The Transcriptional and Epigenetic Role of Brd4 in the Regulation of the Cellular Stress Response

Total Page:16

File Type:pdf, Size:1020Kb

The Transcriptional and Epigenetic Role of Brd4 in the Regulation of the Cellular Stress Response THE TRANSCRIPTIONAL AND EPIGENETIC ROLE OF BRD4 IN THE REGULATION OF THE CELLULAR STRESS RESPONSE INAUGURAL-DISSERTATION to obtain the academic degree Doctor rerum naturalium (Dr. rer. nat.) submitted to the Department of Biology, Chemistry and Pharmacy of Freie Universität Berlin by Michelle Hussong from Zweibrücken 2015 Die vorliegende Arbeit wurde im Zeitraum von Juli 2012 bis September 2015 am Max- Planck-Institut für Molekulare Genetik in Berlin sowie an der Universität zu Köln unter der Leitung von Frau Prof. Dr. Dr. Michal-Ruth Schweiger angefertigt. 1. Gutachter: Prof. Dr. Dr. Michal-Ruth Schweiger 2. Gutachter: Prof. Dr. Rupert Mutzel Disputation am 07.12.2015 ACKNOWLEDGMENT ACKNOWLEDGMENT This dissertation would not have been possible without the guidance and the help of many people who in one way or another contributed to the preparation and completion of this study. Firstly, I would like to express my sincere gratitude to my advisor Prof. Dr. Dr. Michal-Ruth Schweiger, for her continuous support throughout my PhD study, for her patience, motivation, and immense knowledge. I am eminently thankful for the multiple possibilities she gave me to work on this interesting and challenging field of research. I also want to thank Professor Dr. Rupert Mutzel for taking the time of being my second supervisor. My sincere thanks also goes to Prof. Dr. Hans Lehrach for having given me the opportunity to do my PhD thesis in the extraordinary and inspiring environment at the Max-Planck- Institute for Molecular Genetics in Berlin. Especially, the multitude of technologies and knowledge in his department made my work successful. This thesis would not have been possible without the help of many people. Many thanks to Prof. Dr. Monica Hirsch-Kauffmann for her never-ending support, inspiring suggestions and interesting discussions. A special thanks to Dr. Martin Kerick, who performed all the sequencing data analysis. This work would not have been possible without his invaluable knowledge and support. In this regard I also want to say thanks to the sequencing core facility around Dr. Bernd Timmermann. I'd especially like to thank Dr. Christian Kähler and Dr. Sylvia Krobitsch for their huge knowledge in the field of heat stress research, for performing the immunofluorescence experiments and for their feedback and suggestions on the manuscript. Furthermore, I'd like to thank Dr. Jörg Isenssee for conducting the quantitative high-content screening microscopy. I want to thank all former members of the Schweiger lab, especially Dr. Stefan Börno and Dr. Andrea Wunderlich for their support in experiments, for interesting and fruitful discussions and for their contribution and comments on the manuscript. Many thanks also to Nada Kumer who was always a great help in the lab. I’m very grateful to my present colleagues for the friendly atmosphere in the lab. Many thanks to Christina Grimm, Sabrina Grasse, Susann Siebert and Anne Steinbach who all contributed to making our lab a happy place. I ACKNOWLEDGMENT My special thanks go to Sabrina Grasse for all the fun we have had in the last three years. I am especially grateful to get such a good friend even outside of work. I also gratefully acknowledge the “Studienstiftung des Deutschen Volkes” for their financial support throughout my PhD study. Last but not the least, my deepest debt is to my family, my parents and my sister for their everlasting support and encouragement throughout writing this thesis and my whole life in general. II ZUSAMMENFASSUNG ZUSAMMENFASSUNG Die zelluläre Stressantwort umfasst die Anpassung eines Organismus auf umweltbedingte und endogene Stressfaktoren, welche durch eine Vielzahl von molekularen Prozessen gesteuert wird. Eine Deregulierung dieser Antwort ist ein Indikator und möglicher Auslöser vieler Krankheiten, insbesondere Tumorerkrankungen, und bietet daher einen interessanten Angriffspunkt für Therapien. Ein sehr wichtiges und für die Tumorforschung auch aus therapeutischer Sicht äußerst vielversprechendes Protein ist das Bromodomänen enthaltende Protein 4, kurz BRD4. BRD4 spielt in sehr vielen Bereichen der Zelle eine wichtige Rolle, unter anderem als epigenetischer Sensor sowie transkriptioneller Regulator und ist damit ein wichtiges Bindeglied zwischen dem transkriptionellen Prozess und epigenetischen Mustern. Ziel dieser Arbeit war es, die Rolle von BRD4 bei der epigenetischen, als auch der transkriptionellen Regulation im Verlauf von zellulären Stressantworten zu untersuchen. Durch Genexpressionsanalysen in BRD4-defizienten Zellen, sowie Chromatin-Protein- Interaktionsstudien konnte ich 52 BRD4-regulierte Zielgene identifizieren, welche vor