Investigation of the Role of Antagonism of the Interleukin-7 Receptor in The
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ENSG Gene Encodes Effector TCR Pathway Costimulation Inhibitory/Exhaustion Synapse/Adhesion Chemokines/Receptors
ENSG Gene Encodes Effector TCR pathway Costimulation Inhibitory/exhaustion Synapse/adhesion Chemokines/receptors ENSG00000111537 IFNG IFNg x ENSG00000109471 IL2 IL-2 x ENSG00000232810 TNF TNFa x ENSG00000271503 CCL5 CCL5 x x ENSG00000139187 KLRG1 Klrg1 x ENSG00000117560 FASLG Fas ligand x ENSG00000121858 TNFSF10 TRAIL x ENSG00000134545 KLRC1 Klrc1 / NKG2A x ENSG00000213809 KLRK1 Klrk1 / NKG2D x ENSG00000188389 PDCD1 PD-1 x x ENSG00000117281 CD160 CD160 x x ENSG00000134460 IL2RA IL-2 receptor x subunit alpha ENSG00000110324 IL10RA IL-10 receptor x subunit alpha ENSG00000115604 IL18R1 IL-18 receptor 1 x ENSG00000115607 IL18RAP IL-18 receptor x accessory protein ENSG00000081985 IL12RB2 IL-12 receptor x beta 2 ENSG00000186810 CXCR3 CXCR3 x x ENSG00000005844 ITGAL CD11a x ENSG00000160255 ITGB2 CD18; Integrin x x beta-2 ENSG00000156886 ITGAD CD11d x ENSG00000140678 ITGAX; CD11c x x Integrin alpha-X ENSG00000115232 ITGA4 CD49d; Integrin x x alpha-4 ENSG00000169896 ITGAM CD11b; Integrin x x alpha-M ENSG00000138378 STAT4 Stat4 x ENSG00000115415 STAT1 Stat1 x ENSG00000170581 STAT2 Stat2 x ENSG00000126561 STAT5a Stat5a x ENSG00000162434 JAK1 Jak1 x ENSG00000100453 GZMB Granzyme B x ENSG00000145649 GZMA Granzyme A x ENSG00000180644 PRF1 Perforin 1 x ENSG00000115523 GNLY Granulysin x ENSG00000100450 GZMH Granzyme H x ENSG00000113088 GZMK Granzyme K x ENSG00000057657 PRDM1 Blimp-1 x ENSG00000073861 TBX21 T-bet x ENSG00000115738 ID2 ID2 x ENSG00000176083 ZNF683 Hobit x ENSG00000137265 IRF4 Interferon x regulatory factor 4 ENSG00000140968 IRF8 Interferon -
Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 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. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
IL-7 Receptor Blockade Blunts Antigen-Specific Memory T Cell
ARTICLE DOI: 10.1038/s41467-018-06804-y OPEN IL-7 receptor blockade blunts antigen-specific memory T cell responses and chronic inflammation in primates Lyssia Belarif1,2, Caroline Mary1,2, Lola Jacquemont1, Hoa Le Mai1, Richard Danger1, Jeremy Hervouet1, David Minault1, Virginie Thepenier1,2, Veronique Nerrière-Daguin1, Elisabeth Nguyen1, Sabrina Pengam1,2, Eric Largy3,4, Arnaud Delobel3, Bernard Martinet1, Stéphanie Le Bas-Bernardet1,5, Sophie Brouard1,5, Jean-Paul Soulillou1, Nicolas Degauque 1,5, Gilles Blancho1,5, Bernard Vanhove1,2 & Nicolas Poirier1,2 1234567890():,; Targeting the expansion of pathogenic memory immune cells is a promising therapeutic strategy to prevent chronic autoimmune attacks. Here we investigate the therapeutic efficacy and mechanism of new anti-human IL-7Rα monoclonal antibodies (mAb) in non-human primates and show that, depending on the target epitope, a single injection of antagonistic anti-IL-7Rα mAbs induces a long-term control of skin inflammation despite repeated antigen challenges in presensitized monkeys. No modification in T cell numbers, phenotype, function or metabolism is observed in the peripheral blood or in response to polyclonal stimulation ex vivo. However, long-term in vivo hyporesponsiveness is associated with a significant decrease in the frequency of antigen-specific T cells producing IFN-γ upon antigen resti- mulation ex vivo. These findings indicate that chronic antigen-specific memory T cell responses can be controlled by anti-IL-7Rα mAbs, promoting and maintaining remission in T- cell mediated chronic inflammatory diseases. 1 Centre de Recherche en Transplantation et Immunologie (CRTI) UMR1064, INSERM, Université de Nantes, Nantes 44093, France. 2 OSE Immunotherapeutics, Nantes 44200, France. -
Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only. -
A1068-CD86 Polyclonal Antibody
