Report of Genemania Search

Total Page:16

File Type:pdf, Size:1020Kb

Report of Genemania Search GeneMANIA http://www.genemania.org/print Created on: 5 December 2012 00:37:59 Last database update: 19 July 2012 20:00:00 Application version: 3.1.1 Report of GeneMANIA search Network image PCNA RRM2B BCL2 3.08 Functions legend Networks legend induction of apoptosis by intracellular signals Co-expression query genes Co-localization Genetic interactions Pathway Physical interactions Predicted Shared protein domains 第1页 共60页 2012/12/5 14:07 GeneMANIA http://www.genemania.org/print Search parameters Organism: H. sapiens (human) Genes: BID; IGF1; FAS; CASP8; TCOF1; GTSE1; TP73; CD82; BAX; GADD45B; TSC2; CCNE1; CDK6; UBTF; CCND1; PERP; CCNG1; CCND2; APAF1; CDK2; CDKN1A; GADD45G; SESN2; CASP9; CCNB1; CDK4; THBS1; CCNG2; TP53; PMAIP1; CDKN2A; SESN3; EI24; CHEK1; CCNB2; CASP3; CDK1; POLR1C; RRM2; PTEN; CYCS; ZMAT3; ATR; CCNE2; SFN; LRDD; POLR1D; SIAH1A Networks: Attributes: Network weighting: Automatically selected weighting method (Assigned based on query genes) Number of gene results: 20 第2页 共60页 2012/12/5 14:07 GeneMANIA http://www.genemania.org/print Networks Predicted 27.86 % I2D-Tarassov-PCA-Yeast2Human 6.55 % An in vivo map of the yeast protein interactome. Tarassov et al. (2008). Science . Note: I2D predictions of protein protein interactions using Tarassov-Michnick-2008 Saccharomyces cerevisiae data Source: Direct interaction with 441 interactions from I2D Tags: cell proliferation I2D-IntAct-Mouse2Human 4.34 % The IntAct molecular interaction database in 2010. Aranda et al. (2010). Nucleic Acids Res . Note: I2D predictions of protein protein interactions using IntAct Mus musculus data Source: Direct interaction with 3,422 interactions from I2D I2D-MGI-Mouse2Human 3.32 % Ontological visualization of protein-protein interactions. Drabkin et al. (2005). BMC Bioinformatics . Note: I2D predictions of protein protein interactions using MGI Mus musculus data Source: Direct interaction with 724 interactions from I2D I2D-BioGRID-Mouse2Human 3.06 % BioGRID: a general repository for interaction datasets. Stark et al. (2006). Nucleic Acids Res . Note: I2D predictions of protein protein interactions using BioGRID Mus musculus data Source: Direct interaction with 288 interactions from I2D I2D-MINT-Rat2Human 2.78 % MINT: a Molecular INTeraction database. Zanzoni et al. (2002). FEBS Lett . Note: I2D predictions of protein protein interactions using MINT Rattus norvegicus data Source: Direct interaction with 574 interactions from I2D I2D-INNATEDB-Mouse2Human 2.21 % InnateDB: facilitating systems-level analyses of the mammalian innate immune response. Lynn et al. (2008). Mol Syst Biol . Note: I2D predictions of protein protein interactions using INNATEDB Mus musculus data Source: Direct interaction with 1,455 interactions from I2D Tags: signal transduction; immune system I2D-BIND-Mouse2Human 1.95 % BIND--a data specification for storing and describing biomolecular interactions, molecular complexes and pathways. Bader et al. (2000). Bioinformatics . Note: I2D predictions of protein protein interactions using BIND Mus musculus data Source: Direct interaction with 1,198 interactions from I2D I2D-Giot-Rothbert-2003-High-Fly2Human 1.88 % A protein interaction map of Drosophila melanogaster. Giot et al. (2003). Science . Note: I2D predictions of protein protein interactions using Giot-Rothbert-2003 Drosophila melanogaster data Source: Direct interaction with 602 interactions from I2D Tags: cell proliferation; signal transduction; nervous system; immune system I2D-BIND-Yeast2Human 0.78 % BIND--a data specification for storing and describing biomolecular interactions, molecular complexes and pathways. Bader et