DOCSLIB.ORG

Peripheral Blood Gene Expression in Alopecia Areata Reveals Molecular Pathways Distinguishing Heritability, Disease and Severity

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Peripheral Blood Gene Expression in Alopecia Areata Reveals Molecular Pathways Distinguishing Heritability, Disease and Severity Genes and Immunity (2010) 11, 531–541 & 2010 Macmillan Publishers Limited All rights reserved 1466-4879/10 www.nature.com/gene ORIGINAL ARTICLE Peripheral blood gene expression in alopecia areata reveals molecular pathways distinguishing heritability, disease and severity AB Coda, V Qafalijaj Hysa, K Seiffert-Sinha and AA Sinha Center for Investigative Dermatology, Division of Dermatology and Cutaneous Sciences, College of Human Medicine, East Lansing, MI, USA Alopecia areata (AA) is an autoimmune hair loss disorder in which systemic disturbances have been described, but are poorly understood. To evaluate disease mechanisms, we examined gene expression in the blood of defined clinical subgroups (patchy AA persistent type, AAP, n ¼ 5; alopecia universalis, AU, n ¼ 4) and healthy controls (unaffected relatives, UaR, n ¼ 5; unaffected non-relatives, UaNR, n ¼ 4) using microarrays. Unsupervised hierarchical clustering separates all four patient and control groups, producing three distinct expression patterns reflective of ‘inheritance’, ‘disease’ and ‘severity’ signatures. Functional classification of differentially expressed genes (DEGs) comparing disease (AAP, AU) vs normal (UaR) groups reveals upregulation in immune response, cytokine signaling, signal transduction, cell cycle, proteolysis and cell adhesion- related genes. Pathway analysis further reveals the activation of several genes related to natural killer-cell cytotoxicity, apoptosis, mitogen activated protein kinase, Wnt signaling and B- and T-cell receptor signaling in AA patients. Finally, 35 genes differentially expressed in AA blood overlap with DEGs previously identified in AA skin lesions. Our results implicate innate and adaptive immune processes while also revealing novel pathways, such as Wnt signaling and apoptosis, relevant to AA pathogenesis. Our data suggest that peripheral blood expression profiles of AA patients likely carry new biomarkers associated with disease susceptibility and expression. Genes and Immunity (2010) 11, 531–541; doi:10.1038/gene.2010.32; published online 10 June 2010 Keywords: alopecia areata; alopecia; microarray; pathogenesis; genetics Introduction highlighting the role of immune dysfunction as a crucial feature in AA pathogenesis. Alopecia areata (AA) is an autoimmune skin disorder The etiopathogenesis of AA is not completely under- typically characterized by the spontaneous onset of stood. The most widely accepted hypothesis describes patchy hair loss of the scalp. Although 80% of patients AA as a T-cell mediated autoimmune response targeting present with a minimal number of patches (AA; patchy an unknown antigen in anagen-stage hair follicles.8,9 persistent, AAP or transient, AAT), 7% of cases progress It has also been postulated that compromise of immune in clinical severity to total scalp-hair loss (alopecia totalis; privilege in normal hair follicles, mediated in part by AT) or total body hair loss (alopecia universalis, AU). interferon-gamma (INF-g),10 has a role in the suscep- The prevalence of AA in the United States is reported to tibility and pathogenesis of AA.11,12 Considerable evi- be 0.1–0.2% in the general population, with a lifetime risk dence indicates that genetic elements have a significant of 1.7%.1,2 The histopathological hallmark of AA is the role in the etiology of AA, as evidenced by the recent presence of a perifollicular and intrafollicular lympho- identification of a number of suggested susceptibility cytic infiltrate. T lymphocytes (predominantly CD4 þ loci,13 the high incidence of positive family history in cells), as well as Langerhans cells, macrophages and affected individuals14,15 and high twin concordance natural killer (NK) cells are found in the dermal papilla rates.16–20 Many epidemiologic studies have shown and matrix of the involved hair follicles.3,4 Lymphocytic a higher prevalence of autoimmune diseases, such as infiltration