Cellular and Molecular Mechanisms Underlying Prostate Cancer Development: Therapeutic Implications
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Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
RI-Mediated Mast Cell Activation Ε of Fc Tetraspanin CD151 Is A
Tetraspanin CD151 Is a Negative Regulator of Fc εRI-Mediated Mast Cell Activation Hiam Abdala-Valencia, Paul J. Bryce, Robert P. Schleimer, Joshua B. Wechsler, Lucas F. Loffredo, Joan M. Cook-Mills, This information is current as Chia-Lin Hsu and Sergejs Berdnikovs of September 26, 2021. J Immunol 2015; 195:1377-1387; Prepublished online 1 July 2015; doi: 10.4049/jimmunol.1302874 http://www.jimmunol.org/content/195/4/1377 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2015/07/01/jimmunol.130287 Material 4.DCSupplemental http://www.jimmunol.org/ References This article cites 63 articles, 28 of which you can access for free at: http://www.jimmunol.org/content/195/4/1377.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision by guest on September 26, 2021 • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2015 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Tetraspanin CD151 Is a Negative Regulator of Fc«RI-Mediated Mast Cell Activation Hiam Abdala-Valencia,* Paul J. -
Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only. -
GATA3 As an Adjunct Prognostic Factor in Breast Cancer Patients with Less Aggressive Disease: a Study with a Review of the Literature
diagnostics Article GATA3 as an Adjunct Prognostic Factor in Breast Cancer Patients with Less Aggressive Disease: A Study with a Review of the Literature Patrizia Querzoli 1, Massimo Pedriali 1 , Rosa Rinaldi 2 , Paola Secchiero 3, Paolo Giorgi Rossi 4 and Elisabetta Kuhn 5,6,* 1 Section of Anatomic Pathology, Department of Morphology, Surgery and Experimental Medicine, University of Ferrara, 44124 Ferrara, Italy; [email protected] (P.Q.); [email protected] (M.P.) 2 Section of Anatomic Pathology, ASST Mantova, Ospedale Carlo Poma, 46100 Mantova, Italy; [email protected] 3 Surgery and Experimental Medicine and Interdepartmental Center of Technology of Advanced Therapies (LTTA), Department of Morphology, University of Ferrara, 44121 Ferrara, Italy; [email protected] 4 Epidemiology Unit, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, 42122 Reggio Emilia, Italy; [email protected] 5 Division of Pathology, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milano, Italy 6 Department of Biomedical, Surgical, and Dental Sciences, University of Milan, 20122 Milano, Italy * Correspondence: [email protected]; Tel.: +39-02-5032-0564; Fax: +39-02-5503-2860 Abstract: Background: GATA binding protein 3 (GATA3) expression is positively correlated with Citation: Querzoli, P.; Pedriali, M.; estrogen receptor (ER) expression, but its prognostic value as an independent factor remains unclear. Rinaldi, R.; Secchiero, P.; Rossi, P.G.; Thus, we undertook the current study to evaluate the expression of GATA3 and its prognostic value Kuhn, E. GATA3 as an Adjunct in a large series of breast carcinomas (BCs) with long-term follow-up. Methods: A total of 702 Prognostic Factor in Breast Cancer consecutive primary invasive BCs resected between 1989 and 1993 in our institution were arranged Patients with Less Aggressive in tissue microarrays, immunostained for ER, progesterone receptor (PR), ki-67, HER2, p53, and Disease: A Study with a Review of GATA3, and scored. -
Chromatin State Barriers Enforce an Irreversible Mammalian Cell Fate Decision
bioRxiv preprint doi: https://doi.org/10.1101/2021.05.12.443709; this version posted May 14, 2021. 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. Chromatin state barriers… Blanco et al. 2021 Chromatin state barriers enforce an irreversible mammalian cell fate decision M. Andrés Blanco1,19,*,†,, David B. Sykes6,8,19, Lei Gu2,15,17,18,19, Mengjun Wu2,4,15, Ricardo Petroni1, Rahul Karnik7,8,9, Mathias Wawer10, Joshua Rico1, Haitao Li1, William D. Jacobus2,12,15, Ashwini Jambhekar2,15,11, Sihem Cheloufi5, Alexander Meissner7,8,9,13, Konrad Hochedlinger6,7,8,14, David T. Scadden6,8,9,*, and Yang Shi2,3,* 1 Department of Biomedical Sciences, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA 2 Division of Newborn Medicine, Boston Children’s Hospital, Boston, MA 02115, USA 3 Ludwig Institute for Cancer Research, Oxford Branch, Oxford University, UK 4 Current address: The Bioinformatics Centre, Department of Biology and Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark 5 Department of Biochemistry, Stem Cell Center, University of California, Riverside, Riverside, CA 92521, USA. 6 Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA. 7 Broad Institute of MIT and Harvard, Cambridge, MA, USA 8 Harvard Stem Cell Institute, Cambridge, Massachusetts, -