al. (2000). Bioinformatics . Note: I2D predictions of protein protein interactions using BIND Saccharomyces cerevisiae data Source: Direct interaction with 1,543 interactions from I2D Stuart-Kim-2003 0.52 % 第3页 共60页 2012/12/5 14:07 GeneMANIA http://www.genemania.org/print A gene-coexpression network for global discovery of conserved genetic modules. Stuart et al. (2003). Science . Source: 24,952 interactions from supplementary material Tags: cell proliferation; cultured cells; signal transduction; cancer I2D-Yu-Vidal-2008-GoldStd-Yeast2Human 0.25 % High-quality binary protein interaction map of the yeast interactome network. Yu et al. (2008). Science . Note: I2D predictions of protein protein interactions using Yu Gold Standard Saccharomyces cerevisiae data Source: Direct interaction with 386 interactions from I2D Tags: transcription factors; signal transduction I2D-BIND-Fly2Human 0.21 % BIND--a data specification for storing and describing biomolecular interactions, molecular complexes and pathways. Bader et al. (2000). Bioinformatics . Note: I2D predictions of protein protein interactions using BIND Drosophila melanogaster data Source: Direct interaction with 2,625 interactions from I2D Physical interactions 25.39 % Ramachandran-LaBaer-2004 14.50 % Self-assembling protein microarrays. Ramachandran et al. (2004). Science . Source: Direct interaction with 119 interactions from iRefIndex IREF-CORUM 3.53 % Source: Direct interaction with 637 interactions from iRefIndex IREF-MPPI 3.52 % Source: Direct interaction with 385 interactions from iRefIndex IREF-DIP 1.95 % Source: Direct interaction with 12,700 interactions from iRefIndex IREF-GRID 0.51 % Source: Direct interaction with 33,623 interactions from iRefIndex IREF-INTACT 0.48 % Source: Direct interaction with 21,448 interactions from iRefIndex Rual-Vidal-2005 B 0.42 % Towards a proteome-scale map of the human protein-protein interaction network. Rual et al. (2005). Nature . Note: One of 2 datasets produced from this publication. Source: Direct interaction with 2,624 interactions from iRefIndex Rual-Vidal-2005 A 0.23 % Towards a proteome-scale map of the human protein-protein interaction network. Rual et al. (2005). Nature . Note: One of 2 datasets produced from this publication. Source: Direct interaction with 2,581 interactions from BioGRID IREF-BIND 0.22 % Source: Direct interaction with 5,310 interactions from iRefIndex BIOGRID-SMALL-SCALE-STUDIES 0.02 % Source: Direct interaction with 28,821 interactions from BioGRID Hutchins-Peters-2010 0.01 % Systematic analysis of human protein complexes identifies chromosome segregation proteins. Hutchins et al. (2010). Science . Source: Direct interaction with 141 interactions from iRefIndex Tags: cell proliferation; nervous system; localization Co-expression 15.99 % 第4页 共60页 2012/12/5 14:07 GeneMANIA http://www.genemania.org/print Nakayama-Hasegawa-2007 2.95 % Gene expression analysis of soft tissue sarcomas: characterization and reclassification of malignant fibrous histiocytoma. Nakayama et al. (2007). Mod Pathol . Source: Pearson correlation with 361,398 interactions from GEO Tags: transcription factors; cancer Rieger-Chu-2004 2.05 % Toxicity from radiation therapy associated with abnormal transcriptional responses to DNA damage. Rieger et al. (2004). Proc Natl Acad Sci U S A . Source: Pearson correlation with 220,846 interactions from GEO Tags: cultured cells; cell line Jones-Libermann-2005 1.80 % Gene signatures of progression and metastasis in renal cell cancer. Jones et al. (2005). Clin Cancer Res . Source: Pearson correlation with 365,428 interactions from GEO Tags: transcription factors; disease; cancer Peng-Katze-2009 1.19 % Computational identification of hepatitis C virus associated