WO 2016/103269 Al 30 June 2016 (30.06.2016) P O P C T
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1 Evidence for Gliadin Antibodies As Causative Agents in Schizophrenia
1 Evidence for gliadin antibodies as causative agents in schizophrenia. C.J.Carter PolygenicPathways, 20 Upper Maze Hill, Saint-Leonard’s on Sea, East Sussex, TN37 0LG [email protected] Tel: 0044 (0)1424 422201 I have no fax Abstract Antibodies to gliadin, a component of gluten, have frequently been reported in schizophrenia patients, and in some cases remission has been noted following the instigation of a gluten free diet. Gliadin is a highly immunogenic protein, and B cell epitopes along its entire immunogenic length are homologous to the products of numerous proteins relevant to schizophrenia (p = 0.012 to 3e-25). These include members of the DISC1 interactome, of glutamate, dopamine and neuregulin signalling networks, and of pathways involved in plasticity, dendritic growth or myelination. Antibodies to gliadin are likely to cross react with these key proteins, as has already been observed with synapsin 1 and calreticulin. Gliadin may thus be a causative agent in schizophrenia, under certain genetic and immunological conditions, producing its effects via antibody mediated knockdown of multiple proteins relevant to the disease process. Because of such homology, an autoimmune response may be sustained by the human antigens that resemble gliadin itself, a scenario supported by many reports of immune activation both in the brain and in lymphocytes in schizophrenia. Gluten free diets and removal of such antibodies may be of therapeutic benefit in certain cases of schizophrenia. 2 Introduction A number of studies from China, Norway, and the USA have reported the presence of gliadin antibodies in schizophrenia 1-5. Gliadin is a component of gluten, intolerance to which is implicated in coeliac disease 6. -
Bioinformatics Identi Cation of Prognostic Factors Associated With
Bioinformatics Identication of Prognostic Factors Associated with Breast Cancer Ying Wei Sichuan University https://orcid.org/0000-0001-8178-4705 Shipeng Zhang College of Pharmacy, North Sichuan Medical College Li Xiao West China School of Basic Medical Sciences and Forensic Medicine Jing Zou West China School of Basic Medical Sciences and Forensic Medicine Yingqing Fu West China School of Basic Medical Sciences and Forensic Medicine Yi Ye West China School of Basic Medical Sciences and Forensic Medicine Linchuan Liao ( [email protected] ) West China School of Basic Medical Sciences and Forensic Medicine https://orcid.org/0000-0003-3700-8471 Research Keywords: Breast cancer, Differentially expressed genes, miRNAs, Transcription factors, Bioinformatic analysis Posted Date: December 2nd, 2020 DOI: https://doi.org/10.21203/rs.3.rs-117477/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/23 Abstract Background: Breast cancer (BRCA) remains one of the most common forms of cancer and is the most prominent driver of cancer-related death among women. The mechanistic basis for BRCA, however, remains incompletely understood. In particular, the relationships between driver mutations and signaling pathways in BRCA are poorly characterized, making it dicult to identify reliable clinical biomarkers that can be employed in diagnostic, therapeutic, or prognostic contexts. Methods: First, we downloaded publically available BRCA datasets (GSE45827, GSE42568, and GSE61304) from the Gene Expression Omnibus (GEO) database. We then compared gene expression proles between tumor and control tissues in these datasets using Venn diagrams and the GEO2R analytical tool. We further explore the functional relevance of BRCA-associated differentially expressed genes (DEGs) via functional and pathway enrichment analyses using the DAVID tool, and we then constructed a protein-protein interaction network incorporating DEGs of interest using the Search Tool for the Retrieval of Interacting Genes (STRING) database. -
Genetic Inhibition of the Ubiquitin Ligase Rnf5 Attenuates Phenotypes
www.nature.com/scientificreports OPEN Genetic Inhibition Of The Ubiquitin Ligase Rnf5 Attenuates Phenotypes Associated To F508del Received: 02 February 2015 Accepted: 17 June 2015 Cystic Fibrosis Mutation Published: 17 July 2015 Valeria Tomati1, Elvira Sondo1, Andrea Armirotti2, Emanuela Caci1, Emanuela Pesce1, Monica Marini1, Ambra Gianotti1, Young Ju Jeon3, Michele Cilli4, Angela Pistorio1, Luca Mastracci4,5, Roberto Ravazzolo1,6, Bob Scholte7, Ze’ev Ronai3, Luis J. V. Galietta1 & Nicoletta Pedemonte1 Cystic fibrosis (CF) is caused by mutations in the CFTR chloride channel. Deletion of phenylalanine 508 (F508del), the most frequent CF mutation, impairs CFTR trafficking and gating. F508del- CFTR mistrafficking may be corrected by acting directly on mutant CFTR itself or by modulating expression/activity of CFTR-interacting proteins, that may thus represent potential drug targets. To evaluate possible candidates for F508del-CFTR rescue, we screened a siRNA library targeting known CFTR