Novel Cell type-specific aptamer-siRNA delivery system for HIV-1 therapy

The successful use of small interfering RNAs (siRNAs) for therapeutic purposes requires safe and efficient delivery to specific cells and tissues. Here we demonstrate cell type-specific delivery of anti-HIV siRNAs via fusion to an anti-gp120 aptamer. The envelope glycoprotein is expressed on the surface of HIV-1 infected cells, allowing binding and interalization of the aptamer-siRNA chimeric molecules. We demonstrate that the anti-gp120 aptamer-siRNA chimera is specifically taken up by cells expressing HIV-1 gp120, and the appended siRNA is processed by Dicer, releasing an anti-tat/rev siRNA which in turn inhibits HIV replication. We show for the first time a dual functioning aptamer-siRNA chimera in which both the aptamer and the siRNA portions have potent anti-HIV activities and that gp120 expressed on the surface of HIV infected cells can be used for aptamer mediated delivery of anti-HIV siRNAs

GAGrank: Software for Glycosaminoglycan Sequence Ranking using a Bipartite Graph Model

The Sulfated Glycosaminoglycans (GAGs) Are Long, Linear Polysaccharide Chains that Are Typically Found as the Glycan Portion of Proteoglycans. These GAGs Are Characterized by Repeating Disaccharide Units with Variable Sulfation and Acetylation Patterns Along the Chain. GAG Length and Modification Patterns Have Profound Impacts on Growth Factor Signaling Mechanisms Central to Numerous Physiological Processes. Electron Activated Dissociation Tandem Mass Spectrometry is a Very Effective Technique for Assigning the Structures of GAG Saccharides; However, Manual Interpretation of the Resulting Complex Tandem Mass Spectra is a Difficult and Time-Consuming Process that Drives the Development of Computational Methods for Accurate and Efficient Sequencing. We Have Recently Published GAGfinder, the First Peak Picking and Elemental Composition Assignment Algorithm Specifically Designed for GAG Tandem Mass Spectra. Here, We Present GAGrank, a Novel Network-Based Method for Determining GAG Structure using Information Extracted from Tandem Mass Spectra using GAGfinder. GAGrank is based on Google\u27s PageRank Algorithm for Ranking Websites for Search Engine Output. in Particular, It is an Implementation of BiRank, an Extension of PageRank for Bipartite Networks. in Our Implementation, the Two Partitions Comprise Every Possible Sequence for a Given GAG Composition and the Tandem MS Fragments Found using GAGfinder. Sequences Are Given a Higher Ranking If They Link to Many Important Fragments. using the Simulated Annealing Probabilistic Optimization Technique, We Optimized GAGrank\u27s Parameters on Ten Training Sequences. We Then Validated GAGrank\u27s Performance on Three Validation Sequences. We Also Demonstrated GAGrank\u27s Ability to Sequence Isomeric Mixtures using Two Mixtures at Five Different Ratios

HIV Status Does Not Affect the Outcome of Autologous Stem Cell Transplantation (ASCT) for Non-Hodgkin Lymphoma (NHL)

Randomized trials comparing autologous stem cell transplant (ASCT) to conventional chemotherapy have demonstrated superior survival among HIV-negative ASCT patients with relapsed non-Hodgkin lymphoma (NHL). Recent trials explored the feasibility of ASCT in the HIV setting. Although these studies have shown that ASCT in HIV-positive NHL patients (HIVpos-NHL) is well tolerated, the impact of HIV infection on long-term transplant outcome is not well characterized. Ongoing comparison of long-term survival following ASCT in HIVpos-NHL patients and HIVneg-NHL patients will allow investigators to explore whether there should be inclusion of HIVpos-NHL patients in ASCT trials. To study long-term outcome we conducted a single-institution matched case-controlled study in HIVpos-NHL patients (cases) and HIVneg-NHL patients (controls). Twenty-nine patients with HIVpos-NHL were matched with HIVneg-NHL controls on sex, time to ASCT, year of transplant, histology, age, disease status, number prior regimens, and conditioning regimen. Nonrelapse mortality (NRM) was similar: 11% (95% confidence interval [CI]: 4%-28%) in HIVpos-NHL patients and 4% (95% CI: 1%-25%) in HIVneg-NHL controls (P = .18). Two-year disease-free survival (DFS) for the HIVpos-NHL patients was 76% (95% CI: 62%-85%) and 56% (95% CI: 45%-66%) for the HIVneg-NHL controls (P = .33). Overall survival was also similar; the 2-year point estimates were 75% (95% CI: 61%-85%) and 75% (95% CI: 60%-85%), respectively (P = .93), despite inclusion of more poor risk HIVpos-NHL patients. These results provide further evidence that HIV status does not affect the long-term outcome of ASCT for NHL, and therefore HIV status alone should no longer exclude these patients from transplant clinical trials

