Immune-Checkpoint Blockade Therapy in Lymphoma
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Immuno-Oncology Panel 1
Immuno-Oncology panel 1 Gene Symbol Target protein name UniProt ID (& link) Modification* (56 analytes) ADA17 ADAM17 metalloprotease domain 17 P78536 *blanks mean the assay detects the ANXA1 Annexin A1 P04083 non-modified peptide sequence ANXA1 Annexin A1 P04083 ARG2 arginase, type II P78540 ATM Serine-protein kinase ATM, Ataxia telangiectasia mutated Q13315 pS2996 ATM Serine-protein kinase ATM, Ataxia telangiectasia mutated Q13315 ATM Serine-protein kinase ATM, Ataxia telangiectasia mutated Q13315 pS367 ATM Serine-protein kinase ATM, Ataxia telangiectasia mutated Q13315 C10orf54 / VISTA chromosome 10 open reading frame 54 Q9H7M9 CCL5 C-C motif chemokine ligand 5 P13501 CD14 CD14 molecule P08571 CD163 CD163 molecule Q86VB7 CD274 / PDL1 Programmed cell death 1 ligand 1 CD274 Q9NZQ7 CD33 CD33 molecule P20138 CD40/TNR5 tumor necrosis factor receptor superfamily member 5 P25942 CD40/TNR5 tumor necrosis factor receptor superfamily member 5 P25942 CD47 CD47 molecule Q08722 CD70 CD70 antigen P32970 CD74/HG2A CD74 molecule, major histocompatibility complex, class II invariant chain Q8SNA0 CEACAM8 carcinoembryonic antigen-related cell adhesion molecule 8 P31997 CX3CL1 C-X3-C motif chemokine ligand 1 P78423 CXCL10 C-X-C motif chemokine ligand 10 P02778 CXCL13 chemokine (C-X-C motif) ligand 13 O43927 ENTPD1 ectonucleoside triphosphate diphosphohydrolase 1 Q86VV3 FAS/TNR6 Fas (TNF receptor superfamily, member 6) P25445 pY291 FAS/TNR6 Fas (TNF receptor superfamily, member 6) P25445 GAPDH Glyceraldehyde-3-phosphate dehydrogenase P04406 HAVCR2 hepatitis -
Predictive QSAR Tools to Aid in Early Process Development of Monoclonal Antibodies
Predictive QSAR tools to aid in early process development of monoclonal antibodies John Micael Andreas Karlberg Published work submitted to Newcastle University for the degree of Doctor of Philosophy in the School of Engineering November 2019 Abstract Monoclonal antibodies (mAbs) have become one of the fastest growing markets for diagnostic and therapeutic treatments over the last 30 years with a global sales revenue around $89 billion reported in 2017. A popular framework widely used in pharmaceutical industries for designing manufacturing processes for mAbs is Quality by Design (QbD) due to providing a structured and systematic approach in investigation and screening process parameters that might influence the product quality. However, due to the large number of product quality attributes (CQAs) and process parameters that exist in an mAb process platform, extensive investigation is needed to characterise their impact on the product quality which makes the process development costly and time consuming. There is thus an urgent need for methods and tools that can be used for early risk-based selection of critical product properties and process factors to reduce the number of potential factors that have to be investigated, thereby aiding in speeding up the process development and reduce costs. In this study, a framework for predictive model development based on Quantitative Structure- Activity Relationship (QSAR) modelling was developed to link structural features and properties of mAbs to Hydrophobic Interaction Chromatography (HIC) retention times and expressed mAb yield from HEK cells. Model development was based on a structured approach for incremental model refinement and evaluation that aided in increasing model performance until becoming acceptable in accordance to the OECD guidelines for QSAR models. -
Development of Red Blood Cell Autoantibodies Following Treatment with Checkpoint Inhibitors
