Crystal Structure of the Human NKR-P1 Bound to Its Lymphocyte Ligand LLT1 Reveals Receptor Clustering in the Immune Synapse
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The Inhibitory NKR-P1B:Clr-B Recognition Axis Facilitates Detection of Oncogenic Transformation and Cancer Immunosurveillance Miho Tanaka1,2, Jason H
Published OnlineFirst April 24, 2018; DOI: 10.1158/0008-5472.CAN-17-1688 Cancer Tumor Biology and Immunology Research The Inhibitory NKR-P1B:Clr-b Recognition Axis Facilitates Detection of Oncogenic Transformation and Cancer Immunosurveillance Miho Tanaka1,2, Jason H. Fine1,2, Christina L. Kirkham1,2, Oscar A. Aguilar1,2, Antoaneta Belcheva1, Alberto Martin1, Troy Ketela3,4, Jason Moffat3,4, David S.J. Allan1,2, and James R. Carlyle1,2 Abstract Natural killer (NK) cells express receptors specific for MHC class in a primary lymphoma model despite preferential rejection of – – I (MHC-I) molecules involved in "missing-self" recognition of Clr-b / hematopoietic cells previously observed following adop- cancer and virus-infected cells. Here we elucidate the role of MHC- tive transfer into na€ve wild-type mice in vivo. Collectively, these I-independent NKR-P1B:Clr-b interactions in the detection of findings suggest that the inhibitory NKR-P1B:Clr-b axis plays a oncogenic transformation by NK cells. Ras oncogene overexpres- beneficial role in innate detection of oncogenic transformation sion was found to promote a real-time loss of Clr-b on mouse via NK-cell–mediated cancer immune surveillance, in addition fibroblasts and leukemia cells, mediated in part via the Raf/MEK/ to a pathologic role in the immune escape of primary lympho- ERK and PI3K pathways. Ras-driven Clr-b downregulation ma cells in Em-cMyc mice in vivo. These results provide a model occurred at the level of the Clrb (Clec2d) promoter, nascent Clr-b for the human NKR-P1A:LLT1 system in cancer immunosur- transcripts, and cell surface Clr-b protein, in turn promoting veillance in patients with lymphoma and suggest it may rep- missing-self recognition via the NKR-P1B inhibitory receptor. -
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. -
CD29 Identifies IFN-Γ–Producing Human CD8+ T Cells With
+ CD29 identifies IFN-γ–producing human CD8 T cells with an increased cytotoxic potential Benoît P. Nicoleta,b, Aurélie Guislaina,b, Floris P. J. van Alphenc, Raquel Gomez-Eerlandd, Ton N. M. Schumacherd, Maartje van den Biggelaarc,e, and Monika C. Wolkersa,b,1 aDepartment of Hematopoiesis, Sanquin Research, 1066 CX Amsterdam, The Netherlands; bLandsteiner Laboratory, Oncode Institute, Amsterdam University Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; cDepartment of Research Facilities, Sanquin Research, 1066 CX Amsterdam, The Netherlands; dDivision of Molecular Oncology and Immunology, Oncode Institute, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands; and eDepartment of Molecular and Cellular Haemostasis, Sanquin Research, 1066 CX Amsterdam, The Netherlands Edited by Anjana Rao, La Jolla Institute for Allergy and Immunology, La Jolla, CA, and approved February 12, 2020 (received for review August 12, 2019) Cytotoxic CD8+ T cells can effectively kill target cells by producing therefore developed a protocol that allowed for efficient iso- cytokines, chemokines, and granzymes. Expression of these effector lation of RNA and protein from fluorescence-activated cell molecules is however highly divergent, and tools that identify and sorting (FACS)-sorted fixed T cells after intracellular cytokine + preselect CD8 T cells with a cytotoxic expression profile are lacking. staining. With this top-down approach, we performed an un- + Human CD8 T cells can be divided into IFN-γ– and IL-2–producing biased RNA-sequencing (RNA-seq) and mass spectrometry cells. Unbiased transcriptomics and proteomics analysis on cytokine- γ– – + + (MS) analyses on IFN- and IL-2 producing primary human producing fixed CD8 T cells revealed that IL-2 cells produce helper + + + CD8 Tcells. -