microRNA-mRNA regulatory modules in human livers. Peng et al. (2009). BMC Genomics . Source: Pearson correlation with 349,954 interactions from GEO Tags: liver Burington-Shaughnessy-2008 1.01 % Tumor cell gene expression changes following short-term in vivo exposure to single agent chemotherapeutics are related to survival in multiple myeloma. Burington et al. (2008). Clin Cancer Res . Source: Pearson correlation with 266,464 interactions from GEO Tags: transcription factors; time series; cancer; chemotherapy Hummel-Siebert-2006 0.92 % A biologic definition of Burkitt's lymphoma from transcriptional and genomic profiling. Hummel et al. (2006). N Engl J Med . Source: Pearson correlation with 466,765 interactions from GEO Tags: cancer Kang-Willman-2010 0.90 % Gene expression classifiers for relapse-free survival and minimal residual disease improve risk classification and outcome prediction in pediatric B-precursor acute lymphoblastic leukemia. Kang et al. (2010). Blood . Source: Pearson correlation with 549,783 interactions from GEO Tags: transcription factors; lymphoma; cancer Gobble-Singer-2011 0.89 % Expression profiling of liposarcoma yields a multigene predictor of patient outcome and identifies genes that contribute to liposarcomagenesis. Gobble et al. (2011). Cancer Res . Source: Pearson correlation with 449,507 interactions from GEO Tags: apoptosis; cell line; cultured cells; cancer; transcription factors Radtke-Downing-2009 0.87 % Genomic analysis reveals few genetic alterations in pediatric acute myeloid leukemia. Radtke et al. (2009). Proc Natl Acad Sci U S A . Source: Pearson correlation with 377,767 interactions from GEO Tags: transcription factors; nervous system; cancer Raue-Trappe-2012 0.65 % Transcriptome signature of resistance exercise adaptations: mixed muscle and fiber type specific profiles in young and old adults. Raue et al. (2012). J Appl Physiol . Source: Pearson correlation with 483,849 interactions from GEO Wang-Maris-2006 0.60 % 第5页 共60页 2012/12/5 14:07 GeneMANIA http://www.genemania.org/print Integrative genomics identifies distinct molecular classes of neuroblastoma and shows that multiple genes are targeted by regional alterations
Recommended publications
  • Open Data for Differential Network Analysis in Glioma
    International Journal of Molecular Sciences Article Open Data for Differential Network Analysis in Glioma , Claire Jean-Quartier * y , Fleur Jeanquartier y and Andreas Holzinger Holzinger Group HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, 8036 Graz, Austria; [email protected] (F.J.); [email protected] (A.H.) * Correspondence: [email protected] These authors contributed equally to this work. y Received: 27 October 2019; Accepted: 3 January 2020; Published: 15 January 2020 Abstract: The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics. We exploit openly available data via cancer gene expression analysis, we apply refinement as well as enrichment analysis via gene ontology and conclude with graph-based visualization of involved protein interaction networks as a basis for signaling. The different databases allowed for the construction of huge networks or specified ones consisting of high-confidence interactions only. Several genes associated to glioma were isolated via a network analysis from top hub nodes as well as from an outlier analysis. The latter approach highlights a mitogen-activated protein kinase next to a member of histondeacetylases and a protein phosphatase as genes uncommonly associated with glioma. Cluster analysis from top hub nodes lists several identified glioma-associated gene products to function within protein complexes, including epidermal growth factors as well as cell cycle proteins or RAS proto-oncogenes.