CASE R EP O RT Development of red blood cell autoantibodies following treatment with checkpoint inhibitors: a new class of anti-neoplastic, immunotherapeutic agents associated with immune dysregulation L.L.W. Cooling, J. Sherbeck, J.C. Mowers, and S.L. Hugan Ipilimumab, nivolumab, and pembrolizumab represent a new Table 1. Checkpoint inhibitors class of immunotherapeutic drugs for treating patients with Drug class (trade name, manufacturer) advanced cancer. Known as checkpoint inhibitors, these drugs act to upregulate the cellular and humoral immune response Anti-CTLA-4 to tumor antigens by inhibiting T-cell autoregulation. As a Ipilimumab (Yervoy, Bristol-Myers Squibb) consequence, they can be associated with immune-related adverse Tremelimumab (AstraZeneca, compassionate use only) events (irAEs) due to loss of self-tolerance, including rare cases of immune-related cytopenias. We performed a retrospective Anti-PD-1 clinical chart review, including serologic, hematology, and Nivolumab (Opdivo, Bristol-Myers Squibb) chemistry laboratory results, of two patients who developed Pembrolizumab (Keytruda, Merck Sharp & Dohme) red blood cell (RBC) autoantibodies during treatment with a Pidilizumab (Medivations, in clinical trials) checkpoint inhibitor. Serologic testing of blood samples from these patients during induction therapy with ipilimumab and Anti-PD-L1 nivolumab, respectively, showed their RBCs to be positive by Atezolizumab (Genentech, in clinical trials) the direct antiglobulin test (IgG+, C3+) and their plasma to Durvalumab (AstraZeneca, approved bladder cancer) contain panreactive RBC autoantibodies. Neither patient had evidence of hemolysis. Both patients developed an additional CTLA-4 = cytotoxic T-lymphocyte–associated antigen 4; PD-1 = programmed cell death protein 1; PD-L1 = programmed cell death ligand 1. -
Mirati's Clinical Programs
NASDAQ: MRTX Targeting the genetic and immunological drivers of cancer Corporate Presentation August 2019 1 Safe Harbor Statement Certain statements contained in this presentation, other than statements of fact that are independently verifiable at the date hereof, are "forward-looking" statements, within the meaning of the Private Securities Litigation Reform Act of 1955, that involve significant risks and uncertainties. Forward looking statements can be identified by the use of forward looking words such as “believes,” “expects,” “hopes,” “may,” “will,” “plan,” “intends,” “estimates,” “could,” “should,” “would,” “continue,” “seeks,” “pro forma,” or “anticipates,” or other similar words (including their use in the negative), or by discussions of future matters such as the development of current or future product candidates, timing of potential development activities and milestones, business plans and strategies, possible changes in legislation and other statements that are not historical. Forward-looking statements are based on current expectations of management and on what management believes to be reasonable assumptions based on information currently available to them, and are subject to risks and uncertainties. Such risks and uncertainties may cause actual results to differ materially from those anticipated in the forward-looking statements. Such risks and uncertainties include without limitation potential delays in development timelines, negative clinical trial results, reliance on third parties for development efforts, changes in the competitive landscape, changes in the standard of care, as well as other risks detailed in Mirati's recent filings on Forms 10-K and 10-Q with the U.S. Securities and Exchange Commission. Except as required by law, Mirati undertakes no obligation to update any forward-looking statements to reflect new information, events or circumstances, or to reflect the occurrence of unanticipated events. -
Classification Decisions Taken by the Harmonized System Committee from the 47Th to 60Th Sessions (2011
