Epigenetic Modulation of Immune Synaptic-Cytoskeletal Networks
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Genomic and Expression Profiling of Chromosome 17 in Breast Cancer Reveals Complex Patterns of Alterations and Novel Candidate Genes
[CANCER RESEARCH 64, 6453–6460, September 15, 2004] Genomic and Expression Profiling of Chromosome 17 in Breast Cancer Reveals Complex Patterns of Alterations and Novel Candidate Genes Be´atrice Orsetti,1 Me´lanie Nugoli,1 Nathalie Cervera,1 Laurence Lasorsa,1 Paul Chuchana,1 Lisa Ursule,1 Catherine Nguyen,2 Richard Redon,3 Stanislas du Manoir,3 Carmen Rodriguez,1 and Charles Theillet1 1Ge´notypes et Phe´notypes Tumoraux, EMI229 INSERM/Universite´ Montpellier I, Montpellier, France; 2ERM 206 INSERM/Universite´ Aix-Marseille 2, Parc Scientifique de Luminy, Marseille cedex, France; and 3IGBMC, U596 INSERM/Universite´Louis Pasteur, Parc d’Innovation, Illkirch cedex, France ABSTRACT 17q12-q21 corresponding to the amplification of ERBB2 and collinear genes, and a large region at 17q23 (5, 6). A number of new candidate Chromosome 17 is severely rearranged in breast cancer. Whereas the oncogenes have been identified, among which GRB7 and TOP2A at short arm undergoes frequent losses, the long arm harbors complex 17q21 or RP6SKB1, TBX2, PPM1D, and MUL at 17q23 have drawn combinations of gains and losses. In this work we present a comprehensive study of quantitative anomalies at chromosome 17 by genomic array- most attention (6–10). Furthermore, DNA microarray studies have comparative genomic hybridization and of associated RNA expression revealed additional candidates, with some located outside current changes by cDNA arrays. We built a genomic array covering the entire regions of gains, thus suggesting the existence of additional amplicons chromosome at an average density of 1 clone per 0.5 Mb, and patterns of on 17q (8, 9). gains and losses were characterized in 30 breast cancer cell lines and 22 Our previous loss of heterozygosity mapping data pointed to the primary tumors. -
An Ontogenetic Switch Drives the Positive and Negative Selection of B Cells
An ontogenetic switch drives the positive and negative selection of B cells Xijin Xua, Mukta Deobagkar-Lelea, Katherine R. Bulla, Tanya L. Crockforda, Adam J. Meadb, Adam P. Cribbsc, David Simsc, Consuelo Anzilottia, and Richard J. Cornalla,1 aMedical Research Council Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, OX3 9DS Oxford, United Kingdom; bMedical Research Council Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, OX3 9DS Oxford, United Kingdom; and cMedical Research Council, Weatherall Institute of Molecular Medicine, Centre for Computational Biology, Weatherall Institute of Molecular Medicine, University of Oxford, OX3 9DS Oxford, United Kingdom Edited by Michael Reth, University of Freiburg, Freiburg, Germany, and approved January 6, 2020 (received for review September 3, 2019) + Developing B cells can be positively or negatively selected by self- BM HSCs increased CD5 B-1a B cell development (15), while antigens, but the mechanisms that determine these outcomes are expression of let-7b in FL pro-B cells blocked the development of incompletely understood. Here, we show that a B cell intrinsic B-1 B cells (17). These findings support the notion of hard-wired switch between positive and negative selection during ontogeny differences during ontogeny, but possibly downstream of the HSC is determined by a change from Lin28b to let-7 gene expression. commitment stage. Ectopic expression of a Lin28b transgene in murine B cells restored Several lines of evidence also suggest that B-1 B cells can un- the positive selection of autoreactive B-1 B cells by self-antigen in dergo positive selection, which is linked to their B cell receptor adult bone marrow. -
B Cell Checkpoints in Autoimmune Rheumatic Diseases
