Anti-MAML1 (Aa 655-754) Polyclonal Antibody (DPAB-DC3896) This Product Is for Research Use Only and Is Not Intended for Diagnostic Use

Total Page:16

File Type:pdf, Size:1020Kb

Anti-MAML1 (Aa 655-754) Polyclonal Antibody (DPAB-DC3896) This Product Is for Research Use Only and Is Not Intended for Diagnostic Use Anti-MAML1 (aa 655-754) polyclonal antibody (DPAB-DC3896) This product is for research use only and is not intended for diagnostic use. PRODUCT INFORMATION Antigen Description This protein is the human homolog of mastermind, a Drosophila protein that plays a role in the Notch signaling pathway involved in cell-fate determination. There is in vitro evidence that the human homolog forms a complex with the intracellular portion of human Notch receptors and can increase expression of a Notch-induced gene. This evidence supports its proposed function as a transcriptional co-activator in the Notch signaling pathway. Immunogen MAML1 (NP_055572, 655 a.a. ~ 754 a.a) partial recombinant protein with GST tag. The sequence is AEQEKQQFQRHLTRPPPQYQDPTQGSFPQQVGQFTGSSAAVPGMNTLGPSNSSCPRVFPQA GNLMPMGPGHASVSSLPTNSGQQDRGVAQFPGSQNMPQS Source/Host Mouse Species Reactivity Human Conjugate Unconjugated Applications WB (Recombinant protein), ELISA, Size 50 μl Buffer 50 % glycerol Preservative None Storage Store at -20°C or lower. Aliquot to avoid repeated freezing and thawing. GENE INFORMATION Gene Name MAML1 mastermind-like 1 (Drosophila) [ Homo sapiens (human) ] Official Symbol MAML1 Synonyms MAML1; mastermind-like 1 (Drosophila); Mam1; Mam-1; mastermind-like protein 1; mastermind homolog; 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 1 © Creative Diagnostics All Rights Reserved Entrez Gene ID 9794 Protein Refseq NP_055572 UniProt ID Q92585 Chromosome Location 5q35 Pathway Constitutive Signaling by NOTCH1 HD+PEST Domain Mutants; Delta-Notch Signaling Pathway; FBXW7 Mutants and NOTCH1 in Cancer; Generic Transcription Pathway Function peptide antigen binding; protein binding; protein kinase binding; transcription coactivator activity 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 2 © Creative Diagnostics All Rights Reserved.
Recommended publications
  • MAML1 Antibody A
    Revision 1 C 0 2 - t MAML1 Antibody a e r o t S Orders: 877-616-CELL (2355) [email protected] Support: 877-678-TECH (8324) 8 0 Web: [email protected] 6 www.cellsignal.com 4 # 3 Trask Lane Danvers Massachusetts 01923 USA For Research Use Only. Not For Use In Diagnostic Procedures. Applications: Reactivity: Sensitivity: MW (kDa): Source: UniProt ID: Entrez-Gene Id: WB, IP H Endogenous 130 Rabbit Q92585 9794 Product Usage Information Application Dilution Western Blotting 1:1000 Immunoprecipitation 1:50 Storage Supplied in 10 mM sodium HEPES (pH 7.5), 150 mM NaCl, 100 µg/ml BSA and 50% glycerol. Store at –20°C. Do not aliquot the antibody. Specificity / Sensitivity MAML1 Antibody detects endogenous levels of total MAML1 protein. It does not cross- react with MAML2 and MAML3. Species Reactivity: Human Source / Purification Polyclonal antibodies are produced by immunizing animals with a synthetic peptide corresponding to residues surrounding His811 of human MAML1. Antibodies are purified by protein A and peptide affinity chromatography. Background Mastermind-like (MAML) family of proteins are homologs of Drosophila Mastermind. The family is composed of three members in mammals: MAML1, MAML2, and MAML3 (1,2). MAML proteins form complexes with the intracellular domain of Notch (ICN) and the transcription factor CSL (RBP-Jκ) to regulate Notch target gene expression (3-5). MAML1 also interacts with myocyte enhancer factor 2C (MEF2C) to regulate myogenesis (6). MAML2 is frequently found to be fused with Mucoepidermoid carcinoma translocated gene 1 (MECT1, also know as WAMTP1 or TORC1) in patients with mucoepidermoid carcinomas and Warthin's tumors (7).
