Detection of Classical 17P11.2 Deletions, an Atypical Deletion and RAI1 Alterations in Patients with Features Suggestive of Smith–Magenis Syndrome
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Cell Division Symmetry Control and Cancer Stem Cells
AIMS Molecular Science, 7(2): 82–98. DOI: 10.3934/molsci.2020006 Received: 15 February 2020 Accepted: 26 April 2020 Published: 06 May 2020 http://www.aimspress.com/journal/Molecular Review Cell division symmetry control and cancer stem cells Sreemita Majumdar and Song-Tao Liu* Department of Biological Sciences, University of Toledo, Toledo, OH 43606, USA * Correspondence: Email: [email protected]; Tel: +14195307853. Table S1. Genes encoding polarity and fate-determinant proteins involved in asymmetric cell division. C. elegans1 D. melanogaster 1 Mammals1 Description2 Associated with/ Interactors 3 Cellular Localization (mammalian cell)4 Serine/threonine protein microtubule-associated protein cell membrane, peripheral and lateral, par-1 par-1 MARK1/2/3/4 kinase MAPT/TAU cytoplasm, dendrite RING, Lipid binding par-2 - - domain PDZ for membrane, cell junction, adherens junction, cell cortex, par-3 baz PARD3 Oligomerization domain at actin, PARD6 endomembrane system, NTD Continued on next page 2 C. elegans1 D. melanogaster 1 Mammals1 Description2 Associated with/ Interactors 3 Cellular Localization (mammalian cell)4 Serine/threonine-protein nucleus, mitochondria, cytoplasm, par-4 Lkb1 STK11/LKB1 STRAD complex kinase membrane 14-3-3 domain binding par-5 14-3-3 YWHAB phosphoserine/ adapter to many proteins cytoplasm phosphothreonine motif cell membrane, centriolar satellite, actin par-6 par-6 PARD6A/B/G PB1, CRIB, PDZ PARD3 cytoskeleton,centrosome, cytoplasm ,ruffles PARD3, and a PARD6 protein PB1, AGC-Kinase (PARD6A, PARD6B or PARD6G) pkc-3 aPKC PRKCI/Z domain, DAG binding, cytoplasm, nucleus, membrane and a GTPase protein (CDC42 or Zinc finger domain RAC1), LLGL1,ECT2 LRR and PDZ protein Cadherin, Scrib-APC-beta-catenin nucleoplasm, basolateral plasma membrane, let-413 scrib SCRIB family. -
A Clinicopathological and Molecular Genetic Analysis of Low-Grade Glioma in Adults
A CLINICOPATHOLOGICAL AND MOLECULAR GENETIC ANALYSIS OF LOW-GRADE GLIOMA IN ADULTS Presented by ANUSHREE SINGH MSc A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy Brain Tumour Research Centre Research Institute in Healthcare Sciences Faculty of Science and Engineering University of Wolverhampton November 2014 i DECLARATION This work or any part thereof has not previously been presented in any form to the University or to any other body whether for the purposes of assessment, publication or for any other purpose (unless otherwise indicated). Save for any express acknowledgments, references and/or bibliographies cited in the work, I confirm that the intellectual content of the work is the result of my own efforts and of no other person. The right of Anushree Singh to be identified as author of this work is asserted in accordance with ss.77 and 78 of the Copyright, Designs and Patents Act 1988. At this date copyright is owned by the author. Signature: Anushree Date: 30th November 2014 ii ABSTRACT The aim of the study was to identify molecular markers that can determine progression of low grade glioma. This was done using various approaches such as IDH1 and IDH2 mutation analysis, MGMT methylation analysis, copy number analysis using array comparative genomic hybridisation and identification of differentially expressed miRNAs using miRNA microarray analysis. IDH1 mutation was present at a frequency of 71% in low grade glioma and was identified as an independent marker for improved OS in a multivariate analysis, which confirms the previous findings in low grade glioma studies. -
Tyrosine Kinase Oncogenes in Normal Hematopoiesis and Hematological Disease