BioVision 05/16 For research use only CD86 Polyclonal Antibody CATALOG NO: A1068-100 ALTERNATIVE NAMES: T-lymphocyte activation antigen CD86, Activation B7-2 antigen, B70, BU63, CTLA-4 counter-receptor B72, FUN-1, CD86, CD86, CD28LG2 Western blot analysis of CD86 in NCI-H292 cell line lysate AMOUNT: 100 µl IMMUNOGEN: KLH conjugated synthetic peptide between 269-298 amino acids from the C-terminal region of human CD86. MOLECULAR WEIGHT: 37 kDa HOST/ISOTYPE: Rabbit IgG SPECIES REACTIVITY: Human PURIFICATION: This antibody is purified through a protein A column, followed by peptide affinity purification. FORM: Liquid FORMULATION: Supplied in PBS with 0.09% (W/V) sodium azide. STORAGE CONDITIONS: Maintain refrigerated at 2-8°C for up to 6 months. For long term RELATED PRODUCTS storage store at -20°C in small aliquots to prevent freeze-thaw cycles. DESCRIPTION: This gene encodes a type I membrane protein that is a member of the immunoglobulin superfamily. This protein is expressed by Human CellExp™ B7-2 /CD86, human recombinant (Cat. No. 7496-10, -50) antigen-presenting cells, and it is the ligand for two proteins at the CD86 (Human) ELISA Kit (Cat. No. K4175-100) cell surface of T cells, CD28 antigen and cytotoxic T-lymphocyte- Human CellExp™LAG3 /CD223, human recombinant (Cat. No. 7278-10, -50) associated protein 4. Binding of this protein with CD28 antigen is a costimulatory signal for activation of the T-cell. Binding of this CD223 (LAG3) Polyclonal Antibody (Cat. No. A1067-100) protein with cytotoxic T-lymphocyte-associated protein 4 negatively regulates T-cell activation and diminishes the immune response. -
Molecular and Clinical Characterization of LAG3 in Breast Cancer Through 2994 Samples
Molecular and Clinical Characterization of LAG3 in Breast Cancer Through 2994 Samples Qiang Liu Chinese Academy of Medical Sciences & Peking Union Medical College Yihang Qi ( [email protected] ) Chinese Academy of Medical Sciences and Peking Union Medical College https://orcid.org/0000-0001- 7589-0333 Jie Zhai Chinese Academy of Medical Sciences & Peking Union Medical College Xiangyi Kong Chinese Academy of Medical Sciences & Peking Union Medical College Xiangyu Wang Chinese Academy of Medical Sciences & Peking Union Medical College Yi Fang Chinese Academy of Medical Sciences & Peking Union Medical College Jing Wang Chinese Academy of Medical Sciences & Peking Union Medical College Research Keywords: Cancer immunotherapy, CD223, LAG3, Immune response, Inammatory activity Posted Date: June 19th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-36422/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/33 Abstract Background Despite the promising impact of cancer immunotherapy targeting CTLA4 and PD1/PDL1, a large number of cancer patients fail to respond. LAG3 (Lymphocyte Activating 3), also named CD233, is a protein Coding gene served as alternative inhibitory receptors to be targeted in the clinic. The impact of LAG3 on immune cell populations and co-regulation of immune response in breast cancer remained largely unknown. Methods To characterize the role of LAG3 in breast cancer, we investigated transcriptome data and associated clinical information derived from a total of 2994 breast cancer patients. Results We observed that LAG3 was closely correlated with major molecular and clinical characteristics, and was more likely to be enriched in higher malignant subtype, suggesting LAG3 was a potential biomarker of triple-negative breast cancer. -
Diabetes in the Absence of LAG-3 Cutting Edge
Cutting Edge: Accelerated Autoimmune Diabetes in the Absence of LAG-3 Maria Bettini, Andrea L. Szymczak-Workman, Karen Forbes, Ashley H. Castellaw, Mark Selby, Xiaoyu Pan, This information is current as Charles G. Drake, Alan J. Korman and Dario A. A. Vignali of September 24, 2021. J Immunol 2011; 187:3493-3498; Prepublished online 26 August 2011; doi: 10.4049/jimmunol.1100714 http://www.jimmunol.org/content/187/7/3493 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2011/08/26/jimmunol.110071 Material 4.DC1 http://www.jimmunol.org/ References This article cites 25 articles, 11 of which you can access for free at: http://www.jimmunol.org/content/187/7/3493.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision by guest on September 24, 2021 • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2011 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Cutting Edge: Accelerated Autoimmune Diabetes in the Absence of LAG-3 Maria Bettini,* Andrea L. -