allem für Proteine der oxidativen Stressantwort sowie der Hitzestressantwort kodieren. Weiterführende Analysen identifizierten BRD4 als einen wichtigen Modulator eines der wichtigsten, mit oxidativem Stress assoziierten Signalwege, dem KEAP1/NRF2 Signalweg. Durch eine transkriptionelle Regulierung von KEAP1 kontrolliert BRD4 die Aktivität des Transkriptionsfaktors NRF2, welche wiederum die Expression zytoprotektiver Gene induziert. Eine Hemmung der BRD4 Aktivität führt unter Stress-Bedingungen zu einer Verringerung an reaktiven Sauerstoffspezies (ROS) in der Zelle und zu einem Schutz der Zellen vor oxidativem Stress-vermittelten Zelltod. Zudem konnte ich anhand einer Vielzahl von molekularbiologischen Experimenten zeigen, dass BRD4 direkt die Expression von HMOX1, einem ROS-regulierendes Protein, über eine Bindung an den Transkriptionsfaktor SP1, reguliert. Dieses transkriptionelle Regulationsnetzwerk scheint bei Prostatakrebs gestört zu sein, was möglicherweise eine zentrale Rolle beim malignen Prozess der Tumorentstehung spielt. Zusätzlich zu seiner Funktion bei der transkriptionellen Regulation gibt es bereits einige Hinweise, die eine Rolle von BRD4 bei dem zellulären Spleißprozess wahrscheinlich machen. III ZUSAMMENFASSUNG Im Rahmen meiner Arbeit konnte ich zeigen, dass BRD4 eine wichtige Rolle bei dem Spleißvorgang unter Hitzestress spielt. So fördert es das, unter Hitzestress beeinträchtigte, Herausschneiden von Introns. Weitere molekularbiologische Analysen zeigten, dass unter diesen Stressbedingungen BRD4 in sub-nukleären Strukturen, den sogenannten „nuclear stress bodies“, rekrutiert wird. Dort aktiviert BRD4, zusammen mit dem Hitzeschock Faktor HSF1, die Transkription von nicht-kodierenden Sat III RNAs. Diese werden als wichtige Modulatoren der Stress- induzierten Spleißreaktion diskutiert. Zusammenfassend konnte ich zeigen, dass BRD4 sowohl in die Transkiption, als auch in den Spleissprozess unter zellulärem Stress involviert ist. Dies stellt eine weitere Grundlage dar, Pathomechanismen der Tumorentstehung besser zu verstehen, aber auch, um neue Therapieansätze zu entwickeln. IV SUMMARY SUMMARY The cellular stress response describes the adaptation of an organism to environmental stressors by a variety of molecular changes. Deregulation of this response is an indicator and possible promoter of many diseases, in particular cancers, and therefore offers an interesting target for tumor therapies. A for the tumor therapy very promising target is the bromodomains containing protein 4 (BRD4). BRD4 plays a significant role in many cellular processes: It is an epigenetic reader and transcriptional regulator and therefore links the transcription process to epigenetic patterns. The aim of this study was to further understand the role of BRD4 in the epigenetic and transcriptional regulation of cellular stress responses. Through genome-wide gene expression profiling in BRD4-deficient cells, and chromatin-protein interaction studies, I was able to identify 52 BRD4-regulated target genes, mainly encoded for proteins of the oxidative stress - and heat stress response. Further analyses highlighted BRD4 as regulator of the oxidative stress-induced KEAP1/NRF2 signalling pathway. By regulating the transcription of KEAP1, BRD4 modulates the activity of the transcription factor NRF2 and, in turn, the expression of cyto-protective genes under stress. An inhibition of BRD4 resulted in decreased reactive oxygen species (ROS) production and protected cells from oxidative stress mediated cell death. In addition, BRD4 also interacts with the transcription factor SP1 and directly regulates the expression of HMOX1, a ROS reducing protein. Remarkably, this regulatory network is disrupted in prostate cancer and thus might play a central role in tumorigenesis. Furthermore, using RNA-sequencing analyses of BRD4-deficient and heat treated cells I showed that a reduction of BRD4 expression increased the heat shock-mediated splicing inhibition, in particular intron retentions. Subsequent experiments revealed that under heat stress BRD4 binds to the heat shock factor 1 (HSF1), which leads to the recruitment of BRD4 to sub-nuclear structures, the so- called "nuclear stress bodies". The translocation of BRD4 is associated with the transcriptional activation of non-coding Sat III RNA expression. Sat III RNAs, in turn, are discussed as important modulators of the stress-induced splicing process. Taken together, my results link BRD4 not only to the transcription machinery, but also to the splicing process under oxidative or heat stress, respectively. This gives additional insights into the mode of action of BRD4 inhibitors and could lay the foundation for the development of new therapeutic strategies. V VI TABLE OF CONTENT TABLE OF CONTENT ACKNOWLEDGMENT .....................................................................................................................
