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Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Protein Domain-Level Landscape of Cancer-Type-Specific Somatic We Explored the Protein Domain-Level Landscape of Cancer-Type-Specific Somatic Mutations
RESEARCH ARTICLE Protein Domain-Level Landscape of Cancer- Type-Specific Somatic Mutations Fan Yang1,2,3, Evangelia Petsalaki2,3, Thomas Rolland4,5, David E. Hill4, Marc Vidal4, Frederick P. Roth1,2,3,4,6,7* 1 Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada, 2 Donnelly Centre, University of Toronto, Toronto, Ontario, Canada, 3 Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital, Toronto, Ontario, Canada, 4 Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America, 5 Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America, 6 Canadian Institute for Advanced Research, Toronto, Ontario, Canada, 7 Department of Computer Science, University of Toronto, Toronto, Ontario, Canada * [email protected] Abstract OPEN ACCESS Identifying driver mutations and their functional consequences is critical to our understand- Citation: Yang F, Petsalaki E, Rolland T, Hill DE, ing of cancer. Towards this goal, and because domains are the functional units of a protein, Vidal M, Roth FP (2015) Protein Domain-Level Landscape of Cancer-Type-Specific Somatic we explored the protein domain-level landscape of cancer-type-specific somatic mutations. Mutations. PLoS Comput Biol 11(3): e1004147. Specifically, we systematically examined tumor genomes from 21 cancer types to identify doi:10.1371/journal.pcbi.1004147 domains with high mutational density in specific tissues, the positions of mutational hotspots Editor: Mona Singh, Princeton University, United within these domains, and the functional and structural context where possible. While hot- States of America spots corresponding to specific gain-of-function mutations are expected for oncoproteins, Received: August 22, 2014 we found that tumor suppressor proteins also exhibit strong biases toward being mutated in Accepted: January 22, 2015 particular domains. -
Negative Regulation of Diacylglycerol Kinase &Theta
Cell Death and Differentiation (2010) 17, 1059–1068 & 2010 Macmillan Publishers Limited All rights reserved 1350-9047/10 $32.00 www.nature.com/cdd Negative regulation of diacylglycerol kinase h mediates adenosine-dependent hepatocyte preconditioning G Baldanzi1,5, E Alchera2,5, C Imarisio2, M Gaggianesi1, C Dal Ponte2, M Nitti3, C Domenicotti3, WJ van Blitterswijk4, E Albano2, A Graziani1,5 and R Carini*,2,5 In liver ischemic preconditioning (IP), stimulation of adenosine A2a receptors (A2aR) prevents ischemia/reperfusion injury by promoting diacylglycerol-mediated activation of protein kinase C (PKC). By concerting diacylglycerol to phosphatidic acid, diacylglycerol kinases (DGKs) act as terminator of diacylglycerol signalling. This study investigates the role of DGK in the development of hepatocyte IP. DGK activity and cell viability were evaluated in isolated rat hepatocytes preconditioned by 10 min hypoxia followed by 10 min re-oxygenation or by the treatment with the A2aR agonist, CGS21680, and subsequently exposed to prolonged hypoxia. We observed that after IP or A2aR activation, a decrease in DGK activity was associated with the onset of hepatocyte tolerance to hypoxia. CGS21680-induced stimulation of A2aR specifically inhibited DGK isoform h by activating RhoA–GTPase. Consistently, both siRNA-mediated downregulation of DGK h and hepatocyte pretreatment with the DGK inhibitor R59949 induced cell tolerance to hypoxia. The pharmacological inhibition of DGK was associated with the diacylglycerol- dependent activation of PKC d and e and of their downstream target p38 MAPK. In conclusion, we unveil a novel signalling pathway contributing to the onset of hepatocyte preconditioning, which through RhoA–GTPase, couples A2aR to the downregulation of DGK. -
