Single-Cell Transcriptomic Profiling Maps Monocyte/Macrophage Transitions After Myocardial Infarction in Mice
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CD74 Targeted Nanoparticles As Dexamethasone Delivery System for B Lymphoid Malignancies
CD74 targeted nanoparticles as Dexamethasone Delivery System for B lymphoid malignancies DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Georgia Triantafillou, MPH Integrated Biomedical Sciences Graduate Program The Ohio State University 2011 Dissertation Committee John C. Byrd, MD, advisor Natarajan Muthusamy, PhD co-advisor Robert J.Lee, PhD, co-advisor Mitch A.Phelps, PhD, co-advisor Guido Marcucci, MD committee member Susheela Tridandapani, PhD committee member Copyright page Georgia Triantafillou 2011 ABSTRACT Chronic Lymphocytic Leukemia (CLL) is the most common adult leukemia and is not curable with standard therapy. In CLL the B lymphocytes appear morphologically mature but immunologically express less mature B cell makers. Specifically, the CLL B cells co-express surface antigens including CD19, CD20, CD5, CD23. Due to nonspecific delivery of the drugs to malignant as well as normal cells, patients experience numerous side effects. Targeted drug delivery to cancer cells is a desirable goal for all anti cancer strategies. Corticosteroids have been proven to be a beneficial and well established part of CLL treatment. Dexamethasone(DEX) is frequently used in CLL therapies as well as other malignancies and antiinflammatory diseases. However, DEX nonspecifically enters all tissues inducing various toxicities to patients. Therefore, DEX treatment is often discontinued or not administered to certain patients. We aimed to deliver this efficient clinical agent via a targeted delivery vehicle and examine its effect on its target B-CLL cells. The main scope of the work presented is the creation of a sterically stable nanoparticle, an ii immunoliposome (ILP), that has DEX encapsulated in its interior and a monoclonal antibody(Mab) in its exterior targeting CLL B cells expressing the surface antigen that is recognized by the Mab. -
Single-Cell RNA Sequencing Identifies Candidate Renal
BASIC RESEARCH www.jasn.org Single-Cell RNA Sequencing Identifies Candidate Renal Resident Macrophage Gene Expression Signatures across Species Kurt A. Zimmerman,1 Melissa R. Bentley,1 Jeremie M. Lever ,2 Zhang Li,1 David K. Crossman,3 Cheng Jack Song,1 Shanrun Liu,4 Michael R. Crowley,3 James F. George,5 Michal Mrug,2,6 and Bradley K. Yoder1 1Department of Cell, Developmental, and Integrative Biology, 2Division of Nephrology, Department of Medicine, 3Department of Genetics, 4Department of Biochemistry and Molecular Genetics, and 5Division of Cardiothoracic Surgery, Department of Surgery, University of Alabama at Birmingham, Birmingham, Alabama; and 6Department of Veterans Affairs Medical Center, Birmingham, Alabama ABSTRACT Background Resident macrophages regulate homeostatic and disease processes in multiple tissues, in- cluding the kidney. Despite having well defined markers to identify these cells in mice, technical limita- tions have prevented identification of a similar cell type across species. The inability to identify resident macrophage populations across species hinders the translation of data obtained from animal model to human patients. Methods As an entry point to determine novel markers that could identify resident macrophages across species, we performed single-cell RNA sequencing (scRNAseq) analysis of all T and B cell–negative CD45+ innate immune cells in mouse, rat, pig, and human kidney tissue. Results We identified genes with enriched expression in mouse renal resident macrophages that were also present in candidate resident macrophage populations across species. Using the scRNAseq data, we defined a novel set of possible cell surface markers (Cd74 and Cd81) for these candidate kidney resident macrophages. We confirmed, using parabiosis and flow cytometry, that these proteins are indeed enriched in mouse resident macrophages. -