Changes in Peripheral and Local Tumor Immunity After Neoadjuvant Chemotherapy Reshape Clinical Outcomes in Patients with Breast Cancer Margaret L
Published OnlineFirst August 21, 2020; DOI: 10.1158/1078-0432.CCR-19-3685 CLINICAL CANCER RESEARCH | TRANSLATIONAL CANCER MECHANISMS AND THERAPY Changes in Peripheral and Local Tumor Immunity after Neoadjuvant Chemotherapy Reshape Clinical Outcomes in Patients with Breast Cancer Margaret L. Axelrod1, Mellissa J. Nixon1, Paula I. Gonzalez-Ericsson2, Riley E. Bergman1, Mark A. Pilkinton3, Wyatt J. McDonnell3, Violeta Sanchez1,2, Susan R. Opalenik1, Sherene Loi4, Jing Zhou5, Sean Mackay5, Brent N. Rexer1, Vandana G. Abramson1, Valerie M. Jansen1, Simon Mallal3, Joshua Donaldson1, Sara M. Tolaney6, Ian E. Krop6, Ana C. Garrido-Castro6, Jonathan D. Marotti7,8, Kevin Shee9, Todd. W. Miller8,9, Melinda E. Sanders2,10, Ingrid A. Mayer1,2, Roberto Salgado4,11, and Justin M. Balko1,2 ABSTRACT ◥ Purpose: The recent approval of anti-programmed death-ligand Results: In non-TNBC, no change in expression of any single 1 immunotherapy in combination with nab-paclitaxel for meta- gene was associated with RFS or OS, while in TNBC upregulation of static triple-negative breast cancer (TNBC) highlights the need to multiple immune-related genes and gene sets were associated with understand the role of chemotherapy in modulating the tumor improved long-term outcome. High cytotoxic T-cell signatures immune microenvironment (TIME). present in the peripheral blood of patients with breast cancer at Experimental Design: We examined immune-related gene surgery were associated with persistent disease and recurrence, expression patterns before and after neoadjuvant chemotherapy suggesting active antitumor immunity that may indicate ongoing (NAC) in a series of 83 breast tumors, including 44 TNBCs, from disease burden. patients with residual disease (RD). -
Human Lectins, Their Carbohydrate Affinities and Where to Find Them
biomolecules Review Human Lectins, Their Carbohydrate Affinities and Where to Review HumanFind Them Lectins, Their Carbohydrate Affinities and Where to FindCláudia ThemD. Raposo 1,*, André B. Canelas 2 and M. Teresa Barros 1 1, 2 1 Cláudia D. Raposo * , Andr1 é LAQVB. Canelas‐Requimte,and Department M. Teresa of Chemistry, Barros NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2829‐516 Caparica, Portugal; [email protected] 12 GlanbiaLAQV-Requimte,‐AgriChemWhey, Department Lisheen of Chemistry, Mine, Killoran, NOVA Moyne, School E41 of ScienceR622 Co. and Tipperary, Technology, Ireland; canelas‐ [email protected] NOVA de Lisboa, 2829-516 Caparica, Portugal; [email protected] 2* Correspondence:Glanbia-AgriChemWhey, [email protected]; Lisheen Mine, Tel.: Killoran, +351‐212948550 Moyne, E41 R622 Tipperary, Ireland; [email protected] * Correspondence: [email protected]; Tel.: +351-212948550 Abstract: Lectins are a class of proteins responsible for several biological roles such as cell‐cell in‐ Abstract:teractions,Lectins signaling are pathways, a class of and proteins several responsible innate immune for several responses biological against roles pathogens. such as Since cell-cell lec‐ interactions,tins are able signalingto bind to pathways, carbohydrates, and several they can innate be a immuneviable target responses for targeted against drug pathogens. delivery Since sys‐ lectinstems. In are fact, able several to bind lectins to carbohydrates, were approved they by canFood be and a viable Drug targetAdministration for targeted for drugthat purpose. delivery systems.Information In fact, about several specific lectins carbohydrate were approved recognition by Food by andlectin Drug receptors Administration was gathered for that herein, purpose. plus Informationthe specific organs about specific where those carbohydrate lectins can recognition be found by within lectin the receptors human was body. -
