Computational Analysis of the Genetic And

Total Page:16

File Type:pdf, Size:1020Kb

Computational Analysis of the Genetic And Unicentre CH-1015 Lausanne http://serval.unil.ch Year : 2010 Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders Diana MAREK Diana MAREK, 2010, Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders Originally published at : Thesis, University of Lausanne Posted at the University of Lausanne Open Archive. http://serval.unil.ch Droits d’auteur L'Université de Lausanne attire expressément l'attention des utilisateurs sur le fait que tous les documents publiés dans l'Archive SERVAL sont protégés par le droit d'auteur, conformément à la loi fédérale sur le droit d'auteur et les droits voisins (LDA). A ce titre, il est indispensable d'obtenir le consentement préalable de l'auteur et/ou de l’éditeur avant toute utilisation d'une oeuvre ou d'une partie d'une oeuvre ne relevant pas d'une utilisation à des fins personnelles au sens de la LDA (art. 19, al. 1 lettre a). A défaut, tout contrevenant s'expose aux sanctions prévues par cette loi. Nous déclinons toute responsabilité en la matière. Copyright The University of Lausanne expressly draws the attention of users to the fact that all documents published in the SERVAL Archive are protected by copyright in accordance with federal law on copyright and similar rights (LDA). Accordingly it is indispensable to obtain prior consent from the author and/or publisher before any use of a work or part of a work for purposes other than personal use within the meaning of LDA (art. 19, para. 1 letter a). Failure to do so will expose offenders to the sanctions laid down by this law. We accept no liability in this respect. Département de Génétique Médicale - Computational Biology Group Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid-related disorders Thèse de doctorat ès sciences de la vie (PhD) Présentée à la Faculté de biologie et médecine de l'Université de Lausanne par DIANA MAREK Diplômée de l'Université Paris XI – Orsay (France) Master de Bioinformatique et Biostatistiques Jury Prof. Jérôme Biollaz, Président Prof. Sven Bergmann, Directeur de thèse Prof. Jacques Beckmann, co-Directeur de thèse Prof. Murielle Bochud, Expert Prof. Eckart Zitzler, Expert Lausanne, 2010 Ici et ailleurs, A mes parents, A tous ceux et celles qui ont marqué ma vie, De quelque manière qui soit. Acknowledgements I spent five years in the Department of Medical Genetics at the University of Lausanne for my PhD. Since 2005, I met many people at work and in my life in Lausanne. They all participated in different ways to a very special step in my scientific career and life as a human being. I would like to start with the Department of Medical Genetics (DGM). I saw the DGM growing. I appreciated being one of the first DGM member and the first student of the Computational Biology Group (CBG) founded by Professor Sven Bergmann. I would like to thank the Swiss Institute of Bioinformatics (SIB). The CBG is affiliated to the SIB. It allowed me to meet other scientists from the community, to attend conferences, and especially through the SIB Doctoral School program that I joined to meet other PhD students, and share my experience with them. It has been a fantastic way of knowing what other bioinformaticians are doing in Switzerland and abroad. Thanks to all of you! Through my PhD, I established collaborations with different research groups. I want here to thank them for giving me the opportunity to work with them. First, thanks to Professor Amalio Telenti and Dr Philip Tarr who provided me with the Swiss HIV Cohort Study data and for the fruitful exchanges we had. Working on that topic was very stimulating for me. Thanks to the Cohorte of Lausanne (CoLaus) Study, especially Vincent Mooser (from GSK), Peter Vollenweider and Gérard Waeber (from the CHUV) for setting up such a rich study that allowed me to be part of important large-scale projects which brought together lots of scientists, clinicians and researchers from all around the world. I learnt a lot and I developed my sense of collaboration and teamwork within two big consortia. Thanks to the different members of GIANT and MAGIC. It was very pleasant and rewarding working and exchanging with you. Thanks to the Hypergenes project led by Dr. Carlo Rivolta. I have been involved in the primary steps of this study, which was a different and profitable experience for me. I would also like to thank