Identification and Interaction Analysis of Molecular Markers in Pancreatic
medRxiv preprint doi: https://doi.org/10.1101/2020.12.20.20248601; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Integrated Bioinformatics Analysis and Molecular Docking Experiments Basavaraj Vastrad1 , Chanabasayya Vastrad *2, Anandkumar Tengli3 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics,Chanabasava Nilaya, Bharthinagar, Dharwad, Karanataka 580001, India. 3. Department of Pharmaceutical Chemistry, JSS College of Pharmacy, Mysuru and JSS Academy of Higher Education & Research, Mysuru- 570015, Karnataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.20.20248601; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Abstract The current investigation aimed to mine therapeutic molecular targets that play an key part in the advancement of pancreatic ductal adenocarcinoma (PDAC). The expression profiling by high throughput sequencing dataset profile GSE133684 dataset was downloaded from the Gene Expression Omnibus (GEO) database. -
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. -
CD29 Identifies IFN-Γ–Producing Human CD8+ T Cells With
+ CD29 identifies IFN-γ–producing human CD8 T cells with an increased cytotoxic potential Benoît P. Nicoleta,b, Aurélie Guislaina,b, Floris P. J. van Alphenc, Raquel Gomez-Eerlandd, Ton N. M. Schumacherd, Maartje van den Biggelaarc,e, and Monika C. Wolkersa,b,1 aDepartment of Hematopoiesis, Sanquin Research, 1066 CX Amsterdam, The Netherlands; bLandsteiner Laboratory, Oncode Institute, Amsterdam University Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; cDepartment of Research Facilities, Sanquin Research, 1066 CX Amsterdam, The Netherlands; dDivision of Molecular Oncology and Immunology, Oncode Institute, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands; and eDepartment of Molecular and Cellular Haemostasis, Sanquin Research, 1066 CX Amsterdam, The Netherlands Edited by Anjana Rao, La Jolla Institute for Allergy and Immunology, La Jolla, CA, and approved February 12, 2020 (received for review August 12, 2019) Cytotoxic CD8+ T cells can effectively kill target cells by producing therefore developed a protocol that allowed for efficient iso- cytokines, chemokines, and granzymes. Expression of these effector lation of RNA and protein from fluorescence-activated cell molecules is however highly divergent, and tools that identify and sorting (FACS)-sorted fixed T cells after intracellular cytokine + preselect CD8 T cells with a cytotoxic expression profile are lacking. staining. With this top-down approach, we performed an un- + Human CD8 T cells can be divided into IFN-γ– and IL-2–producing biased RNA-sequencing (RNA-seq) and mass spectrometry cells. Unbiased transcriptomics and proteomics analysis on cytokine- γ– – + + (MS) analyses on IFN- and IL-2 producing primary human producing fixed CD8 T cells revealed that IL-2 cells produce helper + + + CD8 Tcells. -
The Chemokine System in Innate Immunity
Downloaded from http://cshperspectives.cshlp.org/ on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press The Chemokine System in Innate Immunity Caroline L. Sokol and Andrew D. Luster Center for Immunology & Inflammatory Diseases, Division of Rheumatology, Allergy and Immunology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114 Correspondence: [email protected] Chemokines are chemotactic cytokines that control the migration and positioning of immune cells in tissues and are critical for the function of the innate immune system. Chemokines control the release of innate immune cells from the bone marrow during homeostasis as well as in response to infection and inflammation. Theyalso recruit innate immune effectors