An Unconventional Interaction Between Dis1/TOG and Mal3/EB1 in Fission Yeast Promotes the Fidelity of Chromosome Segregation Yuzy Matsuo1,2, Sebastian P
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Title a New Centrosomal Protein Regulates Neurogenesis By
Title A new centrosomal protein regulates neurogenesis by microtubule organization Authors: Germán Camargo Ortega1-3†, Sven Falk1,2†, Pia A. Johansson1,2†, Elise Peyre4, Sanjeeb Kumar Sahu5, Loïc Broic4, Camino De Juan Romero6, Kalina Draganova1,2, Stanislav Vinopal7, Kaviya Chinnappa1‡, Anna Gavranovic1, Tugay Karakaya1, Juliane Merl-Pham8, Arie Geerlof9, Regina Feederle10,11, Wei Shao12,13, Song-Hai Shi12,13, Stefanie M. Hauck8, Frank Bradke7, Victor Borrell6, Vijay K. Tiwari§, Wieland B. Huttner14, Michaela Wilsch- Bräuninger14, Laurent Nguyen4 and Magdalena Götz1,2,11* Affiliations: 1. Institute of Stem Cell Research, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 2. Physiological Genomics, Biomedical Center, Ludwig-Maximilian University Munich, Germany. 3. Graduate School of Systemic Neurosciences, Biocenter, Ludwig-Maximilian University Munich, Germany. 4. GIGA-Neurosciences, Molecular regulation of neurogenesis, University of Liège, Belgium 5. Institute of Molecular Biology (IMB), Mainz, Germany. 6. Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d’Alacant, Spain. 7. Laboratory for Axon Growth and Regeneration, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. 8. Research Unit Protein Science, Helmholtz Centre Munich, German Research Center for Environmental Health, Munich, Germany. 9. Protein Expression and Purification Facility, Institute of Structural Biology, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 10. Institute for Diabetes and Obesity, Monoclonal Antibody Core Facility, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 11. SYNERGY, Excellence Cluster of Systems Neurology, Biomedical Center, Ludwig- Maximilian University Munich, Germany. 12. Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, USA 13. -
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. -
Identifying the Optimal Gene and Gene Set in Hepatocellular Carcinoma Based on Differential Expression and Differential Co-Expression Algorithm
1066 ONCOLOGY REPORTS 37: 1066-1074, 2017 Identifying the optimal gene and gene set in hepatocellular carcinoma based on differential expression and differential co-expression algorithm LI-YANG DONG1*, WEI-ZHONG ZHOU1*, JUN-WEI NI1, WEI XIANG1, WEN-HAO HU1, CHANG YU1 and HAI-YAN LI2 Departments of 1Invasive Technology and 2Rehabilitation, The First Affiliated Hospital of Wenzhou Medical University, Ouhai, Wenzhou, Zhejiang 325000, P.R. China Received June 23, 2016; Accepted August 10, 2016 DOI: 10.3892/or.2016.5333 * Abstract. The objective of this study was to identify the with ΔG = 18.681 and 24 HDE-HDC partitions in total. In optimal gene and gene set for hepatocellular carcinoma conclusion, we successfully investigated the optimal gene, (HCC) utilizing differential expression and differential MAPRE1, and gene set, nucleoside metabolic process, which co-expression (DEDC) algorithm. The DEDC algorithm may be potential biomarkers for targeted therapy and provide consisted of four parts: calculating differential expression significant insight for revealing the pathological mechanism (DE) by absolute t-value in t-statistics; computing differential underlying HCC. co-expression (DC) based on Z-test; determining optimal thresholds on the basis of Chi-squared (χ2) maximization and Introduction the corresponding gene was the optimal gene; and evaluating functional relevance of genes categorized into different Hepatocellular carcinoma (HCC) is the fifth most common partitions to determine the optimal gene set with highest mean cancer worldwide and the third leading cause of cancer-related * minimum functional information (FI) gain (ΔG). The optimal mortality (1), making it urgent to identify early diagnostic thresholds divided genes into four partitions, high DE and markers and therapeutic targets (2). -
The P53/P73 - P21cip1 Tumor Suppressor Axis Guards Against Chromosomal Instability by Restraining CDK1 in Human Cancer Cells
