Posttranslational Regulation of the Exon Skipping Machinery Controls Aberrant Splicing in Leukemia
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PSMA4 Antibody (Monoclonal) (M01) Mouse Monoclonal Antibody Raised Against a Full Length Recombinant PSMA4
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 PSMA4 Antibody (monoclonal) (M01) Mouse monoclonal antibody raised against a full length recombinant PSMA4. Catalog # AT3454a Specification PSMA4 Antibody (monoclonal) (M01) - Product Information Application IF, WB, E Primary Accession P25789 Other Accession BC005361 Reactivity Human Host mouse Clonality Monoclonal Isotype IgG2b kappa Calculated MW 29484 PSMA4 Antibody (monoclonal) (M01) - Additional Information Immunofluorescence of monoclonal antibody to PSMA4 on HeLa cell. [antibody concentration 10 ug/ml] Gene ID 5685 Other Names Proteasome subunit alpha type-4, Macropain subunit C9, Multicatalytic endopeptidase complex subunit C9, Proteasome component C9, Proteasome subunit L, PSMA4, HC9, PSC9 Target/Specificity PSMA4 (AAH05361, 1 a.a. ~ 261 a.a) full-length recombinant protein with GST tag. MW of the GST tag alone is 26 KDa. Dilution WB~~1:500~1000 Antibody Reactive Against Recombinant Protein.Western Blot detection against Format Immunogen (54.45 KDa) . Clear, colorless solution in phosphate buffered saline, pH 7.2 . Storage Store at -20°C or lower. Aliquot to avoid repeated freezing and thawing. Precautions PSMA4 Antibody (monoclonal) (M01) is for research use only and not for use in diagnostic or therapeutic procedures. Page 1/3 10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 PSMA4 Antibody (monoclonal) (M01) - Protocols Provided below are standard protocols that you may find useful for product applications. • Western Blot • Blocking Peptides • Dot Blot • Immunohistochemistry • Immunofluorescence • Immunoprecipitation • Flow Cytomety • Cell Culture PSMA4 monoclonal antibody (M01), clone 2A10-E4 Western Blot analysis of PSMA4 expression in Hela ( (Cat # AT3454a ) Detection limit for recombinant GST tagged PSMA4 is approximately 3ng/ml as a capture antibody. -
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. -
Constitutive Activation of RAS/MAPK Pathway Cooperates with Trisomy 21 and Is Therapeutically Exploitable in Down Syndrome B-Cell Leukemia
Author Manuscript Published OnlineFirst on March 27, 2020; DOI: 10.1158/1078-0432.CCR-19-3519 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Constitutive activation of RAS/MAPK pathway cooperates with trisomy 21 and is therapeutically exploitable in Down syndrome B-cell Leukemia Anouchka P. Laurent1,2, Aurélie Siret1, Cathy Ignacimouttou1, Kunjal Panchal3, M’Boyba K. Diop4, Silvia Jenny5, Yi-Chien Tsai5, Damien Ross-Weil1, Zakia Aid1, Naïs Prade6, Stéphanie Lagarde6, Damien Plassard7, Gaelle Pierron8, Estelle Daudigeos-Dubus4, Yann Lecluse4, Nathalie Droin1, Beat Bornhauser5, Laurence C. Cheung3,9, John D. Crispino10, Muriel Gaudry1, Olivier A. Bernard1, Elizabeth Macintyre11, Carole Barin Bonnigal12, Rishi S. Kotecha3,9,13, Birgit Geoerger4, Paola Ballerini14, Jean-Pierre Bourquin5, Eric Delabesse6, Thomas Mercher1,15 and Sébastien Malinge1,3 1INSERM U1170, Gustave Roussy Institute, Université Paris Saclay, Villejuif, France 2Université Paris Diderot, Paris, France 3Telethon Kids Cancer Centre, Telethon Kids Institute, University of Western Australia, Perth, Australia 4Gustave Roussy Institute Cancer Campus, Department of Pediatric and Adolescent Oncology, INSERM U1015, Equipe Labellisée Ligue Nationale contre le Cancer, Université Paris-Saclay, Villejuif, France 5Department of Pediatric Oncology, Children’s Research Centre, University Children’s Hospital Zurich, Zurich, Switzerland 6Centre of Research on Cancer of Toulouse (CRCT), CHU Toulouse, Université Toulouse III, Toulouse, France 7IGBMC, Plateforme GenomEast, UMR7104 CNRS, Ilkirch, France 8Service de Génétique, Institut Curie, Paris, France 9School of Pharmacy and Biomedical Sciences, Curtin University, Bentley, Australia 10Division of Hematology/Oncology, Northwestern University, Chicago, USA 11Hematology, Université de Paris, Institut Necker-Enfants Malades and Assistance Publique – Hopitaux de Paris, Paris, France 12Centre Hospitalier Universitaire de Tours, Tours, France 1 Downloaded from clincancerres.aacrjournals.org on September 30, 2021. -
Role of Phytochemicals in Colon Cancer Prevention: a Nutrigenomics Approach
Role of phytochemicals in colon cancer prevention: a nutrigenomics approach Marjan J van Erk Promotor: Prof. Dr. P.J. van Bladeren Hoogleraar in de Toxicokinetiek en Biotransformatie Wageningen Universiteit Co-promotoren: Dr. Ir. J.M.M.J.G. Aarts Universitair Docent, Sectie Toxicologie Wageningen Universiteit Dr. Ir. B. van Ommen Senior Research Fellow Nutritional Systems Biology TNO Voeding, Zeist Promotiecommissie: Prof. Dr. P. Dolara University of Florence, Italy Prof. Dr. J.A.M. Leunissen Wageningen Universiteit Prof. Dr. J.C. Mathers University of Newcastle, United Kingdom Prof. Dr. M. Müller Wageningen Universiteit Dit onderzoek is uitgevoerd binnen de onderzoekschool VLAG Role of phytochemicals in colon cancer prevention: a nutrigenomics approach Marjan Jolanda van Erk Proefschrift ter verkrijging van graad van doctor op gezag van de rector magnificus van Wageningen Universiteit, Prof.Dr.Ir. L. Speelman, in het openbaar te verdedigen op vrijdag 1 oktober 2004 des namiddags te vier uur in de Aula Title Role of phytochemicals in colon cancer prevention: a nutrigenomics approach Author Marjan Jolanda van Erk Thesis Wageningen University, Wageningen, the Netherlands (2004) with abstract, with references, with summary in Dutch ISBN 90-8504-085-X ABSTRACT Role of phytochemicals in colon cancer prevention: a nutrigenomics approach Specific food compounds, especially from fruits and vegetables, may protect against development of colon cancer. In this thesis effects and mechanisms of various phytochemicals in relation to colon cancer prevention were studied through application of large-scale gene expression profiling. Expression measurement of thousands of genes can yield a more complete and in-depth insight into the mode of action of the compounds. -
Supplementary Table S1. Correlation Between the Mutant P53-Interacting Partners and PTTG3P, PTTG1 and PTTG2, Based on Data from Starbase V3.0 Database
Supplementary Table S1. Correlation between the mutant p53-interacting partners and PTTG3P, PTTG1 and PTTG2, based on data from StarBase v3.0 database. PTTG3P PTTG1 PTTG2 Gene ID Coefficient-R p-value Coefficient-R p-value Coefficient-R p-value NF-YA ENSG00000001167 −0.077 8.59e-2 −0.210 2.09e-6 −0.122 6.23e-3 NF-YB ENSG00000120837 0.176 7.12e-5 0.227 2.82e-7 0.094 3.59e-2 NF-YC ENSG00000066136 0.124 5.45e-3 0.124 5.40e-3 0.051 2.51e-1 Sp1 ENSG00000185591 −0.014 7.50e-1 −0.201 5.82e-6 −0.072 1.07e-1 Ets-1 ENSG00000134954 −0.096 3.14e-2 −0.257 4.83e-9 0.034 4.46e-1 VDR ENSG00000111424 −0.091 4.10e-2 −0.216 1.03e-6 0.014 7.48e-1 SREBP-2 ENSG00000198911 −0.064 1.53e-1 −0.147 9.27e-4 −0.073 1.01e-1 TopBP1 ENSG00000163781 0.067 1.36e-1 0.051 2.57e-1 −0.020 6.57e-1 Pin1 ENSG00000127445 0.250 1.40e-8 0.571 9.56e-45 0.187 2.52e-5 MRE11 ENSG00000020922 0.063 1.56e-1 −0.007 8.81e-1 −0.024 5.93e-1 PML ENSG00000140464 0.072 1.05e-1 0.217 9.36e-7 0.166 1.85e-4 p63 ENSG00000073282 −0.120 7.04e-3 −0.283 1.08e-10 −0.198 7.71e-6 p73 ENSG00000078900 0.104 2.03e-2 0.258 4.67e-9 0.097 3.02e-2 Supplementary Table S2. -
Identification of Differential Modules in Ankylosing Spondylitis Using Systemic Module Inference and the Attract Method
EXPERIMENTAL AND THERAPEUTIC MEDICINE 16: 149-154, 2018 Identification of differential modules in ankylosing spondylitis using systemic module inference and the attract method FANG-CHANG YUAN1, BO LI2 and LI-JUN ZHANG3 1Department of Orthopedics, People's Hospital of Rizhao, Rizhao, Shandong 276826; 2Department of Joint Surgery, Hospital of Xinjiang Production and Construction Corps, Urumchi, Xinjiang Uygur Autonomous Region 830002; 3Department of Orthopedics, The Fifth People's Hospital of Jinan, Jinan, Shandong 250022, P.R. China Received July 15, 2016; Accepted April 28, 2017 DOI: 10.3892/etm.2018.6134 Abstract. The objective of the present study was to identify spondyloarthropathies, which also includes reactive arthritis, differential modules in ankylosing spondylitis (AS) by inte- psoriatic arthritis and enteropathic arthritis (1). Several grating network analysis, module inference and the attract features, such as synovitis, chondroid metaplasia, cartilage method. To achieve this objective, four steps were conducted. destruction and subchondral bone marrow changes, are The first step was disease objective network (DON) for AS, commonly observed in the joints of patients with AS (2). Due and healthy objective network (HON) inference dependent on to the complex progression of the joint remodeling process, gene expression data, protein-protein interaction networks and clinical research has not systematically evaluated histopatho- Spearman's correlation coefficient. In the second step, module logical changes (3), and no clear sequence of the pathological detection was performed by utilizing a clique-merging algo- mechanism has been obtained for this disease. rithm, which comprised of exploring maximal cliques by clique With the development of high throughput technology and algorithm and refining or merging maximal cliques with a high gene data analysis over the past decade, rapid progress has been overlap. -
Table 1. Swine Proteins Identified As Differentially Expressed at 24Dpi in OURT 88/3 Infected Animals
Table 1. swine proteins identified as differentially expressed at 24dpi in OURT 88/3 infected animals. Gene name Protein ID Protein Name -Log p-value control vs A_24DPI Difference control Vs A_24DPI F8 K7GL28 Coagulation factor VIII 2.123919902 5.42533493 PPBP F1RUL6 C-X-C motif chemokine 3.219079808 4.493174871 SDPR I3LDR9 Caveolae associated protein 2 2.191007299 4.085711161 IGHG L8B0X5 IgG heavy chain 2.084611488 -4.282530149 LOC100517145 F1S3H9 Complement C3 (LOC100517145) 3.885740476 -4.364484406 GOLM1 F1S4I1 Golgi membrane protein 1 1.746130664 -4.767168681 FCN2 I3L5W3 Ficolin-2 2.937884686 -6.029483795 Table 2. swine proteins identified as differentially expressed at 7dpi in Benin ΔMGF infected animals. Gene name Protein ID Protein Name -Log p-value control vs B_7DPI Difference control Vs B_7DPI A0A075B7I5 Ig-like domain-containing protein 1.765578164 -3.480728149 ATP5A1 F1RPS8_PIG ATP synthase subunit alpha 2.270386995 3.270935059 LOC100627396 F1RX35_PIG Fibrinogen C-terminal domain-containing protein 2.211242648 3.967363358 LOC100514666;LOC102158263 F1RX36_PIG Fibrinogen alpha chain 2.337934993 3.758180618 FGB F1RX37_PIG Fibrinogen beta chain 2.411948004 4.03753376 PSMA8 F1SBA5_PIG Proteasome subunit alpha type 1.473601007 -3.815182686 ACAN F1SKR0_PIG Aggrecan core protein 1.974489764 -3.726634026 TFG F1SL01_PIG PB1 domain-containing protein 1.809215274 -3.131304741 LOC100154408 F1SSL6_PIG Proteasome subunit alpha type 1.701949053 -3.944885254 PSMA4 F2Z528_PIG Proteasome subunit alpha type 2.045768185 -4.502977371 PSMA5 F2Z5K2_PIG -
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. -
The Genetics of Bipolar Disorder
Molecular Psychiatry (2008) 13, 742–771 & 2008 Nature Publishing Group All rights reserved 1359-4184/08 $30.00 www.nature.com/mp FEATURE REVIEW The genetics of bipolar disorder: genome ‘hot regions,’ genes, new potential candidates and future directions A Serretti and L Mandelli Institute of Psychiatry, University of Bologna, Bologna, Italy Bipolar disorder (BP) is a complex disorder caused by a number of liability genes interacting with the environment. In recent years, a large number of linkage and association studies have been conducted producing an extremely large number of findings often not replicated or partially replicated. Further, results from linkage and association studies are not always easily comparable. Unfortunately, at present a comprehensive coverage of available evidence is still lacking. In the present paper, we summarized results obtained from both linkage and association studies in BP. Further, we indicated new potential interesting genes, located in genome ‘hot regions’ for BP and being expressed in the brain. We reviewed published studies on the subject till December 2007. We precisely localized regions where positive linkage has been found, by the NCBI Map viewer (http://www.ncbi.nlm.nih.gov/mapview/); further, we identified genes located in interesting areas and expressed in the brain, by the Entrez gene, Unigene databases (http://www.ncbi.nlm.nih.gov/entrez/) and Human Protein Reference Database (http://www.hprd.org); these genes could be of interest in future investigations. The review of association studies gave interesting results, as a number of genes seem to be definitively involved in BP, such as SLC6A4, TPH2, DRD4, SLC6A3, DAOA, DTNBP1, NRG1, DISC1 and BDNF. -
Role of Genomic Variants in the Response to Biologics Targeting Common Autoimmune Disorders
Role of genomic variants in the response to biologics targeting common autoimmune disorders by Gordana Lenert, PhD The thesis submitted to the Faculty of Graduate and Postdoctoral Affairs in partial fulfillment of the requirements for the degree of Master of Science Ottawa-Carleton Joint Program in Bioinformatics Carleton University Ottawa, Canada © 2016 Gordana Lenert Abstract Autoimmune diseases (AID) are common chronic inflammatory conditions initiated by the loss of the immunological tolerance to self-antigens. Chronic immune response and uncontrolled inflammation provoke diverse clinical manifestations, causing impairment of various tissues, organs or organ systems. To avoid disability and death, AID must be managed in clinical practice over long periods with complex and closely controlled medication regimens. The anti-tumor necrosis factor biologics (aTNFs) are targeted therapeutic drugs used for AID management. However, in spite of being very successful therapeutics, aTNFs are not able to induce remission in one third of AID phenotypes. In our research, we investigated genomic variability of AID phenotypes in order to explain unpredictable lack of response to aTNFs. Our hypothesis is that key genetic factors, responsible for the aTNFs unresponsiveness, are positioned at the crossroads between aTNF therapeutic processes that generate remission and pathogenic or disease processes that lead to AID phenotypes expression. In order to find these key genetic factors at the intersection of the curative and the disease pathways, we combined genomic variation data collected from publicly available curated AID genome wide association studies (AID GWAS) for each disease. Using collected data, we performed prioritization of genes and other genomic structures, defined the key disease pathways and networks, and related the results with the known data by the bioinformatics approaches. -
Supplementary Table 2
Supplementary Table 2. Differentially Expressed Genes following Sham treatment relative to Untreated Controls Fold Change Accession Name Symbol 3 h 12 h NM_013121 CD28 antigen Cd28 12.82 BG665360 FMS-like tyrosine kinase 1 Flt1 9.63 NM_012701 Adrenergic receptor, beta 1 Adrb1 8.24 0.46 U20796 Nuclear receptor subfamily 1, group D, member 2 Nr1d2 7.22 NM_017116 Calpain 2 Capn2 6.41 BE097282 Guanine nucleotide binding protein, alpha 12 Gna12 6.21 NM_053328 Basic helix-loop-helix domain containing, class B2 Bhlhb2 5.79 NM_053831 Guanylate cyclase 2f Gucy2f 5.71 AW251703 Tumor necrosis factor receptor superfamily, member 12a Tnfrsf12a 5.57 NM_021691 Twist homolog 2 (Drosophila) Twist2 5.42 NM_133550 Fc receptor, IgE, low affinity II, alpha polypeptide Fcer2a 4.93 NM_031120 Signal sequence receptor, gamma Ssr3 4.84 NM_053544 Secreted frizzled-related protein 4 Sfrp4 4.73 NM_053910 Pleckstrin homology, Sec7 and coiled/coil domains 1 Pscd1 4.69 BE113233 Suppressor of cytokine signaling 2 Socs2 4.68 NM_053949 Potassium voltage-gated channel, subfamily H (eag- Kcnh2 4.60 related), member 2 NM_017305 Glutamate cysteine ligase, modifier subunit Gclm 4.59 NM_017309 Protein phospatase 3, regulatory subunit B, alpha Ppp3r1 4.54 isoform,type 1 NM_012765 5-hydroxytryptamine (serotonin) receptor 2C Htr2c 4.46 NM_017218 V-erb-b2 erythroblastic leukemia viral oncogene homolog Erbb3 4.42 3 (avian) AW918369 Zinc finger protein 191 Zfp191 4.38 NM_031034 Guanine nucleotide binding protein, alpha 12 Gna12 4.38 NM_017020 Interleukin 6 receptor Il6r 4.37 AJ002942 -
Identification of Pediatric Onset Inflammatory Bowel
(19) TZZ ¥_T (11) EP 2 257 643 B1 (12) EUROPEAN PATENT SPECIFICATION (45) Date of publication and mention (51) Int Cl.: of the grant of the patent: C12Q 1/68 (2006.01) 08.04.2015 Bulletin 2015/15 (86) International application number: (21) Application number: 09712711.2 PCT/US2009/034586 (22) Date of filing: 19.02.2009 (87) International publication number: WO 2009/105590 (27.08.2009 Gazette 2009/35) (54) IDENTIFICATION OF PEDIATRIC ONSET INFLAMMATORY BOWEL DISEASE LOCI AND METHODS OF USE THEREOF FOR THE DIAGNOSIS AND TREATMENT OF THE SAME IDENTIFIZIERUNG DES AUSBRUCHS VON ENTZÜNDLICHEN DARMERKRANKUNGS-LOCI BEI KINDERN UND VERFAHREN ZUR VERWENDUNG DAVON BEI DEREN DIAGNOSE UND BEHANDLUNG IDENTIFICATION DE LOCI DE MALADIE INTESTINALE INFLAMMATOIRE À DÉBUT PÉDIATRIQUE ET SES PROCÉDÉS D’UTILISATION POUR SON DIAGNOSTIC ET SON TRAITEMENT (84) Designated Contracting States: (56) References cited: AT BE BG CH CY CZ DE DK EE ES FI FR GB GR WO-A2-2007/073478 HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO SE SI SK TR • YAMAZAKI KEIKO ET AL: "Single nucleotide polymorphisms in TNFSF15 confer susceptibility (30) Priority: 19.02.2008 US 29841 P to Crohn’s disease", HUMAN MOLECULAR 06.06.2008 US 59486 P GENETICS, vol. 14, no. 22, 15 November 2005 (2005-11-15), pages 3499-3506, XP009132501, (43) Date of publication of application: OXFORD UNIVERSITY PRESS, SURREY ISSN: 08.12.2010 Bulletin 2010/49 0964-6906, DOI: 10.1093/HMG/DDI379 [retrieved on 2005-10-13] (73) Proprietor: The Children’s Hospital Of • DATABASE dbSNP 25 May 2006 (2006-05-25), Philadelphia "SINGLE NUCLEOTIDE POLYMORPHISM", Philadelphia, PA 19104 (US) XP008140832, retrieved from ncbi Database accession no.