out of the circulation and into the tissue where, in collaboration with other chemoattractants, they guide these cells to the very sites of tissue injury. Chemokine function is also critical for the positioning of innate immune sentinels in peripheral tissue and then, following innate immune activation, guiding these activated cells to the draining lymph node to initiate and imprint an adaptive immune response. In this review, we will highlight recent advances in understanding how chemokine function regulates the movement and positioning of innate immune cells at homeostasis and in response to acute inflammation, and then we will review how chemokine-mediated innate immune cell trafficking plays an essential role in linking the innate and adaptive immune responses. hemokines are chemotactic cytokines that with emphasis placed on its role in the innate Ccontrol cell migration and cell positioning immune system. throughout development, homeostasis, and in- flammation. The immune system, which is de- pendent on the coordinated migration of cells, CHEMOKINES AND CHEMOKINE RECEPTORS is particularly dependent on chemokines for its function. -
Potent Cytotoxicity of Anti-CD20/CD74 Bispecific Antibodies in Mantle Cell and Other Lymphomas
From www.bloodjournal.org by guest on September 11, 2016. For personal use only. LYMPHOID NEOPLASIA Dual-targeting immunotherapy of lymphoma: potent cytotoxicity of anti-CD20/CD74 bispecific antibodies in mantle cell and other lymphomas Pankaj Gupta,1 David M. Goldenberg,2 Edmund A. Rossi,3 Thomas M. Cardillo,1 John C. Byrd,4 Natarajan Muthusamy,4 Richard R. Furman,5 and Chien-Hsing Chang1,3 1Immunomedics Inc, Morris Plains, NJ; 2Garden State Cancer Center, Center for Molecular Medicine and Immunology, Morris Plains, NJ; 3IBC Pharmaceuticals, Morris Plains, NJ; 4Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH; and 5Weill-Cornell Medical College, New York, NY We describe the use of novel bispecific more potent than their parental mAbs in cells and normal B cells from whole blood hexavalent Abs (HexAbs) to enhance anti- vitro. The juxtaposition of CD20 and CD74 ex vivo and significantly extended the sur- cancer immunotherapy. Two bispecific on MCL cells by the HexAbs resulted in vival of nude mice bearing MCL xenografts HexAbs [IgG-(Fab)4 constructed from vel- homotypic adhesion and triggered intra- in a dose-dependent manner, thus indicat- tuzumab (anti-CD20 IgG) and milatu- cellular changes that include loss of mito- ing stability and antitumor activity in vivo. zumab (anti-CD74 IgG)] show enhanced chondrial transmembrane potential, pro- Such bispecific HexAbs may constitute a cytotoxicity in mantle cell lymphoma duction of reactive oxygen species, rapid new class of therapeutic agents for im- (MCL) and other lymphoma/leukemia cell and sustained phosphorylation of ERKs proved cancer immunotherapy, as shown lines, as well as patient tumor samples, and JNK, down-regulation of pAkt and here for MCL and other CD20؉/CD74؉ without a crosslinking Ab, compared with Bcl-xL, actin reorganization, and lyso- malignancies. -
Cell Survival in a Pathway Induced by CD74 Factor/Scatter Factor
c-Met and Its Ligand Hepatocyte Growth Factor/Scatter Factor Regulate Mature B Cell Survival in a Pathway Induced by CD74 This information is current as Maya Gordin, Melania Tesio, Sivan Cohen, Yael Gore, Frida of September 28, 2021. Lantner, Lin Leng, Richard Bucala and Idit Shachar J Immunol published online 16 July 2010 http://www.jimmunol.org/content/early/2010/07/16/jimmun ol.0902566 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2010/07/16/jimmunol.090256 Material 6.DC1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 28, 2021 *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 All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published July 16, 2010, doi:10.4049/jimmunol.0902566 The Journal of Immunology c-Met and Its Ligand Hepatocyte Growth Factor/Scatter Factor Regulate Mature B Cell Survival in a Pathway Induced by CD74 Maya Gordin,* Melania Tesio,* Sivan Cohen,* Yael Gore,* Frida Lantner,* Lin Leng,† Richard Bucala,† and Idit Shachar* The signals regulating the survival of mature splenic B cells have become a major focus in recent studies of B cell immunology. -
