MAP17's Up-Regulation, a Crosspoint in Cancer and Inflammatory
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Mouse Germ Line Mutations Due to Retrotransposon Insertions Liane Gagnier1, Victoria P
Gagnier et al. Mobile DNA (2019) 10:15 https://doi.org/10.1186/s13100-019-0157-4 REVIEW Open Access Mouse germ line mutations due to retrotransposon insertions Liane Gagnier1, Victoria P. Belancio2 and Dixie L. Mager1* Abstract Transposable element (TE) insertions are responsible for a significant fraction of spontaneous germ line mutations reported in inbred mouse strains. This major contribution of TEs to the mutational landscape in mouse contrasts with the situation in human, where their relative contribution as germ line insertional mutagens is much lower. In this focussed review, we provide comprehensive lists of TE-induced mouse mutations, discuss the different TE types involved in these insertional mutations and elaborate on particularly interesting cases. We also discuss differences and similarities between the mutational role of TEs in mice and humans. Keywords: Endogenous retroviruses, Long terminal repeats, Long interspersed elements, Short interspersed elements, Germ line mutation, Inbred mice, Insertional mutagenesis, Transcriptional interference Background promoter and polyadenylation motifs and often a splice The mouse and human genomes harbor similar types of donor site [10, 11]. Sequences of full-length ERVs can TEs that have been discussed in many reviews, to which encode gag, pol and sometimes env, although groups of we refer the reader for more in depth and general infor- LTR retrotransposons with little or no retroviral hom- mation [1–9]. In general, both human and mouse con- ology also exist [6–9]. While not the subject of this re- tain ancient families of DNA transposons, none view, ERV LTRs can often act as cellular enhancers or currently active, which comprise 1–3% of these genomes promoters, creating chimeric transcripts with genes, and as well as many families or groups of retrotransposons, have been implicated in other regulatory functions [11– which have caused all the TE insertional mutations in 13]. -
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. -
The Cargo Protein MAP17 (PDZK1IP1) Regulates the Immune Microenvironment
www.impactjournals.com/oncotarget/ Oncotarget, 2017, Vol. 8, (No. 58), pp: 98580-98597 Research Paper The cargo protein MAP17 (PDZK1IP1) regulates the immune microenvironment José M. García-Heredia1,2,3 and Amancio Carnero1,3 1Instituto de Biomedicina de Sevilla, IBIS/Hospital Universitario Virgen del Rocío/Universidad de Sevilla/Consejo Superior de Investigaciones Científicas, Seville, Spain 2Department of Vegetal Biochemistry and Molecular Biology, University of Seville, Seville, Spain 3CIBER de Cáncer, Instituto de Salud Carlos III, Madrid, Spain Correspondence to: Amancio Carnero, email: [email protected] Keywords: MAP17; oncogene; inflammation; cancer; inflammatory diseases Received: July 14, 2017 Accepted: August 25, 2017 Published: October 06, 2017 Copyright: García-Heredia et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Inflammation is a complex defensive response activated after various harmful stimuli allowing the clearance of damaged cells and initiating healing and regenerative processes. Chronic, or pathological, inflammation is also one of the causes of neoplastic transformation and cancer development. MAP17 is a cargo protein that transports membrane proteins from the endoplasmic reticulum. Therefore, its overexpression may be linked to an excess of membrane proteins that may be recognized as an unwanted signal, triggering local inflammation. Therefore, we analyzed whether its overexpression is related to an inflammatory phenotype. In this work, we found a correlation between MAP17 expression and inflammatory phenotype in tumors and in other inflammatory diseases such as Crohn's disease, Barrett's esophagus, COPD or psoriasis. -
Identification and Validation of a Blood-Based 18-Gene Expression Signature in Colorectal Cancer
Published OnlineFirst March 27, 2013; DOI: 10.1158/1078-0432.CCR-12-3851 Clinical Cancer Imaging, Diagnosis, Prognosis Research Identification and Validation of a Blood-Based 18-Gene Expression Signature in Colorectal Cancer Ye Xu1,4, Qinghua Xu1,6,7, Li Yang1,4, Xun Ye6,7, Fang Liu6,7, Fei Wu6,7, Shujuan Ni1,2,3,5, Cong Tan1,2,3,5, Guoxiang Cai1,4, Xia Meng6,7, Sanjun Cai1,4, and Xiang Du1,2,3,5 Abstract Purpose: The early detection of colorectal cancer (CRC) is crucial for successful treatment and patient survival. However, compliance with current screening methods remains poor. This study aimed to identify an accurate blood-based gene expression signature for CRC detection. Experimental Design: Gene expression in peripheral blood samples from 216 patients with CRC tumors and 187 controls was investigated in the study.Wefirstconductedamicroarrayanalysistoselect candidate genes that were significantly differentially expressed between patients with cancer and con- trols. A quantitative reverse transcription PCR assay was then used to evaluate the expression of selected genes. A gene expression signature was identified using a training set (n ¼ 200) and then validated using an independent test set (n ¼ 160). Results: We identified an 18-gene signature that discriminated the patients with CRC from controls with 92% accuracy, 91% sensitivity, and 92% specificity. The signature performance was further validated in the independent test set with 86% accuracy, 84% sensitivity, and 88% specificity. The area under the receiver operating characteristics curve was 0.94. The signature was shown to be enriched in genes related to immune functions. Conclusions: This study identified an 18-gene signature that accurately discriminated patients with CRC from controls in peripheral blood samples. -
