Mechanistic Study of Fragile Site Instability by Investigating Ret/Ptc Rearrangements, a Common Cause of Papillary Thyroid Carcinoma
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Influencers on Thyroid Cancer Onset: Molecular Genetic Basis
G C A T T A C G G C A T genes Review Influencers on Thyroid Cancer Onset: Molecular Genetic Basis Berta Luzón-Toro 1,2, Raquel María Fernández 1,2, Leticia Villalba-Benito 1,2, Ana Torroglosa 1,2, Guillermo Antiñolo 1,2 and Salud Borrego 1,2,* 1 Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville (IBIS), University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain; [email protected] (B.L.-T.); [email protected] (R.M.F.); [email protected] (L.V.-B.); [email protected] (A.T.); [email protected] (G.A.) 2 Centre for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain * Correspondence: [email protected]; Tel.: +34-955-012641 Received: 3 September 2019; Accepted: 6 November 2019; Published: 8 November 2019 Abstract: Thyroid cancer, a cancerous tumor or growth located within the thyroid gland, is the most common endocrine cancer. It is one of the few cancers whereby incidence rates have increased in recent years. It occurs in all age groups, from children through to seniors. Most studies are focused on dissecting its genetic basis, since our current knowledge of the genetic background of the different forms of thyroid cancer is far from complete, which poses a challenge for diagnosis and prognosis of the disease. In this review, we describe prevailing advances and update our understanding of the molecular genetics of thyroid cancer, focusing on the main genes related with the pathology, including the different noncoding RNAs associated with the disease. -
Genome-Wide Analysis of Host-Chromosome Binding Sites For
Lu et al. Virology Journal 2010, 7:262 http://www.virologyj.com/content/7/1/262 RESEARCH Open Access Genome-wide analysis of host-chromosome binding sites for Epstein-Barr Virus Nuclear Antigen 1 (EBNA1) Fang Lu1, Priyankara Wikramasinghe1, Julie Norseen1,2, Kevin Tsai1, Pu Wang1, Louise Showe1, Ramana V Davuluri1, Paul M Lieberman1* Abstract The Epstein-Barr Virus (EBV) Nuclear Antigen 1 (EBNA1) protein is required for the establishment of EBV latent infection in proliferating B-lymphocytes. EBNA1 is a multifunctional DNA-binding protein that stimulates DNA replication at the viral origin of plasmid replication (OriP), regulates transcription of viral and cellular genes, and tethers the viral episome to the cellular chromosome. EBNA1 also provides a survival function to B-lymphocytes, potentially through its ability to alter cellular gene expression. To better understand these various functions of EBNA1, we performed a genome-wide analysis of the viral and cellular DNA sites associated with EBNA1 protein in a latently infected Burkitt lymphoma B-cell line. Chromatin-immunoprecipitation (ChIP) combined with massively parallel deep-sequencing (ChIP-Seq) was used to identify cellular sites bound by EBNA1. Sites identified by ChIP- Seq were validated by conventional real-time PCR, and ChIP-Seq provided quantitative, high-resolution detection of the known EBNA1 binding sites on the EBV genome at OriP and Qp. We identified at least one cluster of unusually high-affinity EBNA1 binding sites on chromosome 11, between the divergent FAM55 D and FAM55B genes. A con- sensus for all cellular EBNA1 binding sites is distinct from those derived from the known viral binding sites, sug- gesting that some of these sites are indirectly bound by EBNA1. -
NIH Public Access Author Manuscript Pharmacogenet Genomics
