DOCSLIB.ORG

And Diabetes-Associated Pancreatic Cancer: a GWAS Data Analysis

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Published OnlineFirst October 17, 2013; DOI: 10.1158/1055-9965.EPI-13-0437-T Cancer Epidemiology, Research Article Biomarkers & Prevention Genes–Environment Interactions in Obesity- and Diabetes-Associated Pancreatic Cancer: A GWAS Data Analysis Hongwei Tang1, Peng Wei3, Eric J. Duell4, Harvey A. Risch5, Sara H. Olson6, H. Bas Bueno-de-Mesquita7, Steven Gallinger9, Elizabeth A. Holly10, Gloria M. Petersen11, Paige M. Bracci10, Robert R. McWilliams11, Mazda Jenab12, Elio Riboli16, Anne Tjønneland18, Marie Christine Boutron-Ruault13,14,15, Rudolf Kaaks19, Dimitrios Trichopoulos20,21,22, Salvatore Panico23, Malin Sund24, Petra H.M. Peeters8,16, Kay-Tee Khaw17, Christopher I. Amos2, and Donghui Li1 Abstract Background: Obesity and diabetes are potentially alterable risk factors for pancreatic cancer. Genetic factors that modify the associations of obesity and diabetes with pancreatic cancer have previously not been examined at the genome-wide level. Methods: Using genome-wide association studies (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study of 2,028 cases and 2,109 controls to examine gene–obesity and gene–diabetes interactions in relation to pancreatic cancer risk by using the likelihood-ratio test nested in logistic regression models and Ingenuity Pathway Analysis (IPA). Results: After adjusting for multiple comparisons, a significant interaction of the chemokine signaling À pathway with obesity (P ¼ 3.29 Â 10 6) and a near significant interaction of calcium signaling pathway with À diabetes (P ¼ 1.57 Â 10 4) in modifying the risk of pancreatic cancer were observed. These findings were supported by results from IPA analysis of the top genes with nominal interactions. The major contributing genes to the two top pathways include GNGT2, RELA, TIAM1, and GNAS. None of the individual genes or single-nucleotide polymorphism (SNP) except one SNP remained significant after adjusting for multiple À testing. Notably, SNP rs10818684 of the PTGS1 gene showed an interaction with diabetes (P ¼ 7.91 Â 10 7)ata false discovery rate of 6%. Conclusions: Genetic variations in inflammatory response and insulin resistance may affect the risk of obesity- and diabetes-related pancreatic cancer. These observations should be replicated in additional large datasets. Impact: A gene–environment interaction analysis may provide new insights into the genetic susceptibility and molecular mechanisms of obesity- and diabetes-related pancreatic cancer. Cancer Epidemiol Biomarkers Prev; 23(1); 98–106. Ó2013 AACR. Authors' Affiliations: Departments of 1Gastrointestinal Medical Oncol- dom; 18Institute of Cancer Epidemiology, Danish Cancer Society, ogy and 2Epidemiology, The University of Texas MD Anderson Cancer Copenhagen, Denmark; 19Division of Cancer Epidemiology, German Center; 3Division of Biostatistics and Human Genetics Center, School of Cancer Research Center, Heidelberg, Germany; 20Department of Epi- Public Health, University of Texas Health Science Center, Houston, demiology, Harvard School of Public Health, Boston, Massachusetts; Texas; 4Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain; 21Bureau of Epidemiologic Research, Academy of Athens; 22Hellenic 5Yale University School of Public Health, New Haven, Connecticut; Health Foundation, Athens, Greece; 23Dipartimento di Medicina Clinica 6Department of Epidemiology and Biostatistics, Memorial Sloan-Ketter- e Chirurgia, Federico II University, Naples, Italy; and 24Department of ing Cancer Center, New York, New York; 7National Institute for Public Surgery, Umea University Hospital, Umea,Sweden Health and the Environment (RIVM), Bilthoven and Department of Gastroenterology and Hepatology, University Medical Center Utrecht, Note: Supplementary data for this article are available at Cancer Epide- Utrecht; 8Julius Center for Health Sciences and Primary Care, University miology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/). Medical Center Utrecht, Utrecht, the Netherlands; 9Samuel Lunenfeld Research Institute, Toronto General Hospital, University of Toronto, Current address for Christopher I. Amos: Department of Community and Toronto, Canada; 10Department of Epidemiology & Biostatistics, Uni- Family Medicine, Geisel School of Medicine, Dartmouth College, Lebanon, versity of California San Francisco, San Francisco, California; 11Depart- New Hampshire. ment of Health Sciences Research, Mayo Clinic, Rochester, Minnesota; 12International Agency for Research on Cancer, Lyon; 13Institut national Corresponding Author: Donghui Li, Department of Gastrointestinal Med- de la sante et de la recherche medicale (INSERM), Centre for research in ical Oncology, University of Texas MD Anderson Cancer Center, 1515 Epidemiology and Population Health (CESP), U1018, Nutrition, Hor- Holcombe Boulevard, Unit 426, Houston, TX 77030. Phone: 713-834- mones and Women's Health team; 14Univ. Paris Sud, UMRS 1018; 6690; Fax: 713-834-6153; E-mail: [email protected] 15 16 IGR, F-94805, Villejuif, France; Division of Epidemiology, Public doi: 10.1158/1055-9965.EPI-13-0437-T Health, and Primary Care, Imperial College London, London; 17School of Clinical Medicine, University of Cambridge, Cambridge, United King- Ó2013 American Association for Cancer Research. 