1 Table 1S. Genes Over-Expressed in AILT Vs. Normal T-Lymphocytes
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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. -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
Molecular Markers of Serine Protease Evolution
The EMBO Journal Vol. 20 No. 12 pp. 3036±3045, 2001 Molecular markers of serine protease evolution Maxwell M.Krem and Enrico Di Cera1 ment and specialization of the catalytic architecture should correspond to signi®cant evolutionary transitions in the Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, Box 8231, St Louis, history of protease clans. Evolutionary markers encoun- MO 63110-1093, USA tered in the sequences contributing to the catalytic apparatus would thus give an account of the history of 1Corresponding author e-mail: [email protected] an enzyme family or clan and provide for comparative analysis with other families and clans. Therefore, the use The evolutionary history of serine proteases can be of sequence markers associated with active site structure accounted for by highly conserved amino acids that generates a model for protease evolution with broad form crucial structural and chemical elements of applicability and potential for extension to other classes of the catalytic apparatus. These residues display non- enzymes. random dichotomies in either amino acid choice or The ®rst report of a sequence marker associated with serine codon usage and serve as discrete markers for active site chemistry was the observation that both AGY tracking changes in the active site environment and and TCN codons were used to encode active site serines in supporting structures. These markers categorize a variety of enzyme families (Brenner, 1988). Since serine proteases of the chymotrypsin-like, subtilisin- AGY®TCN interconversion is an uncommon event, it like and a/b-hydrolase fold clans according to phylo- was reasoned that enzymes within the same family genetic lineages, and indicate the relative ages and utilizing different active site codons belonged to different order of appearance of those lineages. -
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. -
1 Metabolic Dysfunction Is Restricted to the Sciatic Nerve in Experimental
Page 1 of 255 Diabetes Metabolic dysfunction is restricted to the sciatic nerve in experimental diabetic neuropathy Oliver J. Freeman1,2, Richard D. Unwin2,3, Andrew W. Dowsey2,3, Paul Begley2,3, Sumia Ali1, Katherine A. Hollywood2,3, Nitin Rustogi2,3, Rasmus S. Petersen1, Warwick B. Dunn2,3†, Garth J.S. Cooper2,3,4,5* & Natalie J. Gardiner1* 1 Faculty of Life Sciences, University of Manchester, UK 2 Centre for Advanced Discovery and Experimental Therapeutics (CADET), Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK 3 Centre for Endocrinology and Diabetes, Institute of Human Development, Faculty of Medical and Human Sciences, University of Manchester, UK 4 School of Biological Sciences, University of Auckland, New Zealand 5 Department of Pharmacology, Medical Sciences Division, University of Oxford, UK † Present address: School of Biosciences, University of Birmingham, UK *Joint corresponding authors: Natalie J. Gardiner and Garth J.S. Cooper Email: [email protected]; [email protected] Address: University of Manchester, AV Hill Building, Oxford Road, Manchester, M13 9PT, United Kingdom Telephone: +44 161 275 5768; +44 161 701 0240 Word count: 4,490 Number of tables: 1, Number of figures: 6 Running title: Metabolic dysfunction in diabetic neuropathy 1 Diabetes Publish Ahead of Print, published online October 15, 2015 Diabetes Page 2 of 255 Abstract High glucose levels in the peripheral nervous system (PNS) have been implicated in the pathogenesis of diabetic neuropathy (DN). However our understanding of the molecular mechanisms which cause the marked distal pathology is incomplete. Here we performed a comprehensive, system-wide analysis of the PNS of a rodent model of DN. -
Serum Albumin OS=Homo Sapiens
Protein Name Cluster of Glial fibrillary acidic protein OS=Homo sapiens GN=GFAP PE=1 SV=1 (P14136) Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 Cluster of Isoform 3 of Plectin OS=Homo sapiens GN=PLEC (Q15149-3) Cluster of Hemoglobin subunit beta OS=Homo sapiens GN=HBB PE=1 SV=2 (P68871) Vimentin OS=Homo sapiens GN=VIM PE=1 SV=4 Cluster of Tubulin beta-3 chain OS=Homo sapiens GN=TUBB3 PE=1 SV=2 (Q13509) Cluster of Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 (P60709) Cluster of Tubulin alpha-1B chain OS=Homo sapiens GN=TUBA1B PE=1 SV=1 (P68363) Cluster of Isoform 2 of Spectrin alpha chain, non-erythrocytic 1 OS=Homo sapiens GN=SPTAN1 (Q13813-2) Hemoglobin subunit alpha OS=Homo sapiens GN=HBA1 PE=1 SV=2 Cluster of Spectrin beta chain, non-erythrocytic 1 OS=Homo sapiens GN=SPTBN1 PE=1 SV=2 (Q01082) Cluster of Pyruvate kinase isozymes M1/M2 OS=Homo sapiens GN=PKM PE=1 SV=4 (P14618) Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 Clathrin heavy chain 1 OS=Homo sapiens GN=CLTC PE=1 SV=5 Filamin-A OS=Homo sapiens GN=FLNA PE=1 SV=4 Cytoplasmic dynein 1 heavy chain 1 OS=Homo sapiens GN=DYNC1H1 PE=1 SV=5 Cluster of ATPase, Na+/K+ transporting, alpha 2 (+) polypeptide OS=Homo sapiens GN=ATP1A2 PE=3 SV=1 (B1AKY9) Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 Dihydropyrimidinase-related protein 2 OS=Homo sapiens GN=DPYSL2 PE=1 SV=1 Cluster of Alpha-actinin-1 OS=Homo sapiens GN=ACTN1 PE=1 SV=2 (P12814) 60 kDa heat shock protein, mitochondrial OS=Homo -
Serine Proteases with Altered Sensitivity to Activity-Modulating
(19) & (11) EP 2 045 321 A2 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 08.04.2009 Bulletin 2009/15 C12N 9/00 (2006.01) C12N 15/00 (2006.01) C12Q 1/37 (2006.01) (21) Application number: 09150549.5 (22) Date of filing: 26.05.2006 (84) Designated Contracting States: • Haupts, Ulrich AT BE BG CH CY CZ DE DK EE ES FI FR GB GR 51519 Odenthal (DE) HU IE IS IT LI LT LU LV MC NL PL PT RO SE SI • Coco, Wayne SK TR 50737 Köln (DE) •Tebbe, Jan (30) Priority: 27.05.2005 EP 05104543 50733 Köln (DE) • Votsmeier, Christian (62) Document number(s) of the earlier application(s) in 50259 Pulheim (DE) accordance with Art. 76 EPC: • Scheidig, Andreas 06763303.2 / 1 883 696 50823 Köln (DE) (71) Applicant: Direvo Biotech AG (74) Representative: von Kreisler Selting Werner 50829 Köln (DE) Patentanwälte P.O. Box 10 22 41 (72) Inventors: 50462 Köln (DE) • Koltermann, André 82057 Icking (DE) Remarks: • Kettling, Ulrich This application was filed on 14-01-2009 as a 81477 München (DE) divisional application to the application mentioned under INID code 62. (54) Serine proteases with altered sensitivity to activity-modulating substances (57) The present invention provides variants of ser- screening of the library in the presence of one or several ine proteases of the S1 class with altered sensitivity to activity-modulating substances, selection of variants with one or more activity-modulating substances. A method altered sensitivity to one or several activity-modulating for the generation of such proteases is disclosed, com- substances and isolation of those polynucleotide se- prising the provision of a protease library encoding poly- quences that encode for the selected variants. -
Transcriptome-Wide Profiling of Cerebral Cavernous Malformations
www.nature.com/scientificreports OPEN Transcriptome-wide Profling of Cerebral Cavernous Malformations Patients Reveal Important Long noncoding RNA molecular signatures Santhilal Subhash 2,8, Norman Kalmbach3, Florian Wegner4, Susanne Petri4, Torsten Glomb5, Oliver Dittrich-Breiholz5, Caiquan Huang1, Kiran Kumar Bali6, Wolfram S. Kunz7, Amir Samii1, Helmut Bertalanfy1, Chandrasekhar Kanduri2* & Souvik Kar1,8* Cerebral cavernous malformations (CCMs) are low-fow vascular malformations in the brain associated with recurrent hemorrhage and seizures. The current treatment of CCMs relies solely on surgical intervention. Henceforth, alternative non-invasive therapies are urgently needed to help prevent subsequent hemorrhagic episodes. Long non-coding RNAs (lncRNAs) belong to the class of non-coding RNAs and are known to regulate gene transcription and involved in chromatin remodeling via various mechanism. Despite accumulating evidence demonstrating the role of lncRNAs in cerebrovascular disorders, their identifcation in CCMs pathology remains unknown. The objective of the current