of the anagen hair bulb and dermal papilla is vitiligo, thyroid disease and collagen vascular disease, in accompanied by aberrant expression of human leukocyte AA patients and unaffected relatives (UaR)21,22 suggest- antigen class I and class II antigens and intercellular ing a genetic predisposition to autoimmunity associated adhesion molecule-1 on the follicular epithelium,5–7 with familial background of AA.23 These findings imply that systemic disturbances contribute to this T-cell Correspondence: Dr AA Sinha, Division of Dermatology and dependent, organ-specific disease. Overall, AA is a Cutaneous Sciences, Michigan State University, 4179 Biomedical complex, polygenic disease likely initiated by the and Physical Sciences Building, East Lansing, MI 48824-1320, USA. E-mail: [email protected] interactions between genetic and environmental factors Received 1 December 2009; revised and accepted 20 April 2010; triggering the immune dysfunction that results in published online 10 June 2010 autoimmune hair loss. Peripheral blood gene expression in alopecia areata AB Coda et al 532 Global gene-expression profiling by DNA microarray Results has become a valuable tool for the study of autoimmune and/or inflammatory diseases.24 Microarray studies on Unsupervised hierarchical clustering separates sample groups organ-specific autoimmune diseases have advanced our by familial inheritance, absence or presence of disease and understanding of autoimmune disease pathogenesis, and clinical subtype revealed targets for clinical biomarkers, prognostic We used Affymetrix U133 Plus 2.0 microarray chips factors and subtype distinction for individualized ther- (Affymetrix, Santa Clara, CA, USA) to generate gene apy.25–27 Our recent microarray analysis in AA patient expression profiles from buffy coat samples obtained skin samples,28 along with a previous microarray study in 5 alopecia areata, patchy persistent (AAP) patients, in murine and human AA skin,29 help to substantiate 4 alopecia universalis (AU) patients, 5 unaffected relatives AA as a Th1-cell-mediated autoimmune disorder with (UaR) and 4 unaffected non-relatives (UaNR) (Table 1). To a late secondary humoral response. No study, however, explore the similarities and differences in global gene has previously used gene microarray technology as a expression patterns among the samples without apriori large-scale screening tool to investigate gene regulatory knowledge of sample identity, we used an unsupervised alterations in the peripheral blood of AA patients. As hierarchical clustering method using those 551 probe sets with many organ-specific diseases, the systemic envi- with the highest variation across samples. This unbiased ronment in AA patients is likely to be critical in the approach was used to determine the extent to which global generation and regulation of the immune response gene expression analysis can be used to distinguish clinically and inflammatory cascade that is ultimately directed to defined subgroups (class prediction), as well as identify novel hair follicles. or unexpected gene expression patterns (class discovery). The aims of the present study were to (1) establish We report that unsupervised hierarchical clustering peripheral gene expression profiles associated with AA reveals distinct separation of AA patients from controls and AA subgroups and (2) examine AA-associated (Figure 1). Upon further evaluation, three unique transcriptional signatures to identify functional path- patterns emerge. First, our data reveal that AA patients ways and genes relevant to AA. On the basis of the and first-degree relatives of AA patients (AAP, AU and global microarray analysis in AA patients and healthy UaR) cluster distinctly from the healthy controls with no control blood, we report three distinct transcriptional familial connection to AA (UaNR), conceivably produ- signatures relevant to (i) the genetic predisposition to cing an ‘inheritance’ signature. Second, within this disease, (ii) the clinical expression of disease and (iii) the ‘inheritance’ cluster, AAP and AU samples further degree of phenotypic severity. Evaluation of each of these separate from UaR controls, with the exception of a signatures implicates several