Anti-Human CD31 (EPR3094)-151Eu
PRD025-3151025D PRODUCT INFORMATION SHEET Anti-Human CD31/PECAM-1-151Eu Pathologist-Verified Clone for Imaging Mass Cytometry™ Catalog: 3151025D Clone: EPR3094 Package size and concentration: 25 µg, 0.5 mg/mL Isotype: Rabbit IgG Storage: Store at 4 °C. Do not freeze. Formulation: Antibody stabilizer with 0.05% sodium azide Reactivity: Human Application: IMC-Paraffin Technical Information Application: The metal-tagged antibody is designed and formulated for the application of Imaging Mass Cytometry (IMC™) using the Fluidigm Hyperion™ Imaging System on formalin-fixed, paraffin-embedded (FFPE) tissue sections. Quality control: Each lot of conjugated antibody is quality control- tested by Imaging Mass Cytometry on tissue sections. Recommended concentration: For optimal performance it is recommended that the antibody be titrated for the desired application. Suggested initial dilution range: IMC-Paraffin: 1:50 to 1:200 Description CD31, also known as platelet endothelial cell adhesion molecule-1 (PECAM-1) or endoCAM, is a type I transmembrane glycoprotein. It is expressed by endothelial cells on blood vessels, as well as by monocytes, granulocytes, platelets and a small subset of T cells. It plays a role in wound healing, angiogenesis and removal of aged neutrophils and in cellular migration in an inflammatory situation. Human spleen (FFPE) stained with 151Eu-anti-CD31 (EPR3094) at a dilution of 1:100 (green pseudocolor), 141Pr-anti-αSMA (1A4) (red pseudocolor), and iridium DNA intercalator (blue pseudocolor). Heat-mediated antigen retrieval was performed using Tris/EDTA buffer pH 9. Scale bar size = 100 µm. References Chang, Q. et al. "Staining of frozen and formalin-fixed, paraffin-embedded tissues with metal-labeled antibodies for imaging mass cytometry analysis." Current Protocols in Cytometry 82 (2017): 12.47.1–12.47.8. -
A Core Transcriptional Network Composed of Pax2/8, Gata3 and Lim1 Regulates Key Players of Pro/Mesonephros Morphogenesis
Developmental Biology 382 (2013) 555–566 Contents lists available at ScienceDirect Developmental Biology journal homepage: www.elsevier.com/locate/developmentalbiology Genomes and Developmental Control A core transcriptional network composed of Pax2/8, Gata3 and Lim1 regulates key players of pro/mesonephros morphogenesis Sami Kamel Boualia a, Yaned Gaitan a, Mathieu Tremblay a, Richa Sharma a, Julie Cardin b, Artur Kania b, Maxime Bouchard a,n a Goodman Cancer Research Centre and Department of Biochemistry, McGill University, 1160 Pine Ave. W., Montreal, Quebec, Canada H3A 1A3 b Institut de Recherches Cliniques de Montréal, Montréal, Québec, Canada H2W 1R7, Department of Anatomy and Cell Biology, Division of Experimental Medicine, McGill University, Montréal, Quebec, Canada, H3A 2B2 and Faculté de médecine, Université de Montréal, Montréal, Quebec, Canada, H3C 3J7. article info abstract Article history: Translating the developmental program encoded in the genome into cellular and morphogenetic Received 23 January 2013 functions requires the deployment of elaborate gene regulatory networks (GRNs). GRNs are especially Received in revised form crucial at the onset of organ development where a few regulatory signals establish the different 27 July 2013 programs required for tissue organization. In the renal system primordium (the pro/mesonephros), Accepted 30 July 2013 important regulators have been identified but their hierarchical and regulatory organization is still Available online 3 August 2013 elusive. Here, we have performed a detailed analysis of the GRN underlying mouse pro/mesonephros Keywords: development. We find that a core regulatory subcircuit composed of Pax2/8, Gata3 and Lim1 turns on a Kidney development deeper layer of transcriptional regulators while activating effector genes responsible for cell signaling Transcription and tissue organization. -
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. -
Mediator of DNA Damage Checkpoint 1 (MDC1) Is a Novel Estrogen Receptor Co-Regulator in Invasive 6 Lobular Carcinoma of the Breast 7 8 Evelyn K