Oncogene (2002) 21, 3314 ± 3333 ã 2002 Nature Publishing Group All rights reserved 0950 ± 9232/02 $25.00 www.nature.com/onc Tyrosine kinase oncogenes in normal hematopoiesis and hematological disease Blanca Scheijen1,2 and James D Grin*,1,2 1Department of Adult Oncology, Dana-Farber Cancer Institute, 44 Binney Street, Boston, Massachusetts, MA 02115, USA; 2Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA Tyrosine kinase oncogenes are formed as a result of Adaptors do not contain intrinsic catalytic activity but mutations that induce constitutive kinase activity. Many consist of independent functioning interaction modules of these tyrosine kinase oncogenes that are derived from like SH2-domain (mediates binding to phosphotyrosine genes, such as c-Abl, c-Fes, Flt3, c-Fms, c-Kit and residues), SH3-domain (interacts with polyproline-rich PDGFRb, that are normally involved in the regulation of PXXP stretch) or pleckstrin homology (PH) domain hematopoiesis or hematopoietic cell function. Despite (binds to inositol lipids). dierences in structure, normal function, and subcellular The ®rst tyrosine kinase oncogene associated with location, many of the tyrosine kinase oncogenes signal human hematologic disease, Bcr ± Abl, was identi®ed through the same pathways, and typically enhance almost twenty years ago, and there is now evidence for proliferation and prolong viability. They represent involvement of multiple tyrosine kinase oncogenes in excellent potential drug targets, and it is likely that acute and chronic leukemias, lymphomas, and myelo- additional mutations will be identi®ed in other kinases, mas. In each case, the tyrosine kinase activity of the their immediate downstream targets, or in proteins oncogene is constitutively activated by mutations that regulating their function. -
Anti-GRAP Antibody (ARG63124)
Product datasheet [email protected] ARG63124 Package: 100 μg anti-GRAP antibody Store at: -20°C Summary Product Description Goat Polyclonal antibody recognizes GRAP Tested Reactivity Hu Predict Reactivity Ms, Rat, Cow Tested Application WB Host Goat Clonality Polyclonal Isotype IgG Target Name GRAP Antigen Species Human Immunogen C-GFFPRSYVQPVHL Conjugation Un-conjugated Alternate Names GRB2-related adapter protein Application Instructions Application table Application Dilution WB 0.3 - 1 µg/ml Application Note WB: Recommend incubate at RT for 1h. * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 25 kDa Properties Form Liquid Purification Purified from goat serum by ammonium sulphate precipitation followed by antigen affinity chromatography using the immunizing peptide. Buffer Tris saline (pH 7.3), 0.02% Sodium azide and 0.5% BSA Preservative 0.02% Sodium azide Stabilizer 0.5% BSA Concentration 0.5 mg/ml Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C or below. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. www.arigobio.com 1/2 Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation Database links GeneID: 10750 Human Swiss-port # Q13588 Human Background This gene encodes a member of the GRB2/Sem5/Drk family and functions as a cytoplasmic signaling protein which contains an SH2 domain flanked by two SH3 domains. -
Genes in a Refined Smith-Magenis Syndrome Critical Deletion Interval on Chromosome 17P11.2 and the Syntenic Region of the Mouse
Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Article Genes in a Refined Smith-Magenis Syndrome Critical Deletion Interval on Chromosome 17p11.2 and the Syntenic Region of the Mouse Weimin Bi,1,6 Jiong Yan,1,6 Paweł Stankiewicz,1 Sung-Sup Park,1,7 Katherina Walz,1 Cornelius F. Boerkoel,1 Lorraine Potocki,1,3 Lisa G. Shaffer,1 Koen Devriendt,4 Małgorzata J.M. Nowaczyk,5 Ken Inoue,1 and James R. Lupski1,2,3,8 Departments of 1Molecular & Human Genetics, 2Pediatrics, Baylor College of Medicine, 3Texas Children’s Hospital, Houston, Texas 77030, USA; 4Centre for Human Genetics, University Hospital Gasthuisberg, Catholic University of Leuven, B-3000 Leuven, Belgium; 5Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario L8S 4J9, Canada Smith-Magenis syndrome (SMS) is a multiple congenital anomaly/mental retardation syndrome associated with behavioral abnormalities and sleep disturbance. Most patients have the same ∼4 Mb interstitial genomic deletion within chromosome 17p11.2. To investigate the molecular bases of the SMS phenotype, we constructed BAC/PAC contigs covering the SMS common deletion interval and its syntenic region on mouse chromosome 11. Comparative genome analysis reveals the absence of all three ∼200-kb SMS-REP low-copy repeats in the mouse and indicates that the evolution of SMS-REPs was accompanied by transposition of adjacent genes. Physical and genetic map comparisons in humans reveal reduced recombination in both sexes. Moreover, by examining the deleted regions in SMS patients with unusual-sized deletions, we refined the minimal Smith-Magenis critical region (SMCR) to an ∼1.1-Mb genomic interval that is syntenic to an ∼1.0-Mb region in the mouse. -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
Biological Databases What Is a Database ?