Dr. Ronan Roussel for the nice collaboration that we established together. In the following section, I want to thank my experts: Prof. Eckart Zitzler and Prof. Murielle Bochud. Writing a thesis takes time but reading all those pages also demands time. Thanks to both of you for accepting to be my experts and for your involvement. Your suggestions, comments and questions have been very much appreciated. During my PhD, my work in the CBG has been supervised by Prof. Sven Bergmann and Prof. Jacques Beckmann. I would like to thank Sven for his patience, advices, open-mindness and support in the good and bad moments of my PhD. I could easily share with you my fears and frustrations regarding my work. It was our first experience as PhD student and supervisor, so we certainly made mistakes but we learnt a lot from each other. I enjoyed working at the CBG with you and the rest of the group. I also want to say a few words about Jacqui. He was always available when needed for scientific and non-scientific matters. I always felt very comfortable talking to you; you pushed me over my limits because you believed I could do it. Both Sven and Jacqui boosted my self-confidence and challenged me to go forward when I wanted to give up. Thanks to the two of you for your encouragement. It helped me a lot all along the way! I have been extremely lucky to be surrounded at work by very smart and nice people. I want to thank here all my colleagues at the CBG for their help and the time they spent with me for questions and discussions. Especially thanks to Zoltán, Bastian, Aitana, Micha, Armand, and Karen. Working with you guys was really great! Aitana, sharing our frustrations and good moments together at work made me realize you are a very special person to me. I also want to thank the whole DGM for all the moments shared together, all the enthusiasm people showed in the department. I had lot of fun working in such a nice environment. I also thank Suzanne, our secretary. She has always been available for any administrative issue, I really appreciated your help. I met lots of people during my PhD time and some of them became good friends. Here I am grateful to them and to my long-time friends. I tried my best not to forget anybody but I am sure that I will. So please, forgive me in advance! Merci à mes amis de plus ou moins longues dates, à ceux que j'ai connus aux différentes époques de la vie, comme Marion et Fred à l'école primaire et en fac. Merci aux étudiants de la filière de Bionfo et Biostats de la fac d'Orsay. Ce furent 3 années géniales. Merci Christophe, merci de m'avoir soutenue durant ces années, que ce soit pour les cours, les TPs, les examens, les coups durs de la vie. Tu as toujours été là, pour m'écouter, rigoler, bosser, et pour m'encourager ! Merci Pierrot pour tous les moments, conversations diverses et variées, partagés au long de nos thèses. Cela m'a permis de continuer le dur cheminement du doctorat. Merci à toi Julien, avec qui j'ai repris contact ces dernières années, nos échanges et nos rencontres autour d'un café sont toujours géniales. Merci à toi Jean, je t'ai connu vers le début de la fin de ma thèse, certainement au moment le plus dur. Tu m'as beaucoup apporté, ton franc-parler, nos convers', nos rigolades et ta façon bien propre à toi de me soutenir m'ont beaucoup aidée. Merci au volley-ball, à ce sport qui est une passion pour moi depuis déjà 16 ans. Il m'a permis de me défouler lorsque j'en avais besoin. Il m'a permis de me vider la tête lorsque je pensais ne plus pouvoir y arriver. Merci à Manon avec qui je prends toujours autant de plaisir à jouer à ce sport. Merci à Sandrine, Gérald, Célia et Sacha, mes Suisses "préférés". Partager le volley, faire les cours de soutien, de bonnes bouffes et des sorties avec vous m'ont fait découvrir une super famille. Je vous ai adoptés comme vous m'avez adoptée. Je suis ravie d'avoir croisé votre chemin et j'en garde d'excellents souvenirs. Merci à Stelle, Marie-Aude, François, Pierre D, Julie, Séverine, Aurélie pour votre bonne humeur, votre écoute, vos encouragements à différents moments de ma thèse. Gracias a vos Marcos, por haberme soportado todos estos años, y haber compartido conmigo momentos de mi vida más o menos fáciles y siempre haberme dado ánimo. Thanks to Arne and David for your encouragement when I was deeply thinking whether I should start a PhD.
Recommended publications
  • 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.