REVIEWS B cell checkpoints in autoimmune rheumatic diseases Samuel J. S. Rubin1,2,3, Michelle S. Bloom1,2,3 and William H. Robinson1,2,3* Abstract | B cells have important functions in the pathogenesis of autoimmune diseases, including autoimmune rheumatic diseases. In addition to producing autoantibodies, B cells contribute to autoimmunity by serving as professional antigen- presenting cells (APCs), producing cytokines, and through additional mechanisms. B cell activation and effector functions are regulated by immune checkpoints, including both activating and inhibitory checkpoint receptors that contribute to the regulation of B cell tolerance, activation, antigen presentation, T cell help, class switching, antibody production and cytokine production. The various activating checkpoint receptors include B cell activating receptors that engage with cognate receptors on T cells or other cells, as well as Toll-like receptors that can provide dual stimulation to B cells via co- engagement with the B cell receptor. Furthermore, various inhibitory checkpoint receptors, including B cell inhibitory receptors, have important functions in regulating B cell development, activation and effector functions. Therapeutically targeting B cell checkpoints represents a promising strategy for the treatment of a variety of autoimmune rheumatic diseases. Antibody- dependent B cells are multifunctional lymphocytes that contribute that serve as precursors to and thereby give rise to acti- cell- mediated cytotoxicity to the pathogenesis of autoimmune diseases -
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. -
A20 Regulates the Therapeutic Effect of Anti-PD-1 Immunotherapy In
Open access Original research J Immunother Cancer: first published as 10.1136/jitc-2020-001866 on 9 December 2020. Downloaded from A20 regulates the therapeutic effect of anti- PD-1 immunotherapy in melanoma Weinan Guo,1 Jinyuan Ma,1 Sen Guo,1 Huina Wang,1 Sijia Wang,1,2 Qiong Shi,1 Lin Liu,1 Tao Zhao,1 Fengfan Yang,3 Shuyang Chen,4 Jianru Chen,1 Jianhong Zhao,1 Chen Yu,1 Xiuli Yi,1 Yuqi Yang,1 Jingjing Ma,1 Qingrong Ni,1 Guannan Zhu,1 1 1 Tianwen Gao, Chunying Li To cite: Guo W, Ma J, Guo S, ABSTRACT (PD-1)/programmed death ligand 1 (PD-L1) et al. A20 regulates the Background The therapeutic effect of immune have been demonstrated as a pair of major therapeutic effect of anti- PD-1 checkpoint blockers, especially the neutralizing immunotherapy in melanoma. immune checkpoint molecules and valuable antibodies of programmed cell death (PD-1) and its ligand 1 Journal for ImmunoTherapy therapeutic targets for melanoma treatment. programmed death ligand 1 (PD-L1), has been well verified of Cancer 2020;8:e001866. For instance, the binding of membrane doi:10.1136/jitc-2020-001866 in melanoma. Nevertheless, the dissatisfactory response rate and the occurrence of resistance significantly hinder PD- L1 on tumor cells to PD-1 on T cells the treatment effect. Inflammation- related molecules like evokes an immunosuppressive signal that ► Additional material is results in the dysfunction and even the apop- published online only. To view A20 are greatly implicated in cancer immune response, please visit the journal online but the role of tumorous A20 in antitumor immunity and tosis of cytotoxic T cells, thereby impairing 2 (http:// dx. -
Human Neonatal B Cell Immunity Differs from the Adult Version by Conserved Ig Repertoires and Rapid, but Transient Response Dynamics