Literature Mining Sustains and Enhances Knowledge Discovery from Omic Studies
LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES by Rick Matthew Jordan B.S. Biology, University of Pittsburgh, 1996 M.S. Molecular Biology/Biotechnology, East Carolina University, 2001 M.S. Biomedical Informatics, University of Pittsburgh, 2005 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Rick Matthew Jordan It was defended on December 2, 2015 and approved by Shyam Visweswaran, M.D., Ph.D., Associate Professor Rebecca Jacobson, M.D., M.S., Professor Songjian Lu, Ph.D., Assistant Professor Dissertation Advisor: Vanathi Gopalakrishnan, Ph.D., Associate Professor ii Copyright © by Rick Matthew Jordan 2016 iii LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES Rick Matthew Jordan, M.S. University of Pittsburgh, 2016 Genomic, proteomic and other experimentally generated data from studies of biological systems aiming to discover disease biomarkers are currently analyzed without sufficient supporting evidence from the literature due to complexities associated with automated processing. Extracting prior knowledge about markers associated with biological sample types and disease states from the literature is tedious, and little research has been performed to understand how to use this knowledge to inform the generation of classification models from ‘omic’ data. Using pathway analysis methods to better understand the underlying biology of complex diseases such as breast and lung cancers is state-of-the-art. However, the problem of how to combine literature- mining evidence with pathway analysis evidence is an open problem in biomedical informatics research. -
University of California Santa Cruz Sample
UNIVERSITY OF CALIFORNIA SANTA CRUZ SAMPLE-SPECIFIC CANCER PATHWAY ANALYSIS USING PARADIGM A dissertation submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in BIOMOLECULAR ENGINEERING AND BIOINFORMATICS by Stephen C. Benz June 2012 The Dissertation of Stephen C. Benz is approved: Professor David Haussler, Chair Professor Joshua Stuart Professor Nader Pourmand Dean Tyrus Miller Vice Provost and Dean of Graduate Studies Copyright c by Stephen C. Benz 2012 Table of Contents List of Figures v List of Tables xi Abstract xii Dedication xiv Acknowledgments xv 1 Introduction 1 1.1 Identifying Genomic Alterations . 2 1.2 Pathway Analysis . 5 2 Methods to Integrate Cancer Genomics Data 10 2.1 UCSC Cancer Genomics Browser . 11 2.2 BioIntegrator . 16 3 Pathway Analysis Using PARADIGM 20 3.1 Method . 21 3.2 Comparisons . 26 3.2.1 Distinguishing True Networks From Decoys . 27 3.2.2 Tumor versus Normal - Pathways associated with Ovarian Cancer 29 3.2.3 Differentially Regulated Pathways in ER+ve vs ER-ve breast can- cers . 36 3.2.4 Therapy response prediction using pathways (Platinum Free In- terval in Ovarian Cancer) . 38 3.3 Unsupervised Stratification of Cancer Patients by Pathway Activities . 42 4 SuperPathway - A Global Pathway Model for Cancer 51 4.1 SuperPathway in Ovarian Cancer . 55 4.2 SuperPathway in Breast Cancer . 61 iii 4.2.1 Chin-Naderi Cohort . 61 4.2.2 TCGA Breast Cancer . 63 4.3 Cross-Cancer SuperPathway . 67 5 Pathway Analysis of Drug Effects 74 5.1 SuperPathway on Breast Cell Lines . -
CLEC2D (NM 001197317) Human Tagged ORF Clone – RG230997 | Origene