Genome-Wide Association Study Identifies Novel Loci Associated with Circulating Phospho- and Sphingolipid Concentrations
Genome-Wide Association Study Identifies Novel Loci Associated with Circulating Phospho- and Sphingolipid Concentrations Ays¸e Demirkan1., Cornelia M. van Duijn1,2,3., Peter Ugocsai4., Aaron Isaacs1,2.*, Peter P. Pramstaller5,6,7., Gerhard Liebisch4., James F. Wilson8.,A˚ sa Johansson9., Igor Rudan8,10,11., Yurii S. Aulchenko1, Anatoly V. Kirichenko12, A. Cecile J. W. Janssens13, Ritsert C. Jansen14, Carsten Gnewuch4, Francisco S. Domingues5, Cristian Pattaro5, Sarah H. Wild8, Inger Jonasson9,11, Ozren Polasek11, Irina V. Zorkoltseva12, Albert Hofman3,13, Lennart C. Karssen1, Maksim Struchalin1, James Floyd15, Wilmar Igl9, Zrinka Biloglav16, Linda Broer1, Arne Pfeufer5, Irene Pichler5, Susan Campbell8, Ghazal Zaboli9, Ivana Kolcic11, Fernando Rivadeneira3,13,17, Jennifer Huffman18, Nicholas D. Hastie18, Andre Uitterlinden3,13,17, Lude Franke19, Christopher S. Franklin15, Veronique Vitart8,18, DIAGRAM Consortium{, Christopher P. Nelson20, Michael Preuss21, CARDIoGRAM Consortium{, Joshua C. Bis22, Christopher J. O’Donnell23,24, Nora Franceschini25, CHARGE Consortium, Jacqueline C. M. Witteman3,13, Tatiana Axenovich12, Ben A. Oostra2,13,26", Thomas Meitinger27,28,29", Andrew A. Hicks5", Caroline Hayward18", Alan F. Wright18", Ulf Gyllensten9", Harry Campbell8", Gerd Schmitz4", on behalf of the EUROSPAN consortium 1 Genetic Epidemiology Unit, Departments of Epidemiology and Clinical Genetics, Erasmus University Medical Center, Rotterdam, The Netherlands, 2 Centre for Medical Sytems Biology, Leiden, The Netherlands, 3 Netherlands Consortium -
Mapping of Diabetes Susceptibility Loci in a Domestic Cat Breed with an Unusually High Incidence of Diabetes Mellitus
G C A T T A C G G C A T genes Article Mapping of Diabetes Susceptibility Loci in a Domestic Cat Breed with an Unusually High Incidence of Diabetes Mellitus 1,2, 3, 4 5 Lois Balmer y , Caroline Ann O’Leary y, Marilyn Menotti-Raymond , Victor David , Stephen O’Brien 6,7, Belinda Penglis 8, Sher Hendrickson 9, Mia Reeves-Johnson 3, 3 10 3 3,11, Susan Gottlieb , Linda Fleeman , Dianne Vankan , Jacquie Rand z and 1, , Grant Morahan * z 1 Centre for Diabetes Research, Harry Perkins Institute for Medical Research, University of Western Australia, Nedlands 6009, Australia; [email protected] 2 School of Medical and Health Sciences, Edith Cowan University, Joondalup, Perth 6027, Australia 3 School of Veterinary Science, the University of Queensland, Gottan 4343, Australia; [email protected] (C.A.O.); [email protected] (M.R.-J.); [email protected] (S.G.); [email protected] (D.V.); [email protected] (J.R.) 4 Laboratory of Genomic Diversity, Center for Cancer Research (FNLCR), Frederick, MD 21702, USA; [email protected] 5 Laboratory of Basic Research, Center for Cancer Research (FNLCR), National Cancer Institute, Frederick, MD 21702, USA; [email protected] 6 Laboratory of Genomics Diversity, Center for Computer Technologies, ITMO University, 197101 St. Petersburg, Russia; [email protected] 7 Guy Harvey Oceanographic Center, Halmos College of Arts and Sciences, Nova Southeastern University, Ft Lauderdale, FL 33004, USA 8 IDEXX Laboratories, East Brisbane 4169, Australia; [email protected] 9 Department of Biology, Shepherd University, Shepherdstown, WV 25443, USA; [email protected] 10 Animal Diabetes Australia, Melbourne 3155, Australia; l.fl[email protected] 11 American College of Veterinary Internal Medicine, University of Zurich, 8006 Zurich, Switzerland * Correspondence: [email protected] These authors contributed equally to this work. -