Cows Selected for Divergent Mastitis Susceptibility Display a Differential
J. Dairy Sci. 103:6364–6373 https://doi.org/10.3168/jds.2019-17612 © 2020, The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Cows selected for divergent mastitis susceptibility display a differential liver transcriptome profile after experimental Staphylococcus aureus mammary gland inoculation A. Heimes,1 J. Brodhagen,1 R. Weikard,1 D. Becker,1 M. M. Meyerholz,2,3 W. Petzl,2 H. Zerbe,2 H.-J. Schuberth,3 M. Hoedemaker,4 M. Schmicke,5 S. Engelmann,6,7 and C. Kühn1,8* 1Leibniz Institute for Farm Animal Biology (FBN), Institute of Genome Biology, 18196 Dummerstorf, Germany 2Clinic for Ruminants with Ambulatory and Herd Health Services, Centre for Clinical Veterinary Medicine, Ludwig-Maximilians-University Munich, 85764 Oberschleißheim, Germany 3Immunology Unit, University of Veterinary Medicine Hannover, 30559 Hannover, Germany 4Clinic for Cattle, University of Veterinary Medicine Hannover, 30173 Hannover, Germany 5Faculty of Natural Sciences III, Martin-Luther Universität Halle-Wittenberg, 06120 Halle, Germany 6Technical University Braunschweig, Institute for Microbiology, 38023 Braunschweig, Germany 7Helmholtz Centre for Infection Research, Microbial Proteomics, 38124 Braunschweig, Germany 8Agricultural and Environmental Faculty, University Rostock, 18059 Rostock, Germany ABSTRACT Key words: BTA18, mastitis, somatic cell score, liver transcriptome, RNAseq Infection and inflammation of the mammary gland, and especially prevention of mastitis, are still major challenges for the dairy industry. Different approaches INTRODUCTION have been tried to reduce the incidence of mastitis. Rapid progress in molecular biology and genetics has Genetic selection of cows with lower susceptibility to made it possible to include information on genomic mastitis promises sustainable success in this regard. -
CD74 Interferes with the Expression of Fas Receptor on the Surface Of
Berkova et al. Journal of Experimental & Clinical Cancer Research 2014, 33:80 http://www.jeccr.com/content/33/1/80 RESEARCH Open Access CD74 interferes with the expression of fas receptor on the surface of lymphoma cells Zuzana Berkova1, Shu Wang1, Xue Ao1, Jillian F Wise1, Frank K Braun1, Abdol H Rezaeian1, Lalit Sehgal1, David M Goldenberg2,3 and Felipe Samaniego1* Abstract Background: Resistance to Fas-mediated apoptosis limits the efficacy of currently available chemotherapy regimens. We identified CD74, which is known to be overexpressed in hematological malignancies, as one of the factors interfering with Fas-mediated apoptosis. Methods: CD74 expression was suppressed in human B-lymphoma cell lines, BJAB and Raji, by either transduction with lentivirus particles or transfection with episomal vector, both encoding CD74-specific shRNAs or non-target shRNA. Effect of CD74 expression on Fas signaling was evaluated by comparing survival of mice hydrodynamically transfected with vector encoding full-length CD74 or empty vector. Sensitivity of cells with suppressed CD74 expression to FasL, edelfosine, doxorubicin, and a humanized CD74-specific antibody, milatuzumab, was evaluatedbyflowcytometryandcomparedto control cells. Fas signaling in response to FasL stimulation and the expression of Fas signaling components were evaluated by Western blot. Surface expression of Fas was detected by flow cytometry. Results: We determined that cells with suppressed CD74 are more sensitive to FasL-induced apoptosis and Fas signaling-dependent chemotherapies, edelfosine and doxorubicin, than control CD74-expressing cells. On the other hand, expression of full-length CD74 in livers protected the mice from a lethal challenge with agonistic anti-Fas antibody Jo2. A detailed analysis of Fas signaling in cells lacking CD74 and control cells revealed increased cleavage/activation of pro-caspase-8 and corresponding enhancement of caspase-3 activation in the absence of CD74, suggesting that CD74 affects the immediate early steps in Fas signaling at the plasma membrane. -
