DOCSLIB.ORG

Correlation Between the CRM and Inflammatory Macrophage Scores Across 10 Renal Transplant Datasets (1,499 Graft Biopsies)

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Correlation Between the CRM and Inflammatory Macrophage Scores Across 10 Renal Transplant Datasets (1,499 Graft Biopsies) Supplementary figure and table legends Supplementary Figure 1: Correlation between the CRM and inflammatory macrophage scores across 10 renal transplant datasets (1,499 graft biopsies). The CRM and inflammatory macrophage scores in each dataset are standardized (mean = 0, SD = 1). Gray bar: 95% confidence interval. Supplementary Figure 2: (A). Correlation analysis of the 27-gene pro-inflammatory macrophage polarization signature across 104 diseases using Metasignature shows that many genes are significantly correlated with each other. (B) Enrichment of the 3-gene signature across 25 immune and epithelial cell types shows that the signature are enriched in inflammatory macrophages. Supplementary Figure 3: M1 score in two independent validation datasets is higher in AR biopsies than in STA. STA, stable; AR, acute rejection. Supplementary Figure 4: RT-qPCR of three genes resulting from LASSO analysis on discovery cohort. (A) Relative expression levels of each gene in AR (blue) samples vs. STA (orange) samples. All genes are significantly over-expressed in AR versus STA. Supplementary Figure 5: AUCs of 3-gene signature in a lung dataset, consisting in 32 biopsies. Supplementary Figure 6: Schematic overview of the longitudinal cohort (GSE25902). Supplementary Figure 7: M1 score is higher in both ACR and AMR, compared to STA biopsies. ACR, acute cellular rejection; AMR, antibody-mediated rejection; STA, stable Supplementary Table 1: Detailed description of datasets used in the discovery and direct validation cohorts. AR, acute rejection; STA, stable; HC, healthy controls; AMR, antibody mediated rejection; ACR, Acute cellular rejection; CAN, chronic allograft nephropathy; HEPC, hepatitis C; TOL, operationally tolerant; CNIT, calcineurin inhibitor toxicity; IF/TA, interstitial fibrosis/tubular atrophy; IF/TA+I, interstitial fibrosis/tubular atrophy plus inflammation; ADNR, acute dysfunction with no rejection. ISHLT, International Society for Heart & Lung Transplantation Supplementary Table 2: Methodology utilized to identify subset genes. A generalized linear regression model with binary classification (AR vs STA) was employed to identify a subset of the inflammatory macrophage polarization genes most discriminative in > four out of eight discovery datasets A B 4 C STA 3 STA AR AR STA 2 4 AR ed) ed) 2 ed) z z z 1 2 0 0 −1 0 CRM score (standardi CRM score (standardi CRM score (standardi Pearson correlation = 0.95 Pearson correlation = 0.77 P-value < 2.2E-16 −2 P-value < 2.2E-16 −2 Pearson correlation = 0.64 −2 P-value < 2.2E-16 −3 −2 0 2 −2.5 0.0 2.5 5.0 −2.5 0.0 2.5 5.0 M(IFN-gamma) score (standardized) M(IL4) score (standardized) M(IL10) score (standardized) Enrichment for 3−gene set A B −1 0 1 2 3 4 NK T−cell Band cell 11 HLAHLADRB1! DRB1 CD8+ T−cell−activated CCL4CCL4 0.80.8 CD4+ T−cell−activated CCL5 CCL5 T−cell FASFAS 0.60.6 NK cell IL15IL15 0.40.4 CCL8CCL8 T−reg CD86CD86 0.20.2 CD8+ T−cell BCL2A1BCL2A1 CD4+ T−cell CD40CD40 00 Neutrophil CCL20CCL20 ! 