SUPPLEMENTARY TABLES and FIGURE LEGENDS Supplementary
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View of HER2: Human Epidermal Growth Factor Receptor 2; TNBC: Triple-Negative Breast Resistance to Systemic Therapy in Patients with Breast Cancer
Wen et al. Cancer Cell Int (2018) 18:128 https://doi.org/10.1186/s12935-018-0625-9 Cancer Cell International PRIMARY RESEARCH Open Access Sulbactam‑enhanced cytotoxicity of doxorubicin in breast cancer cells Shao‑hsuan Wen1†, Shey‑chiang Su2†, Bo‑huang Liou3, Cheng‑hao Lin1 and Kuan‑rong Lee1* Abstract Background: Multidrug resistance (MDR) is a major obstacle in breast cancer treatment. The predominant mecha‑ nism underlying MDR is an increase in the activity of adenosine triphosphate (ATP)-dependent drug efux trans‑ porters. Sulbactam, a β-lactamase inhibitor, is generally combined with β-lactam antibiotics for treating bacterial infections. However, sulbactam alone can be used to treat Acinetobacter baumannii infections because it inhibits the expression of ATP-binding cassette (ABC) transporter proteins. This is the frst study to report the efects of sulbactam on mammalian cells. Methods: We used the breast cancer cell lines as a model system to determine whether sulbactam afects cancer cells. The cell viabilities in the present of doxorubicin with or without sulbactam were measured by MTT assay. Protein identities and the changes in protein expression levels in the cells after sulbactam and doxorubicin treatment were determined using LC–MS/MS. Real-time reverse transcription polymerase chain reaction (real-time RT-PCR) was used to analyze the change in mRNA expression levels of ABC transporters after treatment of doxorubicin with or without sulbactam. The efux of doxorubicin was measures by the doxorubicin efux assay. Results: MTT assay revealed that sulbactam enhanced the cytotoxicity of doxorubicin in breast cancer cells. The results of proteomics showed that ABC transporter proteins and proteins associated with the process of transcription and initiation of translation were reduced. -
Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897 -
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. -
Transcriptional Control of Tissue-Resident Memory T Cell Generation
Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Filip Cvetkovski All rights reserved ABSTRACT Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Tissue-resident memory T cells (TRM) are a non-circulating subset of memory that are maintained at sites of pathogen entry and mediate optimal protection against reinfection. Lung TRM can be generated in response to respiratory infection or vaccination, however, the molecular pathways involved in CD4+TRM establishment have not been defined. Here, we performed transcriptional profiling of influenza-specific lung CD4+TRM following influenza infection to identify pathways implicated in CD4+TRM generation and homeostasis. Lung CD4+TRM displayed a unique transcriptional profile distinct from spleen memory, including up-regulation of a gene network induced by the transcription factor IRF4, a known regulator of effector T cell differentiation. In addition, the gene expression profile of lung CD4+TRM was enriched in gene sets previously described in tissue-resident regulatory T cells. Up-regulation of immunomodulatory molecules such as CTLA-4, PD-1, and ICOS, suggested a potential regulatory role for CD4+TRM in tissues. Using loss-of-function genetic experiments in mice, we demonstrate that IRF4 is required for the generation of lung-localized pathogen-specific effector CD4+T cells during acute influenza infection. Influenza-specific IRF4−/− T cells failed to fully express CD44, and maintained high levels of CD62L compared to wild type, suggesting a defect in complete differentiation into lung-tropic effector T cells. -
(DHFR) As a Modulator of B- Catenin/GSK3 Signaling
A Lentivirus-Mediated Genetic Screen Identifies Dihydrofolate Reductase (DHFR) as a Modulator of b- Catenin/GSK3 Signaling Richard A. Klinghoffer1*, Jason Frazier1, James Annis1, Jason D. Berndt2, Brian S. Roberts1, William T. Arthur1, Raul Lacson3, Xiaohua Douglas Zhang4, Marc Ferrer3, Randall T. Moon2, Michele A. Cleary1 1 Rosetta Inpharmatics, LLC, Seattle, Washington, United States of America, 2 Howard Hughes Medical Institute, Institute for Stem Cell and Regenerative Medicine, and Department of Pharmacology, University of Washington School of Medicine, Seattle, Washington, United States of America, 3 Department of Automated Biotechnology, Merck Research Laboratories, Merck & Co., Inc., North Wales, Pennsylvania, United States of America, 4 Department of Biometrics Research, Merck Research Laboratories, Merck & Co., Inc., West Point, Pennsylvania, United States of America Abstract The multi-protein b-catenin destruction complex tightly regulates b-catenin protein levels by shuttling b-catenin to the proteasome. Glycogen synthase kinase 3b (GSK3b), a key serine/threonine kinase in the destruction complex, is responsible for several phosphorylation events that mark b-catenin for ubiquitination and subsequent degradation. Because modulation of both b-catenin and GSK3b activity may have important implications for treating disease, a complete understanding of the mechanisms that regulate the b-catenin/GSK3b interaction is warranted. We screened an arrayed lentivirus library expressing small hairpin RNAs (shRNAs) targeting 5,201 human druggable genes for silencing events that activate a b- catenin pathway reporter (BAR) in synergy with 6-bromoindirubin-39oxime (BIO), a specific inhibitor of GSK3b. Top screen hits included shRNAs targeting dihydrofolate reductase (DHFR), the target of the anti-inflammatory compound methotrexate. Exposure of cells to BIO plus methotrexate resulted in potent synergistic activation of BAR activity, reduction of b-catenin phosphorylation at GSK3-specific sites, and accumulation of nuclear b-catenin. -
Profilin-1 Is Required for Survival of Adult Hematopoietic Stem Cells
Extended methods Immunohistochemistry HepG-2, SMMC-7721, and 293T cells were obtained from Cell Resource Center of Shanghai Institute for Biological Science, Chinese Academy Science, Shanghai, China. HUVEC cells were kindly provided by Prof. Ping-Jin Gao at Institute of Health Sciences (Shanghai, China). All these cell lines were cultured in DMEM with 10% FBS. MDA- MB-231 cell line was kindly provided by Prof. Ming-Yao Liu (East China Normal University, Shanghai, China) and was cultured in Leibovitz L-15 medium with 10% FBS. All these cell lines were originally purchased from ATCC. MDA-MB-231, SMMC-7721 or HepG2 cells were grown on coverslips in 24-well plates and fixed in either 4% paraformaldehyde or pre-chilled methanol (-20°C) for 10 min. In some cases, WT or VPS33B-null Lin-Sca-1+c-Kit+Flk2-CD34- LT-HSCs were collected by flow cytometry and fixed for immunofluorescence staining. Cells were then blocked with 3% BSA in PBS for 60 min followed by incubation with primary antibodies overnight. The antibodies used were anti-HA (Sigma), anti-Flag (Sigma), anti-VPS33B (Sigma), anti- VPS16B (Abcam), anti-GDI2 (Proteintech), anti-LAMP1 (Proteintech), anti-FLOT1 (Abways), anti-CD63 (Proteintech), anti-ANGPTL2 (R&D system), anti-ANGPTL3 (R&D system), anti-TPO (Abways), anti-GLUT1 (Proteintech), anti-LDHA (Proteintech), anti-PKM2 (CST), anti-RAB11A (Abways), anti-RAB27A (Abways) and anti-V5 (Biodragon). Fluorescent-conjugated secondary antibodies (Alexa Fluor® 488 or Alexa Fluor® 555) against mouse, rabbit, or goat were obtained from the Thermo Scientific Inc. The details for all the antibodies are listed in Table S3. -
CD Markers Are Routinely Used for the Immunophenotyping of Cells
ptglab.com 1 CD MARKER ANTIBODIES www.ptglab.com Introduction The cluster of differentiation (abbreviated as CD) is a protocol used for the identification and investigation of cell surface molecules. So-called CD markers are routinely used for the immunophenotyping of cells. Despite this use, they are not limited to roles in the immune system and perform a variety of roles in cell differentiation, adhesion, migration, blood clotting, gamete fertilization, amino acid transport and apoptosis, among many others. As such, Proteintech’s mini catalog featuring its antibodies targeting CD markers is applicable to a wide range of research disciplines. PRODUCT FOCUS PECAM1 Platelet endothelial cell adhesion of blood vessels – making up a large portion molecule-1 (PECAM1), also known as cluster of its intracellular junctions. PECAM-1 is also CD Number of differentiation 31 (CD31), is a member of present on the surface of hematopoietic the immunoglobulin gene superfamily of cell cells and immune cells including platelets, CD31 adhesion molecules. It is highly expressed monocytes, neutrophils, natural killer cells, on the surface of the endothelium – the thin megakaryocytes and some types of T-cell. Catalog Number layer of endothelial cells lining the interior 11256-1-AP Type Rabbit Polyclonal Applications ELISA, FC, IF, IHC, IP, WB 16 Publications Immunohistochemical of paraffin-embedded Figure 1: Immunofluorescence staining human hepatocirrhosis using PECAM1, CD31 of PECAM1 (11256-1-AP), Alexa 488 goat antibody (11265-1-AP) at a dilution of 1:50 anti-rabbit (green), and smooth muscle KD/KO Validated (40x objective). alpha-actin (red), courtesy of Nicola Smart. PECAM1: Customer Testimonial Nicola Smart, a cardiovascular researcher “As you can see [the immunostaining] is and a group leader at the University of extremely clean and specific [and] displays Oxford, has said of the PECAM1 antibody strong intercellular junction expression, (11265-1-AP) that it “worked beautifully as expected for a cell adhesion molecule.” on every occasion I’ve tried it.” Proteintech thanks Dr. -
Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7, -
Intratumoral Injection of SYNB1891, a Synthetic Biotic Medicine Designed
Intratumoral injection of SYNB1891 A Synthetic Biotic medicine designed to activate the innate immune system. Therapy demonstrates target engagement in humans including intratumoral STING activation. Janku F, MD Anderson Cancer Center; Luke JJ, UPMC Hillman Cancer Center; Brennan AM, Synlogic; Riese RJ, Synlogic; Varterasian M, Pharmaceutical Consultant; Kuhn K, Synlogic; Sokolovska A, Synlogic; Strauss J, Mary Crowley Cancer Research Presented by Filip Janku, MD, PhD Study supported by Synlogic, Inc American Association for Cancer Research (AACR) April 2021 Introduction and Methods SYNB1891 Strain Phase 1 First-in-Human Clinical Trial • Live, modified strain of the probiotic E. coli • Enrolling patients with refractory advanced solid Nissle engineered to produce cyclic tumors or lymphoma dinucleotides (CDN) under hypoxia leading to stimulator of interferon genes (STING)- • Intratumoral (IT) injection of SYNB1891 on Days activation 1, 8 and 15 of the first 21-day cycle and then on Day 1 of each subsequent cycle. • Preferentially taken up by phagocytic antigen- presenting cells in tumors, activating • Dose escalation planned across 7 cohorts (1x106 complementary innate immune pathways – 1x109 live cells) with Arm 1 consisting of (direct CDN STING activation; cGAS-mediated SYNB1891 as monotherapy, and Arm 2 in STING activation and TLR4/MyD88 activation by combination with atezolizumab the bacterial chassis) SYNB1891 was safe and well-tolerated in heterogenous population Nov 2020: Interim Analysis IA Updated through 15 Mar 2021 15 Mar 2021: -
The Role of Dubs in the Post-Translational Control of Cell Migration
Essays in Biochemistry (2019) 63 579–594 https://doi.org/10.1042/EBC20190022 Review Article The role of DUBs in the post-translational control of cell migration Guillem Lambies1,2, Antonio Garc´ıade Herreros1,2 and V´ıctor M. D´ıaz1,2,3 1Programa de Recerca en Cancer,` Institut Hospital del Mar d’Investigacions Mediques` (IMIM), Unidad Asociada CSIC, Barcelona, Spain; 2Departament de Ciencies` Experimentals i de la Salut, Universitat Pompeu Fabra (UPF), Barcelona, Spain; 3Faculty of Medicine and Health Sciences, International University of Catalonia, Sant Cugat del Valles,` Barcelona, Spain Downloaded from https://portlandpress.com/essaysbiochem/article-pdf/63/5/579/859061/ebc-2019-0022c.pdf by guest on 05 November 2019 Correspondence: V.M. Dıaz´ ([email protected])orA.Garcıa´ de Herreros ([email protected]) Cell migration is a multifactorial/multistep process that requires the concerted action of growth and transcriptional factors, motor proteins, extracellular matrix remodeling and proteases. In this review, we focus on the role of transcription factors modulat- ing Epithelial-to-Mesenchymal Transition (EMT-TFs), a fundamental process supporting both physiological and pathological cell migration. These EMT-TFs (Snail1/2, Twist1/2 and Zeb1/2) are labile proteins which should be stabilized to initiate EMT and provide full mi- gratory and invasive properties. We present here a family of enzymes, the deubiquitinases (DUBs) which have a crucial role in counteracting polyubiquitination and proteasomal degra- dation of EMT-TFs after their induction by TGFβ, inflammatory cytokines and hypoxia. We also describe the DUBs promoting the stabilization of Smads, TGFβ receptors and other key proteins involved in transduction pathways controlling EMT. -
