SUPPLEMENTARY DATA Supplementary Table 1

Total Page:16

File Type:pdf, Size:1020Kb

SUPPLEMENTARY DATA Supplementary Table 1 SUPPLEMENTARY DATA Supplementary Table 1. Multivariable analysis with circulating CD34+ cell level as dependent variables and clinical characteristics identified by univariate analysis as explanatory variables. Variable Beta-coefficient p-value DAN -0.377 <0.001 Age -0.101 0.297 Diabetes type 0.151 0.121 HbA1c -0.141 0.085 Retinopathy 0.096 0.289 Heart rate 0.023 0.791 Supplementary Table 2. Clinical characteristics of patients with available measure of PBMC expression of p66Shc and Sirt1 (extracted from table 1). Characteristic No DAN DAN Age, years 60.0±14.0 59.7±15.0 Sex male, % 70 70 Type 1 / type 2 diabetes 3/7 3/7 Disease duration, years 10.0±7.8 12.9±7.8 HbA1c, % 7.7±1.8 7.9±1.4 p66Shc / β-actin expression 1.01±0.15 1.63±0.95 Sirt1 / β-actin expression 1.09±0.29 0.75±0.17 ©2013 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db13-0894/-/DC1 SUPPLEMENTARY DATA Supplementary Table 3. Primer sequences. Sequence Genes FW primer sequence RV primer sequence accession number Mouse genes vascular cell adhesion molecule 1 (Vcam1) TATGTCAACGTTGCCCCCAA GCTGTCTGCTCCACAGGATT NM_011693.3 src homology 2 domain-containing transforming protein C1 (Shc1) – p66shc TGACAGGATGGCTGGCTT ACGGACTTCATGGTCTCC NM_001113331.2 intercellular adhesion molecule 1 (Icam1) AGCTCGGAGGATCACAAACG TCCAGCCGAGGACCATACAG NM_010493.2 integrin alpha L (Itgal) – CD11a ACTTCCACTTCCCGATCTGC CCACCTTTTGGTCCCTTGGT NM_001253872.1 integrin alpha 4 (Itga4) – CD49d GTTCTCCACCAAGAGCGCAT GATGAGCCAGCGCTTCGAC NM_010576.3 integrin alpha 5 (Itga5) – CD49e GAACCCTGTGTCCTGCATCA TTGGAGTTCCACCTCGAAGC NM_010577.3 selectin, lymphocyte (Sell) – CD62L TGATGCAGGGTATTACGGGC CACTGGACCACTTGGCAGAT NM_001164059.1 integrin alpha X (Itgax) – CD11c TCTTCTGCTGTTGGGGTTTGT GAGCACACTGTGTCCGAACT NM_021334.2 CAGTAGCACTAATTCCAAGTTCT Sirtuin 1 (Sirt1) A TTGGCATATTCACCACCTAGC NM_001159589.1 ubiquitin C (Ubc) GCCCAGTGTTACCACCAAGA CCCATCACACCCAAGAACA NM_019639.4 Human Genes sirtuin 1 (SIRT1) TACCGAGATAACCTTCTGTTCG GTTCGAGGATCTGTGCCAAT NM_012238.4 selectin L (SELL) – CD62L GCCCTCTGTTACACAGCTTCT GGCCCATAGTACCCCACATC NM_000655.4 actin, beta (ACTB) GGATGCCACAGGACTCCA AGAGCTACGAGCTGCCTGAC NM_001101.3 src homology 2 domain-containing transforming protein C1 (SHC1) – p66shc AATCAGAGAGCCTGCCACATT CTCTTCCTCCTCCTCATC NM_001130040 ©2013 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db13-0894/-/DC1 SUPPLEMENTARY DATA Supplementary Figure 1. Baseline levels of EPC and LKS cells in diabetic and sympathectomized (6- OHDA) mice. * p<0.05 versus non-diabetic control mice. “n.s.” stands for “not significant” compared with non-diabetic control mice. ©2013 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db13-0894/-/DC1 SUPPLEMENTARY DATA Supplementary Figure 2. Effects of STZ and 6-OHDA in vitro on apoptosis and necrosis of total murine bone marrow cells (A), murine CD34+ bone marrow cells (B) and growth of hematopoietic colonies from murine bone marrow cells (C). In panel (A), *p<0.05 versus percentages in the control (CTRL) condition. In (C), both STZ and 6-OHDA were incubated at 10 microM concentration. AB C ©2013 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db13-0894/-/DC1 SUPPLEMENTARY DATA Supplementary Figure 3. Effects of isoproterenol on PBMC Sirt1 and CD62L expression. PBMC of healthy human donors were incubated without or with isoproterenol 100 μM and gene expression of Sirt1 and CD62L (L-selectin, Sell), were analyzed. The cellular concentration of cyclic AMP (cAMP) were also determined to select isoproterenol concentrations that result in increased cAMP production. *p<0.05 100 vs 0 μM isoproterenol. 