Point Mutation in CD19 Facilitates Immune Escape of B Cell Lymphoma from CAR-T Cell Therapy
Open access Original research J Immunother Cancer: first published as 10.1136/jitc-2020-001150 on 6 October 2020. Downloaded from Point mutation in CD19 facilitates immune escape of B cell lymphoma from CAR- T cell therapy 1 1 1 1 1 1 Zhen Zhang, Xinfeng Chen, Yonggui Tian, Feng Li , Xuan Zhao, Jinyan Liu, 1 1,2,3,4 Chang Yao, Yi Zhang To cite: Zhang Z, Chen X, ABSTRACT relapses after CD19 CAR-T cell therapy are Tian Y, et al. Point mutation Background Tumor relapse due to mutation in CD19 can attributed to the antigen loss, indicating an in CD19 facilitates immune hinder the efficacy of chimeric antigen receptor (CAR)- T urgent need for investigating the mechanisms escape of B cell lymphoma from cell therapy. Herein, we focused on lymphoma patients CAR- T cell therapy. Journal underlying recurrence and for improving whose B cells exhibited a point mutation in CD19 of B cells 4 5 for ImmunoTherapy of Cancer the efficacy of CAR- T cell therapy. Inter- 2020; :e001150. doi:10.1136/ after CAR-T cell infusion. 8 + estingly, one of the specific mechanisms jitc-2020-001150 Methods The CAR- T and CD19 B cells from peripheral blood or bone marrow were assessed using flow of tumor escape that has been reported cytometry. Genome sequencing was conducted to identify suggests that exon mutations affecting the ► Additional material is + published online only. To view, the molecular characteristics of CAR- T and CD19 B cells CD19 gene and its splicing isoforms, leading please visit the journal online from pre-rela pse and postrelapse samples. -
LAG-3: from Molecular Functions to Clinical Applications
Open access Review J Immunother Cancer: first published as 10.1136/jitc-2020-001014 on 13 September 2020. Downloaded from LAG-3: from molecular functions to clinical applications Takumi Maruhashi , Daisuke Sugiura , Il- mi Okazaki , Taku Okazaki To cite: Maruhashi T, Sugiura D, ABSTRACT (PD-1) and cytotoxic T lymphocyte antigen Okazaki I, et al. LAG-3: from To prevent the destruction of tissues owing to excessive 4 (CTLA-4) significantly improved the molecular functions to clinical and/or inappropriate immune responses, immune outcomes of patients with diverse cancer applications. Journal for cells are under strict check by various regulatory ImmunoTherapy of Cancer types, revolutionizing cancer treatment. The mechanisms at multiple points. Inhibitory coreceptors, 2020;8:e001014. doi:10.1136/ success of these therapies verified that inhib- including programmed cell death 1 (PD-1) and cytotoxic jitc-2020-001014 itory coreceptors serve as critical checkpoints T lymphocyte antigen 4 (CTLA-4), serve as critical checkpoints in restricting immune responses against for immune cells to not attack the tumor Accepted 29 July 2020 self- tissues and tumor cells. Immune checkpoint inhibitors cells as well as self-tissues. However, response that block PD-1 and CTLA-4 pathways significantly rates are typically lower and immune-related improved the outcomes of patients with diverse cancer adverse events (irAEs) are also observed in types and have revolutionized cancer treatment. However, patients administered with immune check- response rates to such therapies are rather limited, and point inhibitors. This is indicative of the immune-rela ted adverse events are also observed in a continued need to decipher the complex substantial patient population, leading to the urgent need biology of inhibitory coreceptors to increase for novel therapeutics with higher efficacy and lower response rates and prevent such unwanted toxicity. -