Cytomegalovirus Viral Load and Virus-Specific Immune Reconstitution after Peripheral Blood Stem Cell versus Bone Marrow Transplantation

Peripheral blood stem cell (PBSC) products contain more T cells and monocytes when compared with bone marrow (BM), leading to fewer bacterial and fungal infections. Cytomegelovirus (CMV) viral load and disease as well as CMV-specific immune reconstitution were compared in patients enrolled in a randomized trial comparing PSBC and BM transplantation. There was a higher rate of CMV infection and disease during the first 100 days after transplantation among PBSC recipients (any antigenemia/DNAemia: PBSC, 63% vs BM, 42%, P = .04; CMV disease: PBSC, 17% vs BM, 4%, P = .03). By 2 years, CMV disease rates were similar. The early increase in CMV events correlated temporarily with lower CMV-specific CD4+ T helper and CD8+ cytotoxic T lymphocyte function at 30 days after transplantation in PBSC recipients. By 3 months after transplantation and thereafter, CMV-specific immune responses were similar between BM and PBSC recipients. In conclusion, higher CMV infection and disease rates occurred in PBSC transplant recipients early after transplantation. These differences may be because of a transient delay in CMV-specific immune reconstitution following PBSC transplantation

Increased Programmed Death-1 Molecule Expression in Cytomegalovirus Disease and Acute Graft-versus-Host Disease after Allogeneic Hematopoietic Cell Transplantation

To study the role of the programmed death-1 molecule (PD-1) in cytomegalovirus (CMV) infection and disease after allogeneic hematopoietic cell transplantation (HCT), 206 subjects were followed prospectively for immune response to CMV and assigned to 3 groups based on CMV outcome. The subjects were analyzed retrospectively for PD-1 expression in cryopreserved CD4+ and CD8+T cells collected at days 40, 90, 120, 150, 180, and 360 posttransplantation. HCT recipients with CMV disease (n=14) were compared with recipients with prolonged CMV infection, but no CMV disease (median duration of infection, 3 months; n=14) and with controls with no CMV infection who received similar transplants (n=22). The CMV disease group had a significantly higher mean fluorescein intensity of PD-1 in CD4+ (P < .05) and CD8+ (P < .05) lymphocytes at all time points studied. PD-1 expression also was significantly elevated in those with severe acute graft-versus-host disease (aGVHD), including the no-viremia group. The data suggest that PD-1 is induced by aGVHD even in the absence of CMV infection. This enhanced PD-1 expression during severe aGVHD and with CMV reactivation could explain the known role of aGVHD as a risk factor for CMV disease

Simultaneous targeting of B-cell malignancies and human immunodeficiency virus with bispecific chimeric antigen receptor T cells

Not available

RNA-based gene therapy for HIV with lentiviral vector-modified CD34() cells in patients undergoing transplantation for AIDS-related lymphoma

AIDS patients who develop lymphoma are often treated with transplanted hematopoietic progenitor cells. As a first step in developing a hematopoietic cell-based gene therapy treatment, four patients undergoing treatment with these transplanted cells were also given gene-modified peripheral blood-derived (CD34 + ) hematopoietic progenitor cells expressing three RNA-based anti-HIV moieties (tat/rev short hairpin RNA, TAR decoy, and CCR5 ribozyme). In vitro analysis of these gene-modified cells showed no differences in their hematopoietic potential compared with nontransduced cells. In vitro estimates of successful expression of the anti-HIV moieties were initially as high as 22% but declined to~1% over 4 weeks of culture. Ethical study design required that patients be transplanted with both gene-modified and unmanipulated hematopoietic progenitor cells obtained from the patient by apheresis. Transfected cells were successfully engrafted in all four infused patients by day 11, and there were no unexpected infusion-related toxicities. Persistent vector expression in multiple cell lineages was observed at low levels for up to 24 months, as was expression of the introduced small interfering RNA and ribozyme. Therefore, we have demonstrated stable vector expression in human blood cells after transplantation of autologous gene-modified hematopoietic progenitor cells. These results support the development of an RNA-based cell therapy platform for HIV

NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods

Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submit- Avenue, Silver Spring, Maryland 20993; 22Glycoscience Research Laboratory, Genos, Borongajska cesta 83h, 10 000 Zagreb, Croatia; 23Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovacˇ ic´ a 1, 10 000 Zagreb, Croatia; 24Department of Chemistry, Georgia State University, 100 Piedmont Avenue, Atlanta, Georgia 30303; 25glyXera GmbH, Brenneckestrasse 20 * ZENIT / 39120 Magdeburg, Germany; 26Health Products and Foods Branch, Health Canada, AL 2201E, 251 Sir Frederick Banting Driveway, Ottawa, Ontario, K1A 0K9 Canada; 27Graduate School of Advanced Sciences of Matter, Hiroshima University, 1-3-1 Kagamiyama Higashi-Hiroshima 739–8530 Japan; 28ImmunoGen, 830 Winter Street, Waltham, Massachusetts 02451; 29Department of Medical Physiology, Jagiellonian University Medical College, ul. Michalowskiego 12, 31–126 Krakow, Poland; 30Department of Pathology, Johns Hopkins University, 400 N. Broadway Street Baltimore, Maryland 21287; 31Mass Spec Core Facility, KBI Biopharma, 1101 Hamlin Road Durham, North Carolina 27704; 32Division of Mass Spectrometry, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongwon-gu, Cheongju Chungbuk, 363–883 Korea (South); 33Advanced Therapy Products Research Division, Korea National Institute of Food and Drug Safety, 187 Osongsaengmyeong 2-ro Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do, 363–700, Korea (South); 34Center for Proteomics and Metabolomics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; 35Ludger Limited, Culham Science Centre, Abingdon, Oxfordshire, OX14 3EB, United Kingdom; 36Biomolecular Discovery and Design Research Centre and ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP), Macquarie University, North Ryde, Australia; 37Proteomics, Central European Institute for Technology, Masaryk University, Kamenice 5, A26, 625 00 BRNO, Czech Republic; 38Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, 39106 Magdeburg, Germany; 39Department of Biomolecular Sciences, Max Planck Institute of Colloids and Interfaces, 14424 Potsdam, Germany; 40AstraZeneca, Granta Park, Cambridgeshire, CB21 6GH United Kingdom; 41Merck, 2015 Galloping Hill Rd, Kenilworth, New Jersey 07033; 42Analytical R&D, MilliporeSigma, 2909 Laclede Ave. St. Louis, Missouri 63103; 43MS Bioworks, LLC, 3950 Varsity Drive Ann Arbor, Michigan 48108; 44MSD, Molenstraat 110, 5342 CC Oss, The Netherlands; 45Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, 5–1 Higashiyama, Myodaiji, Okazaki 444–8787 Japan; 46Graduate School of Pharmaceutical Sciences, Nagoya City University, 3–1 Tanabe-dori, Mizuhoku, Nagoya 467–8603 Japan; 47Medical & Biological Laboratories Co., Ltd, 2-22-8 Chikusa, Chikusa-ku, Nagoya 464–0858 Japan; 48National Institute for Biological Standards and Control, Blanche Lane, South Mimms, Potters Bar, Hertfordshire EN6 3QG United Kingdom; 49Division of Biological Chemistry & Biologicals, National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, Tokyo 158–8501 Japan; 50New England Biolabs, Inc., 240 County Road, Ipswich, Massachusetts 01938; 51New York University, 100 Washington Square East New York City, New York 10003; 52Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, United Kingdom; 53GlycoScience Group, The National Institute for Bioprocessing Research and Training, Fosters Avenue, Mount Merrion, Blackrock, Co. Dublin, Ireland; 54Department of Chemistry, North Carolina State University, 2620 Yarborough Drive Raleigh, North Carolina 27695; 55Pantheon, 201 College Road East Princeton, New Jersey 08540; 56Pfizer Inc., 1 Burtt Road Andover, Massachusetts 01810; 57Proteodynamics, ZI La Varenne 20–22 rue Henri et Gilberte Goudier 63200 RIOM, France; 58ProZyme, Inc., 3832 Bay Center Place Hayward, California 94545; 59Koichi Tanaka Mass Spectrometry Research Laboratory, Shimadzu Corporation, 1 Nishinokyo Kuwabara-cho Nakagyo-ku, Kyoto, 604 8511 Japan; 60Children’s GMP LLC, St. Jude Children’s Research Hospital, 262 Danny Thomas Place Memphis, Tennessee 38105; 61Sumitomo Bakelite Co., Ltd., 1–5 Muromati 1-Chome, Nishiku, Kobe, 651–2241 Japan; 62Synthon Biopharmaceuticals, Microweg 22 P.O. Box 7071, 6503 GN Nijmegen, The Netherlands; 63Takeda Pharmaceuticals International Co., 40 Landsdowne Street Cambridge, Massachusetts 02139; 64Department of Chemistry and Biochemistry, Texas Tech University, 2500 Broadway, Lubbock, Texas 79409; 65Thermo Fisher Scientific, 1214 Oakmead Parkway Sunnyvale, California 94085; 66United States Pharmacopeia India Pvt. Ltd. IKP Knowledge Park, Genome Valley, Shamirpet, Turkapally Village, Medchal District, Hyderabad 500 101 Telangana, India; 67Alberta Glycomics Centre, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 68Department of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 69Department of Chemistry, University of California, One Shields Ave, Davis, California 95616; 70Horva´ th Csaba Memorial Laboratory for Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Egyetem ter 1, Hungary; 71Translational Glycomics Research Group, Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Egyetem ut 10, Hungary; 72Delaware Biotechnology Institute, University of Delaware, 15 Innovation Way Newark, Delaware 19711; 73Proteomics Core Facility, University of Gothenburg, Medicinaregatan 1G SE 41390 Gothenburg, Sweden; 74Department of Medical Biochemistry and Cell Biology, University of Gothenburg, Institute of Biomedicine, Sahlgrenska Academy, Medicinaregatan 9A, Box 440, 405 30, Gothenburg, Sweden; 75Department of Clinical Chemistry and Transfusion Medicine, Sahlgrenska Academy at the University of Gothenburg, Bruna Straket 16, 41345 Gothenburg, Sweden; 76Department of Chemistry, University of Hamburg, Martin Luther King Pl. 6 20146 Hamburg, Germany; 77Department of Chemistry, University of Manitoba, 144 Dysart Road, Winnipeg, Manitoba, Canada R3T 2N2; 78Laboratory of Mass Spectrometry of Interactions and Systems, University of Strasbourg, UMR Unistra-CNRS 7140, France; 79Natural and Medical Sciences Institute, University of Tu¨ bingen, Markwiesenstrae 55, 72770 Reutlingen, Germany; 80Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands; 81Division of Bioanalytical Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, de Boelelaan 1085, 1081 HV Amsterdam, The Netherlands; 82Department of Chemistry, Waters Corporation, 34 Maple Street Milford, Massachusetts 01757; 83Zoetis, 333 Portage St. Kalamazoo, Michigan 49007 Author’s Choice—Final version open access under the terms of the Creative Commons CC-BY license. Received July 24, 2019, and in revised form, August 26, 2019 Published, MCP Papers in Press, October 7, 2019, DOI 10.1074/mcp.RA119.001677 ER: NISTmAb Glycosylation Interlaboratory Study 12 Molecular & Cellular Proteomics 19.1 Downloaded from https://www.mcponline.org by guest on January 20, 2020 ted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide communityderived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods. Molecular & Cellular Proteomics 19: 11–30, 2020. DOI: 10.1074/mcp.RA119.001677.L