CLASSIFICATION DECISIONS TAKEN BY THE HARMONIZED SYSTEM COMMITTEE FROM THE 47TH TO 60TH SESSIONS (2011 - 2018) WORLD CUSTOMS ORGANIZATION Rue du Marché 30 B-1210 Brussels Belgium November 2011 Copyright © 2011 World Customs Organization. All rights reserved. Requests and inquiries concerning translation, reproduction and adaptation rights should be addressed to [email protected]. D/2011/0448/25 The following list contains the classification decisions (other than those subject to a reservation) taken by the Harmonized System Committee ( 47th Session – March 2011) on specific products, together with their related Harmonized System code numbers and, in certain cases, the classification rationale. Advice Parties seeking to import or export merchandise covered by a decision are advised to verify the implementation of the decision by the importing or exporting country, as the case may be. HS codes Classification No Product description Classification considered rationale 1. Preparation, in the form of a powder, consisting of 92 % sugar, 6 % 2106.90 GRIs 1 and 6 black currant powder, anticaking agent, citric acid and black currant flavouring, put up for retail sale in 32-gram sachets, intended to be consumed as a beverage after mixing with hot water. 2. Vanutide cridificar (INN List 100). 3002.20 3. Certain INN products. Chapters 28, 29 (See “INN List 101” at the end of this publication.) and 30 4. Certain INN products. Chapters 13, 29 (See “INN List 102” at the end of this publication.) and 30 5. Certain INN products. Chapters 28, 29, (See “INN List 103” at the end of this publication.) 30, 35 and 39 6. Re-classification of INN products. -
Immune Checkpoint Inhibitor Combinations Current Efforts And
Drug Resistance Updates 45 (2019) 13–29 Contents lists available at ScienceDirect Drug Resistance Updates journal homepage: www.elsevier.com/locate/drup Immune checkpoint inhibitor combinations: Current efforts and important aspects for success T ⁎ Edo Kon, Itai Benhar Department of Molecular Microbiology and Biotechnology, School of Molecular Cell Biology and Biotechnology, The George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel ARTICLE INFO ABSTRACT Keywords: Immune checkpoint inhibitors (ICI) have emerged as a remarkable treatment option for diverse cancer types. Resistance Currently, ICIs are approved for an expanding array of cancer indications. However, the majority of patients still Immunotherapy do not demonstrate a durable long-term response following ICI therapy. In addition, many patients receiving ICI Clinic therapy develop immune-related adverse events (irAEs) affecting a wide variety of organs. To increase the CAR-T percentage of patients who benefit from ICI therapy and to reduce the occurrence of irAEs, there is an ongoing Radiation therapy effort to combine current ICIs with novel checkpoints inhibitors or other therapeutic approaches to achieve a Chemotherapy ff RNA cancer vaccines synergistic e ect which is larger than the sum of its parts. Angiogenesis In this review we highlight the essential factors for more effective ICI combinations. We describe how the Tumor microenvironment design of these strategies should be driven by the tumor's immunological context. We analyze current combi- nation strategies and describe how they can be improved to unleash the immune system's full anti-cancer po- tential as well as convert immunologically "cold" tumors into "hot" ones. -
Immune Checkpoint Inhibition in DLBCL Immunotherapy: “The Cure Is Inside Us”