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 -
The Roles of Diacylglycerol Kinases in the Central Nervous System: Review of Genetic Studies in Mice
J Pharmacol Sci 124, 000 – 000 (2014) Journal of Pharmacological Sciences © The Japanese Pharmacological Society Critical Review The Roles of Diacylglycerol Kinases in the Central Nervous System: Review of Genetic Studies in Mice Mitsue Ishisaka1 and Hideaki Hara1,* 1Molecular Pharmacology, Department of Biofunctional Evaluation, Gifu Pharmaceutical University, Gifu 501-1196, Japan Received November 12, 2013; Accepted January 23, 2014 Abstract. Diacylglycerol kinase (DGK) is an enzyme that converts diacylglycerol to phosphatidic acid. To date, 10 isoforms of DGKs (a, b, g, d, e, z, h, q, i, and k) have been identified in mammals, and these DGKs show characteristic expression patterns and roles. The expression levels of DGKs are comparatively higher in the central nervous system than in other organs and may play several important roles in regulating higher brain functions. Currently, many studies have been performed to reveal the roles of DGKs by knocking down or overexpression of DGKs in vitro. Additionally, knockout or overexpression mice of several DGKs have been generated, and phenotypes of these mice have been studied. In this review, we discuss the roles of DGKs in the central nervous system based on recent findings in genetic models. Keywords: central nervous system, diacylglycerol kinase, genetic mouse, mood disorder 1. Introduction DGKs play unique roles in each isoform. To demonstrate the functions of DGKs, many studies After Gq protein–coupled receptors are stimulated, have been performed using a genetic approach in vitro phospholipase C is activated and produces diacylglycerol and in vivo. To date, several overexpression or knockout (DG) from inositol phospholipids (1). DG is an essential (KO)mice have been generated by many research second messenger in mammalian cells and plays impor groups: DGKaKO (23), cardiacspecific overexpression tant roles in gene transcription, lipid signaling, cyto of DGKa (24), DGKbKO (25), DGKdKO (26), DGKe skeletal dynamics, intracellular membrane trafficking, KO (27), DGKzKO (28), and DGKiKO mice (29). -
Analysis of the Indacaterol-Regulated Transcriptome in Human Airway
Supplemental material to this article can be found at: http://jpet.aspetjournals.org/content/suppl/2018/04/13/jpet.118.249292.DC1 1521-0103/366/1/220–236$35.00 https://doi.org/10.1124/jpet.118.249292 THE JOURNAL OF PHARMACOLOGY AND EXPERIMENTAL THERAPEUTICS J Pharmacol Exp Ther 366:220–236, July 2018 Copyright ª 2018 by The American Society for Pharmacology and Experimental Therapeutics Analysis of the Indacaterol-Regulated Transcriptome in Human Airway Epithelial Cells Implicates Gene Expression Changes in the s Adverse and Therapeutic Effects of b2-Adrenoceptor Agonists Dong Yan, Omar Hamed, Taruna Joshi,1 Mahmoud M. Mostafa, Kyla C. Jamieson, Radhika Joshi, Robert Newton, and Mark A. Giembycz Departments of Physiology and Pharmacology (D.Y., O.H., T.J., K.C.J., R.J., M.A.G.) and Cell Biology and Anatomy (M.M.M., R.N.), Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada Received March 22, 2018; accepted April 11, 2018 Downloaded from ABSTRACT The contribution of gene expression changes to the adverse and activity, and positive regulation of neutrophil chemotaxis. The therapeutic effects of b2-adrenoceptor agonists in asthma was general enriched GO term extracellular space was also associ- investigated using human airway epithelial cells as a therapeu- ated with indacaterol-induced genes, and many