Oncogene (2021) 40:436–451 https://doi.org/10.1038/s41388-020-01524-4 ARTICLE The p53/p73 - p21CIP1 tumor suppressor axis guards against chromosomal instability by restraining CDK1 in human cancer cells 1 1 2 1 2 Ann-Kathrin Schmidt ● Karoline Pudelko ● Jan-Eric Boekenkamp ● Katharina Berger ● Maik Kschischo ● Holger Bastians 1 Received: 2 July 2020 / Revised: 2 October 2020 / Accepted: 13 October 2020 / Published online: 9 November 2020 © The Author(s) 2020. This article is published with open access Abstract Whole chromosome instability (W-CIN) is a hallmark of human cancer and contributes to the evolvement of aneuploidy. W-CIN can be induced by abnormally increased microtubule plus end assembly rates during mitosis leading to the generation of lagging chromosomes during anaphase as a major form of mitotic errors in human cancer cells. Here, we show that loss of the tumor suppressor genes TP53 and TP73 can trigger increased mitotic microtubule assembly rates, lagging chromosomes, and W-CIN. CDKN1A, encoding for the CDK inhibitor p21CIP1, represents a critical target gene of p53/p73. Loss of p21CIP1 unleashes CDK1 activity which causes W-CIN in otherwise chromosomally stable cancer cells. fi Vice versa 1234567890();,: 1234567890();,: Consequently, induction of CDK1 is suf cient to induce abnormal microtubule assembly rates and W-CIN. , partial inhibition of CDK1 activity in chromosomally unstable cancer cells corrects abnormal microtubule behavior and suppresses W-CIN. Thus, our study shows that the p53/p73 - p21CIP1 tumor suppressor axis, whose loss is associated with W-CIN in human cancer, safeguards against chromosome missegregation and aneuploidy by preventing abnormally increased CDK1 activity. -
Supplementary Data
SUPPLEMENTARY DATA A cyclin D1-dependent transcriptional program predicts clinical outcome in mantle cell lymphoma Santiago Demajo et al. 1 SUPPLEMENTARY DATA INDEX Supplementary Methods p. 3 Supplementary References p. 8 Supplementary Tables (S1 to S5) p. 9 Supplementary Figures (S1 to S15) p. 17 2 SUPPLEMENTARY METHODS Western blot, immunoprecipitation, and qRT-PCR Western blot (WB) analysis was performed as previously described (1), using cyclin D1 (Santa Cruz Biotechnology, sc-753, RRID:AB_2070433) and tubulin (Sigma-Aldrich, T5168, RRID:AB_477579) antibodies. Co-immunoprecipitation assays were performed as described before (2), using cyclin D1 antibody (Santa Cruz Biotechnology, sc-8396, RRID:AB_627344) or control IgG (Santa Cruz Biotechnology, sc-2025, RRID:AB_737182) followed by protein G- magnetic beads (Invitrogen) incubation and elution with Glycine 100mM pH=2.5. Co-IP experiments were performed within five weeks after cell thawing. Cyclin D1 (Santa Cruz Biotechnology, sc-753), E2F4 (Bethyl, A302-134A, RRID:AB_1720353), FOXM1 (Santa Cruz Biotechnology, sc-502, RRID:AB_631523), and CBP (Santa Cruz Biotechnology, sc-7300, RRID:AB_626817) antibodies were used for WB detection. In figure 1A and supplementary figure S2A, the same blot was probed with cyclin D1 and tubulin antibodies by cutting the membrane. In figure 2H, cyclin D1 and CBP blots correspond to the same membrane while E2F4 and FOXM1 blots correspond to an independent membrane. Image acquisition was performed with ImageQuant LAS 4000 mini (GE Healthcare). Image processing and quantification were performed with Multi Gauge software (Fujifilm). For qRT-PCR analysis, cDNA was generated from 1 µg RNA with qScript cDNA Synthesis kit (Quantabio). qRT–PCR reaction was performed using SYBR green (Roche). -
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. -
Downloaded the “Top Edge” Version
bioRxiv preprint doi: https://doi.org/10.1101/855338; this version posted December 6, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Drosophila models of pathogenic copy-number variant genes show global and 2 non-neuronal defects during development 3 Short title: Non-neuronal defects of fly homologs of CNV genes 4 Tanzeen Yusuff1,4, Matthew Jensen1,4, Sneha Yennawar1,4, Lucilla Pizzo1, Siddharth 5 Karthikeyan1, Dagny J. Gould1, Avik Sarker1, Yurika Matsui1,2, Janani Iyer1, Zhi-Chun Lai1,2, 6 and Santhosh Girirajan1,3* 7 8 1. Department of Biochemistry and Molecular Biology, Pennsylvania State University, 9 University Park, PA 16802 10 2. Department of Biology, Pennsylvania