Genetic and Genomic Analysis of Hyperlipidemia, Obesity and Diabetes Using (C57BL/6J × TALLYHO/Jngj) F2 Mice
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Nutrition Publications and Other Works Nutrition 12-19-2010 Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P. Stewart Marshall University Hyoung Y. Kim University of Tennessee - Knoxville, [email protected] Arnold M. Saxton University of Tennessee - Knoxville, [email protected] Jung H. Kim Marshall University Follow this and additional works at: https://trace.tennessee.edu/utk_nutrpubs Part of the Animal Sciences Commons, and the Nutrition Commons Recommended Citation BMC Genomics 2010, 11:713 doi:10.1186/1471-2164-11-713 This Article is brought to you for free and open access by the Nutrition at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Nutrition Publications and Other Works by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Stewart et al. BMC Genomics 2010, 11:713 http://www.biomedcentral.com/1471-2164/11/713 RESEARCH ARTICLE Open Access Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P Stewart1, Hyoung Yon Kim2, Arnold M Saxton3, Jung Han Kim1* Abstract Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/ JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
Viewer 4.0 Software [73]
BMC Genomics BioMed Central Research Open Access Bioinformatic search of plant microtubule-and cell cycle related serine-threonine protein kinases Pavel A Karpov1, Elena S Nadezhdina2,3,AllaIYemets1, Vadym G Matusov1, Alexey Yu Nyporko1,NadezhdaYuShashina3 and Yaroslav B Blume*1 Addresses: 1Institute of Food Biotechnology and Genomics, National Academy of Sciences of Ukraine, 04123 Kyiv, Ukraine, 2Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russian Federation and 3AN Belozersky Institute of Physical- Chemical Biology, Moscow State University, Leninsky Gory, 119992 Moscow, Russian Federation E-mail: Pavel A Karpov - [email protected]; Elena S Nadezhdina - [email protected]; Alla I Yemets - [email protected]; Vadym G Matusov - [email protected]; Alexey Yu Nyporko - [email protected]; Nadezhda Yu Shashina - [email protected]; Yaroslav B Blume* - [email protected] *Corresponding author from International Workshop on Computational Systems Biology Approaches to Analysis of Genome Complexity and Regulatory Gene Networks Singapore 20-25 November 2008 Published: 10 February 2010 BMC Genomics 2010, 11(Suppl 1):S14 doi: 10.1186/1471-2164-11-S1-S14 This article is available from: http://www.biomedcentral.com/1471-2164/11/S1/S14 Publication of this supplement was made possible with help from the Bioinformatics Agency for Science, Technology and Research of Singapore and the Institute for Mathematical Sciences at the National University of Singapore. © 2010 Karpov 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. -
The Role of Cdep in the Embryonic Morphogenesis of Drosophila Melanogaster
The Role of Cdep in the Embryonic Morphogenesis of Drosophila melanogaster Dissertation zur Erlangung des akademischen Grades Doctor rerum naturalium (Dr. rer.nat.) vorgelegt der Fakultät Mathematik und Naturwissenschaften der Technischen Universität Dresden von Anne Morbach Geboren am 05. August 1984 in Nordhausen, Deutschland Eingereicht am 30. Oktober 2015 Die Dissertation wurde in der Zeit von April 2012 bis Oktober 2015 im Max-Planck-Institut für molekulare Zellbiologie und Genetik angefertigt Gutachter: Prof. Dr. Elisabeth Knust Prof. Dr. Christian Dahmann Now, here, you see, it takes all the running you can do, to keep in the same place. Lewis Carroll, Through the Looking-Glass I Contents List of Figures V List of Tables VII Abstract IX List of Abbreviations XI 1 Introduction 1 1.1 Epithelial cell polarity . 1 1.1.1 Cellularization and formation of the primary epithelium . 1 1.1.1.1 Establishment of epithelial polarity and adhesion . 2 1.1.2 The epithelial polarity network . 3 1.1.3 Cell-cell adhesion . 5 1.1.3.1 Adherens junctions . 5 1.1.3.2 Septate junctions . 6 1.2 Epithelial movements in Drosophila embryonic morphogenesis . 6 1.2.1 Epithelial tube formation during Drosophila embryogenesis . 7 1.2.2 Coordinated migration of epithelial sheets during Dros. embryogenesis 7 1.2.2.1 FERM domain proteins in epithelial migration . 9 1.2.2.2 Cdep . 10 1.3 Mutagenesis with the CRISPR/Cas9 system . 12 2 Aim of My PhD Thesis Work 15 3 Preliminary Work 17 4 Results 19 4.1 A screen for novel regulators in Drosophila embryonic morphogenesis . -
Statistical and Bioinformatic Analysis of Hemimethylation Patterns in Non-Small Cell Lung Cancer