0.20.2 IL2RAIL2RA Eosinophils CCR7CCR7 Endothelial cell IL7RIL7R B−cell (plasma cell) CCL19 CCL19 MetaMyelocyte CXCL10CXCL10 B−cell CXCL11CXCL11 CXCL9CXCL9 Megakaryocyte IL15RAIL15RA Basophil TNF TNF Monocyte−CD16+ SPHK1SPHK1 B−cell (centrocyte) NOS2NOS2 SLC7A5SLC7A5 Dendritic cells (Plasmacytoid) CXCL16CXCL16 Monocyte IL6 IL6 Monocyte−CD16− CCL15 CCL15 ORM1 Dendritic cells (Myeloid) ORM1 PTX3 Dendritic cells HLA CCL4 CCL5 F IL15 CCL8 CD86 BCL2A1 CD40 CCL20 IL2RA CCR7 IL7R CCL19 CXCL10 CXCL11 CXCL9 IL15RA TNF SPHK1 NOS2 SLC7A5 CXCL16 IL6 CCL15 ORM1 PTX3PTX3 AS F IL15 CCL8 CD86 BCL2A1 CD40 CCL20 IL2RA CCR7 IL7R CCL19 CXCL10 CXCL11 CXCL9 IL15RA TNF SPHK1 NOS2 SLC7A5 CXCL16 IL6 CCL15 ORM1 PTX3 AS M2 macrophage ! DRB1 M1 macrophage Std. Deviations (Z−score) GSE53605 GSE76882 4 2 ● ● STA ● ● STA ● ● AR AR ●● ● ● ● ●● 1 ●●● ●● ●● ● ●● 2 ●● ● ●● ● ●● ● ● ● ●●●● ●● ●● 0 ● ● ● ● ● ● ● ●● ● ● ● ● ●● ●●● ● ● ●● ●●● ●●● ●● ●● ● ● ●● ●● ● ● ● ●●● ●●● ● ● ●● −1 ●● 0 ●●●● ●● ● ●●● ●● ●● ●●●●● ● ●●●● ● ●●●● ● ●●● ●●● ●●● ●● ●●● ●●●●●● ● ●● ● ●●●● ●●●● ●● −2 ●●● ●●● −2 −3 STA AR STA AR p = 6.60353791088933e−06 p = 6.25529816225218e−16 CXCL11 CCL19 CD86 • • • ct ct ct Δ Δ Δ - - - 2 2 2 • • • p < 2.2E-16 p = 0.016 p = 0.009 M1 R 1.00 0.75 0.50 v ositi P 0.25 ue r T A 0.00 0.00 0.25 0.50 0.75 1.00 False Positiv Longitudinal cohort (GSE25902) 120 renal allograft biopsies 24 biopsies from 96 biopsies from AR patients 48 patients 72 longitudinal 24 biopsies from stable biopsies patients from 24 patients 24 biopsies at 6 24 biopsies 24 24 biopsies at time months after months after of implantation implantation implantation GSE36059 GSE48581 1.1e−08 1.9e−11 7.1e−07 2e−05 1.7e-03 1.1e−11 4.9e-03 9.1e-04 2 M1 Score 0 −2 STA ABMR Mixed TCMR STA ABMR Mixed TCMR Enrichment for 3−gene set A B C −1 0 1 2 3 4 CD86 CXCL11 CCL19 NK T−cell Megakaryocyte 4 Band cell 11 Plasma cell HLAHLADRB1! DRB1 CD8+ T−cell−activated CCL4 Basophil CCL4 0.80.8 2 CD4+ T−cell−activated CCL5CCL5 Neutrophil T−cell FASFAS 0.60.6 CD4+ T cell NK cell IL15IL15 0 0.40.4 Eosinophils CCL8CCL8 T−reg NKT cell CD86CD86 0.20.2 CD8+ T−cell BCL2A1BCL2A1 −2 CD4+ T cell (activated) CD4+ T−cell CD40CD40 00 Band cell Neutrophil CCL20CCL20 ! 0.20.2 NK cell −4 IL2RAIL2RA Eosinophils CCR7CCR7 CD8+ T cell Endothelial cell IL7R IL7R CD8+ T cell (activated) B−cell (plasma cell) CCL19CCL19 T cell MetaMyelocyte CXCL10CXCL10 Treg CXCL11CXCL11 B−cell CXCL9CXCL9 Endothelial cell Megakaryocyte IL15RA IL15RA MetaMyelocyte Basophil TNFTNF B cell Monocyte−CD16+ SPHK1SPHK1 Plasmacytoid Dendritic cells B−cell (centrocyte) NOS2NOS2 SLC7A5SLC7A5 B cell (centrocyte) Dendritic cells (Plasmacytoid) CXCL16 CXCL16 CD16- Monocyte Monocyte IL6 IL6 Monocyte−CD16− CCL15 Monocyte CCL15 ORM1 Dendritic cells Dendritic cells (Myeloid) ORM1 PTX3 Dendritic cells HLA CCL4 CCL5 F IL15 CCL8 CD86 BCL2A1 CD40 CCL20 IL2RA CCR7 IL7R CCL19 CXCL10 CXCL11 CXCL9 IL15RA TNF SPHK1 NOS2 SLC7A5 CXCL16 IL6 CCL15 ORM1 PTX3PTX3 CD16+ Monocyte AS CCL5 F IL15 CCL8 CD86 BCL2A1 CD40 CCL20 IL2RA CCR7 IL7R CCL19 CXCL10 CXCL11 CXCL9 IL15RA TNF SPHK1 NOS2 SLC7A5 CXCL16 IL6 CCL15 ORM1 PTX3 AS M2 macrophage ! Myeloid Dendritic cells DRB1 M2 macrophage M1 macrophage M1 macrophage Std. Deviation (Z−score) GSE53605 GSE76882 4 STA STA 2 AR AR 2 0 M1 Score 0 −2 −2 STA AR STA AR p = 2.905e−05 p = 1.134e−08 CXCL11 CCL19 CD86 • • • ct ct ct Δ Δ Δ - - - 2 2 2 • • • p < 2.2E-16 p = 0.016 p = 0.009 M(IFNg) R 1.00 0.75 0.50 v ositi P ue 0.25 r T A 0.00 0.00 0.25 0.50 0.75 1.00 False Positiv Longitudinal cohort (GSE25902) 120 renal allograft biopsies 24 biopsies from 96 biopsies from AR patients 48 patients 72 longitudinal 24 biopsies from stable biopsies patients from 24 patients 24 biopsies at 6 24 biopsies 24 24 biopsies at time months after months after of implantation implantation implantation GSE36059 GSE48581 1.1e−08 1.9e−11 7.1e−07 2e−05 1.7e-03 1.1e−11 4.9e-03 9.1e-04 2 M(IFNg) Score 0 −2 STA AMR Mixed ACR STA AMR Mixed ACR.
Load more

Recommended publications
  • Enhanced Monocyte Migration to CXCR3 and CCR5 Chemokines in COPD
    ERJ Express. Published on March 10, 2016 as doi: 10.1183/13993003.01642-2015 ORIGINAL ARTICLE IN PRESS | CORRECTED PROOF Enhanced monocyte migration to CXCR3 and CCR5 chemokines in COPD Claudia Costa1, Suzanne L. Traves1, Susan J. Tudhope1, Peter S. Fenwick1, Kylie B.R. Belchamber1, Richard E.K. Russell2, Peter J. Barnes1 and Louise E. Donnelly1 Affiliations: 1Airway Disease, National Heart and Lung Institute, Imperial College London, London, UK. 2Chest Clinic, King Edward King VII Hospital, Windsor, UK. Correspondence: Louise E. Donnelly, Airway Disease, National Heart and Lung Institute, Dovehouse Street, London, SW3 6LY, UK. E-mail: [email protected] ABSTRACT Chronic obstructive pulmonary disease (COPD) patients exhibit chronic inflammation, both in the lung parenchyma and the airways, which is characterised by an increased infiltration of macrophages and T-lymphocytes, particularly CD8+ cells. Both cell types can express chemokine (C-X-C motif) receptor (CXCR)3 and C-C chemokine receptor 5 and the relevant chemokines for these receptors are elevated in COPD. The aim of this study was to compare chemotactic responses of lymphocytes and monocytes of nonsmokers, smokers and COPD patients towards CXCR3 ligands and chemokine (C-C motif) ligand (CCL)5. Migration of peripheral blood mononuclear cells, monocytes and lymphocytes from nonsmokers, smokers and COPD patients toward CXCR3 chemokines and CCL5 was analysed using chemotaxis assays. There was increased migration of peripheral blood mononuclear cells from COPD patients towards all chemokines studied when compared with nonsmokers and smokers. Both lymphocytes and monocytes contributed to this enhanced response, which was not explained by increased receptor expression.
