Mir-29B/Sp1/FUT4 Axis Modulates the Malignancy of Leukemia Stem

Total Page:16

File Type:pdf, Size:1020Kb

Mir-29B/Sp1/FUT4 Axis Modulates the Malignancy of Leukemia Stem Liu et al. Journal of Experimental & Clinical Cancer Research (2019) 38:200 https://doi.org/10.1186/s13046-019-1179-y RESEARCH Open Access MiR-29b/Sp1/FUT4 axis modulates the malignancy of leukemia stem cells by regulating fucosylation via Wnt/β-catenin pathway in acute myeloid leukemia Bing Liu1†, Hongye Ma2†, Qianqian Liu1, Yang Xiao1, Shimeng Pan1, Huimin Zhou3 and Li Jia1* Abstract Background: Acute myeloid leukemia (AML) is initiated and maintained by a unique, small subset of leukemia stem cells (LSCs). LSCs are characterized by unrestricted self-renewal and contribute to the malignancy of leukemia. Aberrant protein fucosylation is associated with AML progression. However, it is still less understood that the miR-29b/Sp1/FUT4 crosstalk involved in the fucosylation-mediated LSCs malignancy in AML. Methods: AML cell lines were sorted by magnetic microbeads to obtain the CD34 + CD38- sub-population. The key biomarkers for LSCs were identified by flow cytometry. Fucosyltransferase genes were screened by qRT-PCR, and FUT4 was focused. Effect of FUT4 on LSCs malignancy was determined by CCK8 assay, sphere formation assay, immunofluorescence staining, apoptosis and in vivo xenografts experiments. The linkage of FUT4 promoter and Sp1 was confirmed by dual-luciferase reporter gene assay. ChIP-PCR assay was used to show the directly binding of Sp1 and FUT4 promoter. Activity of Wnt//β-catenin pathway was determined by western blot. Overall survival curves were diagrammed by Kaplan-Meier analysis. Results: Here, the expressional profiles of 11 fucosyltransferase genes were different comparing LSCs and non-LSCs of KG-1a and MOLM13 cells, whereas CD34 + CD38- cells exhibited higher expression of FUT4. Functionally, alteration of FUT4 in CD34 + CD38- cells modulated LSCs malignant behaviors both in vitro and in vivo. Transcriptional inhibitor actinomycin D (Act D) or translational inhibitor cycloheximide (CHX) prevented LSCs progression, and Sp1 was identified as the efficient regulator of FUT4 transcription. Moreover, miR-29b directly affected the binding of Sp1 and FUT4 promoter region, which further mediated LSCs proliferation, apoptosis and drug-resistance through fucosylated-CD44 via activation of Wnt/β-catenin pathway. Clinically, Sp1 and FUT4 were up-regulated and positively correlated with poor overall survival of AML patients. Conclusion: These data indicated that miR-29b/Sp1/FUT4 axis promoted the malignant behaviors of LSCs by regulating fucosylated CD44 via Wnt/β-catenin pathway. Identifying LSCs surface markers and targeting LSCs were important for the development of potential therapies in AML. Keywords: AML, LSCs, FUT4, Sp1, miR-29b, Wnt/β-catenin pathway * Correspondence: [email protected] †Bing Liu and Hongye Ma contributed equally to this work. 1College of Laboratory Medicine, Dalian Medical University, 9 Lushunnan Road Xiduan, Dalian 116044, Liaoning Province, China Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Liu et al. Journal of Experimental & Clinical Cancer Research (2019) 38:200 Page 2 of 14 Background transcription through binding to the 3′-UTR of target Acute myeloid leukemia (AML) is an aggressive malig- mRNA [14]. MiRNAs are also important regulators of nancy of the hematopoietic system, which is character- hematopoiesis, and altered miRNAs expression are ized by the clonal proliferation and differentiation into strongly associated with the pathogenesis of hematologic immature hematopoietic cells of dysfunctional myeloid malignancies [15]. Among the reported miRNAs, the precursors [1]. Despite progress made in the treatment lower expression of miR-34c-5p in LSCs is closely corre- of AML, most patients suffer relapses of the disease [2]. lated with the adverse prognosis and poor responses to AML is typically a stem cell-driven disease, and the ex- therapy of AML patients [16]. MiR-99 is highly istence of leukemia stem cells (LSCs) is first identified expressed in hematopoietic stem cells (HSCs) and LSCs, (CD34 + CD38-) by JE Dick in 1994 [3]. Accumulating and regulates self-renewal in both HSCs and LSCs of evidence shows that LSCs drive the initiation and per- AML [17]. Although several miRNAs have been re- petuation of AML, whereas show less sensitive to ported to regulate LSCs malignancy of AML, the specific chemotherapy. LSCs are major clinical factors in disease role of fucosylation that