2.0 * 2.0 2.0 * 1.5 1.5 1.5 1.0 1.0 1.0 * cAMP (pg/mL) cAMP 0.5 0.5 0.5 Sirt1 mRNA (fold change) (fold Sirt1 mRNA 0.0 0.0 change) (fold mRNA CD62L 0.0 0 M 100 M 0 M 100 M 0 M 100 M [Isoproterenol] [Isoproterenol] [Isoproterenol] Supplementary Figure 4. Generation and characterization of transgenic animals. The breeding strategy used to generate Vav1-Sirt1-/- and Vav1-Sirt1TG mice is shown. Knock-out and overexpression of Sirt1, respectively, was confirmed by real time PCR on LKS cells isolated by FACS. Cre/+ flox/flox Cre/+ stop‐flox Vav1 : Sirt1ex4 Vav1 Sirt1 ∆flox/+ Sirt1ex4 Sirt1 expression Without Dapi With Dapi + Ctr cKit KO Lin– Lin– Sca1+ Over LKS sorting: efficient knock-down / overexpression ©2013 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db13-0894/-/DC1 SUPPLEMENTARY DATA Supplementary Figure 5. Contribution of Vav1+ cells to the microvasculature of ischemic muscles. Vav1-YFP mice were subjected to hind limb ischemia and muscle sections stained for Isolectin B4 (red) to visualize the vascular network (nuclei counterstained in blue with Hoechst); the green/yellow signal represents the spontaneous YFP fluorescence. Merged figures are shown. YFP-expressing cells, indicating Vav1+ cells were only found in sections of ischemic muscles and not of non ischemic contralateral control muscles. Some YFP+ cells were clearly integrated into the vasculature co-staining with Isolectin, while other YFP+ cells did not co-localize with the red Isolectin signal and were considered not integrated (likely intravascular). The right panel shows quantification of total (integrated and non integrated) and integrated cells in ischemic and non ischemic muscle sections. Ischemic muscle section Non-ischemic muscle section Ischemic muscle sections Non-ischemic muscle sections Hoechst 4 Isolectin 2.1 YFP 3 1.4 2 Cells /Cells field 1 integrated 0.0 0.0 0 s s ll ll e e + c + c P P F F Y Y l d not ta e o t T ra integrated g te In Supplementary Figure 6. Expression of niche adhesion molecules in the BM. mRNA was extracted from BM cells of control non diabetic, T1D (STZ) and sympathectomised (6-OHDA) mice and analyzed for expression of typical niche genes encoding for adhesion molecules (n=5/group). *p<0.05 versus non diabetic control. 4 CTRL T1D (STZ) * * * 6-OHDA 3 * * * ** * 2 * 1 BM mRNA expression mRNA BM 0 a e 9d 2L 4 6 CD11 CD11c CD CD49 CD ICAM1 ©2013 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db13-0894/-/DC1 SUPPLEMENTARY DATA Supplementary Figure 7. upregulation of adhesion molecule lower panel, *p<0.05 versus ba Time course analysis of bone 4 3 sal; **p<0.05 versus 1 week. mRNA Basal s in T1D mice from 1 to 4 weeks after STZ administration. In the 1 Week 2 2 Week 3 Week 1 4 Week (fold change vs basal) 0 CD49e CD49d ICAM1 CD62L CD11a marrow neuropathy development and CD11c CD49e CD49d ICAM1 CD62L CD11a CD11c p<0.05 vs basal CD49e CD49d ICAM1 CD62L CD11a CD11c p<0.05 vs basal CD49e CD49d ICAM1 CD62L CD11a n.s. CD11c CD49e CD49d ICAM1 CD62L CD11a CD11c ©2013 American Diabetes Association. Published online at http ://diabetes.diabetesjournals.org /lookup/suppl/doi:10.2337/db13-089 4/-/DC1 .