    [Show full text]
  • UNIVERSITY of CALIFORNIA, IRVINE Combinatorial Regulation By
    UNIVERSITY OF CALIFORNIA, IRVINE Combinatorial regulation by maternal transcription factors during activation of the endoderm gene regulatory network DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Biological Sciences by Kitt D. Paraiso Dissertation Committee: Professor Ken W.Y. Cho, Chair Associate Professor Olivier Cinquin Professor Thomas Schilling 2018 Chapter 4 © 2017 Elsevier Ltd. © 2018 Kitt D. Paraiso DEDICATION To the incredibly intelligent and talented people, who in one way or another, helped complete this thesis. ii TABLE OF CONTENTS Page LIST OF FIGURES vii LIST OF TABLES ix LIST OF ABBREVIATIONS X ACKNOWLEDGEMENTS xi CURRICULUM VITAE xii ABSTRACT OF THE DISSERTATION xiv CHAPTER 1: Maternal transcription factors during early endoderm formation in 1 Xenopus Transcription factors co-regulate in a cell type-specific manner 2 Otx1 is expressed in a variety of cell lineages 4 Maternal otx1 in the endodermal conteXt 5 Establishment of enhancers by maternal transcription factors 9 Uncovering the endodermal gene regulatory network 12 Zygotic genome activation and temporal control of gene eXpression 14 The role of maternal transcription factors in early development 18 References 19 CHAPTER 2: Assembly of maternal transcription factors initiates the emergence 26 of tissue-specific zygotic cis-regulatory regions Introduction 28 Identification of maternal vegetally-localized transcription factors 31 Vegt and OtX1 combinatorially regulate the endodermal 33 transcriptome iii
    [Show full text]
  • The Relevance of Clinical, Genetic and Serological Markers
    AUTREV-01901; No of Pages 18 Autoimmunity Reviews xxx (2016) xxx–xxx Contents lists available at ScienceDirect Autoimmunity Reviews journal homepage: www.elsevier.com/locate/autrev Review Cardiovascular risk assessment in patients with rheumatoid arthritis: The relevance of clinical, genetic and serological markers Raquel López-Mejías a, Santos Castañeda b, Carlos González-Juanatey c,AlfonsoCorralesa, Iván Ferraz-Amaro d, Fernanda Genre a, Sara Remuzgo-Martínez a, Luis Rodriguez-Rodriguez e, Ricardo Blanco a,JavierLlorcaf, Javier Martín g, Miguel A. González-Gay a,h,i,⁎ a Epidemiology, Genetics and Atherosclerosis Research Group on Systemic Inflammatory Diseases, Rheumatology Division, IDIVAL, Santander, Spain b Division of Rheumatology, Hospital Universitario la Princesa, IIS-IPrincesa, Madrid, Spain c Division of Cardiology, Hospital Lucus Augusti, Lugo, Spain d Rheumatology Division, Hospital Universitario de Canarias, Santa Cruz de Tenerife, Spain e Division of Rheumatology, Hospital Clínico San Carlos, Madrid, Spain f Division of Epidemiology and Computational Biology, School of Medicine, University of Cantabria, and CIBER Epidemiología y Salud Pública (CIBERESP), IDIVAL, Santander, Spain g Institute of Parasitology and Biomedicine López-Neyra, IPBLN-CSIC, Granada, Spain h School of Medicine, University of Cantabria, Santander, Spain i Cardiovascular Pathophysiology and Genomics Research Unit, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa article info abstract Article history: Cardiovascular disease (CV) is the most common cause of premature mortality in patients with rheumatoid ar- Received 7 July 2016 thritis (RA). This is the result of an accelerated atherosclerotic process. Adequate CV risk stratification has special Accepted 9 July 2016 relevance in RA to identify patients at risk of CV disease.