immune-related and single AU (‘AU 4’) sample, to produce a ‘disease’ signaling pathways in AA pathogenesis. signature. Third, within the ‘disease’ cluster, AAP Table 1 Demographic data for study subjects Sample code Race Age (years) Gender Disease type Length of disease (years) Unaffected non-relatives (UaNR) UaNR 1 Caucasian 40 F NA NA UaNR 2 Caucasian 32 F NA NA UaNR 3 Hispanic 33 F NA NA UaNR 4 Asian 37 M NA NA Unaffected relatives (UaR) UaR 1 Caucasian 27 F UaR NA UaR 2 Caucasian 57 M UaR NA UaR 3 Caucasian 22 M UaR NA UaR 4 African–American 42 F UaR NA UaR 5 Caucasian 48 F UaR NA Alopecia areata, patchy persistent (AAP) AAP 1 Caucasian 34 F AAP 9 AAP 2 Caucasian 25 F AAP 21 AAP 3 Hispanic 37 F AAP 13 AAP 4 African–American 42 F AAP 1 AAP 5 Caucasian 54 M AAP 29 Alopecia universalis (AU) AU 1 Caucasian 66 F AU 47 AU 2 Caucasian 62 M AU 47 AU 3 Hispanic 31 F AU 26 AU 4 Caucasian 23 M AU 11 Abbreviations: AAP, alopecia areata, patchy persistent; AU, alopecia universalis; F, female; M, male; UaNR, unaffected non-relatives; UaR, unaffected relatives. Genes and Immunity Peripheral blood gene expression in alopecia areata AB Coda et al 533 samples split from the AU samples to define a ‘severity’ signature. It should be noted, however, that one AAP patient (AAP 5) did share gene expression characteristics with control samples. It is noteworthy that this patient was the only one in this study who was undergoing
Load more

Recommended publications
  • 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]
  • To Study Mutant P53 Gain of Function, Various Tumor-Derived P53 Mutants
    Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science By Shama K Khokhar M.Sc., Bilaspur University, 2004 B.Sc., Bhopal University, 2002 2007 1 COPYRIGHT SHAMA K KHOKHAR 2007 2 WRIGHT STATE UNIVERSITY SCHOOL OF GRADUATE STUDIES Date of Defense: 12-03-07 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY SHAMA KHAN KHOKHAR ENTITLED Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science Madhavi P. Kadakia, Ph.D. Thesis Director Daniel Organisciak , Ph.D. Department Chair Committee on Final Examination Madhavi P. Kadakia, Ph.D. Steven J. Berberich, Ph.D. Michael Leffak, Ph.D. Joseph F. Thomas, Jr., Ph.D. Dean, School of Graduate Studies 3 Abstract Khokhar, Shama K. M.S., Department of Biochemistry and Molecular Biology, Wright State University, 2007 Differential effect of TAp63γ mutants on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. p63, a member of the p53 gene family, known to play a role in development, has more recently also been implicated in cancer progression. Mice lacking p63 exhibit severe developmental defects such as limb truncations, abnormal skin, and absence of hair follicles, teeth, and mammary glands. Germline missense mutations of p63 have been shown to be responsible for several human developmental syndromes including SHFM, EEC and ADULT syndromes and are associated with anomalies in the development of organs of epithelial origin.
    [Show full text]
  • UNIVERSITY of CALIFORNIA, IRVINE Combinatorial Regulation By
    UNIVERSITY OF CALIFORNIA, IRVINE Combinatorial regulation by maternal transcription factors during activation of the endoderm gene regulatory network DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Biological Sciences by Kitt D. Paraiso Dissertation Committee: Professor Ken W.Y. Cho, Chair Associate Professor Olivier Cinquin Professor Thomas Schilling 2018 Chapter 4 © 2017 Elsevier Ltd. © 2018 Kitt D. Paraiso DEDICATION To the incredibly intelligent and talented people, who in one way or another, helped complete this thesis. ii TABLE OF CONTENTS Page LIST OF FIGURES vii LIST OF TABLES ix LIST OF ABBREVIATIONS X ACKNOWLEDGEMENTS xi CURRICULUM VITAE xii ABSTRACT OF THE DISSERTATION xiv CHAPTER 1: Maternal transcription factors during early endoderm formation in 1 Xenopus Transcription factors co-regulate in a cell type-specific manner 2 Otx1 is expressed in a variety of cell lineages 4 Maternal otx1 in the endodermal conteXt 5 Establishment of enhancers by maternal transcription factors 9 Uncovering the endodermal gene regulatory network 12 Zygotic genome activation and temporal control of gene eXpression 14 The role of maternal transcription factors in early development 18 References 19 CHAPTER 2: Assembly of maternal transcription factors initiates the emergence 26 of tissue-specific zygotic cis-regulatory regions Introduction 28 Identification of maternal vegetally-localized transcription factors 31 Vegt and OtX1 combinatorially regulate the endodermal 33 transcriptome iii
