Structure of Nkp65 Bound to Its Keratinocyte Ligand Reveals Basis for Genetically Linked Recognition in Natural Killer Gene Complex
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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. -
Integrative Genome Analysis of Somatic P53 Mutant Osteosarcomas Identifies Ets2-Dependent Regulation of Small Nucleolar Rnas by Mutant P53 Protein
Downloaded from genesdev.cshlp.org on September 30, 2021 - Published by Cold Spring Harbor Laboratory Press Integrative genome analysis of somatic p53 mutant osteosarcomas identifies Ets2-dependent regulation of small nucleolar RNAs by mutant p53 protein Rasoul Pourebrahim,1 Yun Zhang,1 Bin Liu,1 Ruli Gao,1 Shunbin Xiong,1 Patrick P. Lin,2 Mark J. McArthur,3 Michael C. Ostrowski,4 and Guillermina Lozano1 1Department of Genetics, University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA; 2Department of Orthopedic Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA; 3Department of Veterinary Medicine and Surgery, University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA; 4Department of Cancer Biology and Genetics, The Ohio State University, Columbus, Ohio 43210, USA TP53 is the most frequently mutated gene in human cancer. Many mutant p53 proteins exert oncogenic gain-of- function (GOF) properties that contribute to metastasis, but the mechanisms mediating these functions remain poorly defined in vivo. To elucidate how mutant p53 GOF drives metastasis, we developed a traceable somatic os- teosarcoma mouse model that is initiated with either a single p53 mutation (p53R172H) or p53 loss in osteoblasts. Our study confirmed that p53 mutant mice developed osteosarcomas with increased metastasis as compared with p53-null mice. Comprehensive transcriptome RNA sequencing (RNA-seq) analysis of 16 tumors identified a cluster of small nucleolar RNAs (snoRNAs) that are highly up-regulated in p53 mutant tumors. Regulatory element analysis of these deregulated snoRNA genes identified strong enrichment of a common Ets2 transcription factor-binding site. Homozygous deletion of Ets2 in p53 mutant mice resulted in strong down-regulation of snoRNAs and reversed the prometastatic phenotype of mutant p53 but had no effect on osteosarcoma development, which remained 100% penetrant. -
Mapping the Genetic Architecture of Gene Regulation in Whole Blood
Mapping the Genetic Architecture of Gene Regulation in Whole Blood Katharina Schramm1,2., Carola Marzi3,4,5., Claudia Schurmann6., Maren Carstensen7,8., Eva Reinmaa9,10, Reiner Biffar11, Gertrud Eckstein1, Christian Gieger12, Hans-Jo¨ rgen Grabe13, Georg Homuth6, Gabriele Kastenmu¨ ller14, Reedik Ma¨gi10, Andres Metspalu9,10, Evelin Mihailov10,15, Annette Peters2, Astrid Petersmann16, Michael Roden7,8,17, Konstantin Strauch12,18, Karsten Suhre14,19, Alexander Teumer6,UweVo¨ lker6, Henry Vo¨ lzke20, Rui Wang-Sattler3,4, Melanie Waldenberger3,4, Thomas Meitinger1,2,21, Thomas Illig22, Christian Herder7,8., Harald Grallert3,4,5., Holger Prokisch1,2*. 1 Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany, 2 Institute of Human Genetics, Technical University Munich, Mu¨nchen, Germany, 3 Research Unit of Molecular Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany, 4 Institute of Epidemiology II, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany, 5 German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany, 6 Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany, 7 Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Du¨sseldorf, Du¨sseldorf, Germany, 8 German Center for Diabetes Research (DZD e.V.), -
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). -
Microarray Analysis of Bone Marrow Lesions in Osteoarthritis
ARD Online First, published on July 13, 2017 as 10.1136/annrheumdis-2017-211396 Basic and translational research Ann Rheum Dis: first published as 10.1136/annrheumdis-2017-211396 on 13 July 2017. Downloaded from EXTENDED REPORT Microarray analysis of bone marrow lesions in osteoarthritis demonstrates upregulation of genes implicated in osteochondral turnover, neurogenesis and inflammation Anasuya Kuttapitiya,1 Lena Assi,1 Ken Laing,1 Caroline Hing,2 Philip Mitchell,2 Guy Whitley,3 Abiola Harrison,1 Franklyn A Howe,3 Vivian Ejindu,2 Christine Heron,2 Nidhi Sofat1 ► Additional material is ABSTRACT affecting the knees in up to 37% of adults over published online only. To view Objective Bone marrow lesions (BMLs) are well 60.1 Pain is a major symptom for people with OA, please visit the journal online described in osteoarthritis (OA) using MRI and are with 16.7% of US adults aged 45 years and above (http:// dx. doi. org/ 10. 1136/ 1 annrheumdis- 2017- 211396). associated with pain, but little is known about their reporting pain as a predominant problem. pathological characteristics and gene expression. We Pain in OA is thought to arise from several 1 Institute for Infection & evaluated BMLs using novel tissue analysis tools to gain structures within the arthritic joint, including the Immunity, St George's, a deeper understanding of their cellular and molecular synovium (from which prostaglandins, leukot- University of London, London, UK expression. rienes and inflammatory mediators are released), 2St George's University Methods We recruited 98 participants, 72 with joint effusions, joint capsule involvement, tendon Hospitals NHS Foundation Trust, advanced OA requiring total knee replacement (TKR), 12 and muscle weakness that all contribute to pain London, UK 3 3 with mild OA and 14 non-OA controls. -
