Its activity is synergistically activated by phosphatidylinositol-3,4,5-triphosphate and the beta gamma subunits of heterotrimeric G protein. May function downstream of heterotrimeric G proteins in neutrophils.,similarity:Contains 1 DEP domain.,similarity:Contains 1 DH (DBL-homology) domain.,similarity:Contains 1 PDZ (DHR) domain.,similarity:Contains 2 PH domains.,subcellular location:Mainly cytosolic.