Recommended publications
  • Allele-Specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish
    Allele-specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish by Ailu Chen A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Auburn, Alabama August 1, 2015 Keywords: catfish, interspecific hybrids, allele-specific expression, ribosomal protein Copyright 2015 by Ailu Chen Approved by Zhanjiang Liu, Chair, Professor, School of Fisheries, Aquaculture and Aquatic Sciences Nannan Liu, Professor, Entomology and Plant Pathology Eric Peatman, Associate Professor, School of Fisheries, Aquaculture and Aquatic Sciences Aaron M. Rashotte, Associate Professor, Biological Sciences Abstract Interspecific hybridization results in a vast reservoir of allelic variations, which may potentially contribute to phenotypical enhancement in the hybrids. Whether the allelic variations are related to the downstream phenotypic differences of interspecific hybrid is still an open question. The recently developed genome-wide allele-specific approaches that harness high- throughput sequencing technology allow direct quantification of allelic variations and gene expression patterns. In this work, I investigated allele-specific expression (ASE) pattern using RNA-Seq datasets generated from interspecific catfish hybrids. The objective of the study is to determine the ASE genes and pathways in which they are involved. Specifically, my study investigated ASE-SNPs, ASE-genes, parent-of-origins of ASE allele and how ASE would possibly contribute to heterosis. My data showed that ASE was operating in the interspecific catfish system. Of the 66,251 and 177,841 SNPs identified from the datasets of the liver and gill, 5,420 (8.2%) and 13,390 (7.5%) SNPs were identified as significant ASE-SNPs, respectively.
    [Show full text]
  • Dual Proteome-Scale Networks Reveal Cell-Specific Remodeling of the Human Interactome
    bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. 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. Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome Edward L. Huttlin1*, Raphael J. Bruckner1,3, Jose Navarrete-Perea1, Joe R. Cannon1,4, Kurt Baltier1,5, Fana Gebreab1, Melanie P. Gygi1, Alexandra Thornock1, Gabriela Zarraga1,6, Stanley Tam1,7, John Szpyt1, Alexandra Panov1, Hannah Parzen1,8, Sipei Fu1, Arvene Golbazi1, Eila Maenpaa1, Keegan Stricker1, Sanjukta Guha Thakurta1, Ramin Rad1, Joshua Pan2, David P. Nusinow1, Joao A. Paulo1, Devin K. Schweppe1, Laura Pontano Vaites1, J. Wade Harper1*, Steven P. Gygi1*# 1Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA. 2Broad Institute, Cambridge, MA, 02142, USA. 3Present address: ICCB-Longwood Screening Facility, Harvard Medical School, Boston, MA, 02115, USA. 4Present address: Merck, West Point, PA, 19486, USA. 5Present address: IQ Proteomics, Cambridge, MA, 02139, USA. 6Present address: Vor Biopharma, Cambridge, MA, 02142, USA. 7Present address: Rubius Therapeutics, Cambridge, MA, 02139, USA. 8Present address: RPS North America, South Kingstown, RI, 02879, USA. *Correspondence: [email protected] (E.L.H.), [email protected] (J.W.H.), [email protected] (S.P.G.) #Lead Contact: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.
    [Show full text]
  • 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.
