DOCSLIB.ORG

Human Transcription Factor Protein-Protein Interactions in Health and Disease

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Human Transcription Factor Protein-Protein Interactions in Health and Disease HELKA GÖÖS GÖÖS HELKA Recent Publications in this Series 45/2019 Mgbeahuruike Eunice Ego Evaluation of the Medicinal Uses and Antimicrobial Activity of Piper guineense (Schumach & Thonn) 46/2019 Suvi Koskinen AND DISEASE IN HEALTH INTERACTIONS PROTEIN-PROTEIN FACTOR HUMAN TRANSCRIPTION Near-Occlusive Atherosclerotic Carotid Artery Disease: Study with Computed Tomography Angiography 47/2019 Flavia Fontana DISSERTATIONES SCHOLAE DOCTORALIS AD SANITATEM INVESTIGANDAM Biohybrid Cloaked Nanovaccines for Cancer Immunotherapy UNIVERSITATIS HELSINKIENSIS 48/2019 Marie Mennesson Kainate Receptor Auxiliary Subunits Neto1 and Neto2 in Anxiety and Fear-Related Behaviors 49/2019 Zehua Liu Porous Silicon-Based On-Demand Nanohybrids for Biomedical Applications 50/2019 Veer Singh Marwah Strategies to Improve Standardization and Robustness of Toxicogenomics Data Analysis HELKA GÖÖS 51/2019 Iryna Hlushchenko Actin Regulation in Dendritic Spines: From Synaptic Plasticity to Animal Behavior and Human HUMAN TRANSCRIPTION FACTOR PROTEIN-PROTEIN Neurodevelopmental Disorders 52/2019 Heini Liimatta INTERACTIONS IN HEALTH AND DISEASE Efectiveness of Preventive Home Visits among Community-Dwelling Older People 53/2019 Helena Karppinen Older People´s Views Related to Their End of Life: Will-to-Live, Wellbeing and Functioning 54/2019 Jenni Laitila Elucidating Nebulin Expression and Function in Health and Disease 55/2019 Katarzyna Ciuba Regulation of Contractile Actin Structures in Non-Muscle Cells 56/2019 Sami Blom Spatial Characterisation of Prostate Cancer by Multiplex Immunohistochemistry and Quantitative Image Analysis 57/2019 Outi Lyytinen Molecular Details of the Double-Stranded RNA Virus Replication and Assembly 58/2019 Markus Räsänen Vascular Endothelial Growth Factor-B and the Bmx Tyrosine Kinase in Cardiac Hypertrophy and Revascularization 59/2019 Vuokko Nummi Insights into Clinical and Laboratory Phenotypes of Von Willebrand Disease 60/2019 Shah Hasan Challenges of Hyper-Prolifcacy in the Pig: Colostrum and Gut Microbiota 61/2019 Sanna Matilainen Pathomechanisms of Leigh Syndrome: Defects of Post-Transcriptional and Post-Translational Regulation of Mitochondrial Metabolism 62/2019 Kirsi Santti Desmoid Tumor: Oncological Management and Prognostic Biomarkers INSTITUTE OF BIOTECHNOLOGY 63/2019 Hesham E. Abdolhfd Mohamed Evaluation of Prognostic Markers for Oropharyngeal Carcinoma Using Tissue Microarray HELSINKI INSTITUTE OF LIFE SCIENCE (HiLIFE) AND 64/2019 Johanna Uhari-Väänänen DEPARTMENT OF BIOSCIENCES Contributions of µ- and κ-Opioidergic Systems to Ethanol Intake and Addiction FACULTY OF BIOLOGICAL AND ENVIROMENTAL SCIENCES 65/2019 Susanna Rapo-Pylkkö DOCTORAL PROGRAMME IN BIOMEDICINE Chronic Pain and Neuropathic Pain among Community-dwelling Older Adults in Primary Health Care Settings UNIVERSITY OF HELSINKI 66/2019 Helsinki 2019 ISSN 2342-3161 ISBN 978-951-51-5480-4 Institute of Biotechnology Helsinki Institute of Life Science (HiLIFE), Faculty of Biological and Environmental Sciences University of Helsinki Helsinki, Finland Doctoral Programme in Biomedicine (DPBM) University of Helsinki Helsinki, Finland HUMAN TRANSCRIPTION FACTOR PROTEIN-PROTEIN INTERACTIONS IN HEALTH AND DISEASE Helka Göös ACADEMIC DISSERTATION To be presented, with the permission of the Faculty of Biological and Environmental Sciences of the University of Helsinki, for public examination in Auditorium 235 (Sali 2) at Infokeskus Korona, Viikinkaari 11, Helsinki, on 29th of November, 2019 at 12 o’clock. Helsinki 2019 Supervision Research Director Markku Varjosalo, Ph.D. Institute of Biotechnology Helsinki Institute of Life Science (HiLIFE) University of Helsinki, Helsinki, Finland Custodian, Thesis Committee member Thesis Committee member Professor Associate Professor Juha Partanen, Ph.D. Ville Hietakangas, Ph.D. Faculty of Biological and Environmental Faculty of Biological and Environmental Sciences Sciences University of Helsinki, University of Helsinki, Helsinki, Finland Helsinki, Finland Thesis Reviewers Professor Gonghong Wei, Ph.D Associate Professor Biocenter Oulu and Faculty of Mikael Björklund, Ph.D. Biochemistry and Molecular Medicine, ZJU-UoE INSTITUTE University of Oulu, Zhejiang University, Oulu, Finland Haining, China Opponent Faculty representative Professor Associate Professor Anna-Liisa Levonen, MD, Ph.D. Susanna Fagerholm A.I.Virtanen Institute for Molecular Sciences Department of Biosciences University of Eastern Finland Faculty of Biological and Environmental Kuopio, Finland Sciences University of Helsinki, Helsinki, Finland Dissertationes Scholae Doctoralis Ad Sanitatem Investigandam Universitatis Helsinkiensis ISBN 978-951-51-5480-4 (paperback.) ISBN 978-951-51-5481-1 (PDF) ISSN 2342-3161 (print) ISSN 2342-317X (online) http://ethesis.helsinki.fi Cover layout: Anita Tienhaara TABLE OF CONTENTS LIST OF ORIGINAL PUBLICATIONS ABBREVIATIONS TIIVISTELMÄ ABSTRACT I LITERATURE REVIEW .............................................................................................................. 