DOCSLIB.ORG

Identification of Tgfβ-Related Genes Regulated in Murine Osteoarthritis and Chondrocyte Hypertrophy by Comparison of Multiple Microarray Datasets

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Identification of Tgfβ-Related Genes Regulated in Murine Osteoarthritis and Chondrocyte Hypertrophy by Comparison of Multiple Microarray Datasets http://hdl.handle.net/1765/109466 Identification of TGFβ-related genes regulated in murine osteoarthritis and chondrocyte hypertrophy by comparison of multiple microarray datasets Laurie M.G. de Kroon1,2,&, Guus G.H. van den Akker1,&, Bent Brachvogel3,4, Roberto Narcisi2, Daniele Belluoccio5, Florien Jenner6, John F. Bateman5, Christopher B. Little7, Pieter Brama8, Esmeralda N. Blaney Davidson1, Peter M. van der Kraan1, Gerjo J.V.M. van Osch2,9* 1Department of Rheumatology, Experimental Rheumatology, Radboud University Medical Center, Nijmegen, the Netherlands 2Department of Orthopedics, Erasmus MC University Medical Center, Rotterdam, the Netherlands 3Center for Biochemistry, Medical Faculty, University of Cologne, Cologne, Germany 4Department of Pediatrics and Adolescent Medicine, Experimental Neonatology, Medical Faculty, University of Cologne, Cologne, Germany 5Murdoch Childrens Research Institute, Royal Children’s Hospital, Parkville, Victoria, Australia 6Equine University Hospital, University of Veterinary Medicine, Vienna, Austria 7Raymond Purves Bone and Joint Research Laboratories, Kolling Institute of Medical Research, University of Sydney, St Leonards, New South Wales, Australia 8Veterinary Clinical Sciences, School of Veterinary Medicine, University College Dublin, Dublin, Ireland 9Department of Otorhinolaryngology, Erasmus MC University Medical Center, Rotterdam, the Netherlands &Both authors contributed equally *Corresponding author: Gerjo van Osch ([email protected]) Address for correspondence: Erasmus MC, Departments of Orthopedics and Otorhinolaryngology, Room Ee1655, Wytemaweg 80, 3015 CN Rotterdam, the Netherlands. Tel: +31-107043661. 2 Erasmus Medical Center Rotterdam █ AbsTrAcT Objective: Osteoarthritis (OA) is a joint disease characterized by progressive degen- eration of articular cartilage. Some features of OA, including chondrocyte hyper- trophy and focal calcification of articular cartilage, resemble the endochondral ossification processes. Alterations in transforming growth factorβ (TGFβ) signaling have been associated with OA as well as with chondrocyte hypertrophy. Our aim was to identify novel candidate genes implicated in chondrocyte hypertrophy during OA pathogenesis by determining which TGFβ-related genes are regulated during murine OA and endochondral ossification. Methods: A list of 580 TGFβ-related genes, including TGFβ signaling pathway com- ponents and TGFβ-target genes, was generated. Regulation of these TGFβ-related genes was assessed in a microarray of murine OA cartilage: 1, 2 and 6 weeks after destabilization of the medial meniscus (DMM). Subsequently, genes regulated in the DMM model were studied in two independent murine microarray datasets on endochondral ossification: the growth plate and transient embryonic cartilage (joint development). results: A total of 106 TGFβ-related genes were differentially expressed in articular cartilage of DMM-operated mice compared to sham-control. From these genes, 43 were similarly regulated during chondrocyte hypertrophy in the growth plate or embryonic joint development. Among these 43 genes, 18 genes have already been associated with OA. The remaining 25 genes were considered as novel candidate genes involved in OA pathogenesis and endochondral ossification. In supplemen- tary data of published human OA microarrays we found indications that 15 of the 25 novel genes are indeed regulated in articular cartilage of human OA patients. conclusion: By focusing on TGFβ-related genes during OA and chondrocyte hyper- trophy in mice, we identified 18 known and 25 new candidate genes potentially implicated in phenotypical changes in chondrocytes leading to OA. We propose that 15 of these candidates warrant further investigation as therapeutic target for OA as they are also regulated in articular cartilage of OA patients. Keywords: osteoarthritis, TGFβ, chondrocyte hypertrophy, microarray TGFβ genes regulated during hypertrophy and OA 3 █ 1. InTrOduction Osteoarthritis (OA) is characterized by degeneration of articular cartilage and the clinical symptoms are joint pain and functional impairment [1, 2]. The chondro- cytes in articular cartilage of OA patients exhibit phenotypic changes that resemble hypertrophic differentiation of chondrocytes during endochondral ossification in the postnatal growth plate [3-8] and in embryonic joint development [9-11]. Since articular cartilage has limited repair capacity, it is essential to prevent cartilage degeneration at an early stage. To accomplish this, the pathogenic mechanisms initiating OA require further elucidation. The transforming growth factor-β (TGFβ) signaling pathway has been impli- cated in OA pathogenesis and in hypertrophic differentiation of chondrocytes [12- 15]. Polymorphisms in TGFB1 and SMAD3, a signaling molecule that is activated by binding of TGFβ to its receptor, have been associated with multiple joint patholo- gies in OA [16-20] and mutations in SMAD3 lead to early-onset of OA in multiple articular joints in humans [21, 22]. We have shown previously that protein expres- sion of Tgfb3 and phosphorylated Smad2 is reduced in two murine models for OA [23]. In mice, deficiency of Smad3, Tgfbr2 or overexpression of a truncated kinase- defective Tgfbr2, result in a degenerative joint disease resembling human OA [24, 25]. Importantly, a decrease in Tgfbr1 in murine and human articular chondrocytes correlates with OA development and elevated expression of markers for chondro- cyte hypertrophy [26]. Aside from its involvement in OA, TGFβ signaling plays a crucial role in maintenance of articular cartilage under normal physiological con- ditions and skeletal development [27, 28]. Chondrocyte-specific deletion of Tgfbr2, Tgfbr1, Smad3 or Smad4 accelerates hypertrophic differentiation of chondrocytes in the growth plate and articular cartilage [29-35]. Moreover, Tgfb2 knockout mice display severe abnormalities in bone formed by endochondral ossification [36]. Together these data indicate that TGFβ is crucial for maintenance of the articular (pre-hypertrophic) chondrocyte phenotype and that alterations in TGFβ signaling lead to chondrocyte hypertrophy and predispose to OA. It is currently not precisely known which aspects of TGFβ signaling are associ- ated with chondrocyte homeostasis, hypertrophy or OA development and whether there is overlap. A second question is whether phenotypic changes of articular chondrocytes in OA show similarity to chondrocyte hypertrophy in normal devel- opmental processes (transient growth plate cartilage, joint development). For the identification of molecular targets that may be involved in early onset and pro- gression of OA, microarray analyses have been performed on murine models for OA (early onset, trauma-induced) rather than on human OA cartilage (end-stage disease) [37-40]. One of the most recent studies in the murine OA model compared multiple independent micro-array experiments and identified the TGFβ pathway 4 Erasmus Medical Center Rotterdam as common denominator [39]. Due to the divergent effects of TGFβ signalling in articular cartilage homeostasis and disease, we hypothesized that defining the regulation of genes involved in, or regulated by, the TGFβ signaling pathway in early OA and endochondral ossification would result in the identification of novel targets implicated in phenotypic changes of chondrocytes in OA pathogenesis. In this study, we first generated a list of TGFβ-related genes, which included genes encoding components of the TGFβ signaling pathway (from the Kyoto Encyclopedia of Genes and Genomes; KEGG) [41] and genes shown to be regulated by TGFβ (i.e. TGFβ-target genes) in cartilaginous cells by microarray analyses [42-44]. Secondly, we determined which of these TGFβ-related genes are regulated in a murine model for early OA as well as during endochondral ossification in murine growth plates and/or embryonic joint development using available microarray datasets [11, 37, 45]. Finally, genes identified by this approach were further explored in the litera- ture to evaluate