modulates LSCs malignancy of progression and relapse, and increasingly being used as AML by miR-29b directly targeting Sp1 to drive FUT4 is critical target for clinical therapeutic intervention [4, 5]. not well understood. LSCs also exhibit stem cell-like characteristics such as In the present study, the expression pattern of FUTs in the capacity for self-renewal, multi-potent differentiation LSCs was examined, and the increased level of FUT4 in potential and relative quiescence [6]. Therefore, it is im- LSCs was positively associated with AML malignancy. portant to target these malignant cells and investigate MiR-29b mediated Sp1 expression, which further facili- the intricate mechanisms to improve outcomes of AML tated FUT4 level in LSCs. Furthermore, the underlying patients. mechanism involved in miR-29b/Sp1/FUT4-regulated Glycosylation is arguably the most abundant and com- malignancy through CD44 fucosylation via Wnt/β-ca- plicated form of post-translational modification found in tenin pathway was explored in LSCs of AML. mammalian cells. Fucosylation is one of the most im- portant types of glycosylation in cancer. Aberrant fuco- Materials and methods sylation of proteins is a well-known hallmark of cancer Cell culture and clinical samples and represents a valuable source of cells interaction [7]. The AML cell lines, KG-1a was obtained from the ATCC All fucosylation reactions in cells are catalyzed by fuco- cell bank, while MOLM13 was purchased from the Ger- syltransferases (FUTs). So far, 13 different FUTs have man Collection of Microorganisms and Cell Culture been identified in the human genome, including FUT1 (DSMZ, Braunschweig, Germany). Cells were cultured in to 11, protein O-fucosyltransferase 1 (POFUT1), and RPMI 1640 medium (Gibco) supplemented with 10% fetal POFUT2 [8]. FUT4 cDNA isolated from the HL-60 cell bovine serum (Gibco) and 1% penicillin-streptomycin corresponds to myeloid type fucosyltransferase [9]. (Gibco) at 37 °C in air containing 5% CO2. Cells were sep- FUT4 mRNA was also highly expressed in both colon arated and enriched for CD34 + CD38- cells using mag- adenocarcinoma and myeloid cell lines [9, 10]. However, netic microbeads (MiltenyiBiotec, Auburn, CA, USA) and the exact molecular function of FUT4 during AML pro- labeled with CD34-FITC, CD38-PE, or isotype control gression and whether FUT4 could be a potential thera- antibodies. peutic target remains largely unknown. Peripheral blood mononuclear cells (PBMCs) were Specificity protein 1 (Sp1) is a sequence-specific collected from 50 newly diagnosed AML patients com- DNA-binding protein, which is involved in the activation prising 28 males and 22 females with age ranging from and regulation of cellular transcription. Thus, Sp1 is an 18 to 65 years (median age of 38.8 years). The samples essential transcription factor for many genes [11]. Ab- were obtained from the First Affiliated Hospital of Da- normal Sp1 expression and activation are considered to lian Medical University (Dalian, China) from Jan 2016 to promote human cancer initiation and progression, in- Feb 2018. Our work was approved by the Institutional cluding leukemia. Evidence demonstrates that Sp1 mod- Ethics Committee of the First Affiliated Hospital of ulates drug resistance of LSCs by regulating survivin Dalian Medical University (Ethics Reference NO: expression [12], and that Sp1 drives DHX15 expression YJ-KY-FB-2016-45). PBMCs of AML were obtained by in acute lymphoblastic leukemia [13]. Nevertheless, the Ficoll-Hypaque density gradient centrifugation (Sig- role of SP1 driving FUT4 transcription in AML LSCs ma-Aldrich) and were further cultured in plastic dishes has not been clarified yet. to remove adherent cells at 37 °C for 24 h. PBMCs cells In recent years, a number of studies on prognostic were purified for CD34 + CD38- cells using magnetic markers in AML have focused on microRNAs (miR- microbeads. The purity of enriched CD34 + CD38- was NAs), which lack protein-coding potential. MiRNAs are evaluated by staining with FITC-conjugated anti-CD34 approximately 22 nucleotides in length, which inhibit and CD38-PE. By adding B27 (1:50; Life Technologies, Liu et al. Journal of Experimental & Clinical Cancer Research (2019) 38:200 Page 3 of 14 Carlsbad, CA, USA), 10 ng/mL basic fibroblast growth Methylcellulose colony formation assay factor (bFGF) and 20 ng/mL epidermal growth factor The colony-forming capacity of LSCs (CD34 + CD38-) of (EGF), the CD34 + CD38- cells were maintained in KG-1a and MOLM13 cells were measured using methyl- DMEM/F12K medium.