    [Show full text]
  • IL-34–Dependent Intrarenal and Systemic Mechanisms Promote Lupus Nephritis in MRL-Faslpr Mice
    BASIC RESEARCH www.jasn.org IL-34–Dependent Intrarenal and Systemic Mechanisms Promote Lupus Nephritis in MRL-Faslpr Mice Yukihiro Wada,1 Hilda M. Gonzalez-Sanchez,1 Julia Weinmann-Menke,2 Yasunori Iwata,1 Amrendra K. Ajay,1 Myriam Meineck,2 and Vicki R. Kelley1 1Renal Division, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts; and 2Department of Nephrology and Rheumatology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany ABSTRACT lpr Background In people with SLE and in the MRL-Fas lupus mouse model, macrophages and autoanti- bodies are central to lupus nephritis. IL-34 mediates macrophage survival and proliferation, is expressed by tubular epithelial cells (TECs), and binds to the cFMS receptor on macrophages and to a newly identified second receptor, PTPRZ. Methods To investigate whether IL-34–dependent intrarenal and systemic mechanisms promote lupus lpr nephritis, we compared lupus nephritis and systemic illness in MRL-Fas mice expressing IL-34 and IL-34 lpr knockout (KO) MRL-Fas mice. We also assessed expression of IL-34 and the cFMS and PTPRZ receptors in patients with lupus nephritis. lpr Results Intrarenal IL-34 and its two receptors increase during lupus nephritis in MRL-Fas mice. In knock- out mice lacking IL-34, nephritis and systemic illness are suppressed. IL-34 fosters intrarenal macrophage accumulation via monocyte proliferation in bone marrow (which increases circulating monocytes that are recruited by chemokines into the kidney) and via intrarenal macrophage proliferation. This accumulation leads to macrophage-mediated TEC apoptosis. We also found suppression of circulating autoantibodies and glomerular antibody deposits in the knockout mice.
    [Show full text]
  • The YY1/Mir-548T-5P/CXCL11 Signaling Axis Regulates Cell
    Ge et al. Cell Death and Disease (2020) 11:294 https://doi.org/10.1038/s41419-020-2475-3 Cell Death & Disease ARTICLE Open Access The YY1/miR-548t-5p/CXCL11 signaling axis regulates cell proliferation and metastasis in human pancreatic cancer Wan-Li Ge1,2,QunChen1,2, Ling-Dong Meng1,2,Xu-MinHuang1,2,Guo-dongShi1,2, Qing-Qing Zong1,3,PengShen1,2, Yi-Chao Lu1,2, Yi-Han Zhang1,2,YiMiao1,2,Jing-JingZhang1,2 andKui-RongJiang 1,2 Abstract Pancreatic cancer (PC) is a malignant tumor with a poor prognosis and high mortality. However, the biological role of miR-548t-5p in PC has not been reported. In this study, we found that miR-548t-5p expression was significantly decreased in PC tissues compared with adjacent tissues, and that low miR-548t-5p expression was associated with malignant PC behavior. In addition, high miR-548t-5p expression inhibited the proliferation, migration, and invasion of PC cell lines. Regarding the molecular mechanism, the luciferase reporter gene, chromatin immunoprecipitation (ChIP), and functional recovery assays revealed that YY1 binds to the miR-548t-5p promoter and positively regulates the expression and function of miR-548t-5p. miR-548t-5p also directly regulates CXCL11 to inhibit its expression. A high level of CXCL11 was associated with worse Tumor Node Metastasis (TNM) staging in patients with PC, enhancing proliferation and metastasis in PC cells. Our study shows that the YY1/miR-548t-5p/CXCL11 axis plays an important role in PC and provides a new potential candidate for the treatment of PC.