Identification of Platform-Independent Diagnostic Biomarker Panel For
bioRxiv preprint doi: https://doi.org/10.1101/758250; this version posted September 5, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Identification of Platform-Independent Diagnostic Biomarker Panel for 2 Hepatocellular Carcinoma using Large-scale Transcriptomics Data 3 Harpreet Kaur1,2, Anjali Dhall2, Rajesh Kumar1,2, Gajendra P. S. Raghava2,* 4 1 Bioinformatics Center, CSIR-Institute of Microbial Technology, Chandigarh, India 5 2 Department of Computational Biology, Indraprastha Institute of Information Technology, New 6 Delhi, India 7 8 Emails of Authors: 9 Harpreet Kaur: [email protected] , [email protected] 10 Anjali Dhall: [email protected] 11 Rajesh Kumar: [email protected] 12 Gajendra P.S. Raghava: [email protected] 13 14 15 * Correspondence 16 Professor, Department of Computational Biology 17 Indraprastha Institute of Information Technology, 18 Okhla Industrial Estate, Phase III, New Delhi 110020, 19 India. Tel.: +91 011 26907444; E-mail address: [email protected] 20 21 22 23 24 25 26 27 28 bioRxiv preprint doi: https://doi.org/10.1101/758250; this version posted September 5, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 29 Abstract 30 The high mortality rate of hepatocellular carcinoma (HCC) is primarily due to its late diagnosis. -
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. -
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 . -
Complexity and Diversity of the NKR-P1:Clr (Klrb1:Clec2) Recognition Systems
REVIEW ARTICLE published: 02 June 2014 doi: 10.3389/fimmu.2014.00214 Complexity and diversity of the NKR-P1:Clr (Klrb1:Clec2) recognition systems Christina L. Kirkham and James R. Carlyle* Department of Immunology, University of Toronto, Sunnybrook Research Institute, Toronto, ON, Canada Edited by: The NKR-P1 receptors were identified as prototypical natural killer (NK) cell surface anti- Andrew P.Makrigiannis, University of gens and later shown to be conserved from rodents to humans on NK cells and subsets of Ottawa, Canada T cells. C-type lectin-like in nature, they were originally shown to be capable of activating Reviewed by: Martin Herrmann, NK cell function and to recognize ligands on tumor cells. However, certain family members Universitätsklinikum Erlangen, have subsequently been shown to be capable of inhibiting NK cell activity, and to recognize Germany proteins encoded by a family of genetically linked C-type lectin-related ligands. Some of Eric O. Long, National Institute of these ligands are expressed by normal, healthy cells, and modulated during transforma- Allergy and Infectious Diseases, USA tion, infection, and cellular stress, while other ligands are upregulated during the immune *Correspondence: James R. Carlyle, Department of response and during pathological circumstances. Here, we discuss historical and recent Immunology, University of Toronto, developments in NKR-P1 biology that demonstrate this NK receptor–ligand system to be Sunnybrook Research Institute, 2075 far more complex and diverse than originally anticipated. -
CLEC1B Human Shrna Plasmid Kit (Locus ID 51266) Product Data
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 TL305362 CLEC1B Human shRNA Plasmid Kit (Locus ID 51266) Product data: Product Type: shRNA Plasmids Product Name: CLEC1B Human shRNA Plasmid Kit (Locus ID 51266) Locus ID: 51266 Synonyms: 1810061I13Rik; CLEC2; CLEC2B; PRO1384; QDED721 Vector: pGFP-C-shLenti (TR30023) Format: Lentiviral plasmids Components: CLEC1B - Human, 4 unique 29mer shRNA constructs in lentiviral GFP vector(Gene ID = 51266). 5µg purified plasmid DNA per construct Non-effective 29-mer scrambled shRNA cassette in pGFP-C-shLenti Vector, TR30021, included for free. RefSeq: NM_001099431, NM_016509, NM_016509.1, NM_016509.2, NM_016509.3, NM_001099431.1, BC029554 Summary: Natural killer (NK) cells express multiple calcium-dependent (C-type) lectin-like receptors, such as CD94 (KLRD1; MIM 602894) and NKG2D (KLRC4; MIM 602893), that interact with major histocompatibility complex class I molecules and either inhibit or activate cytotoxicity and cytokine secretion. CLEC2 is a C-type lectin-like receptor expressed in myeloid cells and NK cells (Colonna et al., 2000 [PubMed 10671229]).[supplied by OMIM, Jan 2011] shRNA Design: These shRNA constructs were designed against multiple splice variants at this gene locus. To be certain that your variant of interest is targeted, please contact [email protected]. If you need a special design or shRNA sequence, please utilize our custom shRNA service. This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 CLEC1B Human shRNA Plasmid Kit (Locus ID 51266) – TL305362 Performance OriGene guarantees that the sequences in the shRNA expression cassettes are verified to Guaranteed: correspond to the target gene with 100% identity. -
Beyond Gene Expression
Beyond gene expression Citation for published version (APA): Gupta, R. (2021). Beyond gene expression: novel methods and applications of transcript expression analyses in RNA-Seq. Maastricht University. https://doi.org/10.26481/dis.20210304rg Document status and date: Published: 01/01/2021 DOI: 10.26481/dis.20210304rg Document Version: Publisher's PDF, also known as Version of record Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.