Supplemental Table S1. Primers for Sybrgreen Quantitative RT-PCR Assays
Supplemental Table S1. Primers for SYBRGreen quantitative RT-PCR assays. Gene Accession Primer Sequence Length Start Stop Tm GC% GAPDH NM_002046.3 GAPDH F TCCTGTTCGACAGTCAGCCGCA 22 39 60 60.43 59.09 GAPDH R GCGCCCAATACGACCAAATCCGT 23 150 128 60.12 56.52 Exon junction 131/132 (reverse primer) on template NM_002046.3 DNAH6 NM_001370.1 DNAH6 F GGGCCTGGTGCTGCTTTGATGA 22 4690 4711 59.66 59.09% DNAH6 R TAGAGAGCTTTGCCGCTTTGGCG 23 4797 4775 60.06 56.52% Exon junction 4790/4791 (reverse primer) on template NM_001370.1 DNAH7 NM_018897.2 DNAH7 F TGCTGCATGAGCGGGCGATTA 21 9973 9993 59.25 57.14% DNAH7 R AGGAAGCCATGTACAAAGGTTGGCA 25 10073 10049 58.85 48.00% Exon junction 9989/9990 (forward primer) on template NM_018897.2 DNAI1 NM_012144.2 DNAI1 F AACAGATGTGCCTGCAGCTGGG 22 673 694 59.67 59.09 DNAI1 R TCTCGATCCCGGACAGGGTTGT 22 822 801 59.07 59.09 Exon junction 814/815 (reverse primer) on template NM_012144.2 RPGRIP1L NM_015272.2 RPGRIP1L F TCCCAAGGTTTCACAAGAAGGCAGT 25 3118 3142 58.5 48.00% RPGRIP1L R TGCCAAGCTTTGTTCTGCAAGCTGA 25 3238 3214 60.06 48.00% Exon junction 3124/3125 (forward primer) on template NM_015272.2 Supplemental Table S2. Transcripts that differentiate IPF/UIP from controls at 5%FDR Fold- p-value Change Transcript Gene p-value p-value p-value (IPF/UIP (IPF/UIP Cluster ID RefSeq Symbol gene_assignment (Age) (Gender) (Smoking) vs. C) vs. C) NM_001178008 // CBS // cystathionine-beta- 8070632 NM_001178008 CBS synthase // 21q22.3 // 875 /// NM_0000 0.456642 0.314761 0.418564 4.83E-36 -2.23 NM_003013 // SFRP2 // secreted frizzled- 8103254 NM_003013 -
The Expression of Genes Contributing to Pancreatic Adenocarcinoma Progression Is Influenced by the Respective Environment – Sagini Et Al
The expression of genes contributing to pancreatic adenocarcinoma progression is influenced by the respective environment – Sagini et al Supplementary Figure 1: Target genes regulated by TGM2. Figure represents 24 genes regulated by TGM2, which were obtained from Ingenuity Pathway Analysis. As indicated, 9 genes (marked red) are down-regulated by TGM2. On the contrary, 15 genes (marked red) are up-regulated by TGM2. Supplementary Table 1: Functional annotations of genes from Suit2-007 cells growing in pancreatic environment Categoriesa Diseases or p-Valuec Predicted Activation Number of genesf Functions activationd Z-scoree Annotationb Cell movement Cell movement 1,56E-11 increased 2,199 LAMB3, CEACAM6, CCL20, AGR2, MUC1, CXCL1, LAMA3, LCN2, COL17A1, CXCL8, AIF1, MMP7, CEMIP, JUP, SOD2, S100A4, PDGFA, NDRG1, SGK1, IGFBP3, DDR1, IL1A, CDKN1A, NREP, SEMA3E SERPINA3, SDC4, ALPP, CX3CL1, NFKBIA, ANXA3, CDH1, CDCP1, CRYAB, TUBB2B, FOXQ1, SLPI, F3, GRINA, ITGA2, ARPIN/C15orf38- AP3S2, SPTLC1, IL10, TSC22D3, LAMC2, TCAF1, CDH3, MX1, LEP, ZC3H12A, PMP22, IL32, FAM83H, EFNA1, PATJ, CEBPB, SERPINA5, PTK6, EPHB6, JUND, TNFSF14, ERBB3, TNFRSF25, FCAR, CXCL16, HLA-A, CEACAM1, FAT1, AHR, CSF2RA, CLDN7, MAPK13, FERMT1, TCAF2, MST1R, CD99, PTP4A2, PHLDA1, DEFB1, RHOB, TNFSF15, CD44, CSF2, SERPINB5, TGM2, SRC, ITGA6, TNC, HNRNPA2B1, RHOD, SKI, KISS1, TACSTD2, GNAI2, CXCL2, NFKB2, TAGLN2, TNF, CD74, PTPRK, STAT3, ARHGAP21, VEGFA, MYH9, SAA1, F11R, PDCD4, IQGAP1, DCN, MAPK8IP3, STC1, ADAM15, LTBP2, HOOK1, CST3, EPHA1, TIMP2, LPAR2, CORO1A, CLDN3, MYO1C,