BIOLOGICAL DATABASES WHAT IS A DATABASE ? A structured collection of data held in computer storage; esp. one that incorporates software to make it accessible in a variety of ways; any large collection of information. A collection of data structured searchable (index) -> table of contents updated periodically (release) -> new edition cross-referenced (hyperlinks ) -> links with other db Includes also associated tools (software) necessary for access, updating, information insertion, information deletion…. A database consists of basic units called records or entries. Each record consists of fields, which hold pre-defined data related to the record. For example, a protein database would have protein sequences as records and protein properties as fields (e.g., name of protein, length, amino-acid sequence, …) 2 DATABASES ON THE INTERNET Biological databases often have web interfaces, which allow users to send queries to the databases. Some databases can be accessed by different web servers, each offering a different interface. request query web page result User Web server Database server 3 WHY BIOLOGICAL DATABASES ? Exponential growth in biological data. Data (genomic sequences, 3D structures, 2D gel analysis, MS analysis, Microarrays….) are no longer published in a conventional manner, but directly submitted to databases. Essential tools for biological research. The only way to publish massive amounts of data without using all the paper in the world. 4 NUCLEOTIDES 5 COMPLETE GENOMES Until 2018: Eukaryotes 5262 Prokaryotes 131446 Viruses 14027 6 SOME STATISTICS More than 1000 different ‘biological’ databases Variable size: <100Kb to >20Gb DNA: > 20 Gb Protein: 1 Gb 3D structure: 5 Gb Other: smaller Update frequency: daily to annually to seldom to forget about it . -
Distinct Genetic Alterations in Colorectal Cancer
Distinct Genetic Alterations in Colorectal Cancer Hassan Ashktorab1*, Alejandro A. Scha¨ffer2, Mohammad Daremipouran3, Duane T. Smoot3, Edward Lee3, Hassan Brim3 1 Department of Medicine and Cancer Center, Howard University, College of Medicine, Washington, DC, United States of America, 2 National Center for Biotechnology Information, National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Bethesda, Maryland, United States of America, 3 Department of Pathology, Howard University, College of Medicine, Washington, DC, United States of America Abstract Background: Colon cancer (CRC) development often includes chromosomal instability (CIN) leading to amplifications and deletions of large DNA segments. Epidemiological, clinical, and cytogenetic studies showed that there are considerable differences between CRC tumors from African Americans (AAs) and Caucasian patients. In this study, we determined genomic copy number aberrations in sporadic CRC tumors from AAs, in order to investigate possible explanations for the observed disparities. Methodology/Principal Findings: We applied genome-wide array comparative genome hybridization (aCGH) using a 105k chip to identify copy number aberrations in samples from 15 AAs. In addition, we did a population comparative analysis with aCGH data in Caucasians as well as with a widely publicized list of colon cancer genes (CAN genes). There was an average of 20 aberrations per patient with more amplifications than deletions. Analysis of DNA copy number of frequently altered chromosomes revealed that deletions occurred primarily in chromosomes 4, 8 and 18. Chromosomal duplications occurred in more than 50% of cases on chromosomes 7, 8, 13, 20 and X. The CIN profile showed some differences when compared to Caucasian alterations. Conclusions/Significance: Chromosome X amplification in male patients and chromosomes 4, 8 and 18 deletions were prominent aberrations in AAs. -
Multivariate Analysis Reveals Genetic Associations of the Resting Default