Recommended publications
  • 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 channu.vastrad@gmail.com 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.
    [Show full text]
  • Expression of the Hematopoietic Stem Cell Antigen CD34 on Blood and Bone Marrow Monoclonal Plasma Cells from Patients with Multiple Myeloma
    Bone Marrow Transplantation, (1997) 19, 553–556 1997 Stockton Press All rights reserved 0268–3369/97 $12.00 Expression of the hematopoietic stem cell antigen CD34 on blood and bone marrow monoclonal plasma cells from patients with multiple myeloma T Kimlinger1 and TE Witzig2 1Department of Laboratory Medicine and 2Division of Internal Medicine and Hematology, Mayo Clinic and Mayo Foundation, Rochester, MN, USA Summary: led to strategies to deplete the tumor cells from the harvest product prior to reinfusion of the stem cells. Monoclonal plasma cells (CD38+CD45−/dim) are typi- One of the current attempts at purifying the harvest pro- cally present in the blood of patients with active mye- duct uses antibody to the CD34 antigen to positively select loma and can contaminate stem cell harvests. This has and enrich hematopoietic stem cells and in the process led to strategies that select CD34+ cells for use in auto- purge the stem cell product of tumor cells and T cells.11–13 logous stem cell transplantation with the goal of The CD34 antigen identifies a lymphohematopoietic stem decreasing tumor cell contamination. The aim of this cell, is present on 1–5% of adult bone marrow cells, and study was to learn if the CD34 antigen is expressed on is expressed on early B cells. The characteristics of this monoclonal plasma cells in the blood or marrow of important antigen and its clinical relevance have recently patients with multiple myeloma. We used three-color been reviewed.14 CD34+ hematopoietic cells from blood or flow cytometry (surface CD38;CD45 and cytoplasmic marrow can reconstitute hematopoiesis after high-dose kappa or lambda) to identify monoclonal plasma cells therapy programs.15 The number of CD34+ cells reinfused in the blood (n = 24) and marrow (n = 37) from patients predicts the time to engraftment.16,17 with plasma cell proliferative disorders.
    [Show full text]
  • 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.
    [Show full text]
  • MUC1 Is a Potential Target for the Treatment of Acute Myeloid Leukemia Stem Cells
    Published OnlineFirst July 18, 2013; DOI: 10.1158/0008-5472.CAN-13-0677 Cancer Tumor and Stem Cell Biology Research MUC1 Is a Potential Target for the Treatment of Acute Myeloid Leukemia Stem Cells Dina Stroopinsky1, Jacalyn Rosenblatt1, Keisuke Ito1, Heidi Mills1, Li Yin2, Hasan Rajabi2, Baldev Vasir2, Turner Kufe1, Katarina Luptakova1, Jon Arnason1, Caterina Nardella1, James D. Levine1, Robin M. Joyce1, Ilene Galinsky2, Yoram Reiter3, Richard M. Stone2, Pier Paolo Pandolfi1, Donald Kufe2, and David Avigan1 Abstract Acute myeloid leukemia (AML) is a malignancy of stem cells with an unlimited capacity for self-renewal. MUC1 is a secreted, oncogenic mucin that is expressed aberrantly in AML blasts, but its potential uses to target AML þ À stem cells have not been explored. Here, we report that MUC1 is highly expressed on AML CD34 /lineage / À CD38 cells as compared with their normal stem cell counterparts. MUC1 expression was not restricted to AML þ À CD34 populations as similar results were obtained with leukemic cells from patients with CD34 disease. Engraftment of AML stem cell populations that highly express MUC1 (MUC1high) led to development of leukemia in NOD-SCID IL2Rgammanull (NSG) immunodeficient mice. In contrast, MUC1low cell populations established normal hematopoiesis in the NSG model. Functional blockade of the oncogenic MUC1-C subunit with the peptide inhibitor GO-203 depleted established AML in vivo, but did not affect engraftment of normal hematopoietic cells. Our results establish that MUC1 is highly expressed in AML stem cells and they define the MUC1-C subunit as a valid target for their therapeutic eradication.