    [Show full text]
  • Exploration of Prognostic Biomarkers and Therapeutic Targets in the Microenvironment of Bladder Cancer Based on CXC Chemokines
    Exploration of Prognostic Biomarkers and Therapeutic Targets in The Microenvironment of Bladder Cancer Based on CXC Chemokines Xiaoqi Sun Department of Urology, Kaiping Central Hospital, Kaiping, 529300, China Qunxi Chen Department of Pathology, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China Lihong Zhang Department of Pathology, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China Jiewei Chen Department of Pathology, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China Xinke Zhang ( [email protected] ) Sun Yat-sen University Cancer Center Research Keywords: Bladder cancer, Biomarkers, CXC Chemokines, Microenvironment Posted Date: February 24th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-223127/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/29 Abstract Background: Bladder cancer (BLCA) has a high rate of morbidity and mortality, and is considered as one of the most malignant tumors of the urinary system. Tumor cells interact with surrounding interstitial cells, playing a key role in carcinogenesis and progression, which is partly mediated by chemokines. CXC chemokines exert anti‐tumor biological roles in the tumor microenvironment and affect patient prognosis. Nevertheless, their expression and prognostic values patients with BLCA remain unclear. Methods: We used online tools, including Oncomine, UALCAN, GEPIA, GEO databases, cBioPortal, GeneMANIA, DAVID 6.8, Metascape, TRUST (version 2.0), LinkedOmics, TCGA, and TIMER2.0 to perform the relevant analysis. Results: The mRNA levels of C-X-C motif chemokine ligand (CXCL)1, CXCL5, CXCL6, CXCL7, CXCL9, CXCL10, CXCL11, CXCL13, CXCL16, and CXCL17 were increased signicantly increased, and those of CXCL2, CXCL3, and CXCL12 were decreased signicantly in BLCA tissues as assessed using the Oncomine, TCGA, and GEO databases.
    [Show full text]
  • Functional Redundancy of CXCR3/CXCL10 Signaling in the Recruitment
    Page 1 of 32 Diabetes Functional redundancy of CXCR3/CXCL10 signaling in the recruitment of diabetogenic CTL to pancreatic islets in a virally induced autoimmune diabetes model Ken T. Coppieters*,§, Natalie Amirian*, Philippe P. Pagni*, Carmen Baca Jones*, Anna Wiberg*, Stanley Lasch#, Edith Hintermann#, Urs Christen# and Matthias G. von Herrath*,§ *Type 1 Diabetes Center, The La Jolla Institute for Allergy and Immunology, 9420 Athena Circle, La Jolla CA 92037, U.S.A. §Type 1 Diabetes R&D Center, Novo Nordisk Inc., Seattle, WA, U.S.A. #Pharmazentrum Frankfurt / ZAFES, Goethe University Hospital, Frankfurt am Main, Germany Short title: CXCR3/CXCL10 signaling in type 1 diabetes Correspondence: Matthias von Herrath, Type 1 Diabetes Center, The La Jolla Institute for Allergy and Immunology, 9420 Athena Circle, La Jolla CA 92037, U.S.A., [email protected], Phone: (858) 752-6817; Fax: (858) 752-6993 1 Diabetes Publish Ahead of Print, published online February 22, 2013 Diabetes Page 2 of 32 Abstract Cytotoxic T lymphocytes (CTL) constitute a major effector population in pancreatic islets from patients suffering from type 1 diabetes (T1D) and thus represent attractive targets for intervention. Some studies have suggested that blocking the interaction between the chemokine CXCL10 and its receptor CXCR3 on activated CTL potently inhibits their recruitment and prevents beta cell death. Since recent studies on human pancreata from T1D patients have indicated that both ligand and receptor are abundantly present, we reevaluated whether their interaction constitutes a pivotal node within the chemokine network associated with T1D. Our present data in a viral mouse model challenge the notion that specific blockade of the CXCL10/CXCR3 chemokine axis halts T1D onset and progression.