NIH Public Access Author Manuscript Pharmacogenet Genomics. Author manuscript; available in PMC 2012 September 01. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Pharmacogenet Genomics. 2011 September ; 21(9): 607–613. doi:10.1097/FPC.0b013e3283415515. PharmGKB summary: very important pharmacogene information for PTGS2 Caroline F. Thorna, Tilo Grosserc, Teri E. Kleina, and Russ B. Altmana,b aDepartment of Genetics, Stanford University Medical Center, Stanford, California bDepartment of Bioengineering, Stanford University Medical Center, Stanford, California cInstitute for Translational Medicine and Therapeutics, University of Pennsylvania, Pennsylvania, USA Keywords cyclooxygenase-2; coxibs; non-steroidal anti-inflammatory drugs; pharmacogenomics; PTGS2; rs20417; rs5275; rs689466 Very important pharmacogene: PTGS2 This PharmGKB summary briefly discusses the PTGS2 gene and current understanding of its function, structure, regulation, and pharmacogenomic relevance. We also present three variants with pharmacogenomic significance and highlight the gaps in our knowledge of PTGS2-drug interactions. Overview The PTGS2 gene codes for prostaglandin G/H synthase-2, which catalyses the first two steps in the metabolism of arachadonic acid. Prostaglandin G/H synthase-2 has two active sites, a hydroperoxidase and a cyclooxygenase (COX) site, and is colloquially termed COX-2. The bifunctional enzyme performs the bis-dioxygenation and reduction of arachadonic acid to form prostaglandin (PG)G2 and H2. PGH2 is then converted to other PGs that modulate inflammation, including PGD2, PGE2, PGF2α, PGI2, and thromboxane A2 (This pathway is shown in the Lipid maps database at http://www.lipidmaps.org/data/IntegratedPathways Data/SetupIntegratedPathways.pl? imgsize=730&Mode=RAW2647&DataType=FAEicosanoidsMedia). COX-2 is the target for nonsteroidal anti-inflammatory drugs (NSAIDS) including those that were purposefully designed (pd) to be selective for COX-2 (pdNSAIDs or coxibs). -
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. -
Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491 -
A Multistep Bioinformatic Approach Detects Putative Regulatory
BMC Bioinformatics BioMed Central Research article Open Access A multistep bioinformatic approach detects putative regulatory elements in gene promoters Stefania Bortoluzzi1, Alessandro Coppe1, Andrea Bisognin1, Cinzia Pizzi2 and Gian Antonio Danieli*1 Address: 1Department of Biology, University of Padova – Via Bassi 58/B, 35131, Padova, Italy and 2Department of Information Engineering, University of Padova – Via Gradenigo 6/B, 35131, Padova, Italy Email: Stefania Bortoluzzi - [email protected]; Alessandro Coppe - [email protected]; Andrea Bisognin - [email protected]; Cinzia Pizzi - [email protected]; Gian Antonio Danieli* - [email protected] * Corresponding author Published: 18 May 2005 Received: 12 November 2004 Accepted: 18 May 2005 BMC Bioinformatics 2005, 6:121 doi:10.1186/1471-2105-6-121 This article is available from: http://www.biomedcentral.com/1471-2105/6/121 © 2005 Bortoluzzi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: Searching for approximate patterns in large promoter sequences frequently produces an exceedingly high numbers of results. Our aim was to exploit biological knowledge for definition of a sheltered search space and of appropriate search parameters, in order to develop a method for identification of a tractable number of sequence motifs. Results: Novel software (COOP) was developed for extraction of sequence motifs, based on clustering of exact or approximate patterns according to the frequency of their overlapping occurrences. -
Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis
Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis Deepti Verma, Anna-Karin Ekman, Cecilia Bivik Eding and Charlotta Enerbäck The self-archived postprint version of this journal article is available at Linköping University Institutional Repository (DiVA): http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-147791 N.B.: When citing this work, cite the original publication. Verma, D., Ekman, A., Bivik Eding, C., Enerbäck, C., (2018), Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis, Journal of Investigative Dermatology, 138(5), 1088-1093. https://doi.org/10.1016/j.jid.2017.11.036 Original publication available at: https://doi.org/10.1016/j.jid.2017.11.036 Copyright: Elsevier http://www.elsevier.com/ Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis Deepti Verma*a, Anna-Karin Ekman*a, Cecilia Bivik Edinga and Charlotta Enerbäcka *Authors contributed equally aIngrid Asp Psoriasis Research Center, Department of Clinical and Experimental Medicine, Division of Dermatology, Linköping University, Linköping, Sweden Corresponding author: Charlotta Enerbäck Ingrid Asp Psoriasis Research Center, Department of Clinical and Experimental Medicine, Linköping University SE-581 85 Linköping, Sweden Phone: +46 10 103 7429 E-mail: [email protected] Short title Differential methylation in psoriasis Abbreviations CGI, CpG island; DMS, differentially methylated site; RRBS, reduced representation bisulphite sequencing Keywords (max 6) psoriasis, epidermis, methylation, Wnt, susceptibility, expression 1 ABSTRACT Psoriasis is a chronic inflammatory skin disease with both local and systemic components. Genome-wide approaches have identified more than 60 psoriasis-susceptibility loci, but genes are estimated to explain only one third of the heritability in psoriasis, suggesting additional, yet unidentified, sources of heritability. -
Resumenedwidekoct13post.Pdf 89.9 KB
Maria Nicole Nedwidek, Ph.D. Maria Nicole Nedwidek, Ph.D. E-mail: [email protected] web: http://d-ned.com EDUCATION City College of New York at the City University of New York New York, NY 10031 NYC Teaching Fellows: Master of Arts, Biology Science Education; GPA 3.97, w/honors: 6/2007. Harvard University School of Medicine - Massachusetts General Hospital Boston, MA 02114 Research Fellowship in Cancer Biology-Dept. of Medicine: appointed to faculty September, 1999. Princeton University Princeton, NJ 08544 Doctor of Philosophy degree in Molecular Biology awarded January, 1999. Princeton University Princeton, NJ 08544 Master of Arts degree in Molecular Biology awarded June, 1994. Massachusetts Institute of Technology Cambridge, MA 02139 Bachelor of Science degree in Biology awarded June, 1992. Grade Point Average: 4.4 out of 5.0 Stuyvesant High School New York, NY 10009 High School Diploma awarded June, 1988. Grade Point Average: 95.45% PUBLICATIONS AND PRESENTATIONS Nedwidek, M. N. and Hecht, M. H. (1997). Minimized protein structures: A little goes a long way. Proceedings of the National Academy of Sciences USA 94 (19), 10010-10011. Nedwidek, M. N. (1999). Rational Combinatorial Design Suggests an Evolutionary Approach for Building Proteins. Ph.D. Dissertation, Department of Molecular Biology, Princeton University, Princeton, NJ, 08544. Avruch, J. (presenter), Khokhlatchev, A., Nedwidek, M., Tzivion, G., Vavvas, D., Zhang, X-f. (2000) Ras Regulation of Protein Kinases. 25th European Symposium on Hormones and Cell Regulation: Protein Kinase Cascades in Signal Transduction; Nunez Lecture, September 2000, Alsace, France. web: http://www.dcb-glostrup.dk/kinase/symposium_2000/abstr_4.htm Ortiz-Vega, S., Khokhlatchev, A., Nedwidek, M., Zhang, X-f., Dammann, R., Pfeifer, G.P., and Avruch, J. -
Bioinformatics Analyses of Genomic Imprinting
Bioinformatics Analyses of Genomic Imprinting Dissertation zur Erlangung des Grades des Doktors der Naturwissenschaften der Naturwissenschaftlich-Technischen Fakultät III Chemie, Pharmazie, Bio- und Werkstoffwissenschaften der Universität des Saarlandes von Barbara Hutter Saarbrücken 2009 Tag des Kolloquiums: 08.12.2009 Dekan: Prof. Dr.-Ing. Stefan Diebels Berichterstatter: Prof. Dr. Volkhard Helms Priv.-Doz. Dr. Martina Paulsen Vorsitz: Prof. Dr. Jörn Walter Akad. Mitarbeiter: Dr. Tihamér Geyer Table of contents Summary________________________________________________________________ I Zusammenfassung ________________________________________________________ I Acknowledgements _______________________________________________________II Abbreviations ___________________________________________________________ III Chapter 1 – Introduction __________________________________________________ 1 1.1 Important terms and concepts related to genomic imprinting __________________________ 2 1.2 CpG islands as regulatory elements ______________________________________________ 3 1.3 Differentially methylated regions and imprinting clusters_____________________________ 6 1.4 Reading the imprint __________________________________________________________ 8 1.5 Chromatin marks at imprinted regions___________________________________________ 10 1.6 Roles of repetitive elements ___________________________________________________ 12 1.7 Functional implications of imprinted genes _______________________________________ 14 1.8 Evolution and parental conflict ________________________________________________ -