whether we identified genes known to be involved in murine and human OA pathology and to determine which genes might be novel candidates implicated in hypertrophic differentiation of articular chondrocytes during OA pathogenesis. █ 2. MeThOds 2.1 List of TGFβ-related genes A list of genes related to TGFβ signaling was compiled by including murine genes of the TGFβ signaling pathway derived from the KEGG database [41] and genes shown to be regulated by TGFβ in four published microarray experiments: 1x in vivo and 3x in vitro [42-44]. Takahashi et al. analyzed gene expression (Murine Genome Array U74Av2; Affymetrix) in unstimulated and TGFβ1-stimulated (10 ng/mL for 9 hours) chondrocytes from the H4 murine cell line [42, 46]. Sohn et al. performed microarray analysis (GeneChip Mouse Genome 430 2.0 Array; Affymetrix) on murine embryonic (E11.5) sclerotome cells cultured in micromass in absence or presence of TGFβ1 (5 ng/mL for 8 hours), and on vertebra isolated from wild-type and Tgbr2 knock-out mice [43]. Ramaswamy et al. evaluated gene expression (GeneChip Bovine Genome Array; Affymetrix) in micromass cultures of chondrocytes (isolated from articular cartilage of 3 cows) that were cultured in absence or presence of TGFβ1 (5 ng/mL for 8 hours) [44]. For the latter study, bovine gene probes (Affymetrix) were translated to mouse orthologs. After merging the results of the three published microarray studies [42-44], one list of 501 unique genes regulated by TGFβ (up and down)
Load more

Recommended publications
  • Propranolol-Mediated Attenuation of MMP-9 Excretion in Infants with Hemangiomas
    Supplementary Online Content Thaivalappil S, Bauman N, Saieg A, Movius E, Brown KJ, Preciado D. Propranolol-mediated attenuation of MMP-9 excretion in infants with hemangiomas. JAMA Otolaryngol Head Neck Surg. doi:10.1001/jamaoto.2013.4773 eTable. List of All of the Proteins Identified by Proteomics This supplementary material has been provided by the authors to give readers additional information about their work. © 2013 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/01/2021 eTable. List of All of the Proteins Identified by Proteomics Protein Name Prop 12 mo/4 Pred 12 mo/4 Δ Prop to Pred mo mo Myeloperoxidase OS=Homo sapiens GN=MPO 26.00 143.00 ‐117.00 Lactotransferrin OS=Homo sapiens GN=LTF 114.00 205.50 ‐91.50 Matrix metalloproteinase‐9 OS=Homo sapiens GN=MMP9 5.00 36.00 ‐31.00 Neutrophil elastase OS=Homo sapiens GN=ELANE 24.00 48.00 ‐24.00 Bleomycin hydrolase OS=Homo sapiens GN=BLMH 3.00 25.00 ‐22.00 CAP7_HUMAN Azurocidin OS=Homo sapiens GN=AZU1 PE=1 SV=3 4.00 26.00 ‐22.00 S10A8_HUMAN Protein S100‐A8 OS=Homo sapiens GN=S100A8 PE=1 14.67 30.50 ‐15.83 SV=1 IL1F9_HUMAN Interleukin‐1 family member 9 OS=Homo sapiens 1.00 15.00 ‐14.00 GN=IL1F9 PE=1 SV=1 MUC5B_HUMAN Mucin‐5B OS=Homo sapiens GN=MUC5B PE=1 SV=3 2.00 14.00 ‐12.00 MUC4_HUMAN Mucin‐4 OS=Homo sapiens GN=MUC4 PE=1 SV=3 1.00 12.00 ‐11.00 HRG_HUMAN Histidine‐rich glycoprotein OS=Homo sapiens GN=HRG 1.00 12.00 ‐11.00 PE=1 SV=1 TKT_HUMAN Transketolase OS=Homo sapiens GN=TKT PE=1 SV=3 17.00 28.00 ‐11.00 CATG_HUMAN Cathepsin G OS=Homo
    [Show full text]
  • A Cell Line P53 Mutation Type UM
    A Cell line p53 mutation Type UM-SCC 1 wt UM-SCC5 Exon 5, 157 GTC --> TTC Missense mutation by transversion (Valine --> Phenylalanine UM-SCC6 wt UM-SCC9 wt UM-SCC11A wt UM-SCC11B Exon 7, 242 TGC --> TCC Missense mutation by transversion (Cysteine --> Serine) UM-SCC22A Exon 6, 220 TAT --> TGT Missense mutation by transition (Tyrosine --> Cysteine) UM-SCC22B Exon 6, 220 TAT --> TGT Missense mutation by transition (Tyrosine --> Cysteine) UM-SCC38 Exon 5, 132 AAG --> AAT Missense mutation by transversion (Lysine --> Asparagine) UM-SCC46 Exon 8, 278 CCT --> CGT Missense mutation by transversion (Proline --> Alanine) B 1 Supplementary Methods Cell Lines and Cell Culture A panel of ten established HNSCC cell lines from the University of Michigan series (UM-SCC) was obtained from Dr. T. E. Carey at the University of Michigan, Ann Arbor, MI. The UM-SCC cell lines were derived from eight patients with SCC of the upper aerodigestive tract (supplemental Table 1). Patient age at tumor diagnosis ranged from 37 to 72 years. The cell lines selected were obtained from patients with stage I-IV tumors, distributed among oral, pharyngeal and laryngeal sites. All the patients had aggressive disease, with early recurrence and death within two years of therapy. Cell lines established from single isolates of a patient specimen are designated by a numeric designation, and where isolates from two time points or anatomical sites were obtained, the designation includes an alphabetical suffix (i.e., "A" or "B"). The cell lines were maintained in Eagle's minimal essential media supplemented with 10% fetal bovine serum and penicillin/streptomycin.
    [Show full text]
  • Steroid-Dependent Regulation of the Oviduct: a Cross-Species Transcriptomal Analysis
    University of Kentucky UKnowledge Theses and Dissertations--Animal and Food Sciences Animal and Food Sciences 2015 Steroid-dependent regulation of the oviduct: A cross-species transcriptomal analysis Katheryn L. Cerny University of Kentucky, [email protected] Right click to open a feedback form in a new tab to let us know how this document benefits ou.y Recommended Citation Cerny, Katheryn L., "Steroid-dependent regulation of the oviduct: A cross-species transcriptomal analysis" (2015). Theses and Dissertations--Animal and Food Sciences. 49. https://uknowledge.uky.edu/animalsci_etds/49 This Doctoral Dissertation is brought to you for free and open access by the Animal and Food Sciences at UKnowledge. It has been accepted for inclusion in Theses and Dissertations--Animal and Food Sciences by an authorized administrator of UKnowledge. For more information, please contact [email protected]. STUDENT AGREEMENT: I represent that my thesis or dissertation and abstract are my original work. Proper attribution has been given to all outside sources. I understand that I am solely responsible for obtaining any needed copyright permissions. I have obtained needed written permission statement(s) from the owner(s) of each third-party copyrighted matter to be included in my work, allowing electronic distribution (if such use is not permitted by the fair use doctrine) which will be submitted to UKnowledge as Additional File. I hereby grant to The University of Kentucky and its agents the irrevocable, non-exclusive, and royalty-free license to archive and make accessible my work in whole or in part in all forms of media, now or hereafter known.
    [Show full text]
  • And Single-Cell RNA-Sequencing to Define the Chondrocyte Gene Expression Signature in the Murine Knee Joint
    bioRxiv preprint doi: https://doi.org/10.1101/2020.06.13.148056; this version posted June 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Full Title: Combining segmental bulk- and single-cell RNA-sequencing to define the chondrocyte gene expression signature in the murine knee joint Authors: Vikram Sunkara1,2 #, Gitta A. Heinz3, Frederik F. Heinrich3, Pawel Durek3, Ali Mobasheri4,5,6,7, Mir-Farzin Mashreghi3,8,9*, Annemarie Lang3,10 * # *These authors contributed equally. #Corresponding authors Affiliations 1Zuse Institute Berlin, Germany 2Department of Mathematics and Computer Science, Freie Universität Berlin, Germany 3German Rheumatism Research Centre (DRFZ) Berlin, a Leibniz Institute, Berlin, Germany 4Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland 5Department of Regenerative Medicine, State Research Institute, Centre for Innovative Medicine, Vilnius, Lithuania 6University Medical Center Utrecht, Departments of Orthopedics, Rheumatology and Clinical Immunology, Utrecht, The Netherlands 7Centre for Sport, Exercise and Osteoarthritis Versus Arthritis, Queen’s Medical Centre, Nottingham, United Kingdom 8Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt- Universität zu Berlin, and Berlin Institute of Health, Department of Pediatrics, Division of Pulmonology, Immunology and Critical Care Medicine, Berlin, Germany 9BCRT/DRFZ Single-Cell Laboratory for Advanced Cellular Therapies - Brandenburg Center for Regenerative Therapies (BCRT), Berlin, Germany 10Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt- Universität zu Berlin, and Berlin Institute of Health, Department of Rheumatology and Clinical Immunology, Berlin, Germany Correspondence: Dr. Annemarie Lang, PhD Dr.
    [Show full text]
  • Bioinformatic Analysis of Next‑Generation Sequencing Data to Identify Dysregulated Genes in Fibroblasts of Idiopathic Pulmonary Fibrosis
    INTERNATIONAL JOURNAL OF MOleCular meDICine 43: 1643-1656, 2019 Bioinformatic analysis of next‑generation sequencing data to identify dysregulated genes in fibroblasts of idiopathic pulmonary fibrosis CHAU‑CHYUN SHEU1-3, WEI‑AN CHANG1,2, MING‑JU TSAI1-3, SSU‑HUI LIAO1, INN‑WEN CHONG2,3 and PO-LIN KUO1 1Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University; 2Division of Pulmonary and Critical Care Medicine, Kaohsiung Medical University Hospital; 3Department of Internal Medicine, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan, R.O.C. Received October 7, 2018; Accepted January 29, 2019 DOI: 10.3892/ijmm.2019.4086 Abstract. Idiopathic pulmonary fibrosis (IPF) is a lethal and miRNA expression data, combined with GEO verifica- fibrotic lung disease with an increasing global burden. It is tion, finally identified Homo sapiens (hsa)-miR-1254-INKA2 hypothesized that fibroblasts have a number of functions that and hsa-miR-766-3p-INKA2 as the potential miRNA-mRNA may affect the development and progression of IPF. However, interactions in IPF fibroblasts. In summary, the results the present understanding of cellular and molecular mecha- of the present study suggest that dysregulation of PAX8, nisms associated with fibroblasts in IPF remains limited. hsa-miR-1254-INKA2 and hsa-miR-766-3p-INKA2 may The present study aimed to identify the dysregulated genes promote the proliferation and survival of IPF fibroblasts. In in IPF fibroblasts, elucidate their functions and explore the functional analysis of the dysregulated genes, a marked potential microRNA (miRNA)‑mRNA interactions. mRNA association between fibroblasts and the ECM was identified.
    [Show full text]
  • The Effect of Rbfox2 Modulation on Retinal Transcriptome and Visual
    www.nature.com/scientificreports OPEN The efect of Rbfox2 modulation on retinal transcriptome and visual function Lei Gu1, Riki Kawaguchi2, Joseph Caprioli1,3 & Natik Piri1,3* Rbfox proteins regulate alternative splicing, mRNA stability and translation. These proteins are involved in neurogenesis and have been associated with various neurological conditions. Here, we analyzed Rbfox2 expression in adult and developing mouse retinas and the efect of its downregulation on visual function and retinal transcriptome. In adult rodents, Rbfox2 is expressed in all retinal ganglion cell (RGC) subtypes, horizontal cells, as well as GABAergic amacrine cells (ACs). Among GABAergic AC subtypes, Rbfox2 was colocalized with cholinergic starburst ACs, NPY (neuropeptide Y)- and EBF1 (early B-cell factor 1)-positive ACs. In diferentiating retinal cells, Rbfox2 expression was observed as early as E12 and, unlike Rbfox1, which changes its subcellular localization from cytoplasmic to predominantly nuclear at around P0, Rbfox2 remains nuclear throughout retinal development. Rbfox2 knockout in adult animals had no detectable efect on retinal gross morphology. However, the visual clif test revealed a signifcant abnormality in the depth perception of Rbfox2- defcient animals. Gene set enrichment analysis identifed genes regulating the RNA metabolic process as a top enriched class of genes in Rbfox2-defcient retinas. Pathway analysis of the top 100 diferentially expressed genes has identifed Rbfox2-regulated genes associated with circadian rhythm and entrainment, glutamatergic/cholinergic/dopaminergic synaptic function, calcium and PI3K-AKT signaling. Te family of RNA binding protein, fox-1 (Rbfox) homolog includes three evolutionarily conserved members, Rbfox1, Rbfox2 and Rbfox3, that regulate cell- or tissue-specifc alternative splicing at diferent developmental stages.
    [Show full text]
  • 1 No. Affymetrix ID Gene Symbol Genedescription Gotermsbp Q Value 1. 209351 at KRT14 Keratin 14 Structural Constituent of Cyto
    1 Affymetrix Gene Q No. GeneDescription GOTermsBP ID Symbol value structural constituent of cytoskeleton, intermediate 1. 209351_at KRT14 keratin 14 filament, epidermis development <0.01 biological process unknown, S100 calcium binding calcium ion binding, cellular 2. 204268_at S100A2 protein A2 component unknown <0.01 regulation of progression through cell cycle, extracellular space, cytoplasm, cell proliferation, protein kinase C inhibitor activity, protein domain specific 3. 33323_r_at SFN stratifin/14-3-3σ binding <0.01 regulation of progression through cell cycle, extracellular space, cytoplasm, cell proliferation, protein kinase C inhibitor activity, protein domain specific 4. 33322_i_at SFN stratifin/14-3-3σ binding <0.01 structural constituent of cytoskeleton, intermediate 5. 201820_at KRT5 keratin 5 filament, epidermis development <0.01 structural constituent of cytoskeleton, intermediate 6. 209125_at KRT6A keratin 6A filament, ectoderm development <0.01 regulation of progression through cell cycle, extracellular space, cytoplasm, cell proliferation, protein kinase C inhibitor activity, protein domain specific 7. 209260_at SFN stratifin/14-3-3σ binding <0.01 structural constituent of cytoskeleton, intermediate 8. 213680_at KRT6B keratin 6B filament, ectoderm development <0.01 receptor activity, cytosol, integral to plasma membrane, cell surface receptor linked signal transduction, sensory perception, tumor-associated calcium visual perception, cell 9. 202286_s_at TACSTD2 signal transducer 2 proliferation, membrane <0.01 structural constituent of cytoskeleton, cytoskeleton, intermediate filament, cell-cell adherens junction, epidermis 10. 200606_at DSP desmoplakin development <0.01 lectin, galactoside- sugar binding, extracellular binding, soluble, 7 space, nucleus, apoptosis, 11. 206400_at LGALS7 (galectin 7) heterophilic cell adhesion <0.01 2 S100 calcium binding calcium ion binding, epidermis 12. 205916_at S100A7 protein A7 (psoriasin 1) development <0.01 S100 calcium binding protein A8 (calgranulin calcium ion binding, extracellular 13.
    [Show full text]
  • Small-Molecule Inhibition of STAT3 in Radioresistant Head and Neck Squamous Cell Carcinoma
    www.impactjournals.com/oncotarget/ Oncotarget, Vol. 7, No. 18 Small-molecule inhibition of STAT3 in radioresistant head and neck squamous cell carcinoma Uddalak Bharadwaj1, T. Kris Eckols1, Xuejun Xu2, Moses M. Kasembeli1, Yunyun Chen3, Makoto Adachi3, Yongcheng Song4, Qianxing Mo5, Stephen Y. Lai3, David J. Tweardy1,6 1 Department of Infectious Disease, Infection Control and Employee Health, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA 2The Key Laboratory of Natural Medicine and Immuno-Engineering, Henan University, Kaifeng, China 3 Department of Head and Neck Surgery, Division of Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA 4 Department of Pharmacology, Baylor College of Medicine, Houston, Texas, USA 5 Department of Medicine, Division of Biostatistics, Dan L. Duncan Cancer Center, Section of Hematology/Oncology, Baylor College of Medicine, Houston, Texas, USA 6Department of Molecular & Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA Correspondence to: David J. Tweardy, e-mail: [email protected] Keywords: STAT3, HNSCC, C188-9, cancer, small molecule Received: December 14, 2015 Accepted: March 14, 2016 Published: March 25, 2016 ABSTRACT While STAT3 has been validated as a target for treatment of many cancers, including head and neck squamous cell carcinoma (HNSCC), a STAT3 inhibitor is yet to enter the clinic. We used the scaffold of C188, a small-molecule STAT3 inhibitor previously identified by us, in a hit-to-lead program to identify C188-9. C188-9 binds to STAT3 with high affinity and represents a substantial improvement over C188 in its ability to inhibit STAT3 binding to its pY-peptide ligand, to inhibit cytokine-stimulated pSTAT3, to reduce constitutive pSTAT3 activity in multiple HNSCC cell lines, and to inhibit anchorage dependent and independent growth of these cells.