    [Show full text]
  • Supplementary Table 1: Adhesion Genes Data Set
    Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,
    [Show full text]
  • Predicting Gene Ontology Biological Process from Temporal Gene Expression Patterns Astrid Lægreid,1,4 Torgeir R
    Methods Predicting Gene Ontology Biological Process From Temporal Gene Expression Patterns Astrid Lægreid,1,4 Torgeir R. Hvidsten,2 Herman Midelfart,2 Jan Komorowski,2,3,4 and Arne K. Sandvik1 1Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, N-7489 Trondheim, Norway; 2Department of Information and Computer Science, Norwegian University of Science and Technology, N-7491 Trondheim, Norway; 3The Linnaeus Centre for Bioinformatics, Uppsala University, SE-751 24 Uppsala, Sweden The aim of the present study was to generate hypotheses on the involvement of uncharacterized genes in biological processes. To this end,supervised learning was used to analyz e microarray-derived time-series gene expression data. Our method was objectively evaluated on known genes using cross-validation and provided high-precision Gene Ontology biological process classifications for 211 of the 213 uncharacterized genes in the data set used. In addition,new roles in biological process were hypothesi zed for known genes. Our method uses biological knowledge expressed by Gene Ontology and generates a rule model associating this knowledge with minimal characteristic features of temporal gene expression profiles. This model allows learning and classification of multiple biological process roles for each gene and can predict participation of genes in a biological process even though the genes of this class exhibit a wide variety of gene expression profiles including inverse coregulation. A considerable number of the hypothesized new roles for known genes were confirmed by literature search. In addition,many biological process roles hypothesi zed for uncharacterized genes were found to agree with assumptions based on homology information.
    [Show full text]
  • DISCLAIMER This Paper Was Submitted to the Bulletin of The
    DISCLAIMER This paper was submitted to the Bulletin of the World Health Organization and was posted to the Zika open site, according to the protocol for public health emergencies for international concern as described in Christopher Dye et al. ( http://dx.doi.org/10.2471/BLT.16.170860 ). The information herein is available for unrestricted use, distribution and reproduction in any medium, provided that the original work is properly cited as indicated by the Creative Commons Attribution 3.0 Intergovernmental Organizations licence (CC BY IGO 3.0). RECOMMENDED CITATION Taylor EW, Ruzicka JA. Antisense inhibition of selenoprotein synthesis by Zika virus may contribute to neurological disorders and microcephaly by mimicking SePP1 knockout and the genetic disease PCCA. [Submitted]. Bull World Health Organ. E-pub: 13 July 2016. doi: http://dx.doi.org/10.2471/BLT.16.182071 Antisense inhibition of selenoprotein synthesis by Zika virus may contribute to neurological disorders and microcephaly by mimicking SePP1 knockout and the genetic disease progressive cerebello-cerebral atrophy a b Ethan Will Taylor & Jan A. Ruzicka aDept. of Chemistry and Biochemistry, University of North Carolina at Greensboro, 435 Patricia A. Sullivan Science Building, PO Box 26170, Greensboro, NC 27402-6170, United States of America bDept. of Basic Pharmaceutical Sciences, Fred Wilson School of Pharmacy, High Point University, One University Parkway, High Point, NC 27268, United States of America Correspondence to Ethan Taylor (email: [email protected] ) (Submitted: 7 July 2016 – Published online: 13 July 2016) Zika-mediated antisense inhibition of selenoprotein synthesis and microcephaly, E.W. Taylor and J.A. Ruzicka, 2016 Abstract Objective: Selenium status plays a major role in health impacts of various RNA viruses.
    [Show full text]
  • Genome-Wide Transcriptome Analysis of Laminar Tissue During the Early Stages of Experimentally Induced Equine Laminitis
    GENOME-WIDE TRANSCRIPTOME ANALYSIS OF LAMINAR TISSUE DURING THE EARLY STAGES OF EXPERIMENTALLY INDUCED EQUINE LAMINITIS A Dissertation by JIXIN WANG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY December 2010 Major Subject: Biomedical Sciences GENOME-WIDE TRANSCRIPTOME ANALYSIS OF LAMINAR TISSUE DURING THE EARLY STAGES OF EXPERIMENTALLY INDUCED EQUINE LAMINITIS A Dissertation by JIXIN WANG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Approved by: Chair of Committee, Bhanu P. Chowdhary Committee Members, Terje Raudsepp Paul B. Samollow Loren C. Skow Penny K. Riggs Head of Department, Evelyn Tiffany-Castiglioni December 2010 Major Subject: Biomedical Sciences iii ABSTRACT Genome-wide Transcriptome Analysis of Laminar Tissue During the Early Stages of Experimentally Induced Equine Laminitis. (December 2010) Jixin Wang, B.S., Tarim University of Agricultural Reclamation; M.S., South China Agricultural University; M.S., Texas A&M University Chair of Advisory Committee: Dr. Bhanu P. Chowdhary Equine laminitis is a debilitating disease that causes extreme sufferring in afflicted horses and often results in a lifetime of chronic pain. The exact sequence of pathophysiological events culminating in laminitis has not yet been characterized, and this is reflected in the lack of any consistently effective therapeutic strategy. For these reasons, we used a newly developed 21,000 element equine-specific whole-genome oligoarray to perform transcriptomic analysis on laminar tissue from horses with experimentally induced models of laminitis: carbohydrate overload (CHO), hyperinsulinaemia (HI), and oligofructose (OF).
    [Show full text]
  • S1 Table Analyzed Transcriptomics Parameters of Lung Tissue of Chronic
    S1 Table Analyzed transcriptomics parameters of lung tissue of chronic obstructive pulmonary disease rats p- FCAbsolute regulation(B_v GeneSymbo GenbankAcces ProbeName value(B (B vs A) s_A) l sion vs A) A_44_P4095 0.0079 1.2996 down Gmpr NM_057188 18 A_44_P2605 NM_0011067 0.0378 1.2427 up Klhl28 80 35 A_44_P1052 0.0018 2.0900 up Hnrpll XM_233805 387 A_43_P1546 0.0365 1.3240 up Pde5a NM_133584 6 A_44_P7283 0.0035 1.2634 up AW915320 87 A_42_P8435 0.0143 1.1393 up 92 A_44_P4310 0.0124 1.3434 down Cyp2d4 U48220 92 A_44_P3056 0.0496 1.1467 up BP465973 36 A_44_P1779 0.0311 1.1157 down Rccd1 XM_218819 07 A_44_P9133 0.0129 1.2963 up 60 A_44_P3412 0.0167 1.3108 up AA997107 04 A_44_P9971 NM_0011057 0.0033 1.2820 up Atrx 74 57 A_42_P7763 0.0310 1.1275 up BF556698 00 A_44_P4634 0.0180 1.3210 up BQ210920 20 A_44_P5212 0.0101 1.2583 up AA925252 64 A_44_P8855 0.0469 1.2051 down 48 A_44_P6998 0.0151 1.5168 up 21 A_44_P1414 0.0236 1.2774 up AI575641 75 A_44_P4922 NM_0011064 0.0041 1.6816 down Eps8l3 14 63 A_43_P2202 0.0488 1.2176 up Setx XM_342400 0 A_44_P2066 0.0205 1.2767 up BF417274 31 A_44_P6213 0.0007 2.0237 up 04 A_44_P3775 0.0068 1.2952 up 20 A_44_P6058 0.0365 1.1240 up 38 A_44_P2861 0.0022 1.4896 up XM_226020 58 A_44_P9139 0.0108 1.5661 up 62 A_43_P1214 0.0058 1.9100 up Hnf4a NM_022180 6 A_44_P6525 NM_0011300 0.0036 1.1586 down Kdm1 85 98 A_44_P3541 0.0061 1.3319 down Cep250 XR_009560 50 A_44_P5160 RGD131055 NM_0011068 0.0293 1.2854 down 73 2 38 A_44_P2237 0.0192 1.3087 up AW142694 41 A_43_P1552 0.0096 1.2036 up Ccnd3 NM_012766 4 A_44_P4098 0.0479
    [Show full text]