1 1. Transcription factors (TFs) ...............................................................................................................1 1.2 TF structure and classification ..................................................................................................2 1.3 TF DNA binding ........................................................................................................................4 2. TF protein-protein interactions .......................................................................................................5 2.1 TF activity regulation by protein-protein interactions...............................................................5 2.1.1 Post-translational modifications in TF activity regulation .................................................................. 6 2.2 TF cooperativity and oligomerization .......................................................................................8 2.3 TF protein-protein interactions with the basal transcription machinery ................................. 10 2.3.1 TF protein-protein interactions with general transcription factors ................................................... 10 2.3.2 TF protein-protein interactions with the Mediator complex ............................................................. 11 2.4 TF protein-protein interactions with chromatin modulating proteins ..................................... 14 2.5 TF protein-protein interactions with RNA splicing machinery ................................................. 16 2.6 TF protein-protein interactions with nuclear acting and myosin signalling proteins ................ 17 2.7 TF protein-protein interactions in DNA repair ........................................................................ 17 2.8 TF protein-protein interactions in DNA replication ................................................................. 18 3. TFs in development and diseases .................................................................................................. 20 3.1 TFs in development ............................................................................................................... 20 3.2 TFs in diseases and disorders ................................................................................................. 20 3.2.1 TFs in cancer .................................................................................................................................. 21 3.2.2 TFs in neurological diseases ............................................................................................................ 22 3.2.3 TFs in diabetes ............................................................................................................................... 22 3.2.4 TFs in cardiac diseases .................................................................................................................... 23 3.3 Primary immunodeficiencies caused by TF mutations ............................................................ 23 3.3.1 NFKBs ............................................................................................................................................ 24 3.3.2 STATs ............................................................................................................................................. 25 3.3.3 CEBPE ............................................................................................................................................ 26 4. Methods for solving TF protein-protein interactions ..................................................................... 28 4.1 Affinity purification coupled to mass spectrometry ................................................................ 31 II STUDY AIMS ......................................................................................................................... 33 III MATERIAL AND METHODS ................................................................................................... 34 1. DNA constructs (I–III) .................................................................................................................... 34 1.1 Mutagenesis .......................................................................................................................... 34 2. Generation of cell lines (I–III) ........................................................................................................ 35 3. Affinity purification (I–III) .............................................................................................................