98 Cancer Epidemiol Biomarkers Prev; 23(1) January 2014 Downloaded from cebp.aacrjournals.org on October 1, 2021. © 2014 American Association for Cancer Research. Published OnlineFirst October 17, 2013; DOI: 10.1158/1055-9965.EPI-13-0437-T G Â E Analysis of GWAS in Pancreatic Cancer Introduction interaction analysis of genetic factors that may modify the Pancreatic cancer is the fourth leading cause of cancer- associations of obesity and diabetes with pancreatic related deaths, accounting for more than 37,600 deaths cancer. each year in the United States (1). Epidemiologic studies Materials and Methods have identified cigarette smoking as the major modifiable risk factor for this disease. Obesity and long-term history Study population and dataset of diabetes mellitus may also affect risk and are also The study population was drawn from seven studies modifiable (2, 3). Genetic factors are known to play a role participating in the previously conducted GWAS of the in pancreatic cancer development. Although genome- Pancreatic Cancer Cohort Consortium (PanScan) and the wide association studies (GWAS) have identified a few PanC4 Consortium (4, 5), including six case–control stud- loci and chromosome regions that are significantly asso- ies conducted at the MD Anderson Cancer Center (Hous- ciated with the risk of pancreatic cancer (4, 5), these ton, TX), Mayo Clinic (Rochester, MN), Yale University findings explain only a portion of the heritability of this (New Haven, CT), University of California (San Francisco, disease. Because of the limitations of single marker anal- CA), Memorial Sloan-Kettering Cancer Center (New York, ysis on GWAS data, there have been increasing efforts NY), and University of Toronto (Toronto, ON, Canada), recently on GWAS pathway analysis, which uses prior and one nested case–control study from the European biologic knowledge of gene function and aims at combin- Prospective Investigation into Cancer and Nutrition ing moderate signals of single-nucleotide polymorphism (EPIC) cohort. Cases were defined as patients diagnosed (SNP) and obtaining biologically interpretable findings (6, with primary adenocarcinoma of the pancreas; in each 7). Despite its great promise in providing insights into study center, controls were matched to cases according to disease mechanisms, current GWAS pathway analysis birth year, sex, and self-reported race/ethnicity and were has some caveats including being limited to enrichment free of pancreatic cancer at the time of recruitment. of marginal genetic effects in biologic pathways without GWAS scanning was performed at the National Cancer considering possible interactions between pathways and Institute Core Genotyping Facility using the Illumina environmental factors (8). On the other hand, environ- HumanHap550 and HumanHap550-Duo SNP arrays and mental factors are likely to interact with multiple genes Illumina Human 610-Quad arrays (4, 5). Genotype data through various biologic pathways, contributing to the covering 562,000 and 621,000 SNPs from 4,195 study susceptibility of complex human diseases. Although cur- subjects (2,163 cases and 2,232 controls) were downloaded rent GWAS top hits account for only limited heritability, from the Database of Genotypes and Phenotypes website gene–environment interactions may account for some of (http://www.ncbi.nlm.nih.gov/gap) with the approval the missing heritability of pancreatic cancer (9). of MD Anderson Institutional Review Board (IRB). We We have previously conducted pathway analyses of the first conducted data cleaning and quality control by GWAS data in pancreatic cancer. Several novel pathways removing SNPs with minor allele frequency (MAF) less significantly associated with risk were identified (10, 11). than 5%, deviating from the Hardy–Weinberg equilibri- For example, the pancreas development pathway [Mature um (P < 0.001) or not genotyped in both SNP array plat- Onset Diabetes of the Young (MODY) pathway] was forms, resulting in a final dataset of 468,114 SNPs. Accord- identified as a top pathway in pancreatic cancer etiology. ing to the International HapMap Project genotype data One possible mechanism related to this pathway is (phase III release #3, NCBI build 36, dbSNP b126, 2010-05- through obesity
Recommended publications
  • Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids

    Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids

    Supplementary Materials: Evaluation of cytotoxicity and α-glucosidase inhibitory activity of amide and polyamino-derivatives of lupane triterpenoids Oxana B. Kazakova1*, Gul'nara V. Giniyatullina1, Akhat G. Mustafin1, Denis A. Babkov2, Elena V. Sokolova2, Alexander A. Spasov2* 1Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences, 71, pr. Oktyabrya, 450054 Ufa, Russian Federation 2Scientific Center for Innovative Drugs, Volgograd State Medical University, Novorossiyskaya st. 39, Volgograd 400087, Russian Federation Correspondence Prof. Dr. Oxana B. Kazakova Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences 71 Prospeсt Oktyabrya Ufa, 450054 Russian Federation E-mail: [email protected] Prof. Dr. Alexander A. Spasov Scientific Center for Innovative Drugs of the Volgograd State Medical University 39 Novorossiyskaya st. Volgograd, 400087 Russian Federation E-mail: [email protected] Figure S1. 1H and 13C of compound 2. H NH N H O H O H 2 2 Figure S2. 1H and 13C of compound 4. NH2 O H O H CH3 O O H H3C O H 4 3 Figure S3. Anticancer screening data of compound 2 at single dose assay 4 Figure S4. Anticancer screening data of compound 7 at single dose assay 5 Figure S5. Anticancer screening data of compound 8 at single dose assay 6 Figure S6. Anticancer screening data of compound 9 at single dose assay 7 Figure S7. Anticancer screening data of compound 12 at single dose assay 8 Figure S8. Anticancer screening data of compound 13 at single dose assay 9 Figure S9. Anticancer screening data of compound 14 at single dose assay 10 Figure S10.
  • Active Rac1 Detection Kit 2012 09/20

    Active Rac1 Detection Kit 2012 09/20

    Active Rac1 Detection Kit 1 Kit Orders n 877-616-CELL (2355) (30 immunoprecipitations) [email protected] Support n 877-678-TECH (8324) [email protected] Web n www.cellsignal.com rev. 09/24/20 #8815 For Research Use Only. Not For Use In Diagnostic Procedures. Species Cross-Reactivity: H, M Components Ship As: 11894S Item # Kit Quantity Storage Temp Description: The Active Rac1 Detection Kit provides all GTPgS 11521 1 X 50 µl –80°C reagents necessary for measuring activation of Rac1 GTPase in the cell. GST-PAK1-PBD fusion protein is used to bind GDP 11522 1 X 50 µl –80°C the activated form of GTP-bound Rac1, which can then be Components Ship As: 11894S Item # Kit Quantity Storage Temp immunoprecipitated with glutathione resin. Rac1 activation levels are then determined by western blot using a Rac1 GST-Human PAK1-PBD 8659 1 X 600 µg –20°C Mouse mAb. Rac1 Mouse mAb 8631 1 X 50 µl –20°C Specificity/Sensitivity: Active Rac1 Detection Kit detects Components Ship As: 11860S Item # Kit Quantity Storage Temp endogenous levels of GTP-bound (active) Rac1 as shown in Lysis/Binding/Wash Buffer 11524 1 X 100 mL 4°C Figure 1. This kit detects proteins from the indicated species, as determined through in-house testing, but may also detect Glutathione Resin 11523 1 X 3 ml 4°C homologous proteins from other species. SDS Sample Buffer 11525 1 X 1.5 ml 4°C Background: The Ras superfamily of small GTP-binding Spin Cup and Collection Tubes 11526 1 X 30 vial RT proteins (G proteins) comprise a large class of proteins (over 150 members) that can be classified into at least five families based on their sequence and functional similarities: 1 2 3 4 Figure 1.
  • Identification of Pathogenic Genes of Pterygium Based on the Gene Expression Omnibus Database