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. 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 4.0 International license. 1 Running Title: MDC1 co-regulates ER in ILC 2 3 Research article 4 5 Mediator of DNA damage checkpoint 1 (MDC1) is a novel estrogen receptor co-regulator in invasive 6 lobular carcinoma of the breast 7 8 Evelyn K. Bordeaux1+, Joseph L. Sottnik1+, Sanjana Mehrotra1, Sarah E. Ferrara2, Andrew E. Goodspeed2,3, James 9 C. Costello2,3, Matthew J. Sikora1 10 11 +EKB and JLS contributed equally to this project. 12 13 Affiliations 14 1Dept. of Pathology, University of Colorado Anschutz Medical Campus 15 2Biostatistics and Bioinformatics Shared Resource, University of Colorado Comprehensive Cancer Center 16 3Dept. of Pharmacology, University of Colorado Anschutz Medical Campus 17 18 Corresponding author 19 Matthew J. Sikora, PhD.; Mail Stop 8104, Research Complex 1 South, Room 5117, 12801 E. 17th Ave.; Aurora, 20 CO 80045. Tel: (303)724-4301; Fax: (303)724-3712; email: [email protected]. Twitter: 21 @mjsikora 22 23 Authors' contributions 24 MJS conceived of the project. MJS, EKB, and JLS designed and performed experiments. JLS developed models 25 for the project. EKB, JLS, SM, and AEG contributed to data analysis and interpretation. SEF, AEG, and JCC 26 developed and performed informatics analyses. MJS wrote the draft manuscript; all authors read and revised the 27 manuscript and have read and approved of this version of the manuscript. -
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. -
Mathematical Modeling of Noise and Discovery of Genetic Expression Classes in Gliomas
Oncogene (2002) 21, 7164 – 7174 ª 2002 Nature Publishing Group All rights reserved 0950 – 9232/02 $25.00 www.nature.com/onc Mathematical modeling of noise and discovery of genetic expression classes in gliomas Hassan M Fathallah-Shaykh*,1, Mo Rigen1, Li-Juan Zhao1, Kanti Bansal1, Bin He1, Herbert H Engelhard3, Leonard Cerullo2, Kelvin Von Roenn2, Richard Byrne2, Lorenzo Munoz2, Gail L Rosseau2, Roberta Glick4, Terry Lichtor4 and Elia DiSavino1 1Department of Neurological Sciences, Rush Presbyterian – St. Lukes Medical Center, Chicago, Illinois, IL 60612, USA; 2Department of Neurosurgery, Rush Presbyterian – St. Lukes Medical Center, Chicago, Illinois, IL 60612, USA; 3Department of Neurosurgery, The University of Illinois at Chicago, Chicago, Illinois, IL 60612, USA; 4Department of Neurosurgery, The Cook County Hospital, Chicago, Illinois, IL 60612, USA The microarray array experimental system generates genetic repertoire in any disease-affected tissue. noisy data that require validation by other experimental However, genome-wide screening is still hampered by methods for measuring gene expression. Here we present the preponderance of false positive data in the gene an algebraic modeling of noise that extracts expression microarray experimental system (Ting Lee et al., 2000). measurements true to a high degree of confidence. This The following experiments are designed to profile the work profiles the expression of 19 200 cDNAs in 35 expression of 19 200 cDNAs in 35 human glioma human gliomas; the experiments are designed to generate samples. Here, we apply mathematical principles to four replicate spots/gene with switching of probes. The separate the noise and extract genes whose expression validity of the extracted measurements is confirmed by: levels are considered truly changed, to a high degree of (1) cluster analysis that generates a molecular classifica- confidence, in the tumor samples as compared to tion differentiating glioblastoma from lower-grade tumors normal brain. -
The Roles of Long Noncoding Rnas HNF1-AS1 and HNF4-AS1 in Drug
non-coding RNA Review The Roles of Long Noncoding RNAs HNF1α-AS1 and HNF4α-AS1 in Drug Metabolism and Human Diseases Liming Chen 1, Yifan Bao 1, Suzhen Jiang 1,2 and Xiao-bo Zhong 1,* 1 Department of Pharmaceutical Sciences, School of Pharmacy, University of Connecticut, Storrs, CT 06269, USA; [email protected] (L.C.); [email protected] (Y.B.); [email protected] (S.J.) 2 School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 51006, China * Correspondence: [email protected]; Tel.: +01-860-486-3697 Received: 25 May 2020; Accepted: 22 June 2020; Published: 24 June 2020 Abstract: Long noncoding RNAs (lncRNAs) are RNAs with a length of over 200 nucleotides that do not have protein-coding abilities. Recent studies suggest that lncRNAs are highly involved in physiological functions and diseases. lncRNAs HNF1α-AS1 and HNF4α-AS1 are transcripts of lncRNA genes HNF1α-AS1 and HNF4α-AS1, which are antisense lncRNA genes located in the neighborhood regions of the transcription factor (TF) genes HNF1α and HNF4α, respectively. HNF1α-AS1 and HNF4α-AS1 have been reported to be involved in several important functions in human physiological activities and diseases. In the liver, HNF1α-AS1 and HNF4α-AS1 regulate the expression and function of several drug-metabolizing cytochrome P450 (P450) enzymes, which also further impact P450-mediated drug metabolism and drug toxicity. In addition, HNF1α-AS1 and HNF4α-AS1 also play important roles in the tumorigenesis, progression, invasion, and treatment outcome of several cancers. Through interacting with different molecules, including miRNAs and proteins, HNF1α-AS1 and HNF4α-AS1 can regulate their target genes in several different mechanisms including miRNA sponge, decoy, or scaffold.