    [Show full text]
  • 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.
    [Show full text]
  • PAPC Couples the Segmentation Clock to Somite Morphogenesis by Regulating N-Cadherin-Dependent Adhesion
    © 2017. Published by The Company of Biologists Ltd | Development (2017) 144, 664-676 doi:10.1242/dev.143974 RESEARCH ARTICLE PAPC couples the segmentation clock to somite morphogenesis by regulating N-cadherin-dependent adhesion Jérome Chal1,2,3,4,5,*, Charlenè Guillot3,4,* and Olivier Pourquié1,2,3,4,5,6,7,‡ ABSTRACT specific level of the PSM called the determination front. The Vertebrate segmentation is characterized by the periodic formation of determination front is defined as a signaling threshold epithelial somites from the mesenchymal presomitic mesoderm implemented by posterior gradients of Wnt and FGF (Aulehla (PSM). How the rhythmic signaling pulse delivered by the et al., 2003; Diez del Corral and Storey, 2004; Dubrulle et al., segmentation clock is translated into the periodic morphogenesis of 2001; Hubaud and Pourquie, 2014; Sawada et al., 2001). Cells of somites remains poorly understood. Here, we focused on the role of the posterior PSM exhibit mesenchymal characteristics and paraxial protocadherin (PAPC/Pcdh8) in this process. We showed express Snail-related transcription factors (Dale et al., 2006; that in chicken and mouse embryos, PAPC expression is tightly Nieto, 2002). In the anterior PSM, cells downregulate snail/slug regulated by the clock and wavefront system in the posterior PSM. We expression and upregulate epithelialization-promoting factors such observed that PAPC exhibits a striking complementary pattern to N- as paraxis (Barnes et al., 1997; Sosic et al., 1997). This molecular cadherin (CDH2), marking the interface of the future somite boundary transition correlates with the anterior PSM cells progressively in the anterior PSM. Gain and loss of function of PAPC in chicken acquiring epithelial characteristics (Duband et al., 1987; Martins embryos disrupted somite segmentation by altering the CDH2- et al., 2009).
    [Show full text]
  • Kinetic Properties of Collagen Receptors on Human Keratinocytes 2337
    Journal of Cell Science 112, 2335-2345 (1999) 2335 Printed in Great Britain © The Company of Biologists Limited 1999 JCS9937 Integrin α and β subunit contribution to the kinetic properties of α2β1 collagen receptors on human keratinocytes analyzed under hydrodynamic conditions Bénédicte Masson-Gadais, Anne Pierres, Anne-Marie Benoliel, Pierre Bongrand* and Jean-Claude Lissitzky Laboratoire d’Immunologie, INSERM U 387, Hôpital de Sainte-Marguerite, BP 29, 13274 Marseille Cedex 09, France *Author for correspondence (e-mail: bongrand@marseille.inserm.fr) Accepted 10 May; published on WWW 24 June 1999 SUMMARY The adhesion of keratinocytes to type I collagen or with ligand recognition and also with the ligand-β1 chain laminin 5 was studied in a laminar flow chamber. These interactions responsible for bond stabilization. The latter experiments provided an insight into the binding kinetics hypothesis was supported by the finding that the partial of integrins in their natural environment and the effects of alteration of α2 chain function by inhibiting antibodies was monoclonal antibodies specific for α and β chains. Cells corrected by anti-β1 chain antibody TS2/16. These results driven by a force too low to alter the natural lifetime of a could not be ascribed to allosteric changes of the functional single bond displayed multiple arrests. Studying the region of β1 integrin subunits regulated by TS2/16 since frequency and duration of these arrests yielded fairly direct there was no competition between the binding of TS2/16 information on the rate of bond formation (on-rate) and and anti-α2 chain antibodies. dissociation (off-rate). Off-rate values obtained on collagen Interpreted within the framework of current concepts of or laminin 5 (0.06 seconds−1) were tenfold lower than values integrin-ligand binding topology, these data suggest that determined on selectins.