Load more

Recommended publications
  • In Vivo Studies Using the Classical Mouse Diversity Panel
    The Mouse Diversity Panel Predicts Clinical Drug Toxicity Risk Where Classical Models Fail Alison Harrill, Ph.D The Hamner-UNC Institute for Drug Safety Sciences 0 The Importance of Predicting Clinical Adverse Drug Reactions (ADR) Figure: Cath O’Driscoll Nature Publishing 2004 Risk ID PGx Testing 1 People Respond Differently to Drugs Pharmacogenetic Markers Identified by Genome-Wide Association Drug Adverse Drug Risk Allele Reaction (ADR) Abacavir Hypersensitivity HLA-B*5701 Flucloxacillin Hepatotoxicity Allopurinol Cutaneous ADR HLA-B*5801 Carbamazepine Stevens-Johnson HLA-B*1502 Syndrome Augmentin Hepatotoxicity DRB1*1501 Ximelagatran Hepatotoxicity DRB1*0701 Ticlopidine Hepatotoxicity HLA-A*3303 Average preclinical populations and human hepatocytes lack the diversity to detect incidence of adverse events that occur only in 1/10,000 people. Current Rodent Models of Risk Assessment The Challenge “At a time of extraordinary scientific progress, methods have hardly changed in several decades ([FDA] 2004)… Toxicologists face a major challenge in the twenty-first century. They need to embrace the new “omics” techniques and ensure that they are using the most appropriate animals if their discipline is to become a more effective tool in drug development.” -Dr. Michael Festing Quantitative geneticist Toxicol Pathol. 2010;38(5):681-90 Rodent Models as a Strategy for Hazard Characterization and Pharmacogenetics Genetically defined rodent models may provide ability to: 1. Improve preclinical prediction of drugs that carry a human safety risk 2.
    [Show full text]
  • 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]
  • 4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
    Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4).
    [Show full text]
  • Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
    Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7
    [Show full text]
  • Sureselect Community Design Glasgow Cancer Panels
    SureSelect Community Design Glasgow Cancer Panels Biomarkers with proven or emerging utility Genomics is a key element in precision medicine's potential to transform in predicting outcome and/or drug response/resistance - The clinical space oncology. Hybrid capture-based, targeted next-generation sequencing (NGS) represents a particularly promising technology as it enables the focused profiling of each of the many cancer-relevant loci. This approach allows for Ca rapid and cost-effective detection of most cancer-relevant genomic events, nc Cancer Core with the added advantage of FFPE tissue sample compatibility. er The Glasgow Precision Oncology Laboratory (GPOL) is a team of scientists Haem Cancer Plus with internationally recognized expertise in the technology, biology, and clinical utility of cancer genomics. Among their achievements is their detailed curation of genomic data to define the landscape of clinically and biologically significant genomic events in cancer. This includes not only a published literature review (see references 1-3), but also the International Cancer High confidence cancer genes, including those that are not currently clinically Genome Consortium (ICGC) and the Pan-Cancer Analysis of Whole Genomes actionable - The development space (PCAWG) study. Figure 1. Illustration of the GPOL cancer assay suite of panels that are commercially available as part of The GPOL has leveraged these insights to design the hybrid capture-based Agilent's Community Designs. We currently offer the SureSelect Community Design (CD) Cancer Core, Cancer SureSelect cancer NGS panels. With the SureSelect platform, the GPOL team Plus, and Cancer Haem panels. This figure illustrates the has developed a suite of affordable, fit-for-purpose cancer genomic assays relative size and content overlap of each panel.