    [Show full text]
  • Drainage of Inflammatory Macromolecules from the Brain To
    RESEARCH ARTICLE Drainage of inflammatory macromolecules from the brain to periphery targets the liver for macrophage infiltration Linlin Yang1, Jessica A Jime´ nez1, Alison M Earley1, Victoria Hamlin1, Victoria Kwon1, Cameron T Dixon1, Celia E Shiau1,2* 1Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, United States; 2Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, United States Abstract Many brain pathologies are associated with liver damage, but a direct link has long remained elusive. Here, we establish a new paradigm for interrogating brain-periphery interactions by leveraging zebrafish for its unparalleled access to the intact whole animal for in vivo analysis in real time after triggering focal brain inflammation. Using traceable lipopolysaccharides (LPS), we reveal that drainage of these inflammatory macromolecules from the brain led to a strikingly robust peripheral infiltration of macrophages into the liver independent of Kupffer cells. We further demonstrate that this macrophage recruitment requires signaling from the cytokine IL-34 and Toll- like receptor adaptor MyD88, and occurs in coordination with neutrophils. These results highlight the possibility for circulation of brain-derived substances to serve as a rapid mode of communication from brain to the liver. Understanding how the brain engages the periphery at times of danger may offer new perspectives for detecting and treating brain pathologies. *For correspondence: [email protected] Introduction Whether a diseased or injured brain transmits signals to the periphery to activate a response is an Competing interests: The interesting prospect in understanding brain-periphery communication, but remains underexplored. authors declare that no Interestingly, liver damage and neutrophil recruitment to the liver are common features in sepsis- competing interests exist.
    [Show full text]
  • CXCL4/Platelet Factor 4 Is an Agonist of CCR1 and Drives Human Monocyte Migration
    This is a repository copy of CXCL4/Platelet Factor 4 is an agonist of CCR1 and drives human monocyte migration. White Rose Research Online URL for this paper: https://eprints.whiterose.ac.uk/132464/ Version: Published Version Article: Fox, James Martin orcid.org/0000-0002-2473-7029, Kausar, Fahima, Day, Amy et al. (7 more authors) (2018) CXCL4/Platelet Factor 4 is an agonist of CCR1 and drives human monocyte migration. Scientific Reports. 9466. ISSN 2045-2322 Reuse This article is distributed under the terms of the Creative Commons Attribution (CC BY) licence. This licence allows you to distribute, remix, tweak, and build upon the work, even commercially, as long as you credit the authors for the original work. More information and the full terms of the licence here: https://creativecommons.org/licenses/ Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ www.nature.com/scientificreports OPEN CXCL4/Platelet Factor 4 is an agonist of CCR1 and drives human monocyte migration Received: 10 March 2016 James M. Fox 1,3, Fahima Kausar1, Amy Day1, Michael Osborne1, Khansa Hussain1, Accepted: 5 June 2018 Anja Mueller1,4, Jessica Lin1, Tomoko Tsuchiya 2, Shiro Kanegasaki2 & James E. Pease1 Published: xx xx xxxx Activated platelets release micromolar concentrations of the chemokine CXCL4/Platelet Factor-4. Deposition of CXCL4 onto the vascular endothelium is involved in atherosclerosis, facilitating monocyte arrest and recruitment by an as yet, unidentified receptor.
    [Show full text]
  • Glial Cell Activation, Recruitment, and Survival of B-Lineage Cells Following MCMV Brain Infection James R
    Lokensgard et al. Journal of Neuroinflammation (2016) 13:114 DOI 10.1186/s12974-016-0582-y RESEARCH Open Access Glial cell activation, recruitment, and survival of B-lineage cells following MCMV brain infection James R. Lokensgard*, Manohar B. Mutnal, Sujata Prasad, Wen Sheng and Shuxian Hu Abstract Background: Chemokines produced by reactive glia drive migration of immune cells and previous studies from our laboratory have demonstrated that CD19+ B cells infiltrate the brain. In this study, in vivo and in vitro experiments investigated the role of reactive glial cells in recruitment and survival of B-lineage cells in response to (murine cytomegalovirus) MCMV infection. Methods: Flow cytometric analysis was used to assess chemokine receptor expression on brain-infiltrating B cells. Real-time RT-PCR and ELISA were used to measure chemokine levels. Dual-immunohistochemical staining was used to co-localize chemokine production by reactive glia. Primary glial cell cultures and migration assays were used to examine chemokine-mediated recruitment. Astrocyte: B cell co-cultures were used to investigate survival and proliferation. Results: The chemokine receptors CXCR3, CXCR5, CCR5, and CCR7 were detected on CD19+ cells isolated from the brain during MCMV infection. In particular, CXCR3 was found to be elevated on an increasing number of cells over the time course of infection, and it was the primary chemokine receptor expressed at 60 days post infection Quite different expression kinetics were observed for CXCR5, CCR5, and CCR7, which were elevated on the highest number of cells early during infection and decreased by 14, 30, and 60 days post infection Correspondingly, elevated levels of CXCL9, CXCL10, and CXCL13, as well as CCL5, were found within the brains of infected animals, and only low levels of CCL3 and CCL19 were detected.