    Identification of Pathogenic Genes of Pterygium Based on the Gene Expression Omnibus Database

    Int J Ophthalmol, Vol. 12, No. 4, Apr.18, 2019 www.ijo.cn Tel: 8629-82245172 8629-82210956 Email: [email protected] ·Basic Research· Identification of pathogenic genes of pterygium based on the Gene Expression Omnibus database Xiao-Li Yue, Zi-Qing Gao Department of Ophthalmology, the First Affiliated Hospital of INTRODUCTION Bengbu Medical College, Bengbu 233000, Anhui Province, terygium is a general ocular surface and degenerative China P disease characterized by conjunctival fibrovascular Correspondence to: Xiao-Li Yue. Department of Ophthalmology, proliferation and invasion of the peripheral cornea. Pterygium the First Affiliated Hospital of Bengbu Medical College, is composed of the head that invades the cornea, the neck Bengbu Xinxin Jiayuan No.3 Building 2 unit 603, Bengbu that includes the superficial limbus and the body that overlie 233000, Anhui Province, China. [email protected] the sclera[1]. Diverse biological pathways including increase Received: 2018-02-06 Accepted: 2019-01-14 of mitotic proteins and protein implicated in tissue invasion were remarkably affected in pterygium. Additionally, Abstract fibrosis, inflammation, angiogenesis, collagen deposition ● AIM: To identify the pathogenic genes in pterygium. and extracellular matrix breakdown are associated with ● METHODS: We obtained mRNA expression profiles pterygium[2]. Pterygium is noted to be more prevalent than from the Gene Expression Omnibus database (GEO) to 20% of some populations and typically affects the younger identify differentially expressed genes
  • Hormone Therapy Use and Breast Tissue DNA

    Hormone Therapy Use and Breast Tissue DNA

    http://www.diva-portal.org This is the published version of a paper published in Epigenetics. Citation for the original published paper (version of record): Harlid, S., Xu, Z., Kirk, E., Wilson, L E., Troester, M A. et al. (2019) Hormone therapy use and breast tissue DNA methylation: analysis of epigenome wide data from the normal breast study Epigenetics, 14(2): 146-157 https://doi.org/10.1080/15592294.2019.1580111 Access to the published version may require subscription. N.B. When citing this work, cite the original published paper. Permanent link to this version: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-157445 EPIGENETICS 2019, VOL. 14, NO. 2, 146–157 https://doi.org/10.1080/15592294.2019.1580111 RESEARCH PAPER Hormone therapy use and breast tissue DNA methylation: analysis of epigenome wide data from the normal breast study Sophia Harlid a,b, Zongli Xuc, Erin Kirkd, Lauren E. Wilson c,e, Melissa A. Troesterd, and Jack A. Taylor a,c aEpigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA; bDepartment of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden; cEpidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA; dDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; eDepartment of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA ABSTRACT ARTICLE HISTORY Hormone therapy (HT) is associated with increased risk of breast cancer, strongly dependent on Received 4 September 2018 type, duration, and recency of use. HT use could affect cancer risk by changing breast tissue Revised 21 December 2018 transcriptional programs.
  • ARHGEF4 (NM 015320) Human Tagged ORF Clone Product Data

    ARHGEF4 (NM 015320) 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 RC215591 ARHGEF4 (NM_015320) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: ARHGEF4 (NM_015320) Human Tagged ORF Clone Tag: Myc-DDK Symbol: ARHGEF4 Synonyms: ASEF; ASEF1; GEF4; SMIM39; STM6 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 / 5 ARHGEF4 (NM_015320) Human Tagged ORF Clone – RC215591 ORF Nucleotide >RC215591 representing NM_015320 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGCCCTGGGAAGAACCAGCAGGTGAGAAGCCCAGTTGCTCTCACAGTCAGAAGGCATTCCACATGGAGC CTGCCCAGAAGCCCTGCTTCACCACTGACATGGTGACATGGGCCCTCCTCTGCATCTCTGCAGAGACTGT GCGTGGGGAGGCTCCTTCACAGCCTAGGGGCATCCCTCACCGCTCGCCCGTCAGTGTGGATGACCTGTGG CTGGAGAAGACACAGAGAAAGAAGTTGCAGAAGCAGGCCCACATCGAAAGGAGGCTGCACATAGGGGCAG TGCACAAAGATGGAGTCAAGTGCTGGAGAAAGACGATCATTACCTCTCCAGAGTCTTTGAATCTCCCTAG AAGAAGCCATCCACTCTCCCAGAGTGCTCCAACGGGACTGAACCACATGGGCTGGCCAGAGCACACACCA GGCACTGCCATGCCTGATGGAGCTCTGGACACAGCTGTCTGCGCTGACGAAGTGGGGAGCGAGGAGGACC TGTATGATGACCTGCACAGCTCCAGCCACCACTACAGCCACCCTGGAGGGGGTGGGGAGCAGCTGGCTAT CAATGAGCTCATCAGCGATGGCAGTGTGGTCTGCGCTGAAGCACTCTGGGACCATGTCACCATGGACGAC
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    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.
  • Focus on Cdc42 in Breast Cancer: New Insights, Target Therapy Development and Non-Coding Rnas