Functional Gene Clusters in Global Pathogenesis of Clear Cell Carcinoma of the Ovary Discovered by Integrated Analysis of Transcriptomes
International Journal of Environmental Research and Public Health Article Functional Gene Clusters in Global Pathogenesis of Clear Cell Carcinoma of the Ovary Discovered by Integrated Analysis of Transcriptomes Yueh-Han Hsu 1,2, Peng-Hui Wang 1,2,3,4,5 and Chia-Ming Chang 1,2,* 1 Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei 112, Taiwan; [email protected] (Y.-H.H.); [email protected] (P.-H.W.) 2 School of Medicine, National Yang-Ming University, Taipei 112, Taiwan 3 Institute of Clinical Medicine, National Yang-Ming University, Taipei 112, Taiwan 4 Department of Medical Research, China Medical University Hospital, Taichung 440, Taiwan 5 Female Cancer Foundation, Taipei 104, Taiwan * Correspondence: [email protected]; Tel.: +886-2-2875-7826; Fax: +886-2-5570-2788 Received: 27 April 2020; Accepted: 31 May 2020; Published: 2 June 2020 Abstract: Clear cell carcinoma of the ovary (ovarian clear cell carcinoma (OCCC)) is one epithelial ovarian carcinoma that is known to have a poor prognosis and a tendency for being refractory to treatment due to unclear pathogenesis. Published investigations of OCCC have mainly focused only on individual genes and lack of systematic integrated research to analyze the pathogenesis of OCCC in a genome-wide perspective. Thus, we conducted an integrated analysis using transcriptome datasets from a public domain database to determine genes that may be implicated in the pathogenesis involved in OCCC carcinogenesis. We used the data obtained from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) DataSets. We found six interactive functional gene clusters in the pathogenesis network of OCCC, including ribosomal protein, eukaryotic translation initiation factors, lactate, prostaglandin, proteasome, and insulin-like growth factor. -
Characterization and Proteomic-Transcriptomic Investigation of Monocarboxylate Transporter 6 Knockout Mice
Supplemental material to this article can be found at: http://molpharm.aspetjournals.org/content/suppl/2019/07/10/mol.119.116731.DC1 1521-0111/96/3/364–376$35.00 https://doi.org/10.1124/mol.119.116731 MOLECULAR PHARMACOLOGY Mol Pharmacol 96:364–376, September 2019 Copyright ª 2019 by The American Society for Pharmacology and Experimental Therapeutics Characterization and Proteomic-Transcriptomic Investigation of Monocarboxylate Transporter 6 Knockout Mice: Evidence of a Potential Role in Glucose and Lipid Metabolism s Robert S. Jones, Chengjian Tu, Ming Zhang, Jun Qu, and Marilyn E. Morris Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, New York (R.S.J., C.T., J.Q., M.E.M.); and New York State Center of Excellence in Bioinformatics and Life Sciences, Buffalo, New York (C.T., M.Z., J.Q.) Received March 21, 2019; accepted June 27, 2019 Downloaded from ABSTRACT Monocarboxylate transporter 6 [(MCT6), SLC16A5] is an or- Mct62/2 mice demonstrated significant changes in 199 genes phan transporter with no known endogenous substrates or in the liver compared with Mct61/1 mice. In silico biological physiological role. Previous in vitro and in vivo experiments pathway analyses revealed significant changes in proteins and molpharm.aspetjournals.org investigated MCT6 substrate/inhibitor specificity in Xenopus genes involved in glucose and lipid metabolism–associated laevis oocytes; however, these data remain limited. Transcrip- pathways. This study is the first to provide evidence for an tomic changes in the livers of mice undergoing different dieting association of Mct6 in the regulation of glucose and lipid schemes have suggested that Mct6 plays a role in glucose metabolism.