    [Show full text]
  • Cystatin-B Negatively Regulates the Malignant Characteristics of Oral Squamous Cell Carcinoma Possibly Via the Epithelium Proliferation/ Differentiation Program
    ORIGINAL RESEARCH published: 24 August 2021 doi: 10.3389/fonc.2021.707066 Cystatin-B Negatively Regulates the Malignant Characteristics of Oral Squamous Cell Carcinoma Possibly Via the Epithelium Proliferation/ Differentiation Program Tian-Tian Xu 1, Xiao-Wen Zeng 1, Xin-Hong Wang 2, Lu-Xi Yang 1, Gang Luo 1* and Ting Yu 1* 1 Department of Periodontics, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China, 2 Department of Oral Pathology and Medicine, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Guangzhou, China Disturbance in the proteolytic process is one of the malignant signs of tumors. Proteolysis Edited by: Eva Csosz, is highly orchestrated by cysteine cathepsin and its inhibitors. Cystatin-B (CSTB) is a University of Debrecen, Hungary general cysteine cathepsin inhibitor that prevents cysteine cathepsin from leaking from Reviewed by: lysosomes and causing inappropriate proteolysis. Our study found that CSTB was Csongor Kiss, downregulated in both oral squamous cell carcinoma (OSCC) tissues and cells University of Debrecen, Hungary Gergely Nagy, compared with normal controls. Immunohistochemical analysis showed that CSTB was University of Debrecen, Hungary mainly distributed in the epithelial structure of OSCC tissues, and its expression intensity *Correspondence: was related to the grade classification. A correlation analysis between CSTB and clinical Gang Luo [email protected] prognosis was performed using gene expression data and clinical information acquired Ting Yu from The Cancer Genome Atlas (TCGA) database. Patients with lower expression levels of [email protected] CSTB had shorter disease-free survival times and poorer clinicopathological features Specialty section: (e.g., lymph node metastases, perineural invasion, low degree of differentiation, and This article was submitted to advanced tumor stage).
    [Show full text]
  • Selenite Inhibits Notch Signaling in Cells and Mice
    International Journal of Molecular Sciences Article Selenite Inhibits Notch Signaling in Cells and Mice Michael Powers 1, Liu Liu 1, Dane Deemer 1, Selina Chen 1, Aaron Scholl 1, Masafumi Yoshinaga 2 and Zijuan Liu 1,* 1 Department of Biological Sciences, Oakland University, Rochester, MI 48309, USA; [email protected] (M.P.); [email protected] (L.L.); [email protected] (D.D.); [email protected] (S.C.); [email protected] (A.S.) 2 Department of Cellular Biology and Pharmacology, Herbert Wertheim College of Medicine, Florida International University, Miami, FL 33199, USA; myoshina@fiu.edu * Correspondence: [email protected]; Tel.: +1-248-370-3554 Abstract: Selenium is an essential micronutrient with a wide range of biological effects in mammals. The inorganic form of selenium, selenite, is supplemented to relieve individuals with selenium deficiency and to alleviate associated symptoms. Additionally, physiological and supranutritional selenite have shown selectively higher affinity and toxicity towards cancer cells, highlighting their potential to serve as chemotherapeutic agents or adjuvants. At varying doses, selenite extensively regulates cellular signaling and modulates many cellular processes. In this study, we report the identification of Delta–Notch signaling as a previously uncharacterized selenite inhibited target. Our transcriptomic results in selenite treated primary mouse hepatocytes revealed that the tran- scription of Notch1, Notch2, Hes1, Maml1, Furin and c-Myc were all decreased following selenite treatment. We further showed that selenite can inhibit Notch1 expression in cultured MCF7 breast adenocarcinoma cells and HEPG2 liver carcinoma cells. In mice acutely treated with 2.5 mg/kg Citation: Powers, M.; Liu, L.; selenite via intraperitoneal injection, we found that Notch1 expression was drastically lowered in Deemer, D.; Chen, S.; Scholl, A.; liver and kidney tissues by 90% and 70%, respectively.
    [Show full text]
  • Computational Approach to Identify Mutations in Genes of Notch Signaling Pathway and Its Association with OSCC
    Journal of Pharmaceutical Research International 32(20): 84-92, 2020; Article no.JPRI.59681 ISSN: 2456-9119 (Past name: British Journal of Pharmaceutical Research, Past ISSN: 2231-2919, NLM ID: 101631759) Computational Approach to Identify Mutations in Genes of Notch Signaling Pathway and Its Association with OSCC Madhumithaa Sivarajan1, A. S. Smiline Girija2, A. Paramasivam3 and J. Vijayashree Priyadharsini3* 1Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, India. 2Department of Microbiology, Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, 162 , Poonamallee High Road, Chennai 600077, Tamil Nadu, India. 3Biomedical Research Unit and Laboratory Animal Centre-Dental Research Cell, Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai 600077, India. Authors’ contributions This work was carried out in collaboration among all authors. Author JVP designed the study, performed the statistical analysis, wrote the protocol and wrote the first draft of the manuscript. Authors ASSG and AP managed the analyses of the study. Author MS managed the literature searches and certain computational analysis. All authors read and approved the final manuscript. Article Information DOI: 10.9734/JPRI/2020/v32i2030732 Editor(s): (1) Dr. Mohamed Fawzy Ramadan Hassanien, Zagazig University, Egypt. Reviewers: (1) Mustika Tuwo, Hasanuddin University, Indonesia. (2) Maysaa
    [Show full text]
  • Interpreting Cancer Genomes Using Systematic Host Perturbations by Tumour Virus Proteins
    Interpreting Cancer Genomes Using Systematic Host Perturbations by Tumour Virus Proteins The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Rozenblatt-Rosen, Orit, Rahul C. Deo, Megha Padi, Guillaume Adelmant, Michael A. Calderwood, Thomas Rolland, Miranda Grace, et al. 2012. Interpreting cancer genomes using systematic host perturbations by tumour virus proteins. Nature 487(7408): 491-495. Published Version doi:10.1038/nature11288 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:10612841 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA NIH Public Access Author Manuscript Nature. Author manuscript; available in PMC 2013 January 26. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Nature. 2012 July 26; 487(7408): 491–495. doi:10.1038/nature11288. Interpreting cancer genomes using systematic host perturbations by tumour virus proteins Orit Rozenblatt-Rosen1,2,*,#, Rahul C. Deo3,4,*,#, Megha Padi5,6,*,#, Guillaume Adelmant3,7,*,#, Michael A. Calderwood8,9,10,*,^, Thomas Rolland8,9,*,^, Miranda Grace11,*,^, Amélie Dricot8,9,*,^, Manor Askenazi3,7,*,^, Maria Tavares1,2,7,*,^, Sam Pevzner8,9,12,^, Fieda Abderazzaq5,*, Danielle Byrdsong8,9,*, Anne-Ruxandra Carvunis8,9, Alyce A. Chen11,*, Jingwei Cheng1,2, Mick Correll5, Melissa Duarte8,10,*, Changyu Fan8,9,*, Mariet C. Feltkamp13, Scott B. Ficarro3,7,*, Rachel Franchi8,14,*, Brijesh K. Garg3,7,*, Natali Gulbahce8,15,16,*, Tong Hao8,9,*, Amy M.
    [Show full text]
  • A Single Cell but Many Different Transcripts
    International Journal of Molecular Sciences Review A Single Cell but Many Different Transcripts: A Journey into the World of Long Non-Coding RNAs Enrico Alessio 1, Raphael Severino Bonadio 1, Lisa Buson 1, Francesco Chemello 1 and Stefano Cagnin 1,2,3,* 1 Department of Biology, University of Padova, 35131 Padova, Italy; [email protected] (E.A.); [email protected] (R.S.B.); [email protected] (L.B.), [email protected] (F.C.) 2 CRIBI Biotechnology Center, University of Padova, 35131 Padova, Italy 3 CIR-Myo Myology Center, University of Padova, 35131 Padova, Italy * Correspondence: [email protected]; Tel.: +39-049-827-6162 Received: 22 November 2019; Accepted: 23 December 2019; Published: 1 January 2020 Abstract: In late 2012 it was evidenced that most of the human genome is transcribed but only a small percentage of the transcripts are translated. This observation supported the importance of non-coding RNAs and it was confirmed in several organisms. The most abundant non-translated transcripts are long non-coding RNAs (lncRNAs). In contrast to protein-coding RNAs, they show a more cell-specific expression. To understand the function of lncRNAs, it is fundamental to investigate in which cells they are preferentially expressed and to detect their subcellular localization. Recent improvements of techniques that localize single RNA molecules in tissues like single-cell RNA sequencing and fluorescence amplification methods have given a considerable boost in the knowledge of the lncRNA functions. In recent years, single-cell transcription variability was associated with non-coding RNA expression, revealing this class of RNAs as important transcripts in the cell lineage specification.
    [Show full text]
  • Data-Driven and Knowledge-Driven Computational Models of Angiogenesis in Application to Peripheral Arterial Disease
    DATA-DRIVEN AND KNOWLEDGE-DRIVEN COMPUTATIONAL MODELS OF ANGIOGENESIS IN APPLICATION TO PERIPHERAL ARTERIAL DISEASE by Liang-Hui Chu A dissertation submitted to Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland March, 2015 © 2015 Liang-Hui Chu All Rights Reserved Abstract Angiogenesis, the formation of new blood vessels from pre-existing vessels, is involved in both physiological conditions (e.g. development, wound healing and exercise) and diseases (e.g. cancer, age-related macular degeneration, and ischemic diseases such as coronary artery disease and peripheral arterial disease). Peripheral arterial disease (PAD) affects approximately 8 to 12 million people in United States, especially those over the age of 50 and its prevalence is now comparable to that of coronary artery disease. To date, all clinical trials that includes stimulation of VEGF (vascular endothelial growth factor) and FGF (fibroblast growth factor) have failed. There is an unmet need to find novel genes and drug targets and predict potential therapeutics in PAD. We use the data-driven bioinformatic approach to identify angiogenesis-associated genes and predict new targets and repositioned drugs in PAD. We also formulate a mechanistic three- compartment model that includes the anti-angiogenic isoform VEGF165b. The thesis can serve as a framework for computational and experimental validations of novel drug targets and drugs in PAD. ii Acknowledgements I appreciate my advisor Dr. Aleksander S. Popel to guide my PhD studies for the five years at Johns Hopkins University. I also appreciate several professors on my thesis committee, Dr. Joel S. Bader, Dr.
    [Show full text]
  • Bioinformatics to Integrate Protein and Gene Information in a Relational Context, Application to Human Proteomic and Transcriptomic Data
    TESIS DOCTORAL BIOINFORMATICS TO INTEGRATE PROTEIN AND GENE INFORMATION IN A RELATIONAL CONTEXT, APPLICATION TO HUMAN PROTEOMIC AND TRANSCRIPTOMIC DATA CONRAD FRIEDRICH DROSTE DIRECTOR DR. JAVIER DE LAS RIVAS SANZ SALAMANCA, JULIO DE 2017 El Dr. Javier De Las Rivas Sanz, con D.N.I. 15949000H, Investigador Científico del Consejo Superior de Investigaciones Científicas (CSIC), director del grupo de Bioinformática y Genómica Funcional en el Instituto de Biología Molecular y Celular del Cáncer (CiC-IBMCC), y profesor del Programa de Doctorado y del Máster de Biología y Clínica del Cáncer de dicho Instituto y la Universidad de Salamanca (USAL). CERTIFICA Que ha dirigido esta Tesis Doctoral titulada "BIOINFORMATICS TO INTEGRATE PROTEIN AND GENE INFORMATION IN A RELATIONAL CONTEXT, APPLICATION TO HUMAN PROTEOMIC AND TRANSCRIPTOMIC DATA" realizada por D. Conrad Friedrich Droste, alumno del Programa de Doctorado de 2012/2013 de la Universidad de Salamanca. y AUTORIZA La presentación de la misma, considerando que reúne las condiciones de originalidad y contenidos requeridos para optar al grado de Doctor por la Universidad de Salamanca. En Salamanca, a 7 de julio de 2017 Dr. Javier De Las Rivas Sanz To my parents, Heike and Friedel and my loved ones. I have to apologize to Pigena for all the time I missed to enjoy with her. ACKNOWLEDGEMENTS & APPRECIATIONS I am deeply grateful to my Ph.D. director Dr. Javier De Las Rivas for the opportunity to realize this work in his research group. His guidance, encouragement and support during these time were always appreciated and needed. I owe a very important debt to Dr.