    [Show full text]
  • Supp Material.Pdf
    Simon et al. Supplementary information: Table of contents p.1 Supplementary material and methods p.2-4 • PoIy(I)-poly(C) Treatment • Flow Cytometry and Immunohistochemistry • Western Blotting • Quantitative RT-PCR • Fluorescence In Situ Hybridization • RNA-Seq • Exome capture • Sequencing Supplementary Figures and Tables Suppl. items Description pages Figure 1 Inactivation of Ezh2 affects normal thymocyte development 5 Figure 2 Ezh2 mouse leukemias express cell surface T cell receptor 6 Figure 3 Expression of EZH2 and Hox genes in T-ALL 7 Figure 4 Additional mutation et deletion of chromatin modifiers in T-ALL 8 Figure 5 PRC2 expression and activity in human lymphoproliferative disease 9 Figure 6 PRC2 regulatory network (String analysis) 10 Table 1 Primers and probes for detection of PRC2 genes 11 Table 2 Patient and T-ALL characteristics 12 Table 3 Statistics of RNA and DNA sequencing 13 Table 4 Mutations found in human T-ALLs (see Fig. 3D and Suppl. Fig. 4) 14 Table 5 SNP populations in analyzed human T-ALL samples 15 Table 6 List of altered genes in T-ALL for DAVID analysis 20 Table 7 List of David functional clusters 31 Table 8 List of acquired SNP tested in normal non leukemic DNA 32 1 Simon et al. Supplementary Material and Methods PoIy(I)-poly(C) Treatment. pIpC (GE Healthcare Lifesciences) was dissolved in endotoxin-free D-PBS (Gibco) at a concentration of 2 mg/ml. Mice received four consecutive injections of 150 μg pIpC every other day. The day of the last pIpC injection was designated as day 0 of experiment.
    [Show full text]
  • GTF3A (NM 002097) 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 RC225554 GTF3A (NM_002097) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: GTF3A (NM_002097) Human Tagged ORF Clone Tag: Myc-DDK Symbol: GTF3A Synonyms: AP2; TFIIIA Vector: pCMV6-Entry (PS100001) E. coli Selection: Kanamycin (25 ug/mL) Cell Selection: Neomycin ORF Nucleotide >RC225554 representing NM_002097 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC CTGGATCCGCCGGCCGTGGTCGCCGAGTCGGTGTCGTCCTTGACCATCGCCGACGCGTTCATTGCAGCCG GCGAGAGCTCAGCTCCGACCCCGCCGCGCCCCGCGCTTCCCAGGAGGTTCATCTGCTCCTTCCCTGACTG CAGCGCCAATTACAGCAAAGCCTGGAAGCTTGACGCGCACCTGTGCAAGCACACGGGGGAGAGACCATTT GTTTGTGACTATGAAGGGTGTGGCAAGGCCTTCATCAGGGACTACCATCTGAGCCGCCACATTCTGACTC ACACAGGAGAAAAGCCGTTTGTTTGTGCAGCCAATGGCTGTGATCAAAAATTCAACACAAAATCAAACTT GAAGAAACATTTTGAACGCAAACATGAAAATCAACAAAAACAATATATATGCAGTTTTGAAGACTGTAAG AAGACCTTTAAGAAACATCAGCAGCTGAAAATCCATCAGTGCCAGCATACCAATGAACCTCTATTCAAGT GTACCCAGGAAGGATGTGGGAAACACTTTGCATCACCCAGCAAGCTGAAACGACATGCCAAGGCCCACGA GGGCTATGTATGTCAAAAAGGATGTTCCTTTGTGGCAAAAACATGGACGGAACTTCTGAAACATGTGAGA GAAACCCATAAAGAGGAAATACTATGTGAAGTATGCCGGAAAACATTTAAACGCAAAGATTACCTTAAGC AACACATGAAAACTCATGCCCCAGAAAGGGATGTATGTCGCTGTCCAAGAGAAGGCTGTGGAAGAACCTA TACAACTGTGTTTAATCTCCAAAGCCATATCCTCTCCTTCCATGAGGAAAGCCGCCCTTTTGTGTGTGAA CATGCTGGCTGTGGCAAAACATTTGCAATGAAACAAAGTCTCACTAGGCATGCTGTTGTACATGATCCTG
    [Show full text]
  • Integrative Bulk and Single-Cell Profiling of Premanufacture T-Cell Populations Reveals Factors Mediating Long-Term Persistence of CAR T-Cell Therapy
    Published OnlineFirst April 5, 2021; DOI: 10.1158/2159-8290.CD-20-1677 RESEARCH ARTICLE Integrative Bulk and Single-Cell Profiling of Premanufacture T-cell Populations Reveals Factors Mediating Long-Term Persistence of CAR T-cell Therapy Gregory M. Chen1, Changya Chen2,3, Rajat K. Das2, Peng Gao2, Chia-Hui Chen2, Shovik Bandyopadhyay4, Yang-Yang Ding2,5, Yasin Uzun2,3, Wenbao Yu2, Qin Zhu1, Regina M. Myers2, Stephan A. Grupp2,5, David M. Barrett2,5, and Kai Tan2,3,5 Downloaded from cancerdiscovery.aacrjournals.org on October 1, 2021. © 2021 American Association for Cancer Research. Published OnlineFirst April 5, 2021; DOI: 10.1158/2159-8290.CD-20-1677 ABSTRACT The adoptive transfer of chimeric antigen receptor (CAR) T cells represents a breakthrough in clinical oncology, yet both between- and within-patient differences in autologously derived T cells are a major contributor to therapy failure. To interrogate the molecular determinants of clinical CAR T-cell persistence, we extensively characterized the premanufacture T cells of 71 patients with B-cell malignancies on trial to receive anti-CD19 CAR T-cell therapy. We performed RNA-sequencing analysis on sorted T-cell subsets from all 71 patients, followed by paired Cellular Indexing of Transcriptomes and Epitopes (CITE) sequencing and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) on T cells from six of these patients. We found that chronic IFN signaling regulated by IRF7 was associated with poor CAR T-cell persistence across T-cell subsets, and that the TCF7 regulon not only associates with the favorable naïve T-cell state, but is maintained in effector T cells among patients with long-term CAR T-cell persistence.