Mariano Provencio Servicio de Oncología Médica Hospital Universitario Puerta de Hierro Immune checkpoint inhibition in DLBCL Immunotherapy: “The Cure is Inside Us” § Our immune system prevents or limit infections by foreign antigens expressed in microorganisms (bacteria, viruses, etc.) § Our immune system can also recognize and destroy cancer cells….. • However, cancer cells have developed “escape mechanisms” to avoid their destruction by immune cells…“put the brakes on” • Immuno-Oncology: Find ways of “unleashing” the power of our body’s immune system to treat or prevent cancer…T-lymphocytes (T- cells) Detectives Dendritic cells Killer –T cells Microenvironment antigen (flags) Detectives Dendritic cells Killer –T cells Tumor infiltranting T cell recognizable ags Cor e Algorithms Margin Neo-antigens antigen (flags) 5 6 Scott DW et al. Nature Rev 2014 Strategy approach § Effective immune response: barriers § microenviroment § Activate anti-tumor immune response § inhibitory receptors: blocking antibodies § Nivo, Pembro, Ipi,…(anti PD 1) (CTLA4) § combining 2 checkpoint inhibitors § combining with chemotherapy § activate receptors: agonist § Urelumab § Utumilumab § Varlilumab Strategy approach § Effective immune response: barriers § microenviroment Inactivated effector T cell angiogenesis metabolism Strategy approach PDL-1 Effective immune CTLA-4 response: barriers Lymphoma PDL-1 PD-1 PDL-1 TIM-3 PDL-1 PDL-1 mTOR LAG-3 OXPHOS MHC1 Aerobic glycolysis Interferon gamma EB virus T cell activation antigen presenting cells Strategy approach § -
On the Horizon: Immuno-Oncology (I-O) Combinations
Immuno-Oncology (I-O) Combinations • Jeffrey A. Sosman, MD • Robert H. Lurie Comprehensive Cancer Center of Northwestern University The Cancer–Immunity Cycle Daniel Chen and Ira Mellman Immunity, Volume 39, Issue 1, 2013, 1 - 10 The Cancer–Immunity Cycle Daniel Chen and Ira Mellman Immunity, Volume 39, Issue 1, 2013, 1 - 10 Stimulatory and Inhibitory Factors in the Cancer-Immunity Cycle Each step of the Cancer-Immunity Cycle requires the coordination of numerous factors, both stimulatory and inhibitory in nature. Stimulatory factors shown in green promote immunity, ... Where will Improvements come from? • Combinations: – Based on Template: anti-PD-1/PD-L1 or with anti-PD- 1/anti-CTLA-4 • Block other co-inhibitory: LAG3, TIM3, KIR, VISTA • Activate co-stimulatory: 4-1BB, OX-40, GITR, CD27, ICOS • Block inhibitory molecules- IDOi, TGFbi, CSF1Ri, anti-IL-6 or anti- IL-10 • Effect trafficking- anti-VEGF, CCL5, CXCR4i • Vaccines- TVEC- oncolytic virus, Neoantigen, other cellular • Adoptive Cellular therapy- TIL, CAR-T cells, TCR T-cells Where will Improvements come from? • Combinations: – Based on Template: anti-PD-1/PD-L1 or with anti-PD- 1/anti-CTLA-4 • Signal Inhibition, BRAF directed (BRAFi+MEKi), MEKi, PI3K inhibition (PTEN effects) • Cytokines- IL-2, IFN a,b,g,, Directed cytokines (FAP-IL-2v or CEA-IL-2v) • Epigenetic modulation- gene expression and EVR expression • Microbiome modification- fecal transplants • Chemotherapy other cytotoxics • Localized Irradiation SBRT, SRS T cells in Tumors Express Multiple Immunoinhibitory Receptors -
2017 Immuno-Oncology Medicines in Development
2017 Immuno-Oncology Medicines in Development Adoptive Cell Therapies Drug Name Organization Indication Development Phase ACTR087 + rituximab Unum Therapeutics B-cell lymphoma Phase I (antibody-coupled T-cell receptor Cambridge, MA www.unumrx.com immunotherapy + rituximab) AFP TCR Adaptimmune liver Phase I (T-cell receptor cell therapy) Philadelphia, PA www.adaptimmune.com anti-BCMA CAR-T cell therapy Juno Therapeutics multiple myeloma Phase I Seattle, WA www.junotherapeutics.com Memorial Sloan Kettering New York, NY anti-CD19 "armored" CAR-T Juno Therapeutics recurrent/relapsed chronic Phase I cell therapy Seattle, WA lymphocytic leukemia (CLL) www.junotherapeutics.com Memorial Sloan Kettering New York, NY anti-CD19 CAR-T cell therapy Intrexon B-cell malignancies Phase I Germantown, MD www.dna.com ZIOPHARM Oncology www.ziopharm.com Boston, MA anti-CD19 CAR-T cell therapy Kite Pharma hematological malignancies Phase I (second generation) Santa Monica, CA www.kitepharma.com National Cancer Institute Bethesda, MD Medicines in Development: Immuno-Oncology 1 Adoptive Cell Therapies Drug Name Organization Indication Development Phase anti-CEA CAR-T therapy Sorrento Therapeutics liver metastases Phase I San Diego, CA www.sorrentotherapeutics.com TNK Therapeutics San Diego, CA anti-PSMA CAR-T cell therapy TNK Therapeutics cancer Phase I San Diego, CA www.sorrentotherapeutics.com Sorrento Therapeutics San Diego, CA ATA520 Atara Biotherapeutics multiple myeloma, Phase I (WT1-specific T lymphocyte South San Francisco, CA plasma cell leukemia www.atarabio.com -
