UC San Diego UC San Diego Electronic Theses and Dissertations

Total Page:16

File Type:pdf, Size:1020Kb

UC San Diego UC San Diego Electronic Theses and Dissertations UC San Diego UC San Diego Electronic Theses and Dissertations Title Insights from reconstructing cellular networks in transcription, stress, and cancer Permalink https://escholarship.org/uc/item/6s97497m Authors Ke, Eugene Yunghung Ke, Eugene Yunghung Publication Date 2012 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Insights from Reconstructing Cellular Networks in Transcription, Stress, and Cancer A dissertation submitted in the partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioinformatics and Systems Biology by Eugene Yunghung Ke Committee in charge: Professor Shankar Subramaniam, Chair Professor Inder Verma, Co-Chair Professor Web Cavenee Professor Alexander Hoffmann Professor Bing Ren 2012 The Dissertation of Eugene Yunghung Ke is approved, and it is acceptable in quality and form for the publication on microfilm and electronically ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ Co-Chair ________________________________________________________________ Chair University of California, San Diego 2012 iii DEDICATION To my parents, Victor and Tai-Lee Ke iv EPIGRAPH [T]here are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there some things we do not know. But there are also unknown unknowns; there are things we do not know we don't know. Donald Rumsfeld v TABLE OF CONTENTS SIGNATURE PAGE .............................................................,............................... iii DEDICATION .......................................................................................................iv EPIGRAPH ........................................................................................................... v TABLE OF CONTENTS .......................................................................................vi LIST OF FIGURES ............................................................................................. xiv LIST OF TABLES ............................................................................................... xix ACKNOWLEDGEMENTS ....................................................................................xx VITA .................................................................................................................. xxii ABSTRACT OF THE DISSERTATION ............................................................. xxiii INTRODUCTION .................................................................................................. 1 Bioinformatics and Systems Biology ................................................................. 1 Experimental Methods ...................................................................................... 2 Microarrays. ................................................................................................... 2 Next-Gen Sequencing. .................................................................................. 3 Computational Methods .................................................................................... 4 Preprocessing. .............................................................................................. 4 Normalization. ............................................................................................... 5 vi Summarization. ............................................................................................. 5 Differentially expressed genes. ..................................................................... 6 Multiple Testing, ............................................................................................ 7 Functional annotation. ................................................................................... 7 Experimental Design ....................................................................................... 11 Curse of Dimensionality .................................................................................. 12 CHAPTER 1 NF-kB BINDING ............................................................................ 14 Introduction ..................................................................................................... 14 Representations of Response Elements. .................................................... 15 NF-kappaB family. ....................................................................................... 17 Secret Word Problem ...................................................................................... 19 Historical Perspective. ................................................................................. 19 Predictive Power. ........................................................................................ 19 Conservation. .............................................................................................. 20 Expression ...................................................................................................... 22 Target genes. .............................................................................................. 22 Expression. .................................................................................................. 23 Guilt By Association. ....................................................................................... 24 Cog in the machine. ........................................................................................ 25 vii Discussion ....................................................................................................... 26 CHAPTER 2 OXIDATIVE STRESS .................................................................... 29 Introduction ..................................................................................................... 29 Hydrogen Peroxide Induces Oxidative Stress in Primary Endothelial Cells .... 31 Results ............................................................................................................ 33 Hemichannels and Connexins. .................................................................... 33 Cellular Sources of ROS. ............................................................................ 34 ROS clearance. ........................................................................................... 37 MAPK/P38 signaling. ................................................................................... 40 NRF Pathway. ............................................................................................. 42 DNA repair pathways. ................................................................................. 43 BCL2 family. ................................................................................................ 45 Loss of Mitochondria. .................................................................................. 46 Caspase Cascade. ...................................................................................... 47 TP53, ROS clearance, and MTOR. ............................................................. 49 Heme function, synthesis and degradation.................................................. 51 Reproducibility Issues ..................................................................................... 53 Verification of microarray trends. ................................................................. 53 Testing of H202 and HMVEC-L. .................................................................. 56 viii Calibration of Assays. .................................................................................. 57 Loss of Hydrogen Peroxide in Media. .......................................................... 59 Assay conditions. ........................................................................................ 60 Real Time-PCR data. .................................................................................. 61 Discussion ....................................................................................................... 63 Heme. .......................................................................................................... 64 Methods .......................................................................................................... 65 Cell culture. ................................................................................................. 65 Cell Staining. ............................................................................................... 65 Spectrophotometry. ..................................................................................... 66 Hydrogen Peroxide Colormetric kit. ............................................................. 66 LDH assay. .................................................................................................. 66 Caspase Activity. ......................................................................................... 66 Total RNA preparation. ................................................................................ 66 RT-PCR. ...................................................................................................... 66 Microarray analysis. .................................................................................... 66 Data analysis. .............................................................................................. 67 Pathways.