    [Show full text]
  • Drosophila and Human Transcriptomic Data Mining Provides Evidence for Therapeutic
    Drosophila and human transcriptomic data mining provides evidence for therapeutic mechanism of pentylenetetrazole in Down syndrome Author Abhay Sharma Institute of Genomics and Integrative Biology Council of Scientific and Industrial Research Delhi University Campus, Mall Road Delhi 110007, India Tel: +91-11-27666156, Fax: +91-11-27662407 Email: [email protected] Nature Precedings : hdl:10101/npre.2010.4330.1 Posted 5 Apr 2010 Running head: Pentylenetetrazole mechanism in Down syndrome 1 Abstract Pentylenetetrazole (PTZ) has recently been found to ameliorate cognitive impairment in rodent models of Down syndrome (DS). The mechanism underlying PTZ’s therapeutic effect is however not clear. Microarray profiling has previously reported differential expression of genes in DS. No mammalian transcriptomic data on PTZ treatment however exists. Nevertheless, a Drosophila model inspired by rodent models of PTZ induced kindling plasticity has recently been described. Microarray profiling has shown PTZ’s downregulatory effect on gene expression in fly heads. In a comparative transcriptomics approach, I have analyzed the available microarray data in order to identify potential mechanism of PTZ action in DS. I find that transcriptomic correlates of chronic PTZ in Drosophila and DS counteract each other. A significant enrichment is observed between PTZ downregulated and DS upregulated genes, and a significant depletion between PTZ downregulated and DS dowwnregulated genes. Further, the common genes in PTZ Nature Precedings : hdl:10101/npre.2010.4330.1 Posted 5 Apr 2010 downregulated and DS upregulated sets show enrichment for MAP kinase pathway. My analysis suggests that downregulation of MAP kinase pathway may mediate therapeutic effect of PTZ in DS. Existing evidence implicating MAP kinase pathway in DS supports this observation.
    [Show full text]
  • Original Article Association Study of BUD13-ZNF259 Gene Rs964184 Polymorphism and Hemorrhagic Stroke Risk
    Int J Clin Exp Med 2015;8(12):22503-22508 www.ijcem.com /ISSN:1940-5901/IJCEM0016028 Original Article Association study of BUD13-ZNF259 gene rs964184 polymorphism and hemorrhagic stroke risk Shengjun Zhou, Jikuang Zhao, Zhepei Wang, Keqin Li, Sheng Nie, Feng Gao, Jie Sun, Xiang Gao, Yi Huang Department of Neurosurgery, Ningbo First Hospital, Ningbo Hospital of Zhejiang University, Ningbo 315010, Zhe- jiang, China Received September 11, 2015; Accepted December 3, 2015; Epub December 15, 2015; Published December 30, 2015 Abstract: We aimed to evaluate the association of rs964184 of BUD13-ZNF259 gene with the risk of hemorrhagic stroke (HS). A total of 138 HS cases and 587 controls were recruited for the association of rs964184 of BUD13- ZNF259 gene with the risk of HS. Tm shift PCR was used for genotyping. We were unable to find the association of rs964184 of BUD13-ZNF259 gene with the risk of HS (P>0.05). Significant difference was found in the TG level among the three genotypes (CC: 1.51±1.02; CG: 1.68±1.10; GG: 1.90±1.11, P=0.036). The TG level showed strong correlation with rs964184 genotypes (P=0.010, correlation=0.101). Significantly higher TC, HDL-C, and LDL-C levels were observed in the case group. And no difference was found in the TG, ApoA-I, ApoB. Our case-control study sup- ported the significant association between rs964184 genotype and the blood TG concentration, although we were unable to find association between BUD13-ZNF259 rs964184 and the risk of HS in Han Chinese.