Statistical and Bioinformatic Analysis of Hemimethylation Patterns in Non-Small Cell Lung Cancer Shuying Sun ( [email protected] ) Texas State University San Marcos https://orcid.org/0000-0003-3974-6996 Austin Zane Texas A&M University College Station Carolyn Fulton Schreiner University Jasmine Philipoom Case Western Reserve University Research article Keywords: Methylation, Hemimethylation, Lung Cancer, Bioinformatics, Epigenetics Posted Date: October 12th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-17794/v2 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Version of Record: A version of this preprint was published on March 12th, 2021. See the published version at https://doi.org/10.1186/s12885-021-07990-7. Page 1/29 Abstract Background: DNA methylation is an epigenetic event involving the addition of a methyl-group to a cytosine-guanine base pair (i.e., CpG site). It is associated with different cancers. Our research focuses on studying non- small cell lung cancer hemimethylation, which refers to methylation occurring on only one of the two DNA strands. Many studies often assume that methylation occurs on both DNA strands at a CpG site. However, recent publications show the existence of hemimethylation and its signicant impact. Therefore, it is important to identify cancer hemimethylation patterns. Methods: In this paper, we use the Wilcoxon signed rank test to identify hemimethylated CpG sites based on publicly available non-small cell lung cancer methylation sequencing data. We then identify two types of hemimethylated CpG clusters, regular and polarity clusters, and genes with large numbers of hemimethylated sites. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Kaposi's Sarcoma–Associated Herpesvirus Stably Clusters Its
Kaposi’s sarcoma–associated herpesvirus stably clusters its genomes across generations to maintain itself extrachromosomally The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Chiu, Ya-Fang, Arthur U. Sugden, Kathryn Fox, Mitchell Hayes, and Bill Sugden. 2017. “Kaposi’s sarcoma–associated herpesvirus stably clusters its genomes across generations to maintain itself extrachromosomally.” The Journal of Cell Biology 216 (9): 2745-2758. doi:10.1083/jcb.201702013. http://dx.doi.org/10.1083/ jcb.201702013. Published Version doi:10.1083/jcb.201702013 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:35982007 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA JCB: Article Kaposi’s sarcoma–associated herpesvirus stably clusters its genomes across generations to maintain itself extrachromosomally Ya-Fang Chiu,1,2,4,5,6 Arthur U. Sugden,7,8 Kathryn Fox,1,3 Mitchell Hayes,1 and Bill Sugden1 1McArdle Laboratory for Cancer Research, 2Morgridge Institute for Research, and 3Flow Cytometry Laboratory, Carbone Cancer Center, University of Wisconsin–Madison, Madison, WI 4Research Center for Emerging Viral Infections and 5Department of Microbiology and Immunology, Chang-Gung University, Taoyuan, Taiwan 6Department of Medical Laboratory, Chang-Gung Memorial Hospital, Taoyuan, Taiwan 7Department of Neuroscience, Brown University, Providence, RI 8Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA Genetic elements that replicate extrachromosomally are rare in mammals; however, several human tumor viruses, in- cluding the papillomaviruses and the gammaherpesviruses, maintain their plasmid genomes by tethering them to cellular chromosomes. -
Modular and Distinct Plexin-A4/FARP2/Rac1 Signaling Controls Dendrite Morphogenesis
The Journal of Neuroscience, July 8, 2020 • 40(28):5413–5430 • 5413 Development/Plasticity/Repair Modular and Distinct Plexin-A4/FARP2/Rac1 Signaling Controls Dendrite Morphogenesis Victor Danelon,1* Ron Goldner,2* Edward Martinez,1 Irena Gokhman,2 Kimberly Wang,1 Avraham Yaron,2 and Tracy S. Tran1 1Department of Biological Sciences, Rutgers University, Newark, New Jersey 07102, and 2Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, 76100, Israel Diverse neuronal populations with distinct cellular morphologies coordinate the complex function of the nervous system. Establishment of distinct neuronal morphologies critically depends on signaling pathways that control axonal and dendritic devel- opment. The Sema3A-Nrp1/PlxnA4 signaling pathway promotes cortical neuron basal dendrite arborization but also repels axons. However, the downstream signaling components underlying these disparate functions of Sema3A signaling are unclear. Using the KRK-AAA novel PlxnA4 knock-in male and female mice, generated by CRISPR/cas9, we show here that the KRK motif in the PlxnA4 cytoplasmic domain is required for Sema3A-mediated cortical neuron dendritic elaboration but is dispensable for inhibitory axon guidance. The RhoGEF FARP2, which binds to the KRK motif, shows identical functional specificity as the KRK motif in the PlxnA4 receptor. We find that Sema3A activates the small GTPase Rac1, and that Rac1 activity is required for dendrite elaboration but not axon growth cone collapse. This work identifies a novel Sema3A-Nrp1/PlxnA4/FARP2/Rac1 signaling pathway that specifi- cally controls dendritic morphogenesis but is dispensable for repulsive guidance events. Overall, our results demonstrate that the divergent signaling output from multifunctional receptor complexes critically depends on distinct signaling motifs, highlighting the modular nature of guidance cue receptors and its potential to regulate diverse cellular responses.