Compressive strength and failure types of cusp replacing direct resin composite restorations in previously amalgam-filled premolars versus sound teeth

This study evaluated the fracture resistance of cusp replacing direct resin composite restorations (DCR) in premolars that had been previously filled with amalgam mesial-occlusal-distal (MOD) restorations and compared their fracture resistance with those made on sound dentin and intact teeth. Recently extracted human premolars with either MOD amalgam restorations or sound/intact ones were selected for the study. Cavities with cusp reduction were made for the following groups: (a) Group 1: DCRs on previously amalgam-affected dentin (n=11), (b) Group 2: DCRs on sound dentin (n=10), and (c) Group 3: intact premolars (n=9). Teeth in Groups 1 and 2 were restored with a 3-step etch and rinse adhesive (Quadrant Unibond) and filled with hybrid composite (Clearfil Photo Posterior). All specimens were thermocycled for 5000cycles (5-55 degrees C). The buccal cusps of the teeth were loaded until fracture under compression at 45 degrees to the long axis of the teeth in a universal testing machine (1mm/min). Data (N) were statistically analyzed using one-way ANOVA and Student's t-test (=0.01). Intact teeth (Group 3) showed significantly higher fracture resistance (893 +/- 196) compared to both restored groups (p0.01). More than half of the teeth of Groups 2 and 3 showed unrepairable fractures with pulp exposure