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RG230997 CLEC2D (NM_001197317) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: CLEC2D (NM_001197317) Human Tagged ORF Clone Tag: TurboGFP Symbol: CLEC2D Synonyms: CLAX; LLT1; OCIL Vector: pCMV6-AC-GFP (PS100010) E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: Neomycin ORF Nucleotide >RG230997 representing NM_001197317 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGCATGACAGTAACAATGTGGAGAAAGACATTACACCATCTGAATTGCCTGCAAACCCAGCAATAAGAG CTAACTGCCATCAAGAGCCATCAGTATGTCTTCAAGCTGCATGCCCAGAAAGCTGGATTGGTTTTCAAAG AAAGTGTTTCTATTTTTCTGATGACACCAAGAACTGGACATCAAGTCAGAGGTTTTGTGACTCACAAGAT GCTGATCTTGCTCAGGTTGAAAGCTTCCAGGAACTGAATTTCCTGTTGAGATATAAAGGCCCATCTGATC ACTGGATTGGGCTGAGCAGAGAACAAGGCCAACCATGGAAATGGATAAATGGTACTGAATGGACAAGACA GTTTCCTATCCTGGGAGCAGGAGAGTGTGCCTATTTGAATGACAAAGGTGCCAGTAGTGCCAGGCACTAC ACAGAGAGGAAGTGGATTTGTTCCAAATCAGATATACATGTC ACGCGTACGCGGCCGCTCGAG - GFP Tag - GTTTAA Protein Sequence: >RG230997 representing NM_001197317 Red=Cloning site Green=Tags(s) MHDSNNVEKDITPSELPANPAIRANCHQEPSVCLQAACPESWIGFQRKCFYFSDDTKNWTSSQRFCDSQD ADLAQVESFQELNFLLRYKGPSDHWIGLSREQGQPWKWINGTEWTRQFPILGAGECAYLNDKGASSARHY TERKWICSKSDIHV TRTRPLE - GFP Tag - V Restriction Sites: SgfI-MluI This product is to be used for laboratory only. Not -
C07k - 2021.08
CPC - C07K - 2021.08 C07K PEPTIDES (peptides in foodstuffs A23; obtaining protein compositions for foodstuffs, working-up proteins for foodstuffs A23J; preparations for medicinal purposes A61K; peptides containing beta-lactam rings C07D; cyclic dipeptides not having in their molecule any other peptide link than those which form their ring, e.g. piperazine-2,5-diones, C07D; ergot alkaloids of the cyclic peptide type C07D 519/02; macromolecular compounds having statistically distributed amino acid units in their molecules, i.e. when the preparation does not provide for a specific; but for a random sequence of the amino acid units, homopolyamides and block copolyamides derived from amino acids C08G 69/00; macromolecular products derived from proteins C08H 1/00; preparation of glue or gelatine C09H; single cell proteins, enzymes C12N; genetic engineering processes for obtaining peptides C12N 15/00; compositions for measuring or testing processes involving enzymes C12Q; investigation or analysis of biological material G01N 33/00) Relationships with other classification places An amino acid per se is classified in C07D while peptides (starting from dipeptides) are classified in C07K. Subclass C07K is a function oriented entry for the compounds themselves and does not cover the application or use of the compounds under the subclass definition. For classifying such information other entries exist, for example: preservation of bodies of humans or animals or plants or parts thereof; Biocides, e.g. as disinfectants, as pesticides, as herbicides; pest repellants or attractants; plant growth regulators are classified in A01N. Preparations for medical, dental, or toilet purposes are classified in A61K. Amino acids or derivatives thereof are classified in C07C or C07D. -
UC San Francisco Previously Published Works
UCSF UC San Francisco Previously Published Works Title FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease. Permalink https://escholarship.org/uc/item/91k8p2km Journal Genome biology, 9(12) ISSN 1474-7596 Authors Chen, Rong Morgan, Alex A Dudley, Joel et al. Publication Date 2008 DOI 10.1186/gb-2008-9-12-r170 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Open Access Research2008ChenetVolume al. 9, Issue 12, Article R170 FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease Rong Chen*†‡, Alex A Morgan*†‡, Joel Dudley*†‡, Tarangini Deshpande§, Li Li†, Keiichi Kodama*†‡, Annie P Chiang*†‡ and Atul J Butte*†‡ Addresses: *Stanford Center for Biomedical Informatics Research, 251 Cmpus Drive, Stanford, CA 94305, USA. †Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA. ‡Lucile Packard Children's Hospital, 725 Welch Road, Palo Alto, CA 94304, USA. §NuMedii Inc., Menlo Park, CA 94025, USA. Correspondence: Atul J Butte. Email: [email protected] Published: 5 December 2008 Received: 17 June 2008 Revised: 26 September 2008 Genome Biology 2008, 9:R170 (doi:10.1186/gb-2008-9-12-r170) Accepted: 5 December 2008 The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2008/9/12/R170 © 2008 Chen et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. -