Recommended publications
  • Connexin 40.1 (GJD4) (NM 153368) Human Tagged ORF Clone Lentiviral Particle – RC222438L3V | 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 RC222438L3V Connexin 40.1 (GJD4) (NM_153368) Human Tagged ORF Clone Lentiviral Particle Product data: Product Type: Lentiviral Particles Product Name: Connexin 40.1 (GJD4) (NM_153368) Human Tagged ORF Clone Lentiviral Particle Symbol: GJD4 Synonyms: CX40.1 Vector: pLenti-C-Myc-DDK-P2A-Puro (PS100092) ACCN: NM_153368 ORF Size: 1110 bp ORF Nucleotide The ORF insert of this clone is exactly the same as(RC222438). Sequence: OTI Disclaimer: The molecular sequence of this clone aligns with the gene accession number as a point of reference only. However, individual transcript sequences of the same gene can differ through naturally occurring variations (e.g. polymorphisms), each with its own valid existence. This clone is substantially in agreement with the reference, but a complete review of all prevailing variants is recommended prior to use. More info OTI Annotation: This clone was engineered to express the complete ORF with an expression tag. Expression varies depending on the nature of the gene. RefSeq: NM_153368.1 RefSeq Size: 1580 bp RefSeq ORF: 1113 bp Locus ID: 219770 UniProt ID: Q96KN9 Protein Families: Transmembrane MW: 40 kDa Gene Summary: Connexins, such as GJD4, are involved in the formation of gap junctions, intercellular conduits that directly connect the cytoplasms of contacting cells. Each gap junction channel is formed by docking of 2 hemichannels, each of which contains 6 connexin subunits (Sohl et al., 2003 [PubMed 12881038]).[supplied by OMIM, Mar 2008] This product is to be used for laboratory only.
    [Show full text]
  • Down-Regulation of Stem Cell Genes, Including Those in a 200-Kb Gene Cluster at 12P13.31, Is Associated with in Vivo Differentiation of Human Male Germ Cell Tumors
    Research Article Down-Regulation of Stem Cell Genes, Including Those in a 200-kb Gene Cluster at 12p13.31, Is Associated with In vivo Differentiation of Human Male Germ Cell Tumors James E. Korkola,1 Jane Houldsworth,1,2 Rajendrakumar S.V. Chadalavada,1 Adam B. Olshen,3 Debbie Dobrzynski,2 Victor E. Reuter,4 George J. Bosl,2 and R.S.K. Chaganti1,2 1Cell Biology Program and Departments of 2Medicine, 3Epidemiology and Biostatistics, and 4Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York Abstract on the degree and type of differentiation (i.e., seminomas, which Adult male germ cell tumors (GCTs) comprise distinct groups: resemble undifferentiated primitive germ cells, and nonseminomas, seminomas and nonseminomas, which include pluripotent which show varying degrees of embryonic and extraembryonic embryonal carcinomas as well as other histologic subtypes patterns of differentiation; refs. 2, 3). Nonseminomatous GCTs are exhibiting various stages of differentiation. Almost all GCTs further subdivided into embryonal carcinomas, which show early show 12p gain, but the target genes have not been clearly zygotic or embryonal-like differentiation, yolk sac tumors and defined. To identify 12p target genes, we examined Affymetrix choriocarcinomas, which exhibit extraembryonal forms of differ- (Santa Clara, CA) U133A+B microarray (f83% coverage of 12p entiation, and teratomas, which show somatic differentiation along genes) expression profiles of 17 seminomas, 84 nonseminoma multiple lineages (3). Both seminomas and embryonal carcinoma GCTs, and 5 normal testis samples. Seventy-three genes on 12p are known to express stem cell markers, such as POU5F1 (4) and were significantly overexpressed, including GLUT3 and REA NANOG (5).