State University, University Park, PA 16802 11 3. Department of Anthropology, Pennsylvania State University, University Park, PA 16802 12 4 contributed equally to work 13 14 *Correspondence: 15 Santhosh Girirajan, MBBS, PhD 16 205A Life Sciences Building 17 Pennsylvania State University 18 University Park, PA 16802 19 E-mail: [email protected] 20 Phone: 814-865-0674 21 1 bioRxiv preprint doi: https://doi.org/10.1101/855338; this version posted December 6, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 22 ABSTRACT 23 While rare pathogenic copy-number variants (CNVs) are associated with both neuronal and non- 24 neuronal phenotypes, functional studies evaluating these regions have focused on the molecular 25 basis of neuronal defects. -
Role and Regulation of the P53-Homolog P73 in the Transformation of Normal Human Fibroblasts
Role and regulation of the p53-homolog p73 in the transformation of normal human fibroblasts Dissertation zur Erlangung des naturwissenschaftlichen Doktorgrades der Bayerischen Julius-Maximilians-Universität Würzburg vorgelegt von Lars Hofmann aus Aschaffenburg Würzburg 2007 Eingereicht am Mitglieder der Promotionskommission: Vorsitzender: Prof. Dr. Dr. Martin J. Müller Gutachter: Prof. Dr. Michael P. Schön Gutachter : Prof. Dr. Georg Krohne Tag des Promotionskolloquiums: Doktorurkunde ausgehändigt am Erklärung Hiermit erkläre ich, dass ich die vorliegende Arbeit selbständig angefertigt und keine anderen als die angegebenen Hilfsmittel und Quellen verwendet habe. Diese Arbeit wurde weder in gleicher noch in ähnlicher Form in einem anderen Prüfungsverfahren vorgelegt. Ich habe früher, außer den mit dem Zulassungsgesuch urkundlichen Graden, keine weiteren akademischen Grade erworben und zu erwerben gesucht. Würzburg, Lars Hofmann Content SUMMARY ................................................................................................................ IV ZUSAMMENFASSUNG ............................................................................................. V 1. INTRODUCTION ................................................................................................. 1 1.1. Molecular basics of cancer .......................................................................................... 1 1.2. Early research on tumorigenesis ................................................................................. 3 1.3. Developing -
MAPRE1 Rabbit Pab
Leader in Biomolecular Solutions for Life Science MAPRE1 Rabbit pAb Catalog No.: A2614 Basic Information Background Catalog No. The protein encoded by this gene was first identified by its binding to the APC protein A2614 which is often mutated in familial and sporadic forms of colorectal cancer. This protein localizes to microtubules, especially the growing ends, in interphase cells. During Observed MW mitosis, the protein is associated with the centrosomes and spindle microtubules. The 34kDa protein also associates with components of the dynactin complex and the intermediate chain of cytoplasmic dynein. Because of these associations, it is thought that this protein Calculated MW is involved in the regulation of microtubule structures and chromosome stability. This 29kDa gene is a member of the RP/EB family. Category Primary antibody Applications WB, IF Cross-Reactivity Human, Mouse, Rat Recommended Dilutions Immunogen Information WB 1:500 - 1:2000 Gene ID Swiss Prot 22919 Q15691 IF 1:50 - 1:200 Immunogen Recombinant fusion protein containing a sequence corresponding to amino acids 134-268 of human MAPRE1 (NP_036457.1). Synonyms MAPRE1;EB1 Contact Product Information www.abclonal.com Source Isotype Purification Rabbit IgG Affinity purification Storage Store at -20℃. Avoid freeze / thaw cycles. Buffer: PBS with 0.02% sodium azide,50% glycerol,pH7.3. Validation Data Western blot analysis of extracts of various cell lines, using MAPRE1 antibody (A2614) at 1:1000 dilution. Secondary antibody: HRP Goat Anti-Rabbit IgG (H+L) (AS014) at 1:10000 dilution. Lysates/proteins: 25ug per lane. Blocking buffer: 3% nonfat dry milk in TBST. Detection: ECL Basic Kit (RM00020). -
Role of the Microtubule-Associated Protein ATIP3 in Cell Migration and Breast Cancer Metastasis Angie Molina Delgado