    [Show full text]
  • Tasuku Honjo Kyoto University, Kyoto, Japan
    333 Serendipities of Acquired Immunity Nobel Lecture, December 7, 2018 by Tasuku Honjo Kyoto University, Kyoto, Japan. INTRODUCTION For a long time, biology was perceived as the lesser of the natural sciences because, unlike physics, deductive reasoning could not be used to solve biological problems. Biology has been full of mystery since I started my career in biological sciences almost half a century ago. Although the basic principles of biology stem from the rules of physics, biological systems have such an extraordinary, layered complexity derived from a tremen- dous number of parameters, beautifully and magically intertwined and controlled to achieve what we call “life”. Paradoxically, we start with a rather limited number (about 20,000) of coding region genes. However, many transcripts can be generated from a single coding gene locus, indi- cating that a single gene can produce many proteins. Furthermore, there are a much higher number of non-coding transcripts that may afect the expression of the coding genes. DNA, RNA and proteins can be chemically modifed by methylation, phosphorylation and acetylation. In addition, at least 20,000 metabolites circulate in our blood. These can also be sensed by cells, interacting with various proteins and infuencing gene expres- sion, thus generating enormously complicated regulatory mechanisms to achieve homeostasis. The origin of metabolites can be traced not only to the biochemistry of our own cells but also to the diverse communities of 334 THE NOBEL PRIZES microbes inhabiting every surface of the body. If we imagine roughly 1013 order of our own cells, each expressing diferent proteins and containing diferent metabolites, in constant dialog with 1014 order of microbial cells, also in diferent metabolic states, the complexity of our biological system exceeds by far the physical and chemical complexity of the universe.
    [Show full text]
  • Of Breast Cancer: a Comprehensive Analysis Based on TCGA Database
    CCL19 has potential to be a prognostic biomarker and a modulator of tumor immune microenvironment (TIME) of breast cancer: a comprehensive analysis based on TCGA database Jinyan Wang The Aliated Jiangning Hospital of Nanjing Medical University Jinqiu Wang Dafeng People's Hospital Quan Gu Nanjing Medical University Yan Yang The Aliated Jiangning Hospital Yajun Ma The Aliated Jiangning Hospital of Nanjing Medical University Quan'an Zhang ( [email protected] ) The aliated Jiangning Hospital of Nanjing Medical University https://orcid.org/0000-0002-6356- 7122 Research article Keywords: tumor microenvironment (TME), tumor immune microenvironment (TIME), tumor-inltrating immune cells (TICs), CCL19, breast cancer Posted Date: October 9th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-87457/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/19 Abstract The development of cancer was determined by not only the intrinsic properties of cancer cells, but also the communication between cancer cells and tumor microenvironment (TME). We applied ESTIMATE and CIBERSORT algorithms to calculate the immune/stromal component and tumor-inltrating immune cells (TICs) in TME of BC. The results showed that immune component in TME predicted patients’ survival and associated with progression of BC. Differentially expressed genes (DEGs) were primarily enriched in immune-related activities. Finally, CCL19 was acquired which shared the leading nodes in PPI network and was associated with patients’ survival. High expression of CCL19 predicted better prognosis and participated in progression of BC. Genes in CCL19 up-regulated group were enriched in immune-related activities and these functions might depend on the communications between CCL19 and multiple TICs in TIME.