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.11.245985; this version posted September 10, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Human neonatal B cell immunity differs from the adult version by conserved Ig repertoires and rapid, but transient response dynamics Bettina Budeus,1,# Artur Kibler,1,# Martina Brauser,1,# Ekaterina Homp,1,# Kevin Bronischewski,1 J. Alexander Ross,1 Andre Görgens,2,3 Marc A. Weniger,1 Josefine Dunst,4,5 Taras Kreslavsky,4,5 Symone Vitoriano da Conceição Castro,2,6 Florian Murke,2 Christopher C. Oakes,7,8 Peter Rusch,9 Dimitrios Andrikos,9 Peter Kern,9 Angela Köninger,9 Monika Lindemann,2 Patricia Johansson,10 Wiebke Hansen,11 Anna-Carin Lundell,12 Anna Rudin,12 Jan Dürig,10 Bernd Giebel,2 Daniel Hoffmann,13 Ralf Küppers,1 Marc Seifert1* 1Institute of Cell Biology (Cancer Research), Medical Faculty, University of Duisburg-Essen, 45147 Essen, Germany. 2Institute for Transfusion Medicine, Medical Faculty, University of Duisburg-Essen, Essen 45147, Germany. 3Department of Laboratory Medicine, Karolinska Institute, Stockholm 17177, Sweden. 4Division of Immunology and Allergy, Department of Medicine Solna, Karolinska Institute, Karolinska University Hospital, Stockholm 17177, Sweden. 5Center for Molecular Medicine, Karolinska Institute, Stockholm 17177, Sweden 6CAPES Foundation, Ministry of Education of Brazil, Brasília 70610-908, Brazil. 7Department of Internal Medicine, Division of Hematology, The Ohio State University, Columbus, OH 43210, USA. 8Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA. 9Department of Gynecology, Medical Faculty, University of Duisburg- Essen, Essen 45147, Germany. -
Gamma Tubulin (TUBG1) (NM 001070) Human Untagged Clone Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for SC119462 gamma Tubulin (TUBG1) (NM_001070) Human Untagged Clone Product data: Product Type: Expression Plasmids Product Name: gamma Tubulin (TUBG1) (NM_001070) Human Untagged Clone Tag: Tag Free Symbol: TUBG1 Synonyms: CDCBM4; GCP-1; TUBG; TUBGCP1 Vector: pCMV6-XL5 E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: None Fully Sequenced ORF: >OriGene ORF within SC119462 sequence for NM_001070 edited (data generated by NextGen Sequencing) ATGCCGAGGGAAATCATCACCCTACAGTTGGGCCAGTGCGGCAATCAGATTGGGTTCGAG TTCTGGAAACAGCTGTGCGCCGAGCATGGTATCAGCCCCGAGGGCATCGTGGAGGAGTTC GCCACCGAGGGCACTGACCGCAAGGACGTCTTTTTCTACCAGGCAGACGATGAGCACTAC ATCCCCCGGGCCGTGCTGCTGGACTTGGAACCCCGGGTGATCCACTCCATCCTCAACTCC CCCTATGCCAAGCTCTACAACCCAGAGAACATCTACCTGTCGGAACATGGAGGAGGAGCT GGCAACAACTGGGCCAGCGGATTCTCCCAGGGAGAAAAGATCCATGAGGACATTTTTGAC ATCATAGACCGGGAGGCAGATGGTAGTGACAGTCTAGAGGGCTTTGTGCTGTGTCACTCC ATTGCTGGGGGGACAGGCTCTGGACTGGGTTCCTACCTCTTAGAACGGCTGAATGACAGG TATCCTAAGAAGCTGGTGCAGACATACTCAGTGTTTCCCAACCAGGACGAGATGAGCGAT GTGGTGGTCCAGCCTTACAATTCACTCCTCACACTCAAGAGGCTGACGCAGAATGCAGAC TGTGTGGTGGTGCTGGACAACACAGCCCTGAACCGGATTGCCACAGACCGCCTGCACATC CAGAACCCATCCTTCTCCCAGATCAACCAGCTGGTGTCTACCATCATGTCAGCCAGCACC ACCACCCTGCGCTACCCTGGCTACATGAACAATGACCTCATCGGCCTCATCGCCTCGCTC ATTCCCACCCCACGGCTCCACTTCCTCATGACCGGCTACACCCCTCTCACTACGGACCAG TCAGTGGCCAGCGTGAGGAAGACCACGGTCCTGGATGTCATGAGGCGGCTGCTGCAGCCC -
Proseek Multiplex Oncology I V296×96
Proseek Multiplex Oncology I v296×96 Adrenomedullin (AM) P35318 Fms-related tyrosine kinase 3 ligand (Flt3L) P49771 Amphiregulin (AR) P15514 Folate receptor alpha (FR-alpha) P15328 Angiopoietin-1 receptor (TIE2) Q02763 Follistatin (FS) P19883 B-cell activating factor (BAFF) Q9Y275 Furin (FUR) P09958 Cadherin-3 (CDH3) P22223 Growth hormone (GH) P01241 Carbonic anhydrase IX (CAIX) Q16790 Growth/differentiation factor 15 (GDF-15) Q99988 Carcinoembryonic antigen (CEA) P06731 Heparin-binding EGF-like growth factor (HB-EGF) Q99075 Caspase-3 (CASP-3) P42574 Hepatocyte growth factor (HGF) P14210 C-C motif chemokine 19 (CCL19) Q99731 ICOS ligand (ICOSLG) O75144 CD40 ligand (CD40-L) P29965 Immunoglobulin-like transcript 3 (ILT-3) Q8NHJ6 C-X-C motif chemokine 5 (CXCL5 ) P42830 Integrin alpha-1 (ITGA1) P56199 C-X-C motif chemokine 9 (CXCL9 ) Q07325 Interferon gamma (IFN-gamma) P01579 C-X-C motif chemokine 10 (CXCL10 ) P02778 Interleukin-1 receptor antagonist protein (IL-1ra) P18510 C-X-C motif chemokine 11 (CXCL11 ) O14625 Interleukin-2 (IL-2) P60568 C-X-C motif chemokine 13 (CXCL13 ) O43927 Interleukin-6 (IL-6) P05231 Cyclin-dependent kinase inhibitor 1 (CDKN1A) P38936 Interleukin-6 receptor subunit alpha (IL-6RA) P08887 Cystatin-B (CSTB) P04080 Interleukin-7 (IL-7) P13232 Early activation antigen CD69 (CD69 ) Q07108 Interleukin-8 (IL-8) P10145 Epidermal growth factor receptor (EGFR ) P00533 Interleukin-12 (IL-12) P29460; P29459 Epididymal secretory protein E4 (HE4 ) Q14508 Interleukin-17 receptor B (IL-17RB ) Q9NRM6 Epithelial cell adhesion molecule -