Multivariate analysis reveals genetic associations of PNAS PLUS the resting default mode network in psychotic bipolar disorder and schizophrenia Shashwath A. Medaa,1, Gualberto Ruañob,c, Andreas Windemuthb, Kasey O’Neila, Clifton Berwisea, Sabra M. Dunna, Leah E. Boccaccioa, Balaji Narayanana, Mohan Kocherlab, Emma Sprootena, Matcheri S. Keshavand, Carol A. Tammingae, John A. Sweeneye, Brett A. Clementzf, Vince D. Calhoung,h,i, and Godfrey D. Pearlsona,h,j aOlin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT 06102; bGenomas Inc., Hartford, CT 06102; cGenetics Research Center, Hartford Hospital, Hartford, CT 06102; dDepartment of Psychiatry, Beth Israel Deaconess Hospital, Harvard Medical School, Boston, MA 02215; eDepartment of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390; fDepartment of Psychology, University of Georgia, Athens, GA 30602; gThe Mind Research Network, Albuquerque, NM 87106; Departments of hPsychiatry and jNeurobiology, Yale University, New Haven, CT 06520; and iDepartment of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM 87106 Edited by Robert Desimone, Massachusetts Institute of Technology, Cambridge, MA, and approved April 4, 2014 (received for review July 15, 2013) The brain’s default mode network (DMN) is highly heritable and is Although risk for psychotic illnesses is driven in small part by compromised in a variety of psychiatric disorders. However, ge- highly penetrant, often private mutations such as copy number netic control over the DMN in schizophrenia (SZ) and psychotic variants, substantial risk also is likely conferred by multiple genes bipolar disorder (PBP) is largely unknown. Study subjects (n = of small effect sizes interacting together (7). According to the 1,305) underwent a resting-state functional MRI scan and were “common disease common variant” (CDCV) model, one would analyzed by a two-stage approach. -
Research Article Loss of LLGL1 Expression Correlates with Diffuse Gastric Cancer and Distant Peritoneal Metastases
Hindawi Canadian Journal of Gastroenterology and Hepatology Volume 2019, Article ID 2920493, 12 pages https://doi.org/10.1155/2019/2920493 Research Article Loss of LLGL1 Expression Correlates with Diffuse Gastric Cancer and Distant Peritoneal Metastases Alexander Desuki,1,2 Frank Staib ,1,3 Ines Gockel,4 Markus Moehler,1 Hauke Lang,5 Stefan Biesterfeld,6 Annett Maderer,1 Peter R. Galle ,1 Martin R. Berger,7 and Carl C. Schimanski 1,8 1 First Department of Internal Medicine, Johannes Gutenberg University, Langenbeckstraße 1, 55131 Mainz, Germany 2Tird Department of Internal Medicine, Johannes Gutenberg University, 55131 Mainz, Germany 3Department of Internal Medicine, Marienhospital Darmstadt gGmbH, Martinspfad 72, 64285 Darmstadt, Germany 4DepartmentofVisceral,Transplantation,ToracicandVascularSurgery,UniversityofLeipzig,Liebigstraße20, 04103 Leipzig, Germany 5Department of Abdominal and General Surgery, Johannes Gutenberg University, Langenbeckstraße 1, 55131 Mainz, Germany 6Institute of Pathology, Johannes Gutenberg University, Langenbeckstraße 1, 55131 Mainz, Germany 7Toxicology and Chemotherapy Unit, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany 8Second Department of Internal Medicine, Klinikum Darmstadt GmbH, Grafenstraße 9, 64283 Darmstadt, Germany Correspondence should be addressed to Peter R. Galle; [email protected] and Carl C. Schimanski; [email protected] Received 29 May 2018; Accepted 21 February 2019; Published 1 April 2019 Academic Editor: Masanao Nakamura Copyright © 2019 Alexander Desuki et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background.LossofLLGL1 has been associated with loss of cellular adhesion and dissemination of cells from colorectal cancer and malignant melanoma. -
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 -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine