Biorxiv Supplementary Fig

Total Page:16

File Type:pdf, Size:1020Kb

Biorxiv Supplementary Fig PLZF is a new substrate of CRBN with thalidomide and 5- hydroxythalidomide Satoshi Yamanaka1, Hidetaka Murai2, Daisuke Saito2#, Gembu Abe2, Etsuko Tokunaga3, Takahiro Iwasaki4, Hirotaka Takahashi1, Hiroyuki Takeda4, Takayuki Suzuki5, Norio Shibata3, Koji Tamura2 & Tatsuya Sawasaki1* 1Division of Cell-Free Sciences, Proteo-Science Center, Ehime University, Matsuyama, 790-8577 Japan, 2Department of Ecological Developmental Adaptability Life Sciences, Graduate School of Life Sciences, Tohoku University, Sendai, 980-8578, Japan, 3Department of Nanopharmaceutical Sciences, Nagoya Institute of Technology, Nagoya, 466-8555, Japan, 4Division of Proteo-Drug-Discovery Sciences, Proteo-Science Center, Ehime University, Matsuyama, 790-8577 Japan. 5Avian Bioscience Research Center, Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 464-8601, Japan. #Present address. Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, 819-0395 Japan. *Corresponding Author: Tatsuya Sawasaki Proteo-Science Center, Ehime University, Matsuyama 790-8577, Japan Tel: 81-89-927-8530 Fax: 81-89-927-9941 E-mail address: [email protected]. 1 Supplementary Figures Supplementary Figure 1. Flowchart of in vitro high-throughput screening and validation assay of candidate clones a, Flowchart of in vitro high-throughput screening. b, Validation of screening using CRBN mutant. Interaction between FLAG-GST-SALL4, -PLZF, or IKZF1 and bls-CRB-WT or - CRBN-YW/AA in the presence of DMSO or 50 µM thalidomide was analysed by in vitro binding assay using AlphaScreen technology. c, In vitro binding assay using pull-down and immunoblot analysis. bls-CRBN-WT or -CRBN-YW/AA was used as bait protein, and thalidomide-dependent interactions between bls-CRBN and FLAG-GST-SALL4, PLZF, and IKZF were confirmed by procedures described in Methods. d, In vitro binding assay for ZBTB family proteins using AlphaScreen technology. FLAG-GST-ZBTB proteins (ZBTB17, ZBTB20, ZBTB38, ZBTB39, ZBTB48, and PLZF) were evaluated for thalidomide- dependent interactions with bls-CRBN by same procedures indicated in Supplementary Fig. 1b. e, In vitro binding assay for thalidomide, pomalidomide, and lenalidomide. Interaction between bls-CRBN and FLAG-GST-SALL4 in the presence of DMSO, (3.125, 6.25, 12.5, 25, 50, 100, or 200 µM) thalidomide, pomalidomide, or lenalidomide was analysed using AlphaScreen technology. All relative AS (AlphaScreen) signals were expressed as relative luminescent signal with luminescent signal of DMSO as one, and error bars mean ± standard deviation (n = 3). 2 a b c Thalidomide Pomalidomide Lenalidomide Thalidomide Pomalidomide Lenalidomide Thalidomide Pomalidomide Lenalidomide 0 1 10 50 1 10 50 1 10 50 IMiD (µM) 0 1 10 50 1 10 50 1 10 50 IMiD (µM) 0 1 10 50 1 10 50 1 10 50 IMiD (µM) (kDa) (kDa) (kDa) 100 100 75 IB: AGIA (PLZF) IB: PLZF IB: PLZF 75 75 150 IB: FLAG (CRBN) 50 IB: CRBN IB: SALL4 50 100 IB: a-TuBulin IB: a-TuBulin 50 50 50 IB: CRBN 150 HEK293T cells IB: AGIA (SALL4) IB: a-TuBulin 50 100 IB: FLAG (CRBN) HuH7 cells 50 IB: a-TuBulin 50 d e CRBN-WT CRBN-YW/AA 0 1 3 6 12 24 Time (h) 0 0.1 1 10 50 0 0.1 1 10 50 Lenalidomide (µM) 0 0 50 0 50 0 50 0 50 0 50 Lenalidomide (µM) (kDa) (kDa) 100 100 IB: AGIA (PLZF) IB: AGIA (PLZF) 75 75 IB: FLAG (CRBN) IB: FLAG (CRBN) 50 50 50 IB: a-TuBulin 50 IB: a-TuBulin Supplementary Figure 2. Destabilization of PLZF in IMiD-treated cells a, Immunoblot analysis of AGIA-PLZF or AGIA-SALL4 protein levels in FLAG-CRBN expressing HEK293T cells treated with DMSO, thalidomide, pomalidomide, or lenalidomide for 16 h. b, Immunoblot analysis of endogenous PLZF or SALL4 protein levels in HuH7 cells treated with DMSO, thalidomide, pomalidomide or lenalidomide for 24 h. c, Immunoblot analysis of endogenous PLZF protein levels in HEK293T cells treated with DMSO, thalidomide, pomalidomide or lenalidomide for 24 h. d, Time course of DMSO or lenalidomide treatment in AGIA-PLZF and FLAG-CRBN expressing HEK293T cells. AGIA-PLZF protein levels were detected by immunoblot analysis. e, Immunoblot analysis of AGIA-PLZF protein levels in FLAG-CRBN-WT or FLAG-CRBN-YW expressing CRBN-/- HEK293T cells treated with DMSO or lenalidomide for 16 h. 3 a b HuH7 HEK293T HuH7 1.5 NS 1.5 NS 0 0.1 1 10 100 Lenalidomide (µM) NS NS (kDa) 100 1.0 IB: PLZF 1.0 75 0.5 IB: CRBN 0.5 50 50 IB: a-Tubulin Relative mRNA expression Relative mRNA 0.0 expression Relative mRNA 0.0 M M M M µ µ µ µ 10 DMSO 100 10 DMSO 100 Lenalidomide Lenalidomide c THP-1 THP-1 1.5 NS NS 0 0.1 1 10 100 Lenalidomide (µM) (kDa) 100 1.0 IB: PLZF 75 0.5 50 IB: CRBN 50 IB: a-Tubulin expression Relative mRNA 0.0 M M µ µ 10 DMSO 100 Lenalidomide Supplementary Figure 3. Analyses of expression of PLZF mRNA and degradation of endogenous PLZF in thalidomide-treated cells Extended Data Figure 3. Analyses of expression of PLZF mRNA and degradation of endogenous PLZF in lenalidomide-treated cells. a, HEK293T cells were treated with the indicated concentrations of lenalidomide for 24 h and PLZF mRNA expression levels were measured by quantitative RT-PCR. b, HuH7 cells were treated with the indicated concentrations of lenalidomide for 24 h. PLZF protein levels were analysed by immunoblot and PLZF mRNA expression levels were measured by quantitative RT-PCR. c, THP-1 cells were treated with the indicated concentrations of lenalidomide for 24 h. PLZF protein levels were analysed by immunoblot and PLZF mRNA expression levels were measured by quantitative RT-PCR. Relative mRNA expression used the expression level with DMSO treatment as one. Error bars mean ± standard deviation (n = 3) and P values were calculated by one-way ANOVA with Tukey’s post-hoc test (NS = Not Significant). 4 Supplementary Figure 4. PLZF is a substrate of CRL4CRBN with thalidomide and lenalidomide for E3 ubiquitin ligase. a, Immunoprecipitation of FLAG-CRBN in FLAG-CRBN and AGIA-PLZF expressing CRBN-/- HEK293T cells treated with DMSO or thalidomide in the presence of DMSO or MG132 for 8 h. Components of CRLFLAG-CRBN and AGIA-PLZF were detected using each specific antibody, as indicated. b, Ubiquitination of AGIA-PLZF in AGIA-PLZF and FLAG- CRBN expressing HEK293T cells treated with DMSO or lenalidomide in the presence of DMSO or MG132 for 10 h. 5 a b HT TK BJAB SU-DHL-4 MT-4 Raji (kDa) DM Le Po DM Le Po DM Le Po DM Le Po DM Le Po IMiD (10 µM) DM 1 10 Pomalidomide (µM) (kDa) 75 75 IB: PLZF IB: PLZF (Short Exp.) 75 IB: CRBN IB: PLZF 50 (Long Exp.) 50 IB: Tubulin IB: CRBN 50 IB: Tubulin 50 Supplementary Figure 5. IMiD-induced protein degradation of PLZF in B cell lymphomas. a, HT, TK, BJAB, SY-DHL-4, and MT-4 cells were treated with DMSO, 10 µM lenalidomide, or pomalidomide for 24 h. PLZF protein levels were analysed by immunoblot. b, Raji cells were treated with DMSO, 10 µM lenalidomide, or pomalidomide for 24 h. PLZF protein levels were analysed by immunoblot. Extended Data Figure 5. IMiD-induced protein degradation of PLZF in B cell lymphomas. 6 Supplementary Figure 6. Sequence comparisons of thalidomide-related regions in vertebrate PLZF, SALL4 and CRBN. a, Alignment of amino acid sequence of ZNF1 and ZNF3 in PLZF among human (Hs), rabbit (Oc), mouse (Mm), chicken (Gg), and zebrafish (Dr). b, Alignment of amino acid sequence of ZNF2 in SALL4 among the species above. c, Alignment of amino acid sequence in CRBN among the species above. 7 a b HsPLZF HsSALL4 ✱✱✱✱ ✱✱✱✱ HsSALL4 HsPLZF MmSall4 MmPlzf GgSall4 GgPlzf ✱✱✱✱ ✱✱✱✱ 80 20 8 ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ ✱✱✱✱ 30 15 ✱✱✱✱ 60 15 6 ✱✱✱✱ ✱✱✱ 20 10 ✱✱✱✱ NS 40 10 4 ✱✱✱✱ ✱ NS 10 5 NS 20 5 2 NS Relative AS signal Relative Relative AS signal Relative Relative AS signal Relative Relative AS signal Relative Relative AS signal Relative 0 0 0 0 0 HsCRBN-WT HsCRBN-WT GgCrbn-WT HsCRBN-EV/VI HsCRBN-WT MmCrbn-WT HsCRBN-E377VHsCRBN-V388I HsCRBN-E377VHsCRBN-V388IHsCRBN-EV/VI HsCRBN-V388I MmCrbn-I391V GgCrbn-I390V c MmPlzf MmSALL4 d ✱✱✱✱ ✱✱✱✱ GgCrbn-WT GgCrbn-E379V ✱✱✱✱ ✱✱✱✱ 20 20 (kDa) 0 50 200 0 50 200 Thalidomide (µM) ✱✱✱✱ ✱✱✱✱ 100 15 ✱✱✱✱ 15 IB: AGIA (GgPlzf) 75 ✱✱✱✱ ✱ 10 10 ✱ IB: FLAG (GgCrbn) 50 5 NS 5 NS Relative AS signal Relative Relative AS signal Relative 50 IB: a-Tubulin 0 0 MmCRBN-WT MmCRBN-WT MmCRBN-I391VMmCRBN-VE/IV MmCRBN-V380EMmCRBN-I391VMmCRBN-VE/IV MmCRBN-V380E Supplementary Figure 7. Interaction and protein degradation analyses between PLZF or SALL4 and CRBN with thalidomide among human, mouse and chicken. a, In vitro binding assay using human, mouse, and chicken proteins. Thalidomide-dependent interaction between biotinylated-HsCRBN, -MmCrbn or -GgCrbn, and FLAG-GST-SALL4, or -PLZF (Hs, Mm or Gg) in the presence of DMSO or 200 µM thalidomide was analysed using AlphaScreen technology. b-c, In vitro binding assay using human or mouse proteins. Thalidomide-dependent interaction in the presence of DMSO or 50 µM thalidomide was analysed using same procedure in Supplementary Fig 7a. d, Immunoblot analysis of AGIA- GgPlzf in FLAG-GgCrbn-WT or -E379V expressing CRBN-/- HEK293T cells treated with DMSO, 50 µM or 200 µM thalidomide for 16 h. All relative AS (AlphaScreen) signals are expressed as relative luminescent signal with luminescent signal of DMSO as one. Error bars mean ± standard deviation (n = 3) and P values were calculated by one-way or two-way ANOVA with Tukey’s post-hoc test (NS = Not Significant, *P < 0.05, ***P < 0.001, and ****P < 0.0001).
Recommended publications
  • Novel TAL1 Targets Beyond Protein-Coding Genes: Identification of TAL1-Regulated Micrornas in T-Cell Acute Lymphoblastic Leukemia
    Letters to the Editor 1603 REFERENCES 8 Yoshida K, Sanada M, Shiraishi Y, Nowak D, Nagata Y, Yamamoto R et al. Frequent 1 Rozman C, Montserrat E. Chronic lymphocytic leukemia. N Engl J Med 1995; 333: pathway mutations of splicing machinery in myelodysplasia. Nature 2011; 478: 64–69. 1052–1057. 9 Papaemmanuil E, Cazzola M, Boultwood J, Malcovati L, Vyas P, Bowen D et al. 2 Zenz T, Mertens D, Kuppers R, Dohner H, Stilgenbauer S. From pathogenesis to Somatic SF3B1 mutation in myelodysplasia with ring sideroblasts. N Engl J Med treatment of chronic lymphocytic leukaemia. Nat Rev Cancer 2010; 10: 37–50. 2011; 365: 1384–1395. 3 Puente XS, Pinyol M, Quesada V, Conde L, Ordonez GR, Villamor N et al. Whole- 10 Damm F, Nguyen-Khac F, Fontenay M, Bernard OA. Spliceosome and other novel genome sequencing identifies recurrent mutations in chronic lymphocytic leu- mutations in chronic lymphocytic leukemia and myeloid malignancies. Leukemia kaemia. Nature 2011; 475: 101–105. 2012; 26: 2027–2031. 4 Quesada V, Conde L, Villamor N, Ordonez GR, Jares P, Bassaganyas L et al. Exome 11 Wahl MC, Will CL, Luhrmann R. The spliceosome: design principles of a dynamic sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in RNP machine. Cell 2009; 136: 701–718. chronic lymphocytic leukemia. Nat Genet 2012; 44: 47–52. 12 David CJ, Manley JL. Alternative pre-mRNA splicing regulation in cancer: pathways 5 Wang L, Lawrence MS, Wan Y, Stojanov P, Sougnez C, Stevenson K et al. SF3B1 and programs unhinged. Genes Dev 2010; 24: 2343–2364.
    [Show full text]
  • Analysis of Trans Esnps Infers Regulatory Network Architecture
    Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Anat Kreimer All rights reserved ABSTRACT Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer eSNPs are genetic variants associated with transcript expression levels. The characteristics of such variants highlight their importance and present a unique opportunity for studying gene regulation. eSNPs affect most genes and their cell type specificity can shed light on different processes that are activated in each cell. They can identify functional variants by connecting SNPs that are implicated in disease to a molecular mechanism. Examining eSNPs that are associated with distal genes can provide insights regarding the inference of regulatory networks but also presents challenges due to the high statistical burden of multiple testing. Such association studies allow: simultaneous investigation of many gene expression phenotypes without assuming any prior knowledge and identification of unknown regulators of gene expression while uncovering directionality. This thesis will focus on such distal eSNPs to map regulatory interactions between different loci and expose the architecture of the regulatory network defined by such interactions. We develop novel computational approaches and apply them to genetics-genomics data in human. We go beyond pairwise interactions to define network motifs, including regulatory modules and bi-fan structures, showing them to be prevalent in real data and exposing distinct attributes of such arrangements. We project eSNP associations onto a protein-protein interaction network to expose topological properties of eSNPs and their targets and highlight different modes of distal regulation.
    [Show full text]
  • Transcription Factor P73 Regulates Th1 Differentiation
    ARTICLE https://doi.org/10.1038/s41467-020-15172-5 OPEN Transcription factor p73 regulates Th1 differentiation Min Ren1, Majid Kazemian 1,4, Ming Zheng2, JianPing He3, Peng Li1, Jangsuk Oh1, Wei Liao1, Jessica Li1, ✉ Jonathan Rajaseelan1, Brian L. Kelsall 3, Gary Peltz 2 & Warren J. Leonard1 Inter-individual differences in T helper (Th) cell responses affect susceptibility to infectious, allergic and autoimmune diseases. To identify factors contributing to these response differ- 1234567890():,; ences, here we analyze in vitro differentiated Th1 cells from 16 inbred mouse strains. Haplotype-based computational genetic analysis indicates that the p53 family protein, p73, affects Th1 differentiation. In cells differentiated under Th1 conditions in vitro, p73 negatively regulates IFNγ production. p73 binds within, or upstream of, and modulates the expression of Th1 differentiation-related genes such as Ifng and Il12rb2. Furthermore, in mouse experimental autoimmune encephalitis, p73-deficient mice have increased IFNγ production and less dis- ease severity, whereas in an adoptive transfer model of inflammatory bowel disease, transfer of p73-deficient naïve CD4+ T cells increases Th1 responses and augments disease severity. Our results thus identify p73 as a negative regulator of the Th1 immune response, suggesting that p73 dysregulation may contribute to susceptibility to autoimmune disease. 1 Laboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute, Bethesda, MD 20892-1674, USA. 2 Department of Anesthesia, Stanford University School of Medicine, Stanford, CA 94305, USA. 3 Laboratory of Molecular Immunology, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA. 4Present address: Department of Biochemistry and Computer Science, Purdue University, West ✉ Lafayette, IN 37906, USA.
    [Show full text]
  • 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]
  • Overlap of Vitamin a and Vitamin D Target Genes with CAKUT- Related Processes [Version 1; Peer Review: 1 Approved with Reservations]
    F1000Research 2021, 10:395 Last updated: 21 JUL 2021 BRIEF REPORT Overlap of vitamin A and vitamin D target genes with CAKUT- related processes [version 1; peer review: 1 approved with reservations] Ozan Ozisik1, Friederike Ehrhart 2,3, Chris T Evelo 2, Alberto Mantovani4, Anaı̈s Baudot 1,5 1Aix Marseille University, Inserm, MMG, Marseille, 13385, France 2Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, 6200 MD, The Netherlands 3Department of Bioinformatics, NUTRIM/MHeNs, Maastricht University, Maastricht, 6200 MD, The Netherlands 4Istituto Superiore di Sanità, Rome, 00161, Italy 5Barcelona Supercomputing Center (BSC), Barcelona, 08034, Spain v1 First published: 18 May 2021, 10:395 Open Peer Review https://doi.org/10.12688/f1000research.51018.1 Latest published: 18 May 2021, 10:395 https://doi.org/10.12688/f1000research.51018.1 Reviewer Status Invited Reviewers Abstract Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) are a 1 group of abnormalities affecting the kidneys and their outflow tracts, which include the ureters, the bladder, and the urethra. CAKUT version 1 patients display a large clinical variability as well as a complex 18 May 2021 report aetiology, as only 5% to 20% of the cases have a monogenic origin. It is thereby suspected that interactions of both genetic and 1. Elena Menegola, Università degli Studi di environmental factors contribute to the disease. Vitamins are among the environmental factors that are considered for CAKUT aetiology. In Milano, Milan, Italy this study, we collected vitamin A and vitamin D target genes and Any reports and responses or comments on the computed their overlap with CAKUT-related gene sets.
    [Show full text]
  • Cyclin D1 Is a Direct Transcriptional Target of GATA3 in Neuroblastoma Tumor Cells
    Oncogene (2010) 29, 2739–2745 & 2010 Macmillan Publishers Limited All rights reserved 0950-9232/10 $32.00 www.nature.com/onc SHORT COMMUNICATION Cyclin D1 is a direct transcriptional target of GATA3 in neuroblastoma tumor cells JJ Molenaar1,2, ME Ebus1, J Koster1, E Santo1, D Geerts1, R Versteeg1 and HN Caron2 1Department of Human Genetics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands and 2Department of Pediatric Oncology, Emma Kinderziekenhuis, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands Almost all neuroblastoma tumors express excess levels of 2000). Several checkpoints normally prevent premature Cyclin D1 (CCND1) compared to normal tissues and cell-cycle progression and cell division. The crucial G1 other tumor types. Only a small percentage of these entry point is controlled by the D-type Cyclins that can neuroblastoma tumors have high-level amplification of the activate CDK4/6 that in turn phosphorylate the pRb Cyclin D1 gene. The other neuroblastoma tumors have protein. This results in a release of the E2F transcription equally high Cyclin D1 expression without amplification. factor that causes transcriptional upregulation of Silencing of Cyclin D1 expression was previously found to numerous genes involved in further progression of the trigger differentiation of neuroblastoma cells. Over- cell cycle (Sherr, 1996). expression of Cyclin D1 is therefore one of the most Neuroblastomas are embryonal tumors that originate frequent mechanisms with a postulated function in neuro- from precursor cells of the sympathetic nervous system. blastoma pathogenesis. The cause for the Cyclin D1 This tumor has a very poor prognosis and despite the overexpression is unknown.
    [Show full text]
  • Characterization of BRCA1-Deficient Premalignant Tissues and Cancers Identifies Plekha5 As a Tumor Metastasis Suppressor
    ARTICLE https://doi.org/10.1038/s41467-020-18637-9 OPEN Characterization of BRCA1-deficient premalignant tissues and cancers identifies Plekha5 as a tumor metastasis suppressor Jianlin Liu1,2, Ragini Adhav1,2, Kai Miao1,2, Sek Man Su1,2, Lihua Mo1,2, Un In Chan1,2, Xin Zhang1,2, Jun Xu1,2, Jianjie Li1,2, Xiaodong Shu1,2, Jianming Zeng 1,2, Xu Zhang1,2, Xueying Lyu1,2, Lakhansing Pardeshi1,3, ✉ ✉ Kaeling Tan1,3, Heng Sun1,2, Koon Ho Wong 1,3, Chuxia Deng 1,2 & Xiaoling Xu 1,2 1234567890():,; Single-cell whole-exome sequencing (scWES) is a powerful approach for deciphering intra- tumor heterogeneity and identifying cancer drivers. So far, however, simultaneous analysis of single nucleotide variants (SNVs) and copy number variations (CNVs) of a single cell has been challenging. By analyzing SNVs and CNVs simultaneously in bulk and single cells of premalignant tissues and tumors from mouse and human BRCA1-associated breast cancers, we discover an evolution process through which the tumors initiate from cells with SNVs affecting driver genes in the premalignant stage and malignantly progress later via CNVs acquired in chromosome regions with cancer driver genes. These events occur randomly and hit many putative cancer drivers besides p53 to generate unique genetic and pathological features for each tumor. Upon this, we finally identify a tumor metastasis suppressor Plekha5, whose deficiency promotes cancer metastasis to the liver and/or lung. 1 Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, SAR, China. 2 Centre for Precision Medicine Research and Training, Faculty of Health Sciences, University of Macau, Macau, SAR, China.
    [Show full text]
  • DNA·RNA Triple Helix Formation Can Function As a Cis-Acting Regulatory
    DNA·RNA triple helix formation can function as a cis-acting regulatory mechanism at the human β-globin locus Zhuo Zhoua, Keith E. Gilesa,b,c, and Gary Felsenfelda,1 aLaboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892; bUniversity of Alabama at Birmingham Stem Cell Institute, University of Alabama at Birmingham, Birmingham, AL 35294; and cDepartment of Biochemistry and Molecular Genetics, University of Alabama at Birmingham, Birmingham, AL 35294 Contributed by Gary Felsenfeld, February 4, 2019 (sent for review January 4, 2019; reviewed by James Douglas Engel and Sergei M. Mirkin) We have identified regulatory mechanisms in which an RNA tran- of the criteria necessary to establish the presence of a triplex script forms a DNA duplex·RNA triple helix with a gene or one of its structure, we first describe and characterize triplex formation at regulatory elements, suggesting potential auto-regulatory mecha- the FAU gene in human erythroid K562 cells. FAU encodes a nisms in vivo. We describe an interaction at the human β-globin protein that is a fusion containing fubi, a ubiquitin-like protein, locus, in which an RNA segment embedded in the second intron of and ribosomal protein S30. Although fubi function is unknown, the β-globin gene forms a DNA·RNA triplex with the HS2 sequence posttranslational processing produces S30, a component of the within the β-globin locus control region, a major regulator of glo- 40S ribosome. We used this system to refine methods necessary bin expression. We show in human K562 cells that the triplex is to detect triplex formation and to distinguish it from R-loop stable in vivo.
    [Show full text]
  • Transcriptomic Characterization of Fibrolamellar Hepatocellular
    Transcriptomic characterization of fibrolamellar PNAS PLUS hepatocellular carcinoma Elana P. Simona, Catherine A. Freijeb, Benjamin A. Farbera,c, Gadi Lalazara, David G. Darcya,c, Joshua N. Honeymana,c, Rachel Chiaroni-Clarkea, Brian D. Dilld, Henrik Molinad, Umesh K. Bhanote, Michael P. La Quagliac, Brad R. Rosenbergb,f, and Sanford M. Simona,1 aLaboratory of Cellular Biophysics, The Rockefeller University, New York, NY 10065; bPresidential Fellows Laboratory, The Rockefeller University, New York, NY 10065; cDivision of Pediatric Surgery, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10065; dProteomics Resource Center, The Rockefeller University, New York, NY 10065; ePathology Core Facility, Memorial Sloan-Kettering Cancer Center, New York, NY 10065; and fJohn C. Whitehead Presidential Fellows Program, The Rockefeller University, New York, NY 10065 Edited by Susan S. Taylor, University of California, San Diego, La Jolla, CA, and approved September 22, 2015 (received for review December 29, 2014) Fibrolamellar hepatocellular carcinoma (FLHCC) tumors all carry a exon of DNAJB1 and all but the first exon of PRKACA. This deletion of ∼400 kb in chromosome 19, resulting in a fusion of the produced a chimeric RNA transcript and a translated chimeric genes for the heat shock protein, DNAJ (Hsp40) homolog, subfam- protein that retains the full catalytic activity of wild-type PKA. ily B, member 1, DNAJB1, and the catalytic subunit of protein ki- This chimeric protein was found in 15 of 15 FLHCC patients nase A, PRKACA. The resulting chimeric transcript produces a (21) in the absence of any other recurrent mutations in the DNA fusion protein that retains kinase activity.
    [Show full text]
  • Watsonjn2018.Pdf (1.780Mb)
    UNIVERSITY OF CENTRAL OKLAHOMA Edmond, Oklahoma Department of Biology Investigating Differential Gene Expression in vivo of Cardiac Birth Defects in an Avian Model of Maternal Phenylketonuria A THESIS SUBMITTED TO THE GRADUATE FACULTY In partial fulfillment of the requirements For the degree of MASTER OF SCIENCE IN BIOLOGY By Jamie N. Watson Edmond, OK June 5, 2018 J. Watson/Dr. Nikki Seagraves ii J. Watson/Dr. Nikki Seagraves Acknowledgements It is difficult to articulate the amount of gratitude I have for the support and encouragement I have received throughout my master’s thesis. Many people have added value and support to my life during this time. I am thankful for the education, experience, and friendships I have gained at the University of Central Oklahoma. First, I would like to thank Dr. Nikki Seagraves for her mentorship and friendship. I lucked out when I met her. I have enjoyed working on this project and I am very thankful for her support. I would like thank Thomas Crane for his support and patience throughout my master’s degree. I would like to thank Dr. Shannon Conley for her continued mentorship and support. I would like to thank Liz Bullen and Dr. Eric Howard for their training and help on this project. I would like to thank Kristy Meyer for her friendship and help throughout graduate school. I would like to thank my committee members Dr. Robert Brennan and Dr. Lilian Chooback for their advisement on this project. Also, I would like to thank the biology faculty and staff. I would like to thank the Seagraves lab members: Jailene Canales, Kayley Pate, Mckayla Muse, Grace Thetford, Kody Harvey, Jordan Guffey, and Kayle Patatanian for their hard work and support.
    [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]
  • To Study Mutant P53 Gain of Function, Various Tumor-Derived P53 Mutants
    Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science By Shama K Khokhar M.Sc., Bilaspur University, 2004 B.Sc., Bhopal University, 2002 2007 1 COPYRIGHT SHAMA K KHOKHAR 2007 2 WRIGHT STATE UNIVERSITY SCHOOL OF GRADUATE STUDIES Date of Defense: 12-03-07 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY SHAMA KHAN KHOKHAR ENTITLED Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science Madhavi P. Kadakia, Ph.D. Thesis Director Daniel Organisciak , Ph.D. Department Chair Committee on Final Examination Madhavi P. Kadakia, Ph.D. Steven J. Berberich, Ph.D. Michael Leffak, Ph.D. Joseph F. Thomas, Jr., Ph.D. Dean, School of Graduate Studies 3 Abstract Khokhar, Shama K. M.S., Department of Biochemistry and Molecular Biology, Wright State University, 2007 Differential effect of TAp63γ mutants on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. p63, a member of the p53 gene family, known to play a role in development, has more recently also been implicated in cancer progression. Mice lacking p63 exhibit severe developmental defects such as limb truncations, abnormal skin, and absence of hair follicles, teeth, and mammary glands. Germline missense mutations of p63 have been shown to be responsible for several human developmental syndromes including SHFM, EEC and ADULT syndromes and are associated with anomalies in the development of organs of epithelial origin.
    [Show full text]