Recommended publications
  • Deep Learning–Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer Kumardeep Chaudhary1, Olivier B
    Published OnlineFirst October 5, 2017; DOI: 10.1158/1078-0432.CCR-17-0853 Statistics in CCR Clinical Cancer Research Deep Learning–Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer Kumardeep Chaudhary1, Olivier B. Poirion1, Liangqun Lu1,2, and Lana X. Garmire1,2 Abstract Identifying robust survival subgroups of hepatocellular car- index (C-index) ¼ 0.68]. More aggressive subtype is associated cinoma (HCC) will significantly improve patient care. Current- with frequent TP53 inactivation mutations, higher expression ly, endeavor of integrating multi-omicsdatatoexplicitlypredict of stemness markers (KRT19 and EPCAM)andtumormarker HCC survival from multiple patient cohorts is lacking. To fill BIRC5, and activated Wnt and Akt signaling pathways. We this gap, we present a deep learning (DL)–based model on HCC validated this multi-omics model on five external datasets of that robustly differentiates survival subpopulations of patients various omics types: LIRI-JP cohort (n ¼ 230, C-index ¼ 0.75), in six cohorts. We built the DL-based, survival-sensitive model NCI cohort (n ¼ 221, C-index ¼ 0.67), Chinese cohort (n ¼ on 360 HCC patients' data using RNA sequencing (RNA-Seq), 166, C-index ¼ 0.69), E-TABM-36 cohort (n ¼ 40, C-index ¼ miRNA sequencing (miRNA-Seq), and methylation data from 0.77), and Hawaiian cohort (n ¼ 27, C-index ¼ 0.82). This TheCancerGenomeAtlas(TCGA),whichpredictsprognosis is the first study to employ DL to identify multi-omics features as good as an alternative model where genomics and clinical linked to the differential survival of patients with HCC. Given data are both considered. This DL-based model provides two its robustness over multiple cohorts, we expect this workflow to optimal subgroups of patients with significant survival differ- be useful at predicting HCC prognosis prediction.
    [Show full text]
  • Primary Antibodies Flyer
    Primary Antibodies Your choice of size and format Format Concentration Size CF® dye conjugates (13 colors) 0.1 mg/mL 100 or 500 uL Biotin, HRP or AP conjugates 0.1 mg/mL 100 or 500 uL R-PE, APC, or Per-CP conjugates 0.1 mg/mL 250 uL Purified, with BSA 0.1 mg/mL 100 or 500 uL Purified, BSA-free (Mix-n-Stain™ Ready) 1 mg/mL 50 uL Advantages Figure 1. IHC staining of human prostate Figure 2. Flow cytometry analysis of U937 • More than 1000 monoclonal antibodies carcinoma with anti-ODC1 clone cells with anti-CD31/PECAM clone C31.7, • Growing selection of monoclonal rabbit ODC1/485. CF647 conjugate (blue) or isotype control (orange). antibodies • Validated in IHC and other applications Your choice of 13 bright and photostable CF® dyes • Choose from 13 bright and stable CF® dyes CF® dye Ex/Em (nm) Features • Also available with R-PE, APC, PerCP, HRP, AP, CF®405S 404/431 • Better fit for the 450/50 flow cytometer channel than Alexa Fluor® 405 or biotin CF®405M 408/452 • More photostable than Pacific Blue®, with less green spill-over • Purified antibodies available BSA-free, 1 mg/mL, • Compatible with super-resolution imaging by SIM ready to use for Mix-n-Stain™ labeling or other CF®488A 490/515 • Less non-specific binding and spill-over than Alexa Fluor® 488 conjugation • Very photostable and pH-insensitive • Compatible with super-resolution imaging by TIRF • Offered in affordable 100 uL size CF®543 541/560 • Brighter than Alexa Fluor® 546 CF®555 555/565 • Brighter than Cy®3 • Validated in multicolor super-resolution imaging by STORM CF®568