    [Show full text]
  • 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.
    [Show full text]
  • The Role of CD40/CD40 Ligand Interactions in Bone Marrow Granulopoiesis
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by PubMed Central Review Article TheScientificWorldJOURNAL (2011) 11, 2011–2019 ISSN 1537-744X; doi:10.1100/2011/671453 The Role of CD40/CD40 Ligand Interactions in Bone Marrow Granulopoiesis Irene Mavroudi1, 2 and Helen A. Papadaki1 1Department of Hematology, University of Crete School of Medicine, P.O. Box 1352, 71110 Heraklion, Crete, Greece 2Graduate Program “Molecular Basis of Human Disease”, University of Crete School of Medicine, 71003 Heraklion, Greece Received 29 August 2011; Accepted 5 October 2011 Academic Editor: Marco Antonio Cassatella The CD40 ligand (CD40L) and CD40 are two molecules belonging to the TNF/TNF receptor super- family, and their role in adaptive immune system has widely been explored. However, the wide range of expression of these molecules on hematopoietic as well as nonhematopoietic cells has revealed multiple functions of the CD40/CD40L interactions on different cell types and processes such as granulopoiesis. CD40 triggering on stromal cells has been documented to enhance the expression of granulopoiesis growth factors such as granulocyte-colony-stimulating factor (G- CSF) and granulocyte/monocyte-colony-stimulating factor (GM-CSF), and upon disruption of the CD40/CD40L-signaling pathway, as in the case of X-linked hyperimmunoglobulin M (IgM) syn- drome (XHIGM), it can lead to neutropenia. In chronic idiopathic neutropenia (CIN) of adults, however, under the influence of an inflammatory microenvironment, CD40L plays a role in granu- locytic progenitor cell depletion, providing thus a pathogenetic cause of CIN. KEYWORDS: CD40L, CD40, granulopoiesis, G-CSF, GM-CSF, Flt3-L, neutropenia, apoptosis, tumor necrosis factor family, and granulocytic progenitor cells Correspondence should be addressed to Helen A.
    [Show full text]
  • 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.
    [Show full text]
  • 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,
    [Show full text]
  • Precursors in Human Bone Marrow Identifies Autonomously
    A Feeder-Free Differentiation System Identifies Autonomously Proliferating B Cell Precursors in Human Bone Marrow This information is current as Helene Kraus, Sandra Kaiser, Konrad Aumann, Peter of September 30, 2021. Bönelt, Ulrich Salzer, Dietmar Vestweber, Miriam Erlacher, Mirjam Kunze, Meike Burger, Kathrin Pieper, Heiko Sic, Antonius Rolink, Hermann Eibel and Marta Rizzi J Immunol 2014; 192:1044-1054; Prepublished online 30 December 2013; Downloaded from doi: 10.4049/jimmunol.1301815 http://www.jimmunol.org/content/192/3/1044 Supplementary http://www.jimmunol.org/content/suppl/2013/12/30/jimmunol.130181 http://www.jimmunol.org/ Material 5.DCSupplemental References This article cites 55 articles, 21 of which you can access for free at: http://www.jimmunol.org/content/192/3/1044.full#ref-list-1 Why The JI? Submit online. by guest on September 30, 2021 • 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 *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
    [Show full text]