Single-Cell Transcriptomes Reveal a Complex Cellular Landscape in the Middle Ear and Differential Capacities for Acute Response to Infection
fgene-11-00358 April 9, 2020 Time: 15:55 # 1 ORIGINAL RESEARCH published: 15 April 2020 doi: 10.3389/fgene.2020.00358 Single-Cell Transcriptomes Reveal a Complex Cellular Landscape in the Middle Ear and Differential Capacities for Acute Response to Infection Allen F. Ryan1*, Chanond A. Nasamran2, Kwang Pak1, Clara Draf1, Kathleen M. Fisch2, Nicholas Webster3 and Arwa Kurabi1 1 Departments of Surgery/Otolaryngology, UC San Diego School of Medicine, VA Medical Center, La Jolla, CA, United States, 2 Medicine/Center for Computational Biology & Bioinformatics, UC San Diego School of Medicine, VA Medical Center, La Jolla, CA, United States, 3 Medicine/Endocrinology, UC San Diego School of Medicine, VA Medical Center, La Jolla, CA, United States Single-cell transcriptomics was used to profile cells of the normal murine middle ear. Clustering analysis of 6770 transcriptomes identified 17 cell clusters corresponding to distinct cell types: five epithelial, three stromal, three lymphocyte, two monocyte, Edited by: two endothelial, one pericyte and one melanocyte cluster. Within some clusters, Amélie Bonnefond, Institut National de la Santé et de la cell subtypes were identified. While many corresponded to those cell types known Recherche Médicale (INSERM), from prior studies, several novel types or subtypes were noted. The results indicate France unexpected cellular diversity within the resting middle ear mucosa. The resolution of Reviewed by: Fabien Delahaye, uncomplicated, acute, otitis media is too rapid for cognate immunity to play a major Institut Pasteur de Lille, France role. Thus innate immunity is likely responsible for normal recovery from middle ear Nelson L. S. Tang, infection. The need for rapid response to pathogens suggests that innate immune The Chinese University of Hong Kong, China genes may be constitutively expressed by middle ear cells. -
Genetic Mapping of the Major Histocompatibility Complex in the Zebra Finch (Taeniopygia Guttata)
This is a repository copy of Genetic mapping of the major histocompatibility complex in the zebra finch (Taeniopygia guttata). White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/152446/ Version: Accepted Version Article: Ekblom, R., Stapley, J., Ball, A.D. et al. (3 more authors) (2011) Genetic mapping of the major histocompatibility complex in the zebra finch (Taeniopygia guttata). Immunogenetics, 63 (8). pp. 523-530. ISSN 0093-7711 https://doi.org/10.1007/s00251-011-0525-9 This is a post-peer-review, pre-copyedit version of an article published in Immunogenetics. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00251-011-0525-9. Reuse Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of the full text version. This is indicated by the licence information on the White Rose Research Online record for the item. Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ Manuscript Click here to download Manuscript: zfMHCmapp_manuscript_resubm2.doc Click here to view linked References 1 Genetic mapping of the major histocompatibility complex in the 1 2 3 4 2 zebra finch (Taeniopygia guttata) 5 6 3 7 8 1,2* 2 2, 3 2 2 9 4 Robert Ekblom , Jessica Stapley , Alex D.