Targeting Costimulatory Molecules in Autoimmune Disease
Targeting costimulatory molecules in autoimmune disease Natalie M. Edner1, Gianluca Carlesso2, James S. Rush3 and Lucy S.K. Walker1 1Institute of Immunity & Transplantation, Division of Infection & Immunity, University College London, Royal Free Campus, London, UK NW3 2PF 2Early Oncology Discovery, Early Oncology R&D, AstraZeneca, Gaithersburg, MD, USA 3Autoimmunity, Transplantation and Inflammation Disease Area, Novartis Institutes for Biomedical Research, Basel, Switzerland *Correspondence: Professor Lucy S.K. Walker. Institute of Immunity & Transplantation, Division of Infection & Immunity, University College London, Royal Free Campus, London, UK NW3 2PF. Tel: +44 (0)20 7794 0500 ext 22468. Email: [email protected]. 1 Abstract Therapeutic targeting of immune checkpoints has garnered significant attention in the area of cancer immunotherapy, and efforts have focused in particular on the CD28 family members CTLA-4 and PD-1. In autoimmunity, these same pathways can be targeted to opposite effect, to curb the over- exuberant immune response. The CTLA-4 checkpoint serves as an exemplar, whereby CTLA-4 activity is blocked by antibodies in cancer immunotherapy and augmented by the provision of soluble CTLA-4 in autoimmunity. Here we review the targeting of costimulatory molecules in autoimmune disease, focusing in particular on the CD28 family and TNFR family members. We present the state-of-the-art in costimulatory blockade approaches, including rational combinations of immune inhibitory agents, and discuss the future opportunities and challenges in this field. 2 The risk of autoimmune disease is an inescapable consequence of the manner in which the adaptive immune system operates. To ensure effective immunity against a diverse array of unknown pathogens, antigen recognition systems based on random gene rearrangement and mutagenesis have evolved to anticipate the antigenic universe. -
A Patient-Derived, Pan-Cancer EMT Signature Identifies Global Molecular Alterations and Immune Target Enrichment Following Epithelial-To-Mesenchymal Transition
Published OnlineFirst September 29, 2015; DOI: 10.1158/1078-0432.CCR-15-0876 Cancer Therapy: Preclinical Clinical Cancer Research A Patient-Derived, Pan-Cancer EMT Signature Identifies Global Molecular Alterations and Immune Target Enrichment Following Epithelial-to-Mesenchymal Transition Milena P. Mak1,2, Pan Tong3, Lixia Diao3, Robert J. Cardnell1, Don L. Gibbons1,4, William N. William1, Ferdinandos Skoulidis1, Edwin R. Parra5, Jaime Rodriguez-Canales5, Ignacio I.Wistuba5, John V.Heymach1, John N.Weinstein3, Kevin R.Coombes6, Jing Wang3, and Lauren Averett Byers1 Abstract Purpose: We previously demonstrated the association between EMT markers across diverse tumor types and identifies differences epithelial-to-mesenchymal transition (EMT) and drug response in in drug sensitivity and global molecular alterations at the DNA, lung cancer using an EMT signature derived in cancer cell lines. RNA, and protein levels. Among those changes associated with Given the contribution of tumor microenvironments to EMT, we EMT, pathway analysis revealed a strong correlation between EMT extended our investigation of EMT to patient tumors from 11 and immune activation. Further supervised analysis demonstrat- cancer types to develop a pan-cancer EMT signature. ed high expression of immune checkpoints and other druggable Experimental Design: Using the pan-cancer EMT signature, we immune targets, such as PD1, PD-L1, CTLA4, OX40L, and PD-L2, conducted an integrated, global analysis of genomic and prote- in tumors with the most mesenchymal EMT scores. Elevated omic profiles associated with EMT across 1,934 tumors including PD-L1 protein expression in mesenchymal tumors was confirmed breast, lung, colon, ovarian, and bladder cancers. Differences in by IHC in an independent lung cancer cohort. -