  • Supplemental Table 1 List of Genes Differentially Expressed In
    Supplemental Table 1 List of genes differentially expressed in normal nasopharyngeal epithelium (N), metaplastic and displastic lesions (R), and carcinoma (T). Parametric Permutation Geom Geom Geom Unique Description Clone UG Gene symbol Map p-value p-value mean mean mean id cluster of of of ratios ratios ratios in in in class class class 1 : N 2 : R 3 : T 1 p < 1e-07 0 0.061 0.123 2.708 169329 secretory leukocyte protease IncytePD:2510171 Hs.251754 SLPI 20q12 inhibitor (antileukoproteinase) 2 p < 1e-07 0 0.125 0.394 1.863 163628 sodium channel, nonvoltage-gated IncytePD:1453049 Hs.446415 SCNN1A 12p13 1 alpha 3 p < 1e-07 0 0.122 0.046 1.497 160401 carcinoembryonic antigen-related IncytePD:2060355 Hs.73848 CEACAM6 19q13.2 cell adhesion molecule 6 (non- specific cross reacting antigen) 4 p < 1e-07 0 0.675 1.64 5.594 165101 monoglyceride lipase IncytePD:2174920 Hs.6721 MGLL 3q21.3 5 p < 1e-07 0 0.182 0.487 0.998 166827 nei endonuclease VIII-like 1 (E. IncytePD:1926409 Hs.28355 NEIL1 15q22.33 coli) 6 p < 1e-07 0 0.194 0.339 0.915 162931 hypothetical protein FLJ22418 IncytePD:2816379 Hs.36563 FLJ22418 1p11.1 7 p < 1e-07 0 1.313 0.645 13.593 162399 S100 calcium binding protein P IncytePD:2060823 Hs.2962 S100P 4p16 8 p < 1e-07 0 0.157 1.445 2.563 169315 selenium binding protein 1 IncytePD:2591494 Hs.334841 SELENBP1 1q21-q22 9 p < 1e-07 0 0.046 0.738 1.213 160115 prominin-like 1 (mouse) IncytePD:2070568 Hs.112360 PROML1 4p15.33 10 p < 1e-07 0 0.787 2.264 3.013 167294 HRAS-like suppressor 3 IncytePD:1969263 Hs.37189 HRASLS3 11q12.3 11 p < 1e-07 0 0.292 0.539 1.493 168221 Homo sapiens cDNA FLJ13510 IncytePD:64451 Hs.37896 2 fis, clone PLACE1005146.
    [Show full text]
  • Genome-Wide Screening Identifies Genes and Biological Processes
    Louisiana State University LSU Digital Commons LSU Doctoral Dissertations Graduate School 10-12-2018 Genome-Wide Screening Identifies Genes and Biological Processes Implicated in Chemoresistance and Oncogene-Induced Apoptosis Tengyu Ko Louisiana State University and Agricultural and Mechanical College, [email protected] Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_dissertations Part of the Cancer Biology Commons, Cell Biology Commons, and the Genomics Commons Recommended Citation Ko, Tengyu, "Genome-Wide Screening Identifies Genes and Biological Processes Implicated in Chemoresistance and Oncogene- Induced Apoptosis" (2018). LSU Doctoral Dissertations. 4715. https://digitalcommons.lsu.edu/gradschool_dissertations/4715 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Doctoral Dissertations by an authorized graduate school editor of LSU Digital Commons. For more information, please [email protected]. GENOME-WIDE SCREENING IDENTIFIES GENES AND BIOLOGICAL PROCESSES IMPLICATED IN CHEMORESISTANCE AND ONCOGENE- INDUCED APOPTOSIS A Dissertation Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical and Veterinary Medical Sciences through the Department of Comparative Biomedical Sciences by Tengyu Ko B.S., University of California, Santa Barbara 2010 December 2018 ACKNOWLEDGEMENTS I would like to express my sincerest gratitude to my major supervisor Dr. Shisheng Li for giving me the opportunity to join his team and the freedom to pursue projects. I appreciate all of his thoughts and efforts. Truly, none of these findings would be possible without his supervisions, supports, insightful discussions, and patience.
    [Show full text]
  • LOXL2-Mediated H3K4 Oxidation Reduces Chromatin Accessibility in Triple-Negative Breast Cancer Cells
    Oncogene (2020) 39:79–121 https://doi.org/10.1038/s41388-019-0969-1 ARTICLE LOXL2-mediated H3K4 oxidation reduces chromatin accessibility in triple-negative breast cancer cells 1 1 2 1 1 1 J. P. Cebrià-Costa ● L. Pascual-Reguant ● A. Gonzalez-Perez ● G. Serra-Bardenys ● J. Querol ● M. Cosín ● 1,3 4 4 2 5 6 G. Verde ● R. A. Cigliano ● W. Sanseverino ● S. Segura-Bayona ● A. Iturbide ● D. Andreu ● 1 1,7 1 1,7,8,9 10 6,10 P. Nuciforo ● C. Bernado-Morales ● V. Rodilla ● J. Arribas ● J. Yelamos ● A. Garcia de Herreros ● 2 1 T. H. Stracker ● S. Peiró Received: 28 January 2019 / Revised: 8 July 2019 / Accepted: 9 August 2019 / Published online: 28 August 2019 © The Author(s) 2019. This article is published with open access Abstract Oxidation of H3 at lysine 4 (H3K4ox) by lysyl oxidase-like 2 (LOXL2) generates an H3 modification with an unknown physiological function. We find that LOXL2 and H3K4ox are higher in triple-negative breast cancer (TNBC) cell lines and patient-derived xenografts (PDXs) than those from other breast cancer subtypes. ChIP-seq revealed that H3K4ox is located primarily in heterochromatin, where it is involved in chromatin compaction. Knocking down LOXL2 reduces H3K4ox levels 1234567890();,: 1234567890();,: and causes chromatin decompaction, resulting in a sustained activation of the DNA damage response (DDR) and increased susceptibility to anticancer agents. This critical role that LOXL2 and oxidized H3 play in chromatin compaction and DDR suggests that functionally targeting LOXL2 could be a way to sensitize TNBC cells to conventional therapy.
    [Show full text]
  • Distinct Roles of Selenoproteins in Facilitating Synaptic Plasticity for Learning and Memory
    DISTINCT ROLES OF SELENOPROTEINS IN FACILITATING SYNAPTIC PLASTICITY FOR LEARNING AND MEMORY A DISSERTATION SUBMITTED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HAWAI‘I AT MĀNOA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN CELL AND MOLECULAR BIOLOGY (NEUROSCIENCES) JULY 2017 By Elizabeth Quynh-Mai Dao Nguyen-Wu Dissertation Committee: Marla Berry, Chairperson Frederick Bellinger Robert Nichols Jun Panee Martin Rayner Lon White Keywords: Selenoprotein, Oxidative Stress, Neurodegeneration, Synaptic Plasticity ii TABLE OF CONTENTS Acknowledgments ………………………………………………………………………….…...ii Abstract……………………………………………………………………………….……….....x List of Tables………………………………………………………………………….………….v List of Figures...………………………………………………………………………….………vi List of Abbreviations..…...……………………………………………………………………..viii Chapter I. INTRODUCTION….…...……………………………….……………………………....1 Brief History of Selenoproteins….……...…….……………………..…..……..2 The Selenoprotein Family…….…………….……………………….…..……..4 Selenium Distribution and Synthesis of Selenoproteins….…..…….………10 Selenoproteins in Brain Function……………...….………………………….12 Selenoprotein P………………….…..…...…….………………………..…....13 Selenoprotein M……………....………….…...…………………………..…...16 Selenoproteins P and Selenoprotein M associated with Alzheimer’s Disease Pathology....………………………………………………………….18 Synaptic Plasticity………………...………………………………...…………21 II. GENETIC RESCUE OF SEPP1 IN SELENOPROTEIN P KNOCKOUT MICE Abstract..………….……………………………………………...…………….32 Introduction…..…………………………………………………...……………32 Methods……..……...……………...……………...……………...……………34
    [Show full text]