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. -
Pancancer IO360 Human Vapril2018
Gene Name Official Full Gene name Alias/Prev Symbols Previous Name(s) Alias Symbol(s) Alias Name(s) A2M alpha-2-macroglobulin FWP007,S863-7,CPAMD5 ABCF1 ATP binding cassette subfamily F member 1 ABC50 ATP-binding cassette, sub-family F (GCN20),EST123147 member 1 ACVR1C activin A receptor type 1C activin A receptor, type IC ALK7,ACVRLK7 ADAM12 ADAM metallopeptidase domain 12 a disintegrin and metalloproteinase domainMCMPMltna,MLTN 12 (meltrin alpha) meltrin alpha ADGRE1 adhesion G protein-coupled receptor E1 TM7LN3,EMR1 egf-like module containing, mucin-like, hormone receptor-like sequence 1,egf-like module containing, mucin-like, hormone receptor-like 1 ADM adrenomedullin AM ADORA2A adenosine A2a receptor ADORA2 RDC8 AKT1 AKT serine/threonine kinase 1 v-akt murine thymoma viral oncogene homologRAC,PKB,PRKBA,AKT 1 ALDOA aldolase, fructose-bisphosphate A aldolase A, fructose-bisphosphate ALDOC aldolase, fructose-bisphosphate C aldolase C, fructose-bisphosphate ANGPT1 angiopoietin 1 KIAA0003,Ang1 ANGPT2 angiopoietin 2 Ang2 ANGPTL4 angiopoietin like 4 angiopoietin-like 4 pp1158,PGAR,ARP4,HFARP,FIAF,NL2fasting-induced adipose factor,hepatic angiopoietin-related protein,PPARG angiopoietin related protein,hepatic fibrinogen/angiopoietin-related protein,peroxisome proliferator-activated receptor (PPAR) gamma induced angiopoietin-related protein,angiopoietin-related protein 4 ANLN anillin actin binding protein anillin (Drosophila Scraps homolog), actin bindingANILLIN,Scraps,scra protein,anillin, actin binding protein (scraps homolog, Drosophila) -
The Indoleamine 2,3 Dioxygenase Pathway Drives Intratumoral B Cell
bioRxiv preprint doi: https://doi.org/10.1101/2021.08.25.456776; this version posted August 27, 2021. 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. The indoleamine 2,3 dioxygenase pathway drives intratumoral B cell maintenance. by Burles A. Johnson III1,2,3, Adam K. Aragaki2, Donna M. Williams3, Ophelia Rogers3, Jack Mountain2, Li Luo3, Wenhao Zhang3, Lingling Xian3, Mingxiao Feng2, Lionel Chia3, Dominic Dordai4, Noah M. Hahn1,2, Stephen Desiderio4, Theodore S. Johnson5, David J. McConkey2, and Linda M.S. Resar1,3,6. 1Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205 2Johns Hopkins Greenberg Bladder Cancer Institute, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Park 219, Baltimore, MD 21287 3Division of Hematology, Department of Medicine, Johns Hopkins University School of Medicine, 720 Rutland Avenue, Ross Research Building, Room 1025, Baltimore, MD 21205 4Institute for Basic Biomedical Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205 5Georgia Cancer Center and Department of Pediatrics, Augusta University, 1120 15th Street, Augusta, GA 30912 6Department of Pathology and Institute for Cellular Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 Abstract: 219 words; Manuscript Text: 4929 words Correspondence: [email protected] or [email protected] Abbreviations: IDO1, indoleamine 2,3 dioxygenase-1; Bregs, regulatory B cells, Tregs, regulatory T cells; LLC, Lewis Lung Carcinoma; PD-1/L, programmed cell death protein-1/ligand; APCs, antigen presenting cells; MDSCs, myeloid derived suppressor cells; IL, interleukin. bioRxiv preprint doi: https://doi.org/10.1101/2021.08.25.456776; this version posted August 27, 2021.