of those, in- tically relevant target. Operational model-fitting established that cluding CRISPLD2, DMBT1, GAS1, and SOCS3, have putative jpet.aspetjournals.org the long-acting b2-adrenoceptor agonists (LABA) indacaterol, anti-inflammatory, antibacterial, and/or antiviral activity. Numer- salmeterol, formoterol, and picumeterol were full agonists on ous indacaterol-regulated genes were also induced or repressed BEAS-2B cells transfected with a cAMP-response element in BEAS-2B cells and human primary bronchial epithelial cells by reporter but differed in efficacy (indacaterol $ formoterol . -
Signature Redacted Thesis Supervisor Certified By
Single-Cell Transcriptomics of the Mouse Thalamic Reticular Nucleus by Taibo Li S.B., Massachusetts Institute of Technology (2015) Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Master of Engineering in Electrical Engineering and Computer Science at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 2017 @ Massachusetts Institute of Technology 2017. All rights reserved. A uthor ... ..................... Department of Electrical Engineering and Computer Science May 25, 2017 Certified by. 3ignature redacted Guoping Feng Poitras Professor of Neuroscience, MIT Signature redacted Thesis Supervisor Certified by... Kasper Lage Assistant Professor, Harvard Medical School Thesis Supervisor Accepted by . Signature redacted Christopher Terman Chairman, Masters of Engineering Thesis Committee MASSACHUSETTS INSTITUTE 0) OF TECHNOLOGY w AUG 14 2017 LIBRARIES 2 Single-Cell Transcriptomics of the Mouse Thalamic Reticular Nucleus by Taibo Li Submitted to the Department of Electrical Engineering and Computer Science on May 25, 2017, in partial fulfillment of the requirements for the degree of Master of Engineering in Electrical Engineering and Computer Science Abstract The thalamic reticular nucleus (TRN) is strategically located at the interface between the cortex and the thalamus, and plays a key role in regulating thalamo-cortical in- teractions. Current understanding of TRN neurobiology has been limited due to the lack of a comprehensive survey of TRN heterogeneity. In this thesis, I developed an integrative computational framework to analyze the single-nucleus RNA sequencing data of mouse TRN in a data-driven manner. By combining transcriptomic, genetic, and functional proteomic data, I discovered novel insights into the molecular mecha- nisms through which TRN regulates sensory gating, and suggested targeted follow-up experiments to validate these findings. -
Supp Table 6.Pdf
Supplementary Table 6. Processes associated to the 2037 SCL candidate target genes ID Symbol Entrez Gene Name Process NM_178114 AMIGO2 adhesion molecule with Ig-like domain 2 adhesion NM_033474 ARVCF armadillo repeat gene deletes in velocardiofacial syndrome adhesion NM_027060 BTBD9 BTB (POZ) domain containing 9 adhesion NM_001039149 CD226 CD226 molecule adhesion NM_010581 CD47 CD47 molecule adhesion NM_023370 CDH23 cadherin-like 23 adhesion NM_207298 CERCAM cerebral endothelial cell adhesion molecule adhesion NM_021719 CLDN15 claudin 15 adhesion NM_009902 CLDN3 claudin 3 adhesion NM_008779 CNTN3 contactin 3 (plasmacytoma associated) adhesion NM_015734 COL5A1 collagen, type V, alpha 1 adhesion NM_007803 CTTN cortactin adhesion NM_009142 CX3CL1 chemokine (C-X3-C motif) ligand 1 adhesion NM_031174 DSCAM Down syndrome cell adhesion molecule adhesion NM_145158 EMILIN2 elastin microfibril interfacer 2 adhesion NM_001081286 FAT1 FAT tumor suppressor homolog 1 (Drosophila) adhesion NM_001080814 FAT3 FAT tumor suppressor homolog 3 (Drosophila) adhesion NM_153795 FERMT3 fermitin family homolog 3 (Drosophila) adhesion NM_010494 ICAM2 intercellular adhesion molecule 2 adhesion NM_023892 ICAM4 (includes EG:3386) intercellular adhesion molecule 4 (Landsteiner-Wiener blood group)adhesion NM_001001979 MEGF10 multiple EGF-like-domains 10 adhesion NM_172522 MEGF11 multiple EGF-like-domains 11 adhesion NM_010739 MUC13 mucin 13, cell surface associated adhesion NM_013610 NINJ1 ninjurin 1 adhesion NM_016718 NINJ2 ninjurin 2 adhesion NM_172932 NLGN3 neuroligin -
Choline Kinase Inhibition As a Treatment Strategy for Cancers With
Choline Kinase Inhibition as a Treatment Strategy of Cancers with Deregulated Lipid Metabolism Sebastian Trousil Imperial College London Department of Surgery and Cancer A dissertation submitted for the degree of Doctor of Philosophy 2 Declaration I declare that this dissertation is my own and original work, except where explicitly acknowledged. The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work. Abstract Aberrant choline metabolism is a characteristic shared by many human cancers. It is predominantly caused by elevated expression of choline kinase alpha, which catalyses the phosphorylation of choline to phosphocholine, an essential precursor of membrane lipids. In this thesis, a novel choline kinase inhibitor has been developed and its therapeutic potential evaluated. Furthermore the probe was used to elaborate choline kinase biology. A lead compound, ICL-CCIC-0019 (IC50 of 0.27 0.06 µM), was identified through a focused library screen. ICL-CCIC-0019 was competitive± with choline and non-competitive with ATP. In a selectivity screen of 131 human kinases, ICL-CCIC-0019 inhibited only 5 kinases more than 20% at a concentration of 10 µM(< 35% in all 131 kinases). ICL- CCIC-0019 potently inhibited cell growth in a panel of 60 cancer cell lines (NCI-60 screen) with a median GI50 of 1.12 µM (range: 0.00389–16.2 µM). -
Effects of Chronic Stress on Prefrontal Cortex Transcriptome in Mice Displaying Different Genetic Backgrounds
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Springer - Publisher Connector J Mol Neurosci (2013) 50:33–57 DOI 10.1007/s12031-012-9850-1 Effects of Chronic Stress on Prefrontal Cortex Transcriptome in Mice Displaying Different Genetic Backgrounds Pawel Lisowski & Marek Wieczorek & Joanna Goscik & Grzegorz R. Juszczak & Adrian M. Stankiewicz & Lech Zwierzchowski & Artur H. Swiergiel Received: 14 May 2012 /Accepted: 25 June 2012 /Published online: 27 July 2012 # The Author(s) 2012. This article is published with open access at Springerlink.com Abstract There is increasing evidence that depression signaling pathway (Clic6, Drd1a,andPpp1r1b). LA derives from the impact of environmental pressure on transcriptome affected by CMS was associated with genetically susceptible individuals. We analyzed the genes involved in behavioral response to stimulus effects of chronic mild stress (CMS) on prefrontal cor- (Fcer1g, Rasd2, S100a8, S100a9, Crhr1, Grm5,and tex transcriptome of two strains of mice bred for high Prkcc), immune effector processes (Fcer1g, Mpo,and (HA)and low (LA) swim stress-induced analgesia that Igh-VJ558), diacylglycerol binding (Rasgrp1, Dgke, differ in basal transcriptomic profiles and depression- Dgkg,andPrkcc), and long-term depression (Crhr1, like behaviors. We found that CMS affected 96 and 92 Grm5,andPrkcc) and/or coding elements of dendrites genes in HA and LA mice, respectively. Among genes (Crmp1, Cntnap4,andPrkcc) and myelin proteins with the same expression pattern in both strains after (Gpm6a, Mal,andMog). The results indicate significant CMS, we observed robust upregulation of Ttr gene contribution of genetic background to differences in coding transthyretin involved in amyloidosis, seizures, stress response gene expression in the mouse prefrontal stroke-like episodes, or dementia.