study was to identify lncRNAs associated with CCMs pathogenesis using patient cohorts having 10 CCM patients and 4 controls from brain. Executing next generation sequencing, we performed whole transcriptome sequencing (RNA-seq) analysis and identifed 1,967 lncRNAs and 4,928 protein coding genes (PCGs) to be diferentially expressed in CCMs patients. Among these, we selected top 6 diferentially expressed lncRNAs each having signifcant correlative expression with more than 100 diferentially expressed PCGs. The diferential expression status of the top lncRNAs, SMIM25 and LBX2-AS1 in CCMs was further confrmed by qRT-PCR analysis. Additionally, gene set enrichment analysis of correlated PCGs revealed critical pathways related to vascular signaling and important biological processes relevant to CCMs pathophysiology. -
Preclinical Characterization of Dostarlimab, a Therapeutic Anti-PD
MABS 2021, VOL. 13, NO. 1, e1954136 (12 pages) https://doi.org/10.1080/19420862.2021.1954136 REPORTS Preclinical characterization of dostarlimab, a therapeutic anti-PD-1 antibody with potent activity to enhance immune function in in vitro cellular assays and in vivo animal models Sujatha Kumara*, Srimoyee Ghoshb, Geeta Sharmac, Zebin Wangd, Marilyn R. Kehrye, Margaret H. Marinof, Tamlyn Y. Nebenf, Sharon Lug, Shouqi Luoh, Simon Robertsi, Sridhar Ramaswamyj, Hadi Danaeek, and David Jenkinsl aTranslational Research, Immuno-Oncology, Checkmate Pharmaceuticals, Cambridge, MA, USA; bOncology Experimental Medicine Unit, GlaxoSmithKline, Waltham, MA, USA; cSynthetic Lethal Research Unit, Oncolog, GlaxoSmithKline, Waltham, MA, USA; dTranslational Strategy & Research, GlaxoSmithKline,Waltham, MA, USA; eCell Biology, AnaptysBio, Inc,San Diego, CA, USA; fProgram Management, AnaptysBio, Inc, San Diego, CA, USA; gClinical Pharmacology, Scholar Rock, Cambridge, MA, USA; hToxicology, Atea Pharmaceuticals, Boston, MA, USA; iNonclinical Development, Research In Vivo/In Vitro Translation, GlaxoSmithKline, Waltham, MA, USA; jGoogle Ventures, Cambridge, MA, USA; kTranslational Medicine, Blue Print Medicines, Cambridge, MA, USA; lExternal Innovations, IPSEN, Cambridge, MA, USA ABSTRACT ARTICLE HISTORY Inhibitors of programmed cell death protein 1 (PD-1) and its ligand (PD-L1) have dramatically changed the Received 17 December 2020 treatment landscape for patients with cancer. Clinical activity of anti-PD-(L)1 antibodies has resulted in Revised 2 July 2021 increased median overall survival and durable responses in patients across selected tumor types. To date, Accepted 7 July 2021 6 PD-1 and PD-L1, here collectively referred to as PD-(L)1, pathway inhibitors are approved by the US Food KEYWORDS and Drug Administration for clinical use. -
Microrna Regulatory Pathways in the Control of the Actin–Myosin Cytoskeleton
cells Review MicroRNA Regulatory Pathways in the Control of the Actin–Myosin Cytoskeleton , , Karen Uray * y , Evelin Major and Beata Lontay * y Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary; [email protected] * Correspondence: [email protected] (K.U.); [email protected] (B.L.); Tel.: +36-52-412345 (K.U. & B.L.) The authors contributed equally to the manuscript. y Received: 11 June 2020; Accepted: 7 July 2020; Published: 9 July 2020 Abstract: MicroRNAs (miRNAs) are key modulators of post-transcriptional gene regulation in a plethora of processes, including actin–myosin cytoskeleton dynamics. Recent evidence points to the widespread effects of miRNAs on actin–myosin cytoskeleton dynamics, either directly on the expression of actin and myosin genes or indirectly on the diverse signaling cascades modulating cytoskeletal arrangement. Furthermore, studies from various human models indicate that miRNAs contribute to the development of various human disorders. The potentially huge impact of miRNA-based mechanisms on cytoskeletal elements is just starting to be recognized. In this review, we summarize recent knowledge about the importance of microRNA modulation of the actin–myosin cytoskeleton affecting physiological processes, including cardiovascular function, hematopoiesis, podocyte physiology, and osteogenesis. Keywords: miRNA; actin; myosin; actin–myosin complex; Rho kinase; cancer; smooth muscle; hematopoiesis; stress fiber; gene expression; cardiovascular system; striated muscle; muscle cell differentiation; therapy 1. Introduction Actin–myosin interactions are the primary source of force generation in mammalian cells. Actin forms a cytoskeletal network and the myosin motor proteins pull actin filaments to produce contractile force. All eukaryotic cells contain an actin–myosin network inferring contractile properties to these cells. -
Novel Myosin Mutations for Hereditary Hearing Loss Revealed by Targeted Genomic Capture and Massively Parallel Sequencing
European Journal of Human Genetics (2014) 22, 768–775 & 2014 Macmillan Publishers Limited All rights reserved 1018-4813/14 www.nature.com/ejhg ARTICLE Novel myosin mutations for hereditary hearing loss revealed by targeted genomic capture and massively parallel sequencing Zippora Brownstein1,6, Amal Abu-Rayyan2,6, Daphne Karfunkel-Doron1, Serena Sirigu3, Bella Davidov4, Mordechai Shohat1,4, Moshe Frydman1,5, Anne Houdusse3, Moien Kanaan2 and Karen B Avraham*,1 Hereditary hearing loss is genetically heterogeneous, with a large number of genes and mutations contributing to this sensory, often monogenic, disease. This number, as well as large size, precludes comprehensive genetic diagnosis of all known deafness genes. A combination of targeted genomic capture and massively parallel sequencing (MPS), also referred to as next-generation sequencing, was applied to determine the deafness-causing genes in hearing-impaired individuals from Israeli Jewish and Palestinian Arab families. Among the mutations detected, we identified nine novel mutations in the genes encoding myosin VI, myosin VIIA and myosin XVA, doubling the number of myosin mutations in the Middle East. Myosin VI mutations were identified in this population for the first time. Modeling of the mutations provided predicted mechanisms for the damage they inflict in the molecular motors, leading to impaired function and thus deafness. The myosin mutations span all regions of these molecular motors, leading to a wide range of hearing phenotypes, reinforcing the key role of this family of proteins in auditory function. This study demonstrates that multiple mutations responsible for hearing loss can be identified in a relatively straightforward manner by targeted-gene MPS technology and concludes that this is the optimal genetic diagnostic approach for identification of mutations responsible for hearing loss. -
Quantikine® ELISA
Quantikine® ELISA Human Granzyme B Immunoassay Catalog Number DGZB00 For the quantitative determination of human Granzyme B concentrations in culture supernates. This package insert must be read in its entirety before using this product. For research use only. Not for use in diagnostic procedures. TABLE OF CONTENTS SECTION PAGE INTRODUCTION .....................................................................................................................................................................1 PRINCIPLE OF THE ASSAY ...................................................................................................................................................2 LIMITATIONS OF THE PROCEDURE .................................................................................................................................2 TECHNICAL HINTS .................................................................................................................................................................2 MATERIALS PROVIDED & STORAGE CONDITIONS ...................................................................................................3 OTHER SUPPLIES REQUIRED .............................................................................................................................................3 PRECAUTIONS .........................................................................................................................................................................4 SAMPLE COLLECTION & STORAGE .................................................................................................................................4