    [Show full text]
  • Derivation of Stable Microarray Cancer-Differentiating Signatures Using Consensus Scoring of Multiple Random Sampling and Gene-Ranking Consistency Evaluation
    Research Article Derivation of Stable Microarray Cancer-Differentiating Signatures Using Consensus Scoring of Multiple Random Sampling and Gene-Ranking Consistency Evaluation Zhi Qun Tang,1,2 Lian Yi Han,1,2 Hong Huang Lin,1,2 Juan Cui,1,2 Jia Jia,1,2 Boon Chuan Low,2,3 Bao Wen Li,2,4 and Yu Zong Chen1,2 1Bioinformatics and Drug Design Group, Department of Pharmacy; 2Center for Computational Science and Engineering; and Departments of 3Biological Sciences and 4Physics, National University of Singapore, Singapore, Singapore Abstract sampling methods. Only 1 to 5 of the 4 to 60 selected predictor Microarrays have been explored for deriving molecular genes in each of these sets are present in more than half of the signatures to determine disease outcomes, mechanisms, other nine sets (Table 1), and 2 to 20 of the predictor genes in each targets, and treatment strategies. Although exhibiting good set are cancer related (Table 2). Despite the use of sophisticated predictive performance, some derived signatures are unstable class differentiation and signature selection methods, the selected due to noises arising from measurement variability and signatures show few overlapping predictor genes, as in the case of biological differences. Improvements in measurement, anno- other microarray data sets including non–Hodgkin lymphoma, tation, and signature selection methods have been proposed. acute lymphocytic leukemia, breast cancer, lung adenocarcinoma, We explored a new signature selection method that incorpo- medulloblastoma, hepatocellular carcinoma, and acute myeloid rates consensus scoring of multiple random sampling and leukemia (9, 15). multistep evaluation of gene-ranking consistency for maxi- Although these signatures display high cancer differentiation mally avoiding erroneous elimination of predictor genes.
    [Show full text]
  • Sorbonne Université/China Scholarship Council Program 2021
    Sorbonne Université/China Scholarship Council program 2021 Thesis proposal Title of the research project: Hnf1b regulation during kidney development and regeneration Joint supervision: no Joint PhD (cotutelle): no Thesis supervisor: … Muriel Umbhauer. Email address of the thesis supervisor: [email protected] Institution: …… Sorbonne Université …. Doctoral school (N°+name): ED …. …… ED 515 Complexité du Vivant Research laboratory: UMR7622 CNRS Laboratory of developmental biology Name of the laboratory director: … Sylvie Schneider-Maunoury Email address of the laboratory director: [email protected] Subject description (2 pages max): 1) Study context The POU homeodomain transcription factor hepatocyte nuclear factor 1β (Hnf1b) plays an essential role in vertebrate kidney development. Heterozygous mutations in human HNF1B cause the complex multisystem syndrome known as Renal Cysts And Diabetes (RCAD). The most prominent clinical features of this autosomal dominant disorder are non-diabetic renal disease resulting from abnormal renal development and diabetes mellitus (reviewed by Clissold RL et al., 2015). During early mouse kidney development, Hnf1b has been shown to be required for ureteric bud branching and initiation of nephrogenesis (Lokmane et al., 2010). Hnf1b conditional inactivation in murine nephron progenitors has revealed an additional role in segment fate Xenopus is a well established and attractive model to study kidney development (Krneta-Stankic V. et al, 2017). Renal function at larval stages relies on two pronephroi located on both sides of the body, each consisting on one giant nephron displaying the same structural and functional organisation than the mammalian nephron. Moreover, pronephric and metanephric differentiation and morphogenesis share most of the signalling cascades and gene regulatory networks.