Role of the microtubule-associated protein ATIP3 in cell migration and breast cancer metastasis Angie Molina Delgado To cite this version: Angie Molina Delgado. Role of the microtubule-associated protein ATIP3 in cell migration and breast cancer metastasis. Molecular biology. Université René Descartes - Paris V, 2014. English. NNT : 2014PA05T022. tel-01068663 HAL Id: tel-01068663 https://tel.archives-ouvertes.fr/tel-01068663 Submitted on 26 Sep 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Université Paris Descartes Ecole doctorale BioSPC Thesis submitted towards fulfillment of the requirement for the degree of DOCTOR of Health & Life Sciences Specialized in Cellular and Molecular Biology Role of the microtubule-associated protein ATIP3 in cell migration and breast cancer metastasis By Angie Molina Delgado Under supervision of Dr. Clara Nahmias Thesis defense 3 September, 2014 Members of jury: Dr. Ali BADACHE Reviewer Dr. Laurence LAFANECHERE Reviewer Dr. Franck PEREZ Examiner Dr. Stéphane HONORE Examiner Dr. Clara NAHMIAS Thesis Director Table of Contents List of abbreviations ....................................................................................................................... 9 “Rôle de la protéine associée aux microtubules ATIP3 dans la migration cellulaire et la formation de métastases du cancer du sein” ................................................................................................ 11 I. -
Suppl. Table 1
Suppl. Table 1. SiRNA library used for centriole overduplication screen. Entrez Gene Id NCBI gene symbol siRNA Target Sequence 1070 CETN3 TTGCGACGTGTTGCTAGAGAA 1070 CETN3 AAGCAATAGATTATCATGAAT 55722 CEP72 AGAGCTATGTATGATAATTAA 55722 CEP72 CTGGATGATTTGAGACAACAT 80071 CCDC15 ACCGAGTAAATCAACAAATTA 80071 CCDC15 CAGCAGAGTTCAGAAAGTAAA 9702 CEP57 TAGACTTATCTTTGAAGATAA 9702 CEP57 TAGAGAAACAATTGAATATAA 282809 WDR51B AAGGACTAATTTAAATTACTA 282809 WDR51B AAGATCCTGGATACAAATTAA 55142 CEP27 CAGCAGATCACAAATATTCAA 55142 CEP27 AAGCTGTTTATCACAGATATA 85378 TUBGCP6 ACGAGACTACTTCCTTAACAA 85378 TUBGCP6 CACCCACGGACACGTATCCAA 54930 C14orf94 CAGCGGCTGCTTGTAACTGAA 54930 C14orf94 AAGGGAGTGTGGAAATGCTTA 5048 PAFAH1B1 CCCGGTAATATCACTCGTTAA 5048 PAFAH1B1 CTCATAGATATTGAACAATAA 2802 GOLGA3 CTGGCCGATTACAGAACTGAA 2802 GOLGA3 CAGAGTTACTTCAGTGCATAA 9662 CEP135 AAGAATTTCATTCTCACTTAA 9662 CEP135 CAGCAGAAAGAGATAAACTAA 153241 CCDC100 ATGCAAGAAGATATATTTGAA 153241 CCDC100 CTGCGGTAATTTCCAGTTCTA 80184 CEP290 CCGGAAGAAATGAAGAATTAA 80184 CEP290 AAGGAAATCAATAAACTTGAA 22852 ANKRD26 CAGAAGTATGTTGATCCTTTA 22852 ANKRD26 ATGGATGATGTTGATGACTTA 10540 DCTN2 CACCAGCTATATGAAACTATA 10540 DCTN2 AACGAGATTGCCAAGCATAAA 25886 WDR51A AAGTGATGGTTTGGAAGAGTA 25886 WDR51A CCAGTGATGACAAGACTGTTA 55835 CENPJ CTCAAGTTAAACATAAGTCAA 55835 CENPJ CACAGTCAGATAAATCTGAAA 84902 CCDC123 AAGGATGGAGTGCTTAATAAA 84902 CCDC123 ACCCTGGTTGTTGGATATAAA 79598 LRRIQ2 CACAAGAGAATTCTAAATTAA 79598 LRRIQ2 AAGGATAATATCGTTTAACAA 51143 DYNC1LI1 TTGGATTTGTCTATACATATA 51143 DYNC1LI1 TAGACTTAGTATATAAATACA 2302 FOXJ1 CAGGACAGACAGACTAATGTA -
Rahu Is a Mutant Allele of Dnmt3c, Encoding a DNA Methyltransferase Required for Meiosis and Transposon Repression in the Mouse Male Germline
bioRxiv preprint doi: https://doi.org/10.1101/121822; this version posted March 29, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. rahu is a mutant allele of Dnmt3c, encoding a DNA methyltransferase required for meiosis and transposon repression in the mouse male germline Devanshi Jain1*, Cem Meydan2,3, Julian Lange1,4, Corentin Claeys Bouuaert1,4, Christopher E. Mason2,3,5, Kathryn V. Anderson6, Scott Keeney1,4* 1Molecular Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America 2Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America 3The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, United States of America 4Howard Hughes Medical Institute, New York, New York, United States of America 5The Feil Family Brain and Mind Research Institute, New York, New York, United States of America 6Developmental Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America *Corresponding Author E-mail: [email protected] (DJ); [email protected] (SK) 1 bioRxiv preprint doi: https://doi.org/10.1101/121822; this version posted March 29, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.