    Focus on Cdc42 in Breast Cancer: New Insights, Target Therapy Development and Non-Coding Rnas

    Review Focus on Cdc42 in Breast Cancer: New Insights, Target Therapy Development and Non-Coding RNAs Yu Zhang †, Jun Li †, Xing-Ning Lai, Xue-Qiao Jiao, Jun-Ping Xiong and Li-Xia Xiong * Department of Pathophysiology, Jiangxi Province Key Laboratory of Tumor Pathogenesis and Molecular Pathology, Medical College, Nanchang University, 461 Bayi Road, Nanchang 330006, China; [email protected] (Y.Z.); [email protected] (J.L.); [email protected] (X.-N.L.); [email protected] (X.-Q.J.); [email protected] (J.-P.X.) * Correspondence: [email protected]; Tel.: +86-791-8636-0556 † These authors contributed equally to this work. Received: 30 December 2018; Accepted: 8 February 2019; Published: 11 February 2019 Abstract: Breast cancer is the most common malignant tumors in females. Although the conventional treatment has demonstrated a certain effect, some limitations still exist. The Rho guanosine triphosphatase (GTPase) Cdc42 (Cell division control protein 42 homolog) is often upregulated by some cell surface receptors and oncogenes in breast cancer. Cdc42 switches from inactive guanosine diphosphate (GDP)-bound to active GTP-bound though guanine-nucleotide- exchange factors (GEFs), results in activation of signaling cascades that regulate various cellular processes such as cytoskeletal changes, proliferation and polarity establishment. Targeting Cdc42 also provides a strategy for precise breast cancer therapy. In addition, Cdc42 is a potential target for several types of non-coding RNAs including microRNAs and lncRNAs. These non-coding RNAs is extensively involved in Cdc42-induced tumor processes, while many of them are aberrantly expressed. Here, we focus on the role of Cdc42 in cell morphogenesis, proliferation, motility, angiogenesis and survival, introduce the Cdc42-targeted non-coding RNAs, as well as present current development of effective Cdc42-targeted inhibitors in breast cancer.
  • Predicting Coupling Probabilities of G-Protein Coupled Receptors Gurdeep Singh1,2,†, Asuka Inoue3,*,†, J

    Predicting Coupling Probabilities of G-Protein Coupled Receptors Gurdeep Singh1,2,†, Asuka Inoue3,*,†, J

    Published online 30 May 2019 Nucleic Acids Research, 2019, Vol. 47, Web Server issue W395–W401 doi: 10.1093/nar/gkz392 PRECOG: PREdicting COupling probabilities of G-protein coupled receptors Gurdeep Singh1,2,†, Asuka Inoue3,*,†, J. Silvio Gutkind4, Robert B. Russell1,2,* and Francesco Raimondi1,2,* 1CellNetworks, Bioquant, Heidelberg University, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany, 2Biochemie Zentrum Heidelberg (BZH), Heidelberg University, Im Neuenheimer Feld 328, 69120 Heidelberg, Germany, 3Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi 980-8578, Japan and 4Department of Pharmacology and Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA Received February 10, 2019; Revised April 13, 2019; Editorial Decision April 24, 2019; Accepted May 01, 2019 ABSTRACT great use in tinkering with signalling pathways in living sys- tems (5). G-protein coupled receptors (GPCRs) control multi- Ligand binding to GPCRs induces conformational ple physiological states by transducing a multitude changes that lead to binding and activation of G-proteins of extracellular stimuli into the cell via coupling to situated on the inner cell membrane. Most of mammalian intra-cellular heterotrimeric G-proteins. Deciphering GPCRs couple with more than one G-protein giving each which G-proteins couple to each of the hundreds receptor a distinct coupling profile (6) and thus specific of GPCRs present in a typical eukaryotic organism downstream cellular responses. Determining these coupling is therefore critical to understand signalling. Here, profiles is critical to understand GPCR biology and phar- we present PRECOG (precog.russelllab.org): a web- macology. Despite decades of research and hundreds of ob- server for predicting GPCR coupling, which allows served interactions, coupling information is still missing for users to: (i) predict coupling probabilities for GPCRs many receptors and sequence determinants of coupling- specificity are still largely unknown.
  • Small Rho Gtpase Family Member Cdc42 and Its Role in Neuronal Survival and Apoptosis

    Small Rho Gtpase Family Member Cdc42 and Its Role in Neuronal Survival and Apoptosis

    University of Denver Digital Commons @ DU Electronic Theses and Dissertations Graduate Studies 1-1-2017 Small Rho GTPase Family Member Cdc42 and Its Role in Neuronal Survival and Apoptosis Noelle Christine Punessen University of Denver Follow this and additional works at: https://digitalcommons.du.edu/etd Part of the Biology Commons, and the Genetics and Genomics Commons Recommended Citation Punessen, Noelle Christine, "Small Rho GTPase Family Member Cdc42 and Its Role in Neuronal Survival and Apoptosis" (2017). Electronic Theses and Dissertations. 1337. https://digitalcommons.du.edu/etd/1337 This Thesis is brought to you for free and open access by the Graduate Studies at Digital Commons @ DU. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of Digital Commons @ DU. For more information, please contact [email protected],[email protected]. Small Rho GTPase Family Member Cdc42 and its Role in Neuronal Survival and Apoptosis A Thesis Presented to the Faculty of Natural Sciences and Mathematics University of Denver In Partial Fulfillment of the Requirements for the Degree Master of Science by Noelle C. Punessen August 2017 Advisor: Dr. Daniel A. Linseman Author: Noelle C. Punessen Title: Small Rho GTPase Family Member Cdc42 and its Role in Neuronal Survival and Apoptosis Advisor: Dr. Daniel A. Linseman Degree Date: August 2017 Abstract Neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), Alzheimer’s and Parkinson’s disease are caused by a progressive and aberrant destruction of neurons in the brain and spinal cord. These disorders lack effective long term treatments, and existing options focus primarily on either delaying disease onset or alleviating symptomology.
  • Supplementary Information Method CLEAR-CLIP. Mouse Keratinocytes

    Supplementary Information Method CLEAR-CLIP. Mouse Keratinocytes

    Supplementary Information Method CLEAR-CLIP. Mouse keratinocytes of the designated genotype were maintained in E-low calcium medium. Inducible cells were treated with 3 ug/ml final concentration doxycycline for 24 hours before performing CLEAR-CLIP. One 15cm dish of confluent cells was used per sample. Cells were washed once with cold PBS. 10mls of cold PBS was then added and cells were irradiated with 300mJ/cm2 UVC (254nM wavelength). Cells were then scraped from the plates in cold PBS and pelleted by centrifugation at 1,000g for 2 minutes. Pellets were frozen at -80oC until needed. Cells were then lysed on ice with occasional vortexing in 1ml of lysis buffer (50mM Tris-HCl pH 7.4, 100mM NaCl, 1mM MgCl2, 0.1 mM CaCl2, 1% NP-40, 0.5% Sodium Deoxycholate, 0.1% SDS) containing 1X protease inhibitors (Roche #88665) and RNaseOUT (Invitrogen #10777019) at 4ul/ml final concentration. Next, TurboDNase (Invitrogen #AM2238, 10U), RNase A (0.13ug) and RNase T1 (0.13U) were added and samples were incubated at 37oC for 5 minutes with occasional mixing. Samples were immediately placed on ice and then centrifuged at 16,160g at 4oC for 20 minutes to clear lysate. 25ul of Protein-G Dynabeads (Invitrogen #10004D) were used per IP. Dynabeads were pre-washed with lysis buffer and pre- incubated with 3ul of Wako Anti-Mouse-Ago2 (2D4) antibody. The dynabead/antibody mixture was added to the lysate and rocked for 2 hours at 4oC. All steps after the IP were done on bead until samples were loaded into the polyacrylamide gel.
  • (Arhgef4) Deficiency Enhances Spatial and Object Recognition Memory

    (Arhgef4) Deficiency Enhances Spatial and Object Recognition Memory

    https://doi.org/10.5607/en20049 Exp Neurobiol. 2020 Oct;29(5):334-343. pISSN 1226-2560 • eISSN 2093-8144 Short Communication Rho Guanine Nucleotide Exchange Factor 4 (Arhgef4) Deficiency Enhances Spatial and Object Recognition Memory Ki-Seo Yoo1, Kina Lee1, Yong-Seok Lee2, Won-Jong Oh3 and Hyong Kyu Kim1* 1Department of Medicine and Microbiology, Graduate Program in Neuroscience, College of Medicine, Chungbuk National University, Cheongju 28644, 2Department of Physiology, Department of Biomedical Science, Seoul National University College of Medicine, Seoul 03080, 3Neurovascular Unit Research Group, Korea Brain Research Institute, Daegu 41062, Korea Guanine nucleotide exchange factors (GEFs) play multiple functional roles in neurons. In a previous study, we reported that Arhgef4 (Rho guanine nucleotide exchange factor 4) functioned as a negative regulator of the excitatory synaptic function by sequestering postsynaptic density protein 95 (PSD-95). However, the role of Arhgef4 in behavior has not been examined. We performed comprehensive behavioral tests in knockout (KO) mice to investigate of the effects of Arhgef4 deficiency. We found that the expressed PSD-95 particle size was significantly increased in hippocampal neuronal cultures from Arhgef4 KO mice, which is consistent with the previous in vitro findings. Arhgef4 KO mice exhibited general motor activity and anxiety-like behavior comparable to those of the wild type littermates. However, spatial memory and object recognition memory were signifi- cantly enhanced in the Arhgef4 KO mice. Taken together, these data confirm the role of Arhgef4 as a negative synaptic regulator at the behavioral level. Key words: Arhgef4, PSD-95, Spatial memory, Recognition INTRODUCTION tin, a GEF of inhibitory synapses selectively activating the small GTPase Cdc42, results in a reduced capability of spatial learning Rho guanine nucleotide exchange factors (GEFs) are involved in and enhances anxiety-like behavior in collybistin-deficient mice the activation of Rho family GTPases by accelerating the exchange [4].
  • G-Protein ␤␥-Complex Is Crucial for Efficient Signal Amplification in Vision

    G-Protein ␤␥-Complex Is Crucial for Efficient Signal Amplification in Vision

    The Journal of Neuroscience, June 1, 2011 • 31(22):8067–8077 • 8067 Cellular/Molecular G-Protein ␤␥-Complex Is Crucial for Efficient Signal Amplification in Vision Alexander V. Kolesnikov,1 Loryn Rikimaru,2 Anne K. Hennig,1 Peter D. Lukasiewicz,1 Steven J. Fliesler,4,5,6,7 Victor I. Govardovskii,8 Vladimir J. Kefalov,1 and Oleg G. Kisselev2,3 1Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, Missouri 63110, Departments of 2Ophthalmology and 3Biochemistry and Molecular Biology, Saint Louis University School of Medicine, Saint Louis, Missouri 63104, 4Research Service, Veterans Administration Western New York Healthcare System, and Departments of 5Ophthalmology (Ross Eye Institute) and 6Biochemistry, University at Buffalo/The State University of New York (SUNY), and 7SUNY Eye Institute, Buffalo, New York 14215, and 8Sechenov Institute for Evolutionary Physiology and Biochemistry, Russian Academy of Sciences, Saint Petersburg 194223, Russia A fundamental question of cell signaling biology is how faint external signals produce robust physiological responses. One universal mechanism relies on signal amplification via intracellular cascades mediated by heterotrimeric G-proteins. This high amplification system allows retinal rod photoreceptors to detect single photons of light. Although much is now known about the role of the ␣-subunit of the rod-specific G-protein transducin in phototransduction, the physiological function of the auxiliary ␤␥-complex in this process remains a mystery. Here, we show that elimination of the transducin ␥-subunit drastically reduces signal amplification in intact mouse rods. The consequence is a striking decline in rod visual sensitivity and severe impairment of nocturnal vision. Our findings demonstrate that transducin ␤␥-complex controls signal amplification of the rod phototransduction cascade and is critical for the ability of rod photoreceptors to function in low light conditions.