    [Show full text]
  • The Role of EZH2 in the Induction and Maintenance of Acute Myeloid Leukaemia
    The Role of EZH2 in the Induction and Maintenance of Acute Myeloid Leukaemia Faisal Basheer Downing College University of Cambridge This dissertation is submitted for the degree of Doctor of Philosophy September 2017 Declaration The work presented in this dissertation was carried out under the supervision of Professor Brian Huntly from November 2013 to November 2016 in the Department of Haematology, University of Cambridge. This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except as declared in the Preface and specified in the text. It is not substantially the same as any that I have submitted, or, is being concurrently submitted for a degree or diploma or other qualification at the University of Cambridge or any other University or similar institution except as declared in the Preface and specified in the text. It does not exceed the prescribed word limit set by the Clinical Medicine and Clinical Veterinary Medicine Degree Committee. Faisal Basheer September 2017 i Acknowledgements First and foremost, I would like to thank my supervisor, Professor Brian Huntly, for providing me with the opportunity to work towards this thesis - for his help, encouragement and support over the last four years of my PhD. His dedicated high-level supervision, meticulous attention to detail and excellent direction throughout this time has undoubtedly helped me to maximise my potential in the lab throughout a highly interesting and rewarding project. I would also like to thank all of my colleagues and friends in the Huntly laboratory over the past four years - working together with all of you as a team has been an unforgettable and rewarding experience.
    [Show full text]
  • WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
    (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US).
    [Show full text]
  • Supporting Information
    Supporting Information Pouryahya et al. SI Text Table S1 presents genes with the highest absolute value of Ricci curvature. We expect these genes to have significant contribution to the network’s robustness. Notably, the top two genes are TP53 (tumor protein 53) and YWHAG gene. TP53, also known as p53, it is a well known tumor suppressor gene known as the "guardian of the genome“ given the essential role it plays in genetic stability and prevention of cancer formation (1, 2). Mutations in this gene play a role in all stages of malignant transformation including tumor initiation, promotion, aggressiveness, and metastasis (3). Mutations of this gene are present in more than 50% of human cancers, making it the most common genetic event in human cancer (4, 5). Namely, p53 mutations play roles in leukemia, breast cancer, CNS cancers, and lung cancers, among many others (6–9). The YWHAG gene encodes the 14-3-3 protein gamma, a member of the 14-3-3 family proteins which are involved in many biological processes including signal transduction regulation, cell cycle pro- gression, apoptosis, cell adhesion and migration (10, 11). Notably, increased expression of 14-3-3 family proteins, including protein gamma, have been observed in a number of human cancers including lung and colorectal cancers, among others, suggesting a potential role as tumor oncogenes (12, 13). Furthermore, there is evidence that loss Fig. S1. The histogram of scalar Ricci curvature of 8240 genes. Most of the genes have negative scalar Ricci curvature (75%). TP53 and YWHAG have notably low of p53 function may result in upregulation of 14-3-3γ in lung cancer Ricci curvatures.
    [Show full text]
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
    [Show full text]
  • 3-D Vascularized Breast Cancer Model to Study the Role of Osteoblast in Formation of a Pre-Metastatic Niche
    bioRxiv preprint doi: https://doi.org/10.1101/2021.05.05.442719; this version posted June 3, 2021. 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. 3-D Vascularized Breast Cancer Model to Study the Role of Osteoblast in Formation of a Pre-Metastatic Niche Rahul Rimal, Prachi Desai, Andrea Bonnin Marquez, Karina Sieg, Yvonne Marquardt, Smriti Singh* R. Rimal, P. Desai, A. B. Marquez, K. Sieg, Dr. S. Singh DWI - Leibniz Institute for Interactive Materials, Forkenbeckstrasse 50, 52074 Aachen, Germany [email protected] Y. Marquardt Department of Dermatology and Allergology, University Hospital, RWTH Aachen University, 52074 Aachen, Germany Dr. S. Singh Max-Planck-Institut für medizinische Forschung, Jahnstraße 29, 69120 Heidelberg, Germany Keywords: breast cancer, triple negative, tumor-microenvironment, pre-clinical, bone metastasis, blood vessels, scaffold-free models Abstract Breast cancer cells (BCCs) preferentially metastasize to bone. It is known that BCCs remotely primes the distant bone site prior to metastasis. However, the reciprocal influence of bone cells on the primary tumor is relatively overlooked. Here, to study the bone-tumor paracrine influence, a tri-cellular 3-D vascularized breast cancer tissue (VBCTs) model is engineered which comprised MDA-MB231, a triple-negative breast cancer cells (TNBC), fibroblasts, and endothelial cells. The VBCTs are indirectly co-cultured with osteoblasts (OBs), thereby constituting a complex quad-cellular tumor progression model. MDA-MB231 alone and in conjunction with OBs led to abnormal vasculature and reduced vessel density but enhanced VEGF production.
    [Show full text]
  • Directing an Artificial Zinc Finger Protein to New Targets by Fusion to a Non-DNA Binding Domain
    Directing an artificial zinc finger protein to new targets by fusion to a non-DNA binding domain Wooi Fang (Catheryn) Lim A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy School of Biotechnology and Biomolecular Sciences Faculty of Science March 2016 Page | 0 THESIS/ DISSERTATION SHEET Page | i ORIGINALITY STATEMENT ‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.’ WOOI FANG LIM Signed …………………………………………….............. 31-03-2016 Date …………………………………………….............. Page | i COPYRIGHT STATEMENT ‘I hereby grant the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation.
    [Show full text]
  • The Role of Inhibitors of Differentiation Proteins ID1 and ID3 in Breast Cancer Metastasis
    The role of Inhibitors of Differentiation proteins ID1 and ID3 in breast cancer metastasis Wee Siang Teo A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy St Vincent’s Clinical School, Faculty of Medicine The University of New South Wales Cancer Research Program The Garvan Institute of Medical Research Sydney, Australia March, 2014 THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet Surname or Family name: Teo First name: Wee Siang Abbreviation for degree as given in the University calendar: PhD (Medicine) School: St Vincent’s Clinical School Faculty: Faculty of Medicine Title: The role of Inhibitors of Differentiation proteins ID1 and ID3 in breast cancer metastasis Abstract 350 words maximum: (PLEASE TYPE) Breast cancer is a leading cause of cancer death in women. While locally-confined breast cancer is generally curable, the survival of patients with metastatic breast cancer is very poor. Treatment for metastatic breast cancer is palliative not curative due to the lack of targeted therapies. Metastasis is a complex process that still remains poorly understood, thus a detailed understanding of the biological complexity that underlies breast cancer metastasis is essential in reducing the lethality of this disease. The Inhibitor of Differentiation proteins 1 and 3 (ID1/3) are transcriptional regulators that control many cell fate and developmental processes and are often deregulated in cancer. ID1/3 are required and sufficient for the metastasis of breast cancer in experimental models. However, the mechanisms by which ID1/3 mediate metastasis in breast cancer remain to be determined. Little is known about pathways regulated by ID1/3 in breast cancer as well as their functional role in the multiple steps of metastatic progression.
    [Show full text]