    [Show full text]
  • Title: Autocrine CCL5 Effect Mediates Trastuzumab Resistance by ERK Pathway
    Author Manuscript Published OnlineFirst on May 13, 2020; DOI: 10.1158/1535-7163.MCT-19-1172 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. 1 TITLE PAGE 2 Title: Autocrine CCL5 effect mediates trastuzumab resistance by ERK pathway 3 activation in HER2-positive breast cancer 4 Authors: Sandra Zazo1, Paula González-Alonso1, Ester Martín-Aparicio1, Cristina 5 Chamizo1, Melani Luque1, Marta Sanz-Álvarez1, Pablo Mínguez2, Gonzalo Gómez- 6 López3, Ion Cristóbal4, Cristina Caramés4, Jesús García-Foncillas4, Pilar Eroles5, Ana 7 Lluch5,6, Oriol Arpí7, Ana Rovira7,8, Joan Albanell7,8,9, Juan Madoz-Gúrpide1§, Federico 8 Rojo1§ 9 Affiliations: 1Pathology, Fundación Jiménez Díaz University Hospital Health Research 10 Institute (IIS—FJD, UAM)—CIBERONC, Madrid 28040, Spain; 2Genetics 11 Department, Health Research Institute-Fundación Jiménez Díaz (IIS-FJD, UAM), 12 Center for Biomedical Network Research on Rare Diseases (CIBERER), ISCIII, Madrid 13 28040, Spain; 3Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), 14 Madrid 28029, Spain; 4Translational Oncology Division, OncoHealth Institute, Health 15 Research Institute-Fundación Jiménez Díaz (IIS-FJD, UAM), Madrid 28040, Spain; 16 5Institute of Health Research INCLIVA-CIBERONC, Valencia 46010, Spain; 17 6Medicine Department, University of Valencia, Valencia 46010, Spain; 7Cancer 18 Research Program, IMIM (Hospital del Mar Research Institute), Barcelona 08003, 19 Spain; 8Medical Oncology Department, Hospital del Mar-CIBERONC, Barcelona 20 08003, Spain; 9Universitat Pompeu Fabra, Barcelona 08002, Spain; §these authors 21 contributed equally to this work. 22 Running title: Trastuzumab resistance by CCL5/ERK axis activation 23 Keywords: breast cancer, HER2-positive, anti-receptor therapy, trastuzumab, 24 resistance, cytokines, CCL5, cell lines 1 Downloaded from mct.aacrjournals.org on October 2, 2021.
    [Show full text]
  • Single-Cell Landscape of Bronchoalveolar Immune Cells in Patients with COVID-19
    BRIEF COMMUNICATION https://doi.org/10.1038/s41591-020-0901-9 Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19 Mingfeng Liao1,6, Yang Liu1,6, Jing Yuan2,6, Yanling Wen1, Gang Xu1, Juanjuan Zhao1, Lin Cheng1, Jinxiu Li2, Xin Wang1, Fuxiang Wang2, Lei Liu1,3 ✉ , Ido Amit 4 ✉ , Shuye Zhang 5 ✉ and Zheng Zhang 1,3 ✉ Respiratory immune characteristics associated with The macrophage compartments differed largely in both compo- Coronavirus Disease 2019 (COVID-19) severity are cur- sition and expression of FCN1, SPP1 and FABP4 in different cell rently unclear. We characterized bronchoalveolar lavage fluid groups (Fig. 1c and Extended Data Fig. 2d). FABP4 was prefer- immune cells from patients with varying severity of COVID-19 entially expressed by controls and patients with moderate infec- and from healthy people by using single-cell RNA sequencing. tion, while FCN1 and SPP1 were highly expressed by patients Proinflammatory monocyte-derived macrophages were abun- with severe/critical infection (Fig. 1d). We conducted differen- dant in the bronchoalveolar lavage fluid from patients with tially expressed gene (DEG) analysis (Extended Data Fig. 2e), gene severe COVID-9. Moderate cases were characterized by the ontology (GO) analysis and gene set enrichment analysis (GSEA) presence of highly clonally expanded CD8+ T cells. This atlas (Extended Data Fig. 2f) between cell groups. Group 1 expressed of the bronchoalveolar immune microenvironment suggests the peripheral monocyte-like markers S100A8, FCN1 and CD14, potential mechanisms underlying pathogenesis and recovery and group 2 expressed high levels of the chemokines CCL2, CCL3, in COVID-19. CXCL10 and other genes.
    [Show full text]