interactors. Our analysis identified RNF5 as a protein whose inhibition promoted significant F508del-CFTR rescue and displayed an additive effect with the investigational drug VX-809. Significantly, RNF5 loss in F508del-CFTR transgenic animals ameliorated intestinal malabsorption and concomitantly led to an increase in CFTR activity in intestinal epithelial cells. In addition, we found that RNF5 is differentially expressed in human bronchial epithelia from CF vs. control patients. Our results identify RNF5 as a target for therapeutic modalities to antagonize mutant CFTR proteins. Cystic Fibrosis (CF), one of the most common inherited diseases (~1/3000 in Caucasian populations), is caused by mutations in the gene encoding the CF transmembrane conductance regulator (CFTR), a cAMP-regulated chloride channel expressed at the apical membrane of many types of epithelial cells1,2. -
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. -
Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights Into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle
animals Article Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle Masoumeh Naserkheil 1 , Abolfazl Bahrami 1 , Deukhwan Lee 2,* and Hossein Mehrban 3 1 Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj 77871-31587, Iran; [email protected] (M.N.); [email protected] (A.B.) 2 Department of Animal Life and Environment Sciences, Hankyong National University, Jungang-ro 327, Anseong-si, Gyeonggi-do 17579, Korea 3 Department of Animal Science, Shahrekord University, Shahrekord 88186-34141, Iran; [email protected] * Correspondence: [email protected]; Tel.: +82-31-670-5091 Received: 25 August 2020; Accepted: 6 October 2020; Published: 9 October 2020 Simple Summary: Hanwoo is an indigenous cattle breed in Korea and popular for meat production owing to its rapid growth and high-quality meat. Its yearling weight and carcass traits (backfat thickness, carcass weight, eye muscle area, and marbling score) are economically important for the selection of young and proven bulls. In recent decades, the advent of high throughput genotyping technologies has made it possible to perform genome-wide association studies (GWAS) for the detection of genomic regions associated with traits of economic interest in different species. In this study, we conducted a weighted single-step genome-wide association study which combines all genotypes, phenotypes and pedigree data in one step (ssGBLUP). It allows for the use of all SNPs simultaneously along with all phenotypes from genotyped and ungenotyped animals. Our results revealed 33 relevant genomic regions related to the traits of interest. -
RNF5 Antibody
RNF5 Antibody CATALOG NUMBER: 27-144 Antibody used in WB on Human HeLa at 0.2-1 ug/ml. Specifications APPLICATIONS: RNF5 antibody can be used for detection of RNF5 by ELISA at 1:12500. RNF5 antibody can be used for detection of RNF5 by western blot at 1 ug/mL, and HRP conjugated secondary antibody should be diluted 1:50,000 - 100,000. USER NOTE: Optimal dilutions for each application to be determined by the researcher. POSITIVE CONTROL: 1) Cat. No. 1201 - HeLa Cell Lysate PREDICTED MOLECULAR 20 kDa WEIGHT: IMMUNOGEN: Antibody produced in rabbits immunized with a synthetic peptide corresponding a region of human RNF5. HOST SPECIES: Rabbit Properties PURIFICATION: Antibody is purified by peptide affinity chromatography method. PHYSICAL STATE: Lyophilized BUFFER: Antibody is lyophilized in PBS buffer with 2% sucrose. Add 50 uL of distilled water. Final antibody concentration is 1 mg/mL. CONCENTRATION: 1 mg/ml STORAGE CONDITIONS: For short periods of storage (days) store at 4˚C. For longer periods of storage, store RNF5 antibody at -20˚C. As with any antibody avoid repeat freeze-thaw cycles. CLONALITY: Polyclonal CONJUGATE: Unconjugated Additional Info ALTERNATE NAMES: RNF5, RING5, RMA1 ACCESSION NO.: NP_008844 PROTEIN GI NO.: 5902054 OFFICIAL SYMBOL: RNF5 GENE ID: 6048 Background BACKGROUND: RNF5 contains a RING finger, which is a motif known to be involved in protein-protein interactions. This protein is a membrane-bound ubiquitin ligase. It can regulate cell motility by targeting paxillin ubiquitination and altering the distribution and localization of paxillin in cytoplasm and cell focal adhesions.The protein encoded by this gene contains a RING finger, which is a motif known to be involved in protein-protein interactions. -
Investigating the Role of the ETS Transcription Factor ELK1 in Stem Cell Transcription