    [Show full text]
  • Overlap of Vitamin a and Vitamin D Target Genes with CAKUT- Related Processes [Version 1; Peer Review: 1 Approved with Reservations]
    F1000Research 2021, 10:395 Last updated: 21 JUL 2021 BRIEF REPORT Overlap of vitamin A and vitamin D target genes with CAKUT- related processes [version 1; peer review: 1 approved with reservations] Ozan Ozisik1, Friederike Ehrhart 2,3, Chris T Evelo 2, Alberto Mantovani4, Anaı̈s Baudot 1,5 1Aix Marseille University, Inserm, MMG, Marseille, 13385, France 2Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, 6200 MD, The Netherlands 3Department of Bioinformatics, NUTRIM/MHeNs, Maastricht University, Maastricht, 6200 MD, The Netherlands 4Istituto Superiore di Sanità, Rome, 00161, Italy 5Barcelona Supercomputing Center (BSC), Barcelona, 08034, Spain v1 First published: 18 May 2021, 10:395 Open Peer Review https://doi.org/10.12688/f1000research.51018.1 Latest published: 18 May 2021, 10:395 https://doi.org/10.12688/f1000research.51018.1 Reviewer Status Invited Reviewers Abstract Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) are a 1 group of abnormalities affecting the kidneys and their outflow tracts, which include the ureters, the bladder, and the urethra. CAKUT version 1 patients display a large clinical variability as well as a complex 18 May 2021 report aetiology, as only 5% to 20% of the cases have a monogenic origin. It is thereby suspected that interactions of both genetic and 1. Elena Menegola, Università degli Studi di environmental factors contribute to the disease. Vitamins are among the environmental factors that are considered for CAKUT aetiology. In Milano, Milan, Italy this study, we collected vitamin A and vitamin D target genes and Any reports and responses or comments on the computed their overlap with CAKUT-related gene sets.
    [Show full text]
  • Podocyte Specific Knockdown of Klf15 in Podocin-Cre Klf15flox/Flox Mice Was Confirmed
    SUPPLEMENTARY FIGURE LEGENDS Supplementary Figure 1: Podocyte specific knockdown of Klf15 in Podocin-Cre Klf15flox/flox mice was confirmed. (A) Primary glomerular epithelial cells (PGECs) were isolated from 12-week old Podocin-Cre Klf15flox/flox and Podocin-Cre Klf15+/+ mice and cultured at 37°C for 1 week. Real-time PCR was performed for Nephrin, Podocin, Synaptopodin, and Wt1 mRNA expression (n=6, ***p<0.001, Mann-Whitney test). (B) Real- time PCR was performed for Klf15 mRNA expression (n=6, *p<0.05, Mann-Whitney test). (C) Protein was also extracted and western blot analysis for Klf15 was performed. The representative blot of three independent experiments is shown in the top panel. The bottom panel shows the quantification of Klf15 by densitometry (n=3, *p<0.05, Mann-Whitney test). (D) Immunofluorescence staining for Klf15 and Wt1 was performed in 12-week old Podocin-Cre Klf15flox/flox and Podocin-Cre Klf15+/+ mice. Representative images from four mice in each group are shown in the left panel (X 20). Arrows show colocalization of Klf15 and Wt1. Arrowheads show a lack of colocalization. Asterisk demonstrates nonspecific Wt1 staining. “R” represents autofluorescence from RBCs. In the right panel, a total of 30 glomeruli were selected in each mouse and quantification of Klf15 staining in the podocytes was determined by the ratio of Klf15+ and Wt1+ cells to Wt1+ cells (n=6 mice, **p<0.01, unpaired t test). Supplementary Figure 2: LPS treated Podocin-Cre Klf15flox/flox mice exhibit a lack of recovery in proteinaceous casts and tubular dilatation after DEX administration.