Recombinant Human TUBG1 Protein Catalog Number: ATGP3767
Recombinant human TUBG1 protein Catalog Number: ATGP3767 PRODUCT INPORMATION Expression system Baculovirus Domain 1-451aa UniProt No. P23258 NCBI Accession No. NP_001061 Alternative Names Tubulin gamma-1 chain, TUBG1, CDCBM4, GCP-1, TUBG, TUBGCP1 PRODUCT SPECIFICATION Molecular Weight 51.9 kDa (457aa) Concentration 0.25mg/ml (determined by Bradford assay) Formulation Liquid in. 20mM Tris-HCl buffer (pH 8.0) containing 40% glycerol, 0.1M NaCl, 2mM DTT, 50mM imidazole. Purity > 85% by SDS-PAGE Endotoxin level < 1 EU per 1ug of protein (determined by LAL method) Tag His-Tag Application SDS-PAGE Storage Condition Can be stored at +2C to +8C for 1 week. For long term storage, aliquot and store at -20C to -80C. Avoid repeated freezing and thawing cycles. BACKGROUND Description TUBG1, also known as tubulin gamma-1 chain, is a member of the tubulin superfamily. This protein is found at microtubule organizing centers (MTOC) such as the spindle poles or the centrosome. It is the pericentriolar matrix component that regulates alpha/beta tubulin minus-end nucleation, centrosome duplication and spindle formation. It is required for microtubule formation and progression of the cell cycle. Also, this protein is interacts 1 Recombinant human TUBG1 protein Catalog Number: ATGP3767 with GCP2, GCP3, and B9D2. The interaction is leading to centrosomal localization of TUBG1 and CDK5RAP2. Recombinant human TUBG1, fused to His-tag at C-terminus, was expressed in insect cell and purified by using conventional chromatography techniques. Amino acid Sequence MPREIITLQL -
1 Beyond Autoantibodies: Biological Roles of Human Autoreactive B Cells in Rheumatoid Arthritis Revealed by Whole Transcriptome
bioRxiv preprint doi: https://doi.org/10.1101/144121; this version posted June 1, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Beyond autoantibodies: Biological roles of human autoreactive B cells in rheumatoid arthritis revealed by whole transcriptome profiling. Ankit Mahendra1, Xingyu Yang2, Shaza Abnouf1, Daechan Park3, Sanam Soomro4, Jay RT Adolacion1, Jason Roszik5, Cristian Coarfa6, Gabrielle Romain1, Keith Wanzeck7, S. Louis Bridges Jr.7, Amita Aggarwal8, Peng Qiu2, Sandeep Krishna Agarwal9, Chandra Mohan4, Navin Varadarajan1 Author affiliations 1. Department of Chemical & Biomolecular Engineering, University of Houston, Houston, TX 2. Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia 3. Center for Theragnosis, Biomedical Research Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea 4. Department of Biomedical Engineering, University of Houston, Houston, TX 5. Department of Melanoma Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 6. Department of Molecular and Cell Biology, Baylor College of Medicine, Houston, TX 7. Division of Clinical Immunology & Rheumatology, University of Alabama at Birmingham, Birmingham, AL 8. Department of Clinical Immunology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India 9. Section of Immunology, Allergy and Immunology, Department of Medicine, Baylor College of Medicine, Houston, TX Address for correspondence: Dr. Navin Varadarajan ([email protected]) 1 bioRxiv preprint doi: https://doi.org/10.1101/144121; this version posted June 1, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.