    [Show full text]
  • Serine Arginine-Rich Protein-Dependent Suppression Of
    Serine͞arginine-rich protein-dependent suppression of exon skipping by exonic splicing enhancers El Che´ rif Ibrahim*, Thomas D. Schaal†, Klemens J. Hertel‡, Robin Reed*, and Tom Maniatis†§ *Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115; †Department of Molecular and Cellular Biology, Harvard University, 7 Divinity Avenue, Cambridge, MA 02138; and ‡Department of Microbiology and Molecular Genetics, University of California, Irvine, CA 92697-4025 Contributed by Tom Maniatis, January 28, 2005 The 5؅ and 3؅ splice sites within an intron can, in principle, be joined mechanisms by which exon skipping is prevented. Our data to those within any other intron during pre-mRNA splicing. How- reveal that splicing to the distal 3Ј splice site is suppressed by ever, exons are joined in a strict 5؅ to 3؅ linear order in constitu- proximal exonic sequences and that SR proteins are required for tively spliced pre-mRNAs. Thus, specific mechanisms must exist to this suppression. Thus, SR protein͞exonic enhancer complexes prevent the random joining of exons. Here we report that insertion not only function in exon and splice-site recognition but also play of exon sequences into an intron can inhibit splicing to the a role in ensuring that 5Ј and 3Ј splice sites within the same intron .downstream 3؅ splice site and that this inhibition is independent of are used, thus suppressing exon skipping intron size. The exon sequences required for splicing inhibition were found to be exonic enhancer elements, and their inhibitory Materials and Methods activity requires the binding of serine͞arginine-rich splicing fac- Construction of Plasmids.
    [Show full text]
  • Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
    Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen,
    [Show full text]
  • Nucleolin and Its Role in Ribosomal Biogenesis
    NUCLEOLIN: A NUCLEOLAR RNA-BINDING PROTEIN INVOLVED IN RIBOSOME BIOGENESIS Inaugural-Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf vorgelegt von Julia Fremerey aus Hamburg Düsseldorf, April 2016 2 Gedruckt mit der Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf Referent: Prof. Dr. A. Borkhardt Korreferent: Prof. Dr. H. Schwender Tag der mündlichen Prüfung: 20.07.2016 3 Die vorgelegte Arbeit wurde von Juli 2012 bis März 2016 in der Klinik für Kinder- Onkologie, -Hämatologie und Klinische Immunologie des Universitätsklinikums Düsseldorf unter Anleitung von Prof. Dr. A. Borkhardt und in Kooperation mit dem ‚Laboratory of RNA Molecular Biology‘ an der Rockefeller Universität unter Anleitung von Prof. Dr. T. Tuschl angefertigt. 4 Dedicated to my family TABLE OF CONTENTS 5 TABLE OF CONTENTS TABLE OF CONTENTS ............................................................................................... 5 LIST OF FIGURES ......................................................................................................10 LIST OF TABLES .......................................................................................................12 ABBREVIATION .........................................................................................................13 ABSTRACT ................................................................................................................19 ZUSAMMENFASSUNG
    [Show full text]
  • Cellular and Molecular Signatures in the Disease Tissue of Early
    Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of
    [Show full text]
  • Comprehensive Array CGH of Normal Karyotype Myelodysplastic
    Leukemia (2011) 25, 387–399 & 2011 Macmillan Publishers Limited All rights reserved 0887-6924/11 www.nature.com/leu LEADING ARTICLE Comprehensive array CGH of normal karyotype myelodysplastic syndromes reveals hidden recurrent and individual genomic copy number alterations with prognostic relevance A Thiel1, M Beier1, D Ingenhag1, K Servan1, M Hein1, V Moeller1, B Betz1, B Hildebrandt1, C Evers1,3, U Germing2 and B Royer-Pokora1 1Institute of Human Genetics and Anthropology, Medical Faculty, Heinrich Heine University, Duesseldorf, Germany and 2Department of Hematology, Oncology and Clinical Immunology, Heinrich Heine University, Duesseldorf, Germany About 40% of patients with myelodysplastic syndromes (MDSs) 40–50% of MDS cases have a normal karyotype. MDS patients present with a normal karyotype, and they are facing different with a normal karyotype and low-risk clinical parameters are courses of disease. To advance the biological understanding often assigned into the IPSS low and intermediate-1 risk groups. and to find molecular prognostic markers, we performed a high- resolution oligonucleotide array study of 107 MDS patients In the absence of genetic or biological markers, prognostic (French American British) with a normal karyotype and clinical stratification of these patients is difficult. To better prognosticate follow-up through the Duesseldorf MDS registry. Recurrent these patients, new parameters to identify patients at higher risk hidden deletions overlapping with known cytogenetic aberra- are urgently needed. With the more recently introduced modern tions or sites of known tumor-associated genes were identi- technologies of whole-genome-wide surveys of genetic aberra- fied in 4q24 (TET2, 2x), 5q31.2 (2x), 7q22.1 (3x) and 21q22.12 tions, it is hoped that more insights into the biology of disease (RUNX1, 2x).