    [Show full text]
  • ZNF259 Inhibits Non-Small Cell Lung Cancer Cells Proliferation and Invasion by FAK-AKT Signaling
    Journal name: Cancer Management and Research Article Designation: ORIGINAL RESEARCH Year: 2017 Volume: 9 Cancer Management and Research Dovepress Running head verso: Shan et al Running head recto: ZNF259 inhibits NSCLC proliferation and invasion open access to scientific and medical research DOI: http://dx.doi.org/10.2147/CMAR.S150614 Open Access Full Text Article ORIGINAL RESEARCH ZNF259 inhibits non-small cell lung cancer cells proliferation and invasion by FAK-AKT signaling Yuemei Shan1,2 Background: Zinc finger protein 259 (ZNF259) is known to play essential roles in embryonic Wei Cao1 development and cell cycle regulation. However, its expression pattern and clinicopathological Tao Wang1 relevance remain unclear. Guiyang Jiang3 Materials and methods: A total of 114 lung cancer specimens were collected. The ZNF259 Yong Zhang4 expression was measured between the lung cancer tissues and the adjacent normal lung tissues by immunohistochemical staining and Western blotting. Moreover, the correlation of ZNF259 Xianghong Yang1 expression with clinicopathological features was analyzed in 114 cases of lung cancer. Addition- 1 Department of Pathology, ally, ZNF259 was depleted in the lung cancer cells in order to analyze its effect in the lung cancer. Shengjing Hospital of China Medical University, Shenyang, China; Results: Immunohistochemical staining of 114 lung cancer specimens revealed significantly 2 For personal use only. Department of Applied Technology, lower ZNF259 expression in lung cancer tissues than in adjacent normal lung tissues (53.5% vs Institute of Technology of China 71.4%, P<0.001). In addition, ZNF259 downregulation was significantly associated with larger Medical University, Shenyang, China; 3Department of Pathology, First tumor size (P=0.001), advanced TNM stage (P=0.002), and positive lymph node metastasis Affiliated Hospital and College (P=0.02).
    [Show full text]
  • Download Special Issue
    BioMed Research International Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data Guest Editors: Julia Tzu-Ya Weng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data BioMed Research International Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data Guest Editors: Julia Tzu-Ya Weng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Copyright © 2014 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “BioMed Research International.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Contents Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data,JuliaTzu-YaWeng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Volume2014,ArticleID814092,3pages Evolution of Network Biomarkers from Early to Late Stage Bladder Cancer Samples,Yung-HaoWong, Cheng-Wei Li, and Bor-Sen Chen Volume 2014, Article ID 159078, 23 pages MicroRNA Expression Profiling Altered by Variant Dosage of Radiation Exposure,Kuei-FangLee, Yi-Cheng Chen, Paul Wei-Che Hsu, Ingrid Y. Liu, and Lawrence Shih-Hsin Wu Volume2014,ArticleID456323,10pages EXIA2: Web Server of Accurate and Rapid Protein Catalytic Residue Prediction, Chih-Hao Lu, Chin-Sheng
    [Show full text]
  • The Kinesin Spindle Protein Inhibitor Filanesib Enhances the Activity of Pomalidomide and Dexamethasone in Multiple Myeloma