    [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]
  • WO 2007/056812 Al
    (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (43) International Publication Date (10) International Publication Number 24 May 2007 (24.05.2007) PCT WO 2007/056812 Al (51) International Patent Classification: Victoria 3941 (AU). WHITTAKER, Jason, S. [AU/AU]; C07K 14/54 (2006.01) C07H 21/04 (2006.01) 24 Maddison Street, Redfern East, New South Wales A61K 38/19 (2006.01) C07K 14/52 (2006.01) 2016 (AU). DOMAGALA, Teresa, A. [AU/AU]; 14/30 A61K 38/20 (2006.01) C07K 14/61 (2006.01) Garden Street, Alexandria, New South Wales 2015 (AU). A61K 38/27 (2006.01) C07K 14/715 (2006.01) SIMPSON, Raina, J. [AU/AU]; 10 Snowgum Street, A61P 7/00 (2006.01) C07 /4/72 (2006.01) Acacia Gardens, New South Wales 2763 (AU). A61P 35/00 (2006.01) C07K 19/00 (2006.01) A61P 37/00 (2006.01) GOlN 33/543 (2006.01) (74) Agents: HUGHES, John, E., L. et al.; DAVIES COLLI- C07H 21/02 (2006.01) SON CAVE, 1Nicholson Street, Melbourne, Victoria 3000 (AU). (21) International Application Number: PCT/AU2006/001718 (81) Designated States (unless otherwise indicated, for every kind of national protection available): AE, AG, AL, AM, (22) International Filing Date: AT,AU, AZ, BA, BB, BG, BR, BW, BY, BZ, CA, CH, CN, 16 November 2006 (16.1 1.2006) CO, CR, CU, CZ, DE, DK, DM, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IS, (25) Filing Language: English JP, KE, KG, KM, KN, KP, KR, KZ, LA, LC, LK, LR, LS, LT, LU, LV,LY,MA, MD, MG, MK, MN, MW, MX, MY, (26)
    [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]
  • Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
    Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A.
    [Show full text]
  • CDG and Immune Response: from Bedside to Bench and Back Authors
    CDG and immune response: From bedside to bench and back 1,2,3 1,2,3,* 2,3 1,2 Authors: Carlota Pascoal , Rita Francisco , Tiago Ferro , Vanessa dos Reis Ferreira , Jaak Jaeken2,4, Paula A. Videira1,2,3 *The authors equally contributed to this work. 1 Portuguese Association for CDG, Lisboa, Portugal 2 CDG & Allies – Professionals and Patient Associations International Network (CDG & Allies – PPAIN), Caparica, Portugal 3 UCIBIO, Departamento Ciências da Vida, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal 4 Center for Metabolic Diseases, UZ and KU Leuven, Leuven, Belgium Word count: 7478 Number of figures: 2 Number of tables: 3 This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/jimd.12126 This article is protected by copyright. All rights reserved. Abstract Glycosylation is an essential biological process that adds structural and functional diversity to cells and molecules, participating in physiological processes such as immunity. The immune response is driven and modulated by protein-attached glycans that mediate cell-cell interactions, pathogen recognition and cell activation. Therefore, abnormal glycosylation can be associated with deranged immune responses. Within human diseases presenting immunological defects are Congenital Disorders of Glycosylation (CDG), a family of around 130 rare and complex genetic diseases. In this review, we have identified 23 CDG with immunological involvement, characterised by an increased propensity to – often life-threatening – infection.
    [Show full text]
  • ©Ferrata Storti Foundation
    Original Articles T-cell/histiocyte-rich large B-cell lymphoma shows transcriptional features suggestive of a tolerogenic host immune response Peter Van Loo,1,2,3 Thomas Tousseyn,4 Vera Vanhentenrijk,4 Daan Dierickx,5 Agnieszka Malecka,6 Isabelle Vanden Bempt,4 Gregor Verhoef,5 Jan Delabie,6 Peter Marynen,1,2 Patrick Matthys,7 and Chris De Wolf-Peeters4 1Department of Molecular and Developmental Genetics, VIB, Leuven, Belgium; 2Department of Human Genetics, K.U.Leuven, Leuven, Belgium; 3Bioinformatics Group, Department of Electrical Engineering, K.U.Leuven, Leuven, Belgium; 4Department of Pathology, University Hospitals K.U.Leuven, Leuven, Belgium; 5Department of Hematology, University Hospitals K.U.Leuven, Leuven, Belgium; 6Department of Pathology, The Norwegian Radium Hospital, University of Oslo, Oslo, Norway, and 7Department of Microbiology and Immunology, Rega Institute for Medical Research, K.U.Leuven, Leuven, Belgium Citation: Van Loo P, Tousseyn T, Vanhentenrijk V, Dierickx D, Malecka A, Vanden Bempt I, Verhoef G, Delabie J, Marynen P, Matthys P, and De Wolf-Peeters C. T-cell/histiocyte-rich large B-cell lymphoma shows transcriptional features suggestive of a tolero- genic host immune response. Haematologica. 2010;95:440-448. doi:10.3324/haematol.2009.009647 The Online Supplementary Tables S1-5 are in separate PDF files Supplementary Design and Methods One microgram of total RNA was reverse transcribed using random primers and SuperScript II (Invitrogen, Merelbeke, Validation of microarray results by real-time quantitative Belgium), as recommended by the manufacturer. Relative reverse transcriptase polymerase chain reaction quantification was subsequently performed using the compar- Ten genes measured by microarray gene expression profil- ative CT method (see User Bulletin #2: Relative Quantitation ing were validated by real-time quantitative reverse transcrip- of Gene Expression, Applied Biosystems).
    [Show full text]
  • Function Study of Arabidopsis Thaliana Core Alpha1,3-Fucosyltransferase (Fucta) Peter Both
    Structure – function study of Arabidopsis thaliana core alpha1,3-fucosyltransferase (FucTA) Peter Both To cite this version: Peter Both. Structure – function study of Arabidopsis thaliana core alpha1,3-fucosyltransferase (FucTA). Biomolecules [q-bio.BM]. Université Joseph-Fourier - Grenoble I, 2009. English. tel- 00449431 HAL Id: tel-00449431 https://tel.archives-ouvertes.fr/tel-00449431 Submitted on 21 Jan 2010 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. UNIVERSITE JOSEPH FOURIER (GRENOBLE I ) ECOLE DOCTORALE CHIMIE ET SCIENCES DU VIVANT UNIVERSITE SLOVAQUE DE TECHNOLOGIE DE BRATISLAVA (STUBA) THESE Pour l’obtention du Diplôme de DOCTEUR DE L’UNIVERSITE JOSEPH FOURIER Discipline: Biologie Présentée et soutenue publiquement le 29 octobre 2009 par PETER BOTH ETUDE STRUCTURE-FUNCTION D’UNE FUCOSYLTRANSFERASE (FUCT-A) DE ARABIDOPSIS THALIANA JURY Rapporteurs : Prof. Abderrahman MAFTAH, Université de Limoges Dr Eva HOSTINOVA, Slovak Academy of Sciences, Bratislava Examinateurs : Dr Eva KUTEJOVA, Slovak Academy of Sciences, Bratislava Dr Serge PEREZ, ESRF, Grenoble Dr Jan MUCHA, Slovak Academy of Sciences, Bratislava Prof. Christelle BRETON, Université Grenoble I Thèse préparée au CERMAV (Grenoble) et ICHSAS (Bratislava) 1 I would like to express my gratitude to all those who gave me the possibility to complete this thesis.
    [Show full text]
  • PP1-Associated Signaling and − B/AP-1 Κ Inhibition of NF- Tolerance
    Downloaded from http://www.jimmunol.org/ by guest on October 3, 2021 is online at: average * and − B/AP-1 κ The Journal of Immunology published online 26 February 2014 from submission to initial decision 4 weeks from acceptance to publication http://www.jimmunol.org/content/early/2014/02/26/jimmun ol.1301610 Identification of Two Forms of TNF Tolerance in Human Monocytes: Differential Inhibition of NF- PP1-Associated Signaling Johannes Günther, Nico Vogt, Katharina Hampel, Rolf Bikker, Sharon Page, Benjamin Müller, Judith Kandemir, Michael Kracht, Oliver Dittrich-Breiholz, René Huber and Korbinian Brand J Immunol Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2014/02/26/jimmunol.130161 0.DCSupplemental Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2014 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of October 3, 2021. Published February 26, 2014, doi:10.4049/jimmunol.1301610 The Journal of Immunology Identification of Two Forms of TNF Tolerance in Human Monocytes: Differential Inhibition of NF-kB/AP-1– and PP1-Associated Signaling Johannes Gunther,*€ ,1 Nico Vogt,*,1 Katharina Hampel,*,1 Rolf Bikker,* Sharon Page,* Benjamin Muller,*€ Judith Kandemir,* Michael Kracht,† Oliver Dittrich-Breiholz,‡ Rene´ Huber,* and Korbinian Brand* The molecular basis of TNF tolerance is poorly understood.
    [Show full text]
  • Transcriptome Profiling Reveals the Complexity of Pirfenidone Effects in IPF
    ERJ Express. Published on August 30, 2018 as doi: 10.1183/13993003.00564-2018 Early View Original article Transcriptome profiling reveals the complexity of pirfenidone effects in IPF Grazyna Kwapiszewska, Anna Gungl, Jochen Wilhelm, Leigh M. Marsh, Helene Thekkekara Puthenparampil, Katharina Sinn, Miroslava Didiasova, Walter Klepetko, Djuro Kosanovic, Ralph T. Schermuly, Lukasz Wujak, Benjamin Weiss, Liliana Schaefer, Marc Schneider, Michael Kreuter, Andrea Olschewski, Werner Seeger, Horst Olschewski, Malgorzata Wygrecka Please cite this article as: Kwapiszewska G, Gungl A, Wilhelm J, et al. Transcriptome profiling reveals the complexity of pirfenidone effects in IPF. Eur Respir J 2018; in press (https://doi.org/10.1183/13993003.00564-2018). This manuscript has recently been accepted for publication in the European Respiratory Journal. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Copyright ©ERS 2018 Copyright 2018 by the European Respiratory Society. Transcriptome profiling reveals the complexity of pirfenidone effects in IPF Grazyna Kwapiszewska1,2, Anna Gungl2, Jochen Wilhelm3†, Leigh M. Marsh1, Helene Thekkekara Puthenparampil1, Katharina Sinn4, Miroslava Didiasova5, Walter Klepetko4, Djuro Kosanovic3, Ralph T. Schermuly3†, Lukasz Wujak5, Benjamin Weiss6, Liliana Schaefer7, Marc Schneider8†, Michael Kreuter8†, Andrea Olschewski1,
    [Show full text]
  • Supplemental Figures 04 12 2017
    Jung et al. 1 SUPPLEMENTAL FIGURES 2 3 Supplemental Figure 1. Clinical relevance of natural product methyltransferases (NPMTs) in brain disorders. (A) 4 Table summarizing characteristics of 11 NPMTs using data derived from the TCGA GBM and Rembrandt datasets for 5 relative expression levels and survival. In addition, published studies of the 11 NPMTs are summarized. (B) The 1 Jung et al. 6 expression levels of 10 NPMTs in glioblastoma versus non‐tumor brain are displayed in a heatmap, ranked by 7 significance and expression levels. *, p<0.05; **, p<0.01; ***, p<0.001. 8 2 Jung et al. 9 10 Supplemental Figure 2. Anatomical distribution of methyltransferase and metabolic signatures within 11 glioblastomas. The Ivy GAP dataset was downloaded and interrogated by histological structure for NNMT, NAMPT, 12 DNMT mRNA expression and selected gene expression signatures. The results are displayed on a heatmap. The 13 sample size of each histological region as indicated on the figure. 14 3 Jung et al. 15 16 Supplemental Figure 3. Altered expression of nicotinamide and nicotinate metabolism‐related enzymes in 17 glioblastoma. (A) Heatmap (fold change of expression) of whole 25 enzymes in the KEGG nicotinate and 18 nicotinamide metabolism gene set were analyzed in indicated glioblastoma expression datasets with Oncomine. 4 Jung et al. 19 Color bar intensity indicates percentile of fold change in glioblastoma relative to normal brain. (B) Nicotinamide and 20 nicotinate and methionine salvage pathways are displayed with the relative expression levels in glioblastoma 21 specimens in the TCGA GBM dataset indicated. 22 5 Jung et al. 23 24 Supplementary Figure 4.
    [Show full text]