    [Show full text]
  • Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
    Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897
    [Show full text]
  • The Purification and Identification of Interactors to Elucidate Novel Connections in the HEK 293 Cell Line
    The Purification and Identification of Interactors to Elucidate Novel Connections in the HEK 293 Cell Line Brett Hawley Biochemistry, Microbiology and Immunology Faculty of Medicine University of Ottawa © Brett Hawley, Ottawa, Canada, 2012 ABSTRACT The field of proteomics studies the structure and function of proteins in a large scale and high throughput manner. My work in the field of proteomics focuses on identifying interactions between proteins and discovering novel interactions. The identification of these interactions provides new information on metabolic and disease pathways and the working proteome of a cell. Cells are lysed and purified using antibody based affinity purification followed by digestion and identification using an HPLC coupled to a mass spectrometer. In my studies, I looked at the interaction networks of several AD related genes (Apolipoprotein E, Clusterin variant 1 and 2, Low-density lipoprotein receptor, Phosphatidylinositol binding clathrin assembly protein, Alpha- synuclein and Platelet-activating factor receptor) and an endosomal recycling pathway involved in cholesterol metabolism (Eps15 homology domain 1,2 and 4, Proprotein convertase subtilisin/kexin type 9 and Low-density lipoprotein receptor). Several novel and existing interactors were identified and these interactions were validated using co-immunopurification, which could be the basis for future research. ii ACKNOWLEDGEMENTS I would like to take this opportunity to thank my supervisor, Dr. Daniel Figeys, for his support and guidance throughout my studies in his lab. It was a great experience to work in his lab and I am very thankful I was given the chance to learn and work under him. I would also like to thank the members of my lab for all their assistance in learning new techniques and equipment in the lab.
    [Show full text]
  • 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.
    [Show full text]
  • Pdf Sub-Classification of Patients with a Molecular Alteration Provides Better Response [57]
    Theranostics 2021, Vol. 11, Issue 12 5759 Ivyspring International Publisher Theranostics 2021; 11(12): 5759-5777. doi: 10.7150/thno.57659 Research Paper Homeobox B5 promotes metastasis and poor prognosis in Hepatocellular Carcinoma, via FGFR4 and CXCL1 upregulation Qin He1, Wenjie Huang2, Danfei Liu1, Tongyue Zhang1, Yijun Wang1, Xiaoyu Ji1, Meng Xie1, Mengyu Sun1, Dean Tian1, Mei Liu1, Limin Xia1 1. Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China. 2. Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases; Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology; Clinical Medicine Research Center for Hepatic Surgery of Hubei Province; Key Laboratory of Organ Transplantation, Ministry of Education and Ministry of Public Health, Wuhan, Hubei, 430030, China. Corresponding author: Dr. Limin Xia, Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China; Phone: 86 27 6937 8507; Fax: 86 27 8366 2832; E-mail: [email protected]. © The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions. Received: 2020.12.29; Accepted: 2021.03.17; Published: 2021.03.31 Abstract Background: Since metastasis remains the main reason for HCC-associated death, a better understanding of molecular mechanism underlying HCC metastasis is urgently needed.