    Plasma Cell Disorders SUPPLEMENTARY APPENDIX The kinesin spindle protein inhibitor filanesib enhances the activity of pomalidomide and dexamethasone in multiple myeloma Susana Hernández-García, 1 Laura San-Segundo, 1 Lorena González-Méndez, 1 Luis A. Corchete, 1 Irena Misiewicz- Krzeminska, 1,2 Montserrat Martín-Sánchez, 1 Ana-Alicia López-Iglesias, 1 Esperanza Macarena Algarín, 1 Pedro Mogollón, 1 Andrea Díaz-Tejedor, 1 Teresa Paíno, 1 Brian Tunquist, 3 María-Victoria Mateos, 1 Norma C Gutiérrez, 1 Elena Díaz- Rodriguez, 1 Mercedes Garayoa 1* and Enrique M Ocio 1* 1Centro Investigación del Cáncer-IBMCC (CSIC-USAL) and Hospital Universitario-IBSAL, Salamanca, Spain; 2National Medicines Insti - tute, Warsaw, Poland and 3Array BioPharma, Boulder, Colorado, USA *MG and EMO contributed equally to this work ©2017 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2017.168666 Received: March 13, 2017. Accepted: August 29, 2017. Pre-published: August 31, 2017. Correspondence: [email protected] MATERIAL AND METHODS Reagents and drugs. Filanesib (F) was provided by Array BioPharma Inc. (Boulder, CO, USA). Thalidomide (T), lenalidomide (L) and pomalidomide (P) were purchased from Selleckchem (Houston, TX, USA), dexamethasone (D) from Sigma-Aldrich (St Louis, MO, USA) and bortezomib from LC Laboratories (Woburn, MA, USA). Generic chemicals were acquired from Sigma Chemical Co., Roche Biochemicals (Mannheim, Germany), Merck & Co., Inc. (Darmstadt, Germany). MM cell lines, patient samples and cultures. Origin, authentication and in vitro growth conditions of human MM cell lines have already been characterized (17, 18). The study of drug activity in the presence of IL-6, IGF-1 or in co-culture with primary bone marrow mesenchymal stromal cells (BMSCs) or the human mesenchymal stromal cell line (hMSC–TERT) was performed as described previously (19, 20).
    [Show full text]
  • Supp Data.Pdf
    Supplementary Methods Verhaak sub-classification The Verhaak called tumor subtype was assigned as determined in the Verhaak et al. manuscript, for those TCGA tumors that were included at the time. TCGA data for expression (Affymetrix platform, level 1) and methylation (Infinium platform level 3) were downloaded from the TCGA portal on 09/29/2011. Affymetrix data were processed using R and Biocondutor with a RMA algorithm using quantile normalization and custom CDF. Level 3 methylation data has already been processed and converted to a beta-value. The genes that make up the signature for each of the 4 Verhaak groups (i.e. Proneural, Neural, Mesenchymal, and Classical) were downloaded. For each tumor, the averaged expression of the 4 genes signatures was calculated generating 4 ‘metagene’ scores, one for each subtype, (Colman et al.2010) for every tumor. Then each subtype metagene score was z-score corrected to allow comparison among the 4 metagenes. Finally, for each tumor the subtype with the highest metagene z-score among the four was used to assign subtype. Thus by this method, a tumor is assigned to the group to which it has the strongest expression signature. The shortcoming is that if a tumor has a ‘dual personality’ – for instance has strong expression of both classical and mesenchymal signature genes, there is some arbitrariness to the tumor’s assignment. Western Blot Analysis and cell fractionation Western blot analysis was performed using standard protocols. To determine protein expression we used the following antibodies: TAZ (Sigma and BD Biosciences), YAP (Santa Cruz Biotechnology), CD44 (Cell Signaling), FN1 (BD Biosciences), TEAD1, TEAD2, TEAD3, TEAD4 (Santa Cruz Biotechnology), MST1, p-MST1, MOB1, LATS1, LATS2, 14-3-3-, 1 ACTG2, (Cell Signaling), p-LATS1/2 (Abcam), Flag (Sigma Aldrich), Actin (Calbiochem), CAV2 (BD Biosciences), CTGF (Santa Cruz), RUNX2 (Sigma Aldrich), Cylin A, Cyclin E, Cyclin B1, p-cdk1, p-cdk4 (Cell Signaling Technologies).
    [Show full text]