DNAJB1-PRKACA in HEK293T Cells Induces LINC00473 Overexpression That Depends on PKA Signaling Stephanie S
bioRxiv preprint doi: https://doi.org/10.1101/2021.08.11.455931; this version posted August 11, 2021. 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. DNAJB1-PRKACA in HEK293T cells induces LINC00473 overexpression that depends on PKA signaling Stephanie S. Kim1*, Ina Kycia1*, Michael Karski1#, Rosanna K. Ma2#, Evan A. Bordt3, Julian Kwan4, Anju Karki1, Elle Winter1, Ranan G. Aktas1, Yuxuan Wu5, Andrew Emili4, Daniel E. Bauer5, Praveen Sethupathy2, Khashayar Vakili1 1. Department of Surgery, Boston Children’s Hospital, Boston, MA, USA 2. Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA 3. Department of Pediatrics, Lurie Center for Autism, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA 4. Center for Networks Systems Biology, Department of Biochemistry, Boston University School of Medicine, 71 E Concord St, Boston MA 02118 5. Division of Hematology/Oncology, Boston Children’s Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Broad Institute, Department of Pediatrics, Harvard Medical School, Boston, MA, USA (*,# -contributed equally to the manuscript) Corresponding Author: Khashayar Vakili, MD Department of Surgery Boston Children’s Hospital 300 Longwood Avenue Boston, MA 02115 Tel: 617-355-8544 [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2021.08.11.455931; this version posted August 11, 2021. 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 Fibrolamellar carcinoma (FLC) is a primary liver cancer that most commonly arises in adolescents and young adults in a background of normal liver tissue and has an poor prognosis due to lack of effective chemotherapeutic agents. -
A-To-I RNA Editing Does Not Change with Age in the Healthy Male Rat Brain
Biogerontology (2013) 14:395–400 DOI 10.1007/s10522-013-9433-8 RESEARCH ARTICLE A-to-I RNA editing does not change with age in the healthy male rat brain Andrew P. Holmes • Shona H. Wood • Brian J. Merry • Joa˜o Pedro de Magalha˜es Received: 18 January 2013 / Accepted: 15 May 2013 / Published online: 26 May 2013 Ó The Author(s) 2013. This article is published with open access at Springerlink.com Abstract RNA editing is a post-transcriptional pro- Introduction cess, which results in base substitution modifications to RNA. It is an important process in generating Adenosine to inosine (A-to-I) RNA editing is a post- protein diversity through amino acid substitution and transcriptional process that alters the sequences of the modulation of splicing events. Previous studies RNA molecules. The adenosine deaminases ADAR have suggested a link between gene-specific reduc- and ADARB1 convert specific adenosine residues on tions in adenosine to inosine RNA editing and aging in RNA to inosine bases. During translation, sequencing, the human brain. Here we demonstrate that changes in and splicing, inosine is recognized as guanosine. RNA editing observed in humans with age are not Therefore, A-to-I RNA editing has important impli- observed during aging in healthy rats. Furthermore, we cations in altering specific amino acids, miRNA identify a conserved editing site in rats, in Cog3.We targeting, and in the modulation of alternative splicing propose that either age-related changes in RNA (Nishikura 2010). editing are specific to primates or humans, or that Targets of A-to-I RNA editing are often genes they are the manifestation of disease pathology. -
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