Investigating the role of the ETS transcription factor ELK1 in stem cell transcription A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Biology, Medicine and Health 2017 Ian E. Prise Division of Molecular & Cellular Function School of Biological Sciences I. Table of Contents II. List of Figures ...................................................................................................................................... 5 III. Abstract .............................................................................................................................................. 7 IV. Declaration ......................................................................................................................................... 8 V. Copyright Statement ........................................................................................................................... 8 VI. Experimental Contributions ............................................................................................................... 9 VII. Acknowledgments .......................................................................................................................... 10 1. Introduction ...................................................................................................................................... 12 1.I Pluripotency ................................................................................................................................. 12 1.II Chromatin -
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. -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
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 -
AURKA, DLGAP5, TPX2, KIF11 and CKAP5: Five Specific Mitosis-Associated Genes Correlate with Poor Prognosis for Non-Small Cell Lung Cancer Patients
INTERNATIONAL JOURNAL OF ONCOLOGY 50: 365-372, 2017 AURKA, DLGAP5, TPX2, KIF11 and CKAP5: Five specific mitosis-associated genes correlate with poor prognosis for non-small cell lung cancer patients MARC A. SCHNEIDER1,8, PETROS CHristopoulos2,8, THOMAS MULEY1,8, ARNE WartH5,8, URSULA KLINGMUELLER6,8,9, MICHAEL THOMAS2,8, FELIX J.F. HertH3,8, HENDRIK DIENEMANN4,8, NIKOLA S. MUELLER7,9, FABIAN THEIS7,9 and MICHAEL MEISTER1,8,9 1Translational Research Unit, 2Department of Thoracic Oncology, 3Department of Pneumology and Critical Care Medicine, and 4Department of Surgery, Thoraxklinik at University Hospital Heidelberg, Heidelberg; 5Institute of Pathology, University of Heidelberg, Heidelberg; 6Systems Biology of Signal Transduction, German Cancer Research Center, Heidelberg; 7Cellular Dynamics and Cell Patterning, Max Planck Institute of Biochemistry, Martinsried; 8Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL) Heidelberg; 9CancerSys network ‘LungSysII’, Heidelberg, Germany Received October 26, 2016; Accepted December 5, 2016 DOI: 10.3892/ijo.2017.3834 Abstract. The growth of a tumor depends to a certain extent genes AURKA, DLGAP5, TPX2, KIF11 and CKAP5 is asso- on an increase in mitotic events. Key steps during mitosis are ciated with the prognosis of NSCLC patients. the regulated assembly of the spindle apparatus and the sepa- ration of the sister chromatids. The microtubule-associated Introduction protein Aurora kinase A phosphorylates DLGAP5 in order to correctly segregate the chromatids. Its activity and recruitment Lung cancer is globally the leading cause of cancer-related to the spindle apparatus is regulated by TPX2. KIF11 and deaths (1). Non-small cell lung cancer (NSCLC), which accounts CKAP5 control the correct arrangement of the microtubules for more than 80% of all cases, is divided in adenocarcinoma and prevent their degradation. -
AURKA Mrna Expression Is an Independent Predictor of Poor Prognosis in Patients with Non-Small Cell Lung Cancer
ONCOLOGY LETTERS 13: 4463-4468, 2017 AURKA mRNA expression is an independent predictor of poor prognosis in patients with non-small cell lung cancer AHMED S.K. AL‑KHAFAJI1,2, MICHAEL W. MARCUS1, MICHAEL P.A. DAVIES1, JANET M. RISK1, RICHARD J. SHAW1, JOHN K. FIELD1 and TRIANTAFILLOS LILOGLOU1 1Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Liverpool L7 8TX, UK; 2Department of Biology, College of Science, University of Baghdad, Al‑Jadriya, Baghdad 10070, Iraq Received September 12, 2016; Accepted January 17, 2017 DOI: 10.3892/ol.2017.6012 Abstract. Deregulation of mitotic spindle genes has been Introduction reported to contribute to the development and progression of malignant tumours. The aim of the present study was to Lung cancer is the most common cause of cancer-associated explore the association between the expression profiles of mortality in the UK for both males and females (1), and Aurora kinases (AURKA, AURKB and AURKC), cytoskel- >1/5 patients with cancer succumb to this malignancy world- eton-associated protein 5 (CKAP5), discs large-associated wide (2). Non-small cell lung carcinoma (NSCLC) accounts protein 5 (DLGAP5), kinesin-like protein 11 (KIF11), micro- for 80-85% of all cases of lung cancer, and develops through tubule nucleation factor (TPX2), monopolar spindle 1 kinase the accumulation of molecular alterations, which may serve as (TTK), and β-tubulins (TUBB) and (TUBB3) genes and clini- prognostic biomarkers for NSCLC outcome (3). copathological characteristics in human non-small cell lung Mitotic spindle formation and the spindle checkpoint are carcinoma (NSCLC). Reverse transcription-quantitative poly- critical for the maintenance of cell division and chromosome merase chain reaction‑based RNA gene expression profiles of segregation (4).