    [Show full text]
  • Interpreting Cancer Genomes Using Systematic Host Perturbations By
    LETTER doi:10.1038/nature11288 Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins Orit Rozenblatt-Rosen1,2,3*, Rahul C. Deo1,4,5*,MeghaPadi1,6,7*, Guillaume Adelmant1,4,8*, Michael A. Calderwood1,9,10,11, Thomas Rolland1,9,10, Miranda Grace1,12,Ame´lie Dricot1,9,10, Manor Askenazi1,4,8, Maria Tavares1,2,3,8,SamuelJ.Pevzner9,10,13, Fieda Abderazzaq1,6, Danielle Byrdsong1,9,10, Anne-Ruxandra Carvunis9,10, Alyce A. Chen1,12, Jingwei Cheng2,3,MickCorrell6, Melissa Duarte1,9,11,ChangyuFan1,9,10, Mariet C. Feltkamp14, Scott B. Ficarro1,4,8, Rachel Franchi1,9,15, Brijesh K. Garg1,4,8, Natali Gulbahce1,9,16,17,TongHao1,9,10, Amy M. Holthaus1,11,RobertJames1,9,10, Anna Korkhin1,2,3, Larisa Litovchick1,2,3, Jessica C. Mar1,6,7,TheodoreR.Pak18, Sabrina Rabello1,3,9,16, Renee Rubio1,6,YunShen1,9,10, Saurav Singh4,8, Jennifer M. Spangle1,12, Murat Tasan1,4,18, Shelly Wanamaker9,10,15, James T. Webber4,8, Jennifer Roecklein-Canfield9,15,EricJohannsen1,11, Albert-La´szlo´ Baraba´si1,3,9,16,RameenBeroukhim3,19,20, Elliott Kieff1,11, Michael E. Cusick1,9,10, David E. Hill1,9,10, Karl Mu¨nger1,12, Jarrod A. Marto1,4,8,JohnQuackenbush1,6,7, Frederick P. Roth1,4,9,18, James A. DeCaprio1,2,3 & Marc Vidal1,9,10 Genotypic differences greatly influence susceptibility and resist- which DNA tumour virus proteins physically target the products of ance to disease. Understanding genotype–phenotype relationships RB1 or TP53, two well-established germline-inherited and somatically requires that phenotypes be viewed as manifestations of network inactivated tumour-suppressor genes6.
    [Show full text]
  • Supporting Information
    Supporting Information Miller et al. 10.1073/pnas.0914257107 SI Materials and Methods files with 20 to 40 samples and 5,629 to 9,731 genes each and 20 Data Set Acquisition and Filtering. All data sets were downloaded mouse expression files with 18 and 44 samples and 5,176 to 6,157 from the GEO database, and consisted of experiments run on genes each. All preprocessed data files (as well as the resulting either mouse or human brain tissue (Fig. 1A). We filtered out all network data and some associated code and support files) are but a core collection of data sets that were similar enough for available at the WGCNA group Web site (www.genetics.ucla.edu/ useful bioinformatic comparison. First, we removed all data sets labs/horvath/CoexpressionNetwork/MouseHumanBrain). that were not run on an Affymetrix platform, leaving three From these preprocessed expression files we created a human platforms in human (HG-U95A, HG-U133A, HG-U133 Plus 2) and a mouse consensus network (method modified from ref. 4). and two in mouse (MG-U74A, MG-U430A). Second, we ex- For each consensus network we first created correlation matrices cluded all samples in each data set that were not taken from from each data set (obtained by calculating the Pearson correla- brain tissue (for example, in one expression atlas study, more tions between all variable probe sets across all subjects in each than 80% of the samples were excluded). Third, to make the data set), and then weighted them based on the number of sam- correlations between genes more comparable across studies, we ples used in that data set.