    [Show full text]
  • DYNC1I1 (NM 001135556) Human Tagged ORF Clone 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 RC226881 DYNC1I1 (NM_001135556) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: DYNC1I1 (NM_001135556) Human Tagged ORF Clone Tag: Myc-DDK Symbol: DYNC1I1 Synonyms: DNCI1; DNCIC1 Vector: pCMV6-Entry (PS100001) E. coli Selection: Kanamycin (25 ug/mL) Cell Selection: Neomycin 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 / 4 DYNC1I1 (NM_001135556) Human Tagged ORF Clone – RC226881 ORF Nucleotide >RC226881 representing NM_001135556 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGTCTGACAAAAGTGACTTAAAAGCTGAGCTAGAGCGCAAAAAGCAGCGCTTAGCACAGATAAGAGAAG AGAAGAAACGGAAGGAAGAGGAGAGGAAAAAGAAAGAGGCTGATATGCAGCAGAAGAAAGAACCCGTTCA GGACGACTCTGATCTGGATCGCAAACGACGAGAGACAGAGGCTTTGCTGCAAAGCATTGGTATCTCACCG GAGCCGCCTCTAGTCCCAACCCCTATGTCTCCCTCCTCGAAATCAGTGAGCACTCCCAGTGAAGCTGGAA GCCAAGACTCAGGCGATCTGGGGCCATTAACAAGGACCCTGCAGTGGGACACAGACCCCTCAGTGCTCCA GCTGCAGTCAGACTCAGAACTTGGAAGAAGACTGCATAAACTGGGCGTGTCAAAGGTCACCCAAGTGGAT TTCCTGCCAAGGGAAGTAGTGTCCTACTCAAAGGAGACCCAGACTCCTCTTGCCACGCATCAGTCTGAAG AGGATGAGGAAGATGAGGAAATGGTGGAATCTAAAGTTGGCCAGGACTCAGAACTGGAAAATCAGGACAA AAAACAGGAAGTGAAGGAAGCCCCTCCAAGAGAGTTGACAGAGGAAGAAAAACAGCAGATCATTCATTCA
    [Show full text]
  • Clinical Vignette Novel Bi-Allelic Variants in GJC2 Associated
    Clinical Vignette Novel Bi-allelic Variants in GJC2 Associated Pelizaeus- Merzbacher-like Disease 1: Clinical Clues and Differential Diagnosis Veronica Arora, Sapna Sandal, Ishwar Verma Institute of Medical Genetics and Genomics, Sir Ganga Ram Hospital, New Delhi Correspondence to: Dr Ishwar C Verma Email: [email protected] Abstract the environment and did not follow objects. Head titubation was present. There was no facial dys- Hypomyelinating Leukodystrophy-2 (HLD2) or morphism. Anthropometric measurements were Pelizaeus-Merzbacher-like disease 1 (PMLD1) is a as follows: length 82cm (+1.2SD), weight 10.6Kg slowly progressive leukodystrophy characterized (+1.1SD) and head circumference 47.7cm (+1.2SD). by nystagmus, hypotonia, and developmental Central nervous system examination showed bilat- delay. It is a close differential diagnosis for eral pendular nystagmus, axial hypotonia, dystonic Pelizaeus- Merzbacher disease (PMD) and should posturing, and choreo-athetoid movements (Figure be suspected in patients with features of PMD but 1). Deep tendon reflexes were brisk with extensor who are negative on testing for duplication of the plantar responses. The rest of the systemic PLP1 gene. We describe a case of a 16-month-old examination was non-contributory. MRI of the boy with a novel homozygous mutation in the GJC2 brain (axial view) showed diffuse hypo-myelination gene resulting in hypomyelinating leukodystrophy- in the peri-ventricular and sub-cortical area and 2. The clinical clues as well as features of other cerebellar white matter changes (Figure 2). disorders presenting similarly are discussed. Given the presence of hypotonia, brisk reflexes, nystagmus and hypomyelination on MRI, a deletion Clinical description duplication analysis for the PLP1 gene was done which was negative.
    [Show full text]