    [Show full text]
  • Identification of Genes Associated with Castration‑Resistant Prostate Cancer by Gene Expression Profile Analysis
    MOLECULAR MEDICINE REPORTS 16: 6803-6813, 2017 Identification of genes associated with castration‑resistant prostate cancer by gene expression profile analysis CHUI GUO HUANG1, FENG XI LI2, SONG PAN3, CHANG BAO XU1, JUN QIANG DAI4 and XING HUA ZHAO1 1Department of Urology, The Second Affiliated Hospital, Zhengzhou University, Zhengzhou, Henan 450014; 2Department of Gastrointestinal Glands Surgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi 530000; 3Department of Urology, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, Henan 450014; 4Department of Neurosurgery, The Second Affiliated Hospital, Lanzhou University, Lanzhou, Gansu 730030, P.R. China Received December 16, 2016; Accepted July 17, 2017 DOI: 10.3892/mmr.2017.7488 Abstract. Prostate cancer (CaP) is a serious and common western countries (1). CaP growth is driven by androgens; genital tumor. Generally, men with metastatic CaP can easily therefore, the conventional treatment option is to lower the develop castration-resistant prostate cancer (CRPC). However, levels of male sex hormones (2). Current treatment strate- the pathogenesis and tumorigenic pathways of CRPC remain to gies for CaP include surgery, external beam radiotherapy, be elucidated. The present study performed a comprehensive brachytherapy, chemotherapy and androgen-deprivation analysis on the gene expression profile of CRPC in order to therapy (ADT) (2,3). ADT often involves surgically determine the pathogenesis and tumorigenic of CRPC. The removing the testicles or using drugs to block the andro- GSE33316 microarray, which consisted of 5 non-castrated gens from affecting the body (4). Unfortunately, ADT has samples and 5 castrated samples, was downloaded from the gene a limited role in preventing majority of patients progressing expression omnibus database.
    [Show full text]
  • Identification of Genomic Targets of Krüppel-Like Factor 9 in Mouse Hippocampal
    Identification of Genomic Targets of Krüppel-like Factor 9 in Mouse Hippocampal Neurons: Evidence for a role in modulating peripheral circadian clocks by Joseph R. Knoedler A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Neuroscience) in the University of Michigan 2016 Doctoral Committee: Professor Robert J. Denver, Chair Professor Daniel Goldman Professor Diane Robins Professor Audrey Seasholtz Associate Professor Bing Ye ©Joseph R. Knoedler All Rights Reserved 2016 To my parents, who never once questioned my decision to become the other kind of doctor, And to Lucy, who has pushed me to be a better person from day one. ii Acknowledgements I have a huge number of people to thank for having made it to this point, so in no particular order: -I would like to thank my adviser, Dr. Robert J. Denver, for his guidance, encouragement, and patience over the last seven years; his mentorship has been indispensable for my growth as a scientist -I would also like to thank my committee members, Drs. Audrey Seasholtz, Dan Goldman, Diane Robins and Bing Ye, for their constructive feedback and their willingness to meet in a frequently cold, windowless room across campus from where they work -I am hugely indebted to Pia Bagamasbad and Yasuhiro Kyono for teaching me almost everything I know about molecular biology and bioinformatics, and to Arasakumar Subramani for his tireless work during the home stretch to my dissertation -I am grateful for the Neuroscience Program leadership and staff, in particular
    [Show full text]
  • A Radiation Hybrid Map of Chicken Chromosome 4
    A radiation hybrid map of chicken Chromosome 4 Tarik S.K.M. Rabie,1* Richard P.M.A. Crooijmans,1 Mireille Morisson,2 Joanna Andryszkiewicz,1 Jan J. van der Poel,1 Alain Vignal,2 Martien A.M. Groenen1 1Wageningen Institute of Animal Sciences, Animal Breeding and Genetics Group, Wageningen University, Marijkeweg 40, 6709 PG Wageningen, The Netherlands 2Laboratoire de ge´ne´tique cellulaire, Institut national de la recherche agronomique, 31326 Castanet-Tolosan, France Received: 15 December 2003 / Accepted: 16 March 2004 Comparative genomics plays an important role in Abstract the understanding of genome dynamics during ev- The mapping resolution of the physical map for olution and as a tool for the transfer of mapping chicken Chromosome 4 (GGA4) was improved by a information from species with gene-dense maps to combination of radiation hybrid (RH) mapping and species whose maps are less well developed (O‘Bri- bacterial artificial chromosome (BAC) mapping. The en et al. 1993, 1999). For farm animals, therefore, ChickRH6 hybrid panel was used to construct an RH the human and mouse have been the logical choice map of GGA4. Eleven microsatellites known to be as the model species used for this comparison. located on GGA4 were included as anchors to the Medium-resolution comparative maps have been genetic linkage map for this chromosome. Based on published for many of the livestock species, in- the known conserved synteny between GGA4 and cluding pig, cattle, sheep, and horse, identifying human Chromosomes 4 and X, sequences were large regions of conserved synteny between these identified for the orthologous chicken genes from species and man and mouse.
    [Show full text]
  • Circulating Mir-1246 Targeting UBE2C, TNNI3, TRAIP, UCHL1
    Journal of Personalized Medicine Article Circulating miR-1246 Targeting UBE2C, TNNI3, TRAIP, UCHL1 Genes and Key Pathways as a Potential Biomarker for Lung Adenocarcinoma: Integrated Biological Network Analysis Siyuan Huang 1, Yong-Kai Wei 2, Satyavani Kaliamurthi 3,4 , Yanghui Cao 5, Asma Sindhoo Nangraj 6, Xin Sui 1, Dan Chu 7, Huan Wang 7, Dong-Qing Wei 3,4,6 , Gilles H. Peslherbe 3, Gurudeeban Selvaraj 3,4 and Jiang Shi 7,* 1 Department of Oncology, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe East Road, Zhengzhou 450052, China; [email protected] (S.H.); [email protected] (X.S.) 2 College of Science, Henan University of Technology, Zhengzhou 450001, China; [email protected] 3 Centre for Research in Molecular Modeling and Department of Chemistry and Biochemistry, Concordia University, 7141 Sherbrooke Street West, Montréal, QC H4B 1R6, Canada; [email protected] (S.K.); [email protected] (D.-Q.W.); [email protected] (G.H.P.); [email protected] (G.S.) 4 Center of Interdisciplinary Science-Computational Life Sciences, College of Biological Engineering, Henan University of Technology, No.100, Lianhua Street, Hi-Tech Development Zone, Zhengzhou 450001, China 5 Department of General Surgery, Henan Tumor Hospital, No.127 Dongming Road, Zhengzhou 450008, China; [email protected] 6 The State Key Laboratory of Microbial Metabolism, College of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China; [email protected] 7 Department of Respiratory, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe East Road, Zhengzhou 450052, China; [email protected] (D.C.); [email protected] (H.W.) * Correspondence: [email protected]; Tel.: +86-15824836717 Received: 20 August 2020; Accepted: 28 September 2020; Published: 11 October 2020 Abstract: Analysis of circulating miRNAs (cmiRNAs) before surgical operation (BSO) and after the surgical operation (ASO) has been informative for lung adenocarcinoma (LUAD) diagnosis, progression, and outcomes of treatment.
    [Show full text]
  • Chromatin Conformation Links Distal Target Genes to CKD Loci
    BASIC RESEARCH www.jasn.org Chromatin Conformation Links Distal Target Genes to CKD Loci Maarten M. Brandt,1 Claartje A. Meddens,2,3 Laura Louzao-Martinez,4 Noortje A.M. van den Dungen,5,6 Nico R. Lansu,2,3,6 Edward E.S. Nieuwenhuis,2 Dirk J. Duncker,1 Marianne C. Verhaar,4 Jaap A. Joles,4 Michal Mokry,2,3,6 and Caroline Cheng1,4 1Experimental Cardiology, Department of Cardiology, Thoraxcenter Erasmus University Medical Center, Rotterdam, The Netherlands; and 2Department of Pediatrics, Wilhelmina Children’s Hospital, 3Regenerative Medicine Center Utrecht, Department of Pediatrics, 4Department of Nephrology and Hypertension, Division of Internal Medicine and Dermatology, 5Department of Cardiology, Division Heart and Lungs, and 6Epigenomics Facility, Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands ABSTRACT Genome-wide association studies (GWASs) have identified many genetic risk factors for CKD. However, linking common variants to genes that are causal for CKD etiology remains challenging. By adapting self-transcribing active regulatory region sequencing, we evaluated the effect of genetic variation on DNA regulatory elements (DREs). Variants in linkage with the CKD-associated single-nucleotide polymorphism rs11959928 were shown to affect DRE function, illustrating that genes regulated by DREs colocalizing with CKD-associated variation can be dysregulated and therefore, considered as CKD candidate genes. To identify target genes of these DREs, we used circular chro- mosome conformation capture (4C) sequencing on glomerular endothelial cells and renal tubular epithelial cells. Our 4C analyses revealed interactions of CKD-associated susceptibility regions with the transcriptional start sites of 304 target genes. Overlap with multiple databases confirmed that many of these target genes are involved in kidney homeostasis.
    [Show full text]
  • UC San Diego Electronic Theses and Dissertations
    UC San Diego UC San Diego Electronic Theses and Dissertations Title Cardiac Stretch-Induced Transcriptomic Changes are Axis-Dependent Permalink https://escholarship.org/uc/item/7m04f0b0 Author Buchholz, Kyle Stephen Publication Date 2016 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Cardiac Stretch-Induced Transcriptomic Changes are Axis-Dependent A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioengineering by Kyle Stephen Buchholz Committee in Charge: Professor Jeffrey Omens, Chair Professor Andrew McCulloch, Co-Chair Professor Ju Chen Professor Karen Christman Professor Robert Ross Professor Alexander Zambon 2016 Copyright Kyle Stephen Buchholz, 2016 All rights reserved Signature Page The Dissertation of Kyle Stephen Buchholz is approved and it is acceptable in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California, San Diego 2016 iii Dedication To my beautiful wife, Rhia. iv Table of Contents Signature Page ................................................................................................................... iii Dedication .......................................................................................................................... iv Table of Contents ................................................................................................................ v List of Figures ...................................................................................................................
    [Show full text]
  • Disruption of MAPK1 Expression in the ERK Signalling
    ONCOLOGY REPORTS 41: 2027-2040, 2019 Disruption of MAPK1 expression in the ERK signalling pathway and the RUNX1‑RUNX1T1 fusion gene attenuate the differentiation and proliferation and induces the growth arrest in t(8;21) leukaemia cells SALEM ALI AL-SALEM BASHANFER2, MOHAMED SALEEM3, OLAF HEIDENREICH4, EMMANUEL JAIRAJ MOSES1 and NARAZAH MOHD YUSOFF1 1Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, Kepala Batas, Pulau Pinang 13200, Malaysia; 2Hematology Department, College of Medicine and Health Sciences, University of Hodiedah, Hodiedah 3730, Yemen; 3Advanced Genomics Lab Sdn Bhd, Kota Damansara, Petaling Jaya, Selangor Darul Ehsan 47810, Malaysia; 4Northern Institute for Cancer Research, Medical School, Newcastle upon Tyne NE2 4HH, UK Received June 28, 2017; Accepted June 8, 2018 DOI: 10.3892/or.2018.6926 Abstract. The t(8;21) translocation is one of the most frequent RUNX1‑RUNX1T1 and MAPK1 depletion induced cell cycle chromosome abnormalities associated with acute myeloid arrest at the G0/G1 phase. Accumulation of cells in the G1 phase leukaemia (AML). This abberation deregulates numerous was largely the result of downregulated expression of TBRG4, molecular pathways including the ERK signalling pathway CCNE2, FOXO4, CDK6, ING4, IL8, MAD2L1 and CCNG2 among others. Therefore, the aim of the present study in the case of RUNX1‑RUNX1T1 depletion and increased was to investigate the gene expression patterns following expression of RASSF1, FBXO6, DADD45A and P53 in the siRNA-mediated suppression of RUNX1‑RUNX1T1 and case of MAPK1 depletion. Taken together, the current results MAPK1 in Kasumi-1 and SKNO-1 cells and to determine the demonstrate that MAPK1 promotes myeloid cell proliferation differentially expressed genes in enriched biological pathways.
    [Show full text]
  • A Genomic View of Estrogen Actions in Human Breast Cancer Cells by Expression Profiling of the Hormone-Responsive Transcriptome
    719 A genomic view of estrogen actions in human breast cancer cells by expression profiling of the hormone-responsive transcriptome Luigi Cicatiello1, Claudio Scafoglio1, Lucia Altucci1, Massimo Cancemi1, Guido Natoli1, Angelo Facchiano2, Giovanni Iazzetti3, Raffaele Calogero4, Nicoletta Biglia6, Michele De Bortoli5,7, Christian Sfiligoi7, Piero Sismondi6,7, Francesco Bresciani1 and Alessandro Weisz1 1Dipartimento di Patologia generale, Seconda Università degli Studi di Napoli, Vico L. De Crecchio 7, 80138 Napoli, Italy 2Istituto di Scienze dell’Alimentazione del Consiglio Nazionale delle Ricerche, Avellino, Italy 3Dipartimento di Genetica, Biologia generale e molecolare, Università di Napoli ‘Federico II’, Napoli, Italy 4Dipartimento di Scienze cliniche e biologiche, Università degli Studi di Torino, Torino, Italy 5Dipartimento di Scienze oncologiche, Università degli Studi di Torino, Torino, Italy 6Dipartimento di Discipline ostetriche e ginecologiche, Università degli Studi di Torino, Torino, Italy 7Laboratorio di Ginecologia oncologica, Istituto per la Ricerca e la Cura del Cancro, Candiolo, Italy (Requests for offprints should be addressed to A Weisz; Email: [email protected]) Abstract Estrogen controls key cellular functions of responsive cells including the ability to survive, replicate, communicate and adapt to the extracellular milieu. Changes in the expression of 8400 genes were monitored here by cDNA microarray analysis during the first 32 h of human breast cancer (BC) ZR-75·1 cell stimulation with a mitogenic dose of 17-estradiol, a timing which corresponds to completion of a full mitotic cycle in hormone-stimulated cells. Hierarchical clustering of 344 genes whose expression either increases or decreases significantly in response to estrogen reveals that the gene expression program activated by the hormone in these cells shows 8 main patterns of gene activation/inhibition.
    [Show full text]
  • Us 2018 / 0305689 A1
    US 20180305689A1 ( 19 ) United States (12 ) Patent Application Publication ( 10) Pub . No. : US 2018 /0305689 A1 Sætrom et al. ( 43 ) Pub . Date: Oct. 25 , 2018 ( 54 ) SARNA COMPOSITIONS AND METHODS OF plication No . 62 /150 , 895 , filed on Apr. 22 , 2015 , USE provisional application No . 62/ 150 ,904 , filed on Apr. 22 , 2015 , provisional application No. 62 / 150 , 908 , (71 ) Applicant: MINA THERAPEUTICS LIMITED , filed on Apr. 22 , 2015 , provisional application No. LONDON (GB ) 62 / 150 , 900 , filed on Apr. 22 , 2015 . (72 ) Inventors : Pål Sætrom , Trondheim (NO ) ; Endre Publication Classification Bakken Stovner , Trondheim (NO ) (51 ) Int . CI. C12N 15 / 113 (2006 .01 ) (21 ) Appl. No. : 15 /568 , 046 (52 ) U . S . CI. (22 ) PCT Filed : Apr. 21 , 2016 CPC .. .. .. C12N 15 / 113 ( 2013 .01 ) ; C12N 2310 / 34 ( 2013. 01 ) ; C12N 2310 /14 (2013 . 01 ) ; C12N ( 86 ) PCT No .: PCT/ GB2016 /051116 2310 / 11 (2013 .01 ) $ 371 ( c ) ( 1 ) , ( 2 ) Date : Oct . 20 , 2017 (57 ) ABSTRACT The invention relates to oligonucleotides , e . g . , saRNAS Related U . S . Application Data useful in upregulating the expression of a target gene and (60 ) Provisional application No . 62 / 150 ,892 , filed on Apr. therapeutic compositions comprising such oligonucleotides . 22 , 2015 , provisional application No . 62 / 150 ,893 , Methods of using the oligonucleotides and the therapeutic filed on Apr. 22 , 2015 , provisional application No . compositions are also provided . 62 / 150 ,897 , filed on Apr. 22 , 2015 , provisional ap Specification includes a Sequence Listing . SARNA sense strand (Fessenger 3 ' SARNA antisense strand (Guide ) Mathew, Si Target antisense RNA transcript, e . g . NAT Target Coding strand Gene Transcription start site ( T55 ) TY{ { ? ? Targeted Target transcript , e .
    [Show full text]
  • Exploration of the Cell-Cycle Genes Found Within the RIKEN Fantom2data Set Alistair R.R
    Downloaded from genome.cshlp.org on September 30, 2015 - Published by Cold Spring Harbor Laboratory Press Letter Exploration of the Cell-Cycle Genes Found Within the RIKEN FANTOM2Data Set Alistair R.R. Forrest,1,2,3,7 Darrin Taylor,1,2,3 RIKEN GER Group4 and GSL Members,5,6 and Sean Grimmond1,2 1The Institute for Molecular Bioscience, University of Queensland, Queensland Q4072, Australia; 2University of Queensland, Queensland Q4072, Australia; 3The Australian Research Council Special Research Centre for Functional and Applied Genomics, University of Queensland, Queensland Q4072, Australia; 4Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan; 5Genome Science Laboratory, RIKEN, Hirosawa, Wako, Saitama 351-0198, Japan The cell cycle is one of the most fundamental processes within a cell. Phase-dependent expression and cell-cycle checkpoints require a high level of control. A large number of genes with varying functions and modes of action are responsible for this biology. In a targeted exploration of the FANTOM2–Variable Protein Set, a number of mouse homologs to known cell-cycle regulators as well as novel members of cell-cycle families were identified. Focusing on two prototype cell-cycle families, the cyclins and the NIMA-related kinases (NEKs), we believe we have identified all of the mouse members of these families, 24 cyclins and 10 NEKs, and mapped them to ENSEMBL transcripts. To attempt to globally identify all potential cell cycle-related genes within mouse, the MGI (Mouse Genome Database) assignments for the RIKEN Representative Set (RPS) and the results from two homology-based queries were merged.
    [Show full text]
  • ONCOGENOMICS a Genome-Wide Study of the Repressive Effects of Estrogen Receptor Beta on Estrogen Receptor Alpha Signaling in Breast Cancer Cells
    Oncogene (2008) 27, 1019–1032 & 2008 Nature Publishing Group All rights reserved 0950-9232/08 $30.00 www.nature.com/onc ONCOGENOMICS A genome-wide study of the repressive effects of estrogen receptor beta on estrogen receptor alpha signaling in breast cancer cells C Williams, K Edvardsson, SA Lewandowski, A Stro¨ m and J-A˚ Gustafsson Department of Biosciences and Nutrition at Novum, Karolinska Institutet, Huddinge, Sweden Transcriptional effects of estrogen result from its activa- mediated via two estrogen receptor (ER) isoforms, that tion of two estrogen receptor (ER) isoforms; ERa that is, ER alpha (ERa) and ER beta (ERb) (Hanstein et al., drives proliferation and ERb that is antiproliferative. 2004). The second ER isoform, ERb, was discovered Expression of ERb in xenograft tumors from the T47D some 10years ago (Kuiper et al., 1996). ERa and ERb breast cancer cell line reduces tumor growth and are homologous, especially in their DNA-binding angiogenesis. If ERb can halt tumor growth, its introduc- domains (97%), but they differ in their ligand-binding tion into cancers may be a novel therapeutic approach to domains (59% identity) and in their transcriptional the treatment of estrogen-responsive cancers. To assess activating function-1 (AF-1) domains. Estrogen is non- the complete impact of ERb on transcription, we have selective for the two receptors and the binding of made a full transcriptome analysis of ERa- and ERb- estrogen results in a receptor–ligand complex that binds mediated gene regulation in T47D cell line with Tet-Off with high affinity to estrogen responsive elements regulated ERb expression.
    [Show full text]