    [Show full text]
  • Atlas Journal
    Atlas of Genetics and Cytogenetics in Oncology and Haematology Home Genes Leukemias Solid Tumours Cancer-Prone Deep Insight Portal Teaching X Y 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 NA Atlas Journal Atlas Journal versus Atlas Database: the accumulation of the issues of the Journal constitutes the body of the Database/Text-Book. TABLE OF CONTENTS Volume 12, Number 3, May-Jun 2008 Previous Issue / Next Issue Genes SOCS2 (suppressor of cytokine signaling 2) (12q21.33). Leandro Fernández-Pérez, Amilcar Flores-Morales. Atlas Genet Cytogenet Oncol Haematol 2008; Vol (12): 351-355. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/SOCS2ID44123ch12q21.html PTHLH (parathyroid hormone-like hormone) (12p11.22). Sai-Ching Jim Yeung. Atlas Genet Cytogenet Oncol Haematol 2008; Vol (12): 356-367. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/PTHLHID41897ch12p11.html MUC17 (mucin 17, cell surface associated) (7q22.1). Wade M Junker, Nicolas Moniaux, Surinder K Batra. Atlas Genet Cytogenet Oncol Haematol 2008; Vol (12): 368-378. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/MUC17ID41456ch7q22.html MUC16 (mucin 16, cell surface associated) (19p13.2). Shantibhusan Senapati, Moorthy P Ponnusamy, Ajay P Singh, Maneesh Jain, Surinder K Batra. Atlas Genet Cytogenet Oncol Haematol 2008; Vol (12): 379-384. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/MUC16ID41455ch19q13.html MAML2 (mastermind-like 2) (11q21) - updated. Kazumi Suzukawa, Jean Loup Huret. Atlas Genet Cytogenet Oncol Haematol 2008; Vol (12): 385-390. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/MAML2ID472.html HYAL1 (hyaluronoglucosaminidase 1) (3p21.3).
    [Show full text]
  • From High-Dimensional Data to Disease Mechanisms
    From High-Dimensional Data to Disease Mechanisms NOTCH Signaling in Hodgkin Lymphoma DISSERTATION zur Erlangung des akademischen Grades doctor rerum naturalium (Dr. rer. nat.) im Fach Biologie eingereicht an der Mathematisch-Naturwissenschaftlichen Fakultät I Humboldt-Universität zu Berlin von Dipl.-Biochemiker Karl Köchert Präsident der Humboldt-Universität zu Berlin: Prof. Dr. Jan-Hendrik Olbertz Dekan der Mathematisch-Naturwissenschaftlichen Fakultät I: Prof. Dr. Andreas Herrmann Gutachter: 1. Prof. Dr. Harald Saumweber 2. Prof. Dr. Georg Lenz 3. Prof. Dr. Joachim Selbig eingereicht am: 27.10.2010 Tag der mündlichen Prüfung: 02.03.2011 Abstract Inappropriate activation of the NOTCH signaling pathway, e.g. by activating mu- tations, contributes to the pathogenesis of various human malignancies. Using a bottom up approach based on the acquisition of high–dimensional microarray data of classical Hodgkin lymphoma (cHL) and non-Hodgkin B cell lymphomas as control, we identify a cHL specific NOTCH gene-expression signature domi- nated by the NOTCH co-activator Mastermind-like 2 (MAML2). This set the basis for demonstrating that aberrant expression of the essential NOTCH co- activator MAML2 provides an alternative mechanism to activate NOTCH signal- ing in human lymphoma cells. Using immunohistochemistry we detected high-level MAML2 expression in several B cell-derived lymphoma types, including cHL cells, whereas in normal B cells no staining for MAML2 was detectable. Inhibition of MAML protein activity by a dominant negative form of MAML or by shRNAs targeting MAML2 in cHL cells resulted in down-regulation of the NOTCH target genes HES7 and HEY1, which we identified as overexpressed in cHL cells, and in reduced proliferation.
    [Show full text]