CD226 T Cells Expressing the Receptors TIGIT and Divergent Phenotypes of Human Regulatory
The Journal of Immunology Divergent Phenotypes of Human Regulatory T Cells Expressing the Receptors TIGIT and CD226 Christopher A. Fuhrman,*,1 Wen-I Yeh,*,1 Howard R. Seay,* Priya Saikumar Lakshmi,* Gaurav Chopra,† Lin Zhang,* Daniel J. Perry,* Stephanie A. McClymont,† Mahesh Yadav,† Maria-Cecilia Lopez,‡ Henry V. Baker,‡ Ying Zhang,x Yizheng Li,{ Maryann Whitley,{ David von Schack,x Mark A. Atkinson,* Jeffrey A. Bluestone,‡ and Todd M. Brusko* Regulatory T cells (Tregs) play a central role in counteracting inflammation and autoimmunity. A more complete understanding of cellular heterogeneity and the potential for lineage plasticity in human Treg subsets may identify markers of disease pathogenesis and facilitate the development of optimized cellular therapeutics. To better elucidate human Treg subsets, we conducted direct transcriptional profiling of CD4+FOXP3+Helios+ thymic-derived Tregs and CD4+FOXP3+Helios2 T cells, followed by comparison with CD4+FOXP32Helios2 T conventional cells. These analyses revealed that the coinhibitory receptor T cell Ig and ITIM domain (TIGIT) was highly expressed on thymic-derived Tregs. TIGIT and the costimulatory factor CD226 bind the common ligand CD155. Thus, we analyzed the cellular distribution and suppressive activity of isolated subsets of CD4+CD25+CD127lo/2 T cells expressing CD226 and/or TIGIT. We observed TIGIT is highly expressed and upregulated on Tregs after activation and in vitro expansion, and is associated with lineage stability and suppressive capacity. Conversely, the CD226+TIGIT2 population was associated with reduced Treg purity and suppressive capacity after expansion, along with a marked increase in IL-10 and effector cytokine production. These studies provide additional markers to delineate functionally distinct Treg subsets that may help direct cellular therapies and provide important phenotypic markers for assessing the role of Tregs in health and disease. -
Single-Cell RNA Sequencing Demonstrates the Molecular and Cellular Reprogramming of Metastatic Lung Adenocarcinoma
ARTICLE https://doi.org/10.1038/s41467-020-16164-1 OPEN Single-cell RNA sequencing demonstrates the molecular and cellular reprogramming of metastatic lung adenocarcinoma Nayoung Kim 1,2,3,13, Hong Kwan Kim4,13, Kyungjong Lee 5,13, Yourae Hong 1,6, Jong Ho Cho4, Jung Won Choi7, Jung-Il Lee7, Yeon-Lim Suh8,BoMiKu9, Hye Hyeon Eum 1,2,3, Soyean Choi 1, Yoon-La Choi6,10,11, Je-Gun Joung1, Woong-Yang Park 1,2,6, Hyun Ae Jung12, Jong-Mu Sun12, Se-Hoon Lee12, ✉ ✉ Jin Seok Ahn12, Keunchil Park12, Myung-Ju Ahn 12 & Hae-Ock Lee 1,2,3,6 1234567890():,; Advanced metastatic cancer poses utmost clinical challenges and may present molecular and cellular features distinct from an early-stage cancer. Herein, we present single-cell tran- scriptome profiling of metastatic lung adenocarcinoma, the most prevalent histological lung cancer type diagnosed at stage IV in over 40% of all cases. From 208,506 cells populating the normal tissues or early to metastatic stage cancer in 44 patients, we identify a cancer cell subtype deviating from the normal differentiation trajectory and dominating the metastatic stage. In all stages, the stromal and immune cell dynamics reveal ontological and functional changes that create a pro-tumoral and immunosuppressive microenvironment. Normal resident myeloid cell populations are gradually replaced with monocyte-derived macrophages and dendritic cells, along with T-cell exhaustion. This extensive single-cell analysis enhances our understanding of molecular and cellular dynamics in metastatic lung cancer and reveals potential diagnostic and therapeutic targets in cancer-microenvironment interactions. 1 Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,