    [Show full text]
  • Breakpoint Mapping and Haplotype Analysis of Translocation T(1;12)(Q43;Q21.1) in Two Apparently Independent Families with Vascular Phenotypes
    Received: 7 August 2017 | Revised: 9 October 2017 | Accepted: 11 October 2017 DOI: 10.1002/mgg3.346 ORIGINAL ARTICLE Breakpoint mapping and haplotype analysis of translocation t(1;12)(q43;q21.1) in two apparently independent families with vascular phenotypes Tiia Maria Luukkonen1,2 | Mana M. Mehrjouy3 | Minna Poyh€ onen€ 4,5 | Anna-Kaisa Anttonen6 | Paivi€ Lahermo1 | Pekka Ellonen1 | Lars Paulin7 | Niels Tommerup3 | Aarno Palotie1,8 | Teppo Varilo2,5 1Institute for molecular medicine Finland FIMM, University of Helsinki, Helsinki, Abstract Finland Background: The risk of serious congenital anomaly for de novo balanced 2Department of Health, National Institute translocations is estimated to be at least 6%. We identified two apparently inde- for Health and Welfare, Helsinki, Finland pendent families with a balanced t(1;12)(q43;q21.1) as an outcome of a “System- 3Wilhelm Johannsen Centre for atic Survey of Balanced Chromosomal Rearrangements in Finns.” In the first Functional Genome Research, Department of Cellular and Molecular family, carriers (n = 6) manifest with learning problems in childhood, and later Medicine, University of Copenhagen, with unexplained neurological symptoms (chronic headache, balance problems, Copenhagen, Denmark tremor, fatigue) and cerebral infarctions in their 50s. In the second family, two 4Clinical Genetics, Helsinki University Hospital, University of Helsinki, carriers suffer from tetralogy of Fallot, one from transient ischemic attack and one Helsinki, Finland from migraine. The translocation cosegregates with these vascular phenotypes and 5Department of Medical Genetics, neurological symptoms. University of Helsinki, Helsinki, Finland Methods and Results: We narrowed down the breakpoint regions using mate 6Laboratory of Genetics, HUSLAB, Helsinki, Finland pair sequencing. We observed conserved haplotypes around the breakpoints, 7Institute of Biotechnology, University of pointing out that this translocation has arisen only once.
    [Show full text]
  • Alterations in TGF-Β Signaling Leads to High HMGA2 Levels Potentially Through Modulation of PJA1/SMAD3 in HCC Cells
    www.Genes&Cancer.com Genes & Cancer, Vol. 11 (1-2), 2020 Alterations in TGF-β signaling leads to high HMGA2 levels potentially through modulation of PJA1/SMAD3 in HCC cells Kazufumi Ohshiro1, Jian Chen2, Jigisha Srivastav3, Lopa Mishra1,4 and Bibhuti Mishra1 1 Department of Surgery, Center for Translational Medicine, George Washington University, Washington DC, USA 2 Department of Gastroenterology, Hepatology, and Nutrition, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 3 University of Toledo College of Medicine, Toledo, OH, USA 4 Department of Gastroenterology and Hepatology, VA Medical Center, Washington DC, USA Correspondence to: Lopa Mishra, email: [email protected] Keywords: TGF-β pathway, HMGA2, PJA1, hepatocellular carcinoma Received: October 07, 2019 Accepted: January 06, 2020 Published: January 22, 2020 Copyright: © 2020 Ohshiro et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Recently, we observed that the TGF-β pathway is altered in 39% of HCCs. The alterations are correlated with a raised HMGA2 level. Therefore, we compared genetic alterations of HMGA2 and 43 TGF-β pathway core genes in HCC patients from TCGA database. Genetic alterations of 15 genes, including INHBE, INHBC, GDF11, ACVRL and TGFB2 out of 43 core genes, highly-moderately matched that of HMGA2. Co- occurrences of mutation amplification, gains, deletions and high/low mRNA of HMGA2 with those of the core genes were highly significant in INHBE, INHBC, ACVR1B, ACVRL and GDF11.
    [Show full text]
  • 6 Signaling and BMP Antagonist Noggin in Prostate Cancer
    [CANCER RESEARCH 64, 8276–8284, November 15, 2004] Bone Morphogenetic Protein (BMP)-6 Signaling and BMP Antagonist Noggin in Prostate Cancer Dominik R. Haudenschild, Sabrina M. Palmer, Timothy A. Moseley, Zongbing You, and A. Hari Reddi Center for Tissue Regeneration and Repair, Department of Orthopedic Surgery, School of Medicine, University of California, Davis, Sacramento, California ABSTRACT antagonists has recently been discovered. These are secreted proteins that bind to BMPs and reduce their bioavailability for interactions It has been proposed that the osteoblastic nature of prostate cancer with the BMP receptors. Extracellular BMP antagonists include nog- skeletal metastases is due in part to elevated activity of bone morphoge- gin, follistatin, sclerostatin, chordin, DCR, BMPMER, cerberus, netic proteins (BMPs). BMPs are osteoinductive morphogens, and ele- vated expression of BMP-6 correlates with skeletal metastases of prostate gremlin, DAN, and others (refs. 11–16; reviewed in ref. 17). There are cancer. In this study, we investigated the expression levels of BMPs and several type I and type II receptors that bind to BMPs with different their modulators in prostate, using microarray analysis of cell cultures affinities. BMP activity is also regulated at the cell membrane level by and gene expression. Addition of exogenous BMP-6 to DU-145 prostate receptor antagonists such as BAMBI (18), which acts as a kinase- cancer cell cultures inhibited their growth by up-regulation of several deficient receptor. Intracellularly, the regulation of BMP activity at cyclin-dependent kinase inhibitors such as p21/CIP, p18, and p19. Expres- the signal transduction level is even more complex. There are inhib- sion of noggin, a BMP antagonist, was significantly up-regulated by itory Smads (Smad-6 and Smad-7), as well as inhibitors of inhibitory BMP-6 by microarray analysis and was confirmed by quantitative reverse Smads (AMSH and Arkadia).
    [Show full text]
  • Identifying Genetic Interactions Associated with Late-Onset
    1 Identifying Genetic Interactions Associated with Late-Onset 2 Alzheimer’s Disease 3 Charalampos S. Floudas, M.D, Ph.D. 1§ , Nara Um, M.D, M.S. 1, M. Ilyas Kamboh, Ph.D. 2, 4 Michael M. Barmada, Ph.D. 2, Shyam Visweswaran, M.D, Ph.D. 1,3 5 6 1Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA s t 7 2Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA n i r 8 3The Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA P e r 9 P 10 §Corresponding author 11 12 13 14 15 16 17 Email addresses : 18 CSF: [email protected] 19 SV: [email protected] 20 1 PeerJ PrePrints | https://peerj.com/preprints/123v2/ | v2 received: 11 Dec 2013, published: 11 Dec 2013, doi: 10.7287/peerj.preprints.123v2 21 Abstract 22 Background 23 Identifying genetic interactions in data obtained from genome-wide association studies (GWASs) 24 can help in understanding the genetic basis of complex diseases. The large number of single 25 nucleotide polymorphisms (SNPs) in GWASs however makes the identification of genetic 26 interactions computationally challenging. We developed the Bayesian Combinatorial Method s t n 27 (BCM) that can identify pairs of SNPs that in combination have high statistical association with i r P 28 disease. e r 29 Results P 30 We applied BCM to two late-onset Alzheimer’s disease (LOAD) GWAS datasets to identify 31 SNP-SNP interactions between a set of known SNP associations and the dataset SNPs. For 32 evaluation we compared our results with those from logistic regression, as implemented in 33 PLINK.
    [Show full text]