    [Show full text]
  • Supplementary Table S1. Correlation Between the Mutant P53-Interacting Partners and PTTG3P, PTTG1 and PTTG2, Based on Data from Starbase V3.0 Database
    Supplementary Table S1. Correlation between the mutant p53-interacting partners and PTTG3P, PTTG1 and PTTG2, based on data from StarBase v3.0 database. PTTG3P PTTG1 PTTG2 Gene ID Coefficient-R p-value Coefficient-R p-value Coefficient-R p-value NF-YA ENSG00000001167 −0.077 8.59e-2 −0.210 2.09e-6 −0.122 6.23e-3 NF-YB ENSG00000120837 0.176 7.12e-5 0.227 2.82e-7 0.094 3.59e-2 NF-YC ENSG00000066136 0.124 5.45e-3 0.124 5.40e-3 0.051 2.51e-1 Sp1 ENSG00000185591 −0.014 7.50e-1 −0.201 5.82e-6 −0.072 1.07e-1 Ets-1 ENSG00000134954 −0.096 3.14e-2 −0.257 4.83e-9 0.034 4.46e-1 VDR ENSG00000111424 −0.091 4.10e-2 −0.216 1.03e-6 0.014 7.48e-1 SREBP-2 ENSG00000198911 −0.064 1.53e-1 −0.147 9.27e-4 −0.073 1.01e-1 TopBP1 ENSG00000163781 0.067 1.36e-1 0.051 2.57e-1 −0.020 6.57e-1 Pin1 ENSG00000127445 0.250 1.40e-8 0.571 9.56e-45 0.187 2.52e-5 MRE11 ENSG00000020922 0.063 1.56e-1 −0.007 8.81e-1 −0.024 5.93e-1 PML ENSG00000140464 0.072 1.05e-1 0.217 9.36e-7 0.166 1.85e-4 p63 ENSG00000073282 −0.120 7.04e-3 −0.283 1.08e-10 −0.198 7.71e-6 p73 ENSG00000078900 0.104 2.03e-2 0.258 4.67e-9 0.097 3.02e-2 Supplementary Table S2.
    [Show full text]
  • 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
    [Show full text]
  • Nuclear PTEN Safeguards Pre-Mrna Splicing to Link Golgi Apparatus for Its Tumor Suppressive Role
    ARTICLE DOI: 10.1038/s41467-018-04760-1 OPEN Nuclear PTEN safeguards pre-mRNA splicing to link Golgi apparatus for its tumor suppressive role Shao-Ming Shen1, Yan Ji2, Cheng Zhang1, Shuang-Shu Dong2, Shuo Yang1, Zhong Xiong1, Meng-Kai Ge1, Yun Yu1, Li Xia1, Meng Guo1, Jin-Ke Cheng3, Jun-Ling Liu1,3, Jian-Xiu Yu1,3 & Guo-Qiang Chen1 Dysregulation of pre-mRNA alternative splicing (AS) is closely associated with cancers. However, the relationships between the AS and classic oncogenes/tumor suppressors are 1234567890():,; largely unknown. Here we show that the deletion of tumor suppressor PTEN alters pre-mRNA splicing in a phosphatase-independent manner, and identify 262 PTEN-regulated AS events in 293T cells by RNA sequencing, which are associated with significant worse outcome of cancer patients. Based on these findings, we report that nuclear PTEN interacts with the splicing machinery, spliceosome, to regulate its assembly and pre-mRNA splicing. We also identify a new exon 2b in GOLGA2 transcript and the exon exclusion contributes to PTEN knockdown-induced tumorigenesis by promoting dramatic Golgi extension and secretion, and PTEN depletion significantly sensitizes cancer cells to secretion inhibitors brefeldin A and golgicide A. Our results suggest that Golgi secretion inhibitors alone or in combination with PI3K/Akt kinase inhibitors may be therapeutically useful for PTEN-deficient cancers. 1 Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China. 2 Institute of Health Sciences, Shanghai Institutes for Biological Sciences of Chinese Academy of Sciences and SJTU-SM, Shanghai 200025, China.
    [Show full text]
  • Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
    Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7,
    [Show full text]