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Acencio ML, Ostaszewski M, Mazein A, Rosenstiel P, Aden K, Mishra N, Andersen V, Sidiropoulos P, Banos A, Filia A, Rahmouni S, Finckh A, Gu W, Schneider R, Satagopam V. The SYSCID map: a graphical and computational resource of molecular mechanisms across rheumatoid arthritis, systemic lupus erythematosus and inflammatory bowel disease. Front Immunol 2023; 14:1257321. [PMID: 38022524 PMCID: PMC10646502 DOI: 10.3389/fimmu.2023.1257321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Chronic inflammatory diseases (CIDs), including inflammatory bowel disease (IBD), rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are thought to emerge from an impaired complex network of inter- and intracellular biochemical interactions among several proteins and small chemical compounds under strong influence of genetic and environmental factors. CIDs are characterised by shared and disease-specific processes, which is reflected by partially overlapping genetic risk maps and pathogenic cells (e.g., T cells). Their pathogenesis involves a plethora of intracellular pathways. The translation of the research findings on CIDs molecular mechanisms into effective treatments is challenging and may explain the low remission rates despite modern targeted therapies. Modelling CID-related causal interactions as networks allows us to tackle the complexity at a systems level and improve our understanding of the interplay of key pathways. Here we report the construction, description, and initial applications of the SYSCID map (https://syscid.elixir-luxembourg.org/), a mechanistic causal interaction network covering the molecular crosstalk between IBD, RA and SLE. We demonstrate that the map serves as an interactive, graphical review of IBD, RA and SLE molecular mechanisms, and helps to understand the complexity of omics data. Examples of such application are illustrated using transcriptome data from time-series gene expression profiles following anti-TNF treatment and data from genome-wide associations studies that enable us to suggest potential effects to altered pathways and propose possible mechanistic biomarkers of treatment response.
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Affiliation(s)
- Marcio Luis Acencio
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Marek Ostaszewski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
- ELIXIR Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Alexander Mazein
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Konrad Aden
- Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany
- Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Neha Mishra
- Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Vibeke Andersen
- Diagnostics and Clinical Research Unit, Institute of Regional Health Research, University Hospital of Southern Denmark, Aabenraa, Denmark
- Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark
| | - Prodromos Sidiropoulos
- Rheumatology and Clinical Immunology, Medical School, University of Crete, Heraklion, Greece
- Laboratory of Rheumatology, Autoimmunity and Inflammation, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology (IMBB-FORTH), Heraklion, Greece
| | - Aggelos Banos
- Autoimmunity and Inflammation Laboratory, Biomedical Research Foundation of the Academy of Athens, Athens and Laboratory of Molecular Hematology, Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupolis, Greece
| | - Anastasia Filia
- Autoimmunity and Inflammation Laboratory, Biomedical Research Foundation of the Academy of Athens, Athens and Laboratory of Molecular Hematology, Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupolis, Greece
| | - Souad Rahmouni
- Unit of Animal Genomics, GIGA-Institute, University of Liège, Liège, Belgium
| | - Axel Finckh
- Rheumatology Division, Geneva University Hospital (HUG), Geneva, Switzerland
- Geneva Center for Inflammation Research (GCIR), University of Geneva (UNIGE), Geneva, Switzerland
| | - Wei Gu
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
- ELIXIR Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Reinhard Schneider
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
- ELIXIR Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Venkata Satagopam
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
- ELIXIR Luxembourg, Esch-sur-Alzette, Luxembourg
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Mazein A, Acencio ML, Balaur I, Rougny A, Welter D, Niarakis A, Ramirez Ardila D, Dogrusoz U, Gawron P, Satagopam V, Gu W, Kremer A, Schneider R, Ostaszewski M. A guide for developing comprehensive systems biology maps of disease mechanisms: planning, construction and maintenance. FRONTIERS IN BIOINFORMATICS 2023; 3:1197310. [PMID: 37426048 PMCID: PMC10325725 DOI: 10.3389/fbinf.2023.1197310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 06/09/2023] [Indexed: 07/11/2023] Open
Abstract
As a conceptual model of disease mechanisms, a disease map integrates available knowledge and is applied for data interpretation, predictions and hypothesis generation. It is possible to model disease mechanisms on different levels of granularity and adjust the approach to the goals of a particular project. This rich environment together with requirements for high-quality network reconstruction makes it challenging for new curators and groups to be quickly introduced to the development methods. In this review, we offer a step-by-step guide for developing a disease map within its mainstream pipeline that involves using the CellDesigner tool for creating and editing diagrams and the MINERVA Platform for online visualisation and exploration. We also describe how the Neo4j graph database environment can be used for managing and querying efficiently such a resource. For assessing the interoperability and reproducibility we apply FAIR principles.
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Affiliation(s)
- Alexander Mazein
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Marcio Luis Acencio
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Irina Balaur
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | | | - Danielle Welter
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Anna Niarakis
- Université Paris-Saclay, Laboratoire Européen de Recherche Pour la Polyarthrite Rhumatoïde–Genhotel, University Evry, Evry, France
- Lifeware Group, Inria Saclay-Ile de France, Palaiseau, France
| | - Diana Ramirez Ardila
- ITTM Information Technology for Translational Medicine, Esch-sur-Alzette, Luxemburg
| | - Ugur Dogrusoz
- Computer Engineering Department, Bilkent University, Ankara, Türkiye
| | - Piotr Gawron
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Venkata Satagopam
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
- ELIXIR Luxembourg, Belvaux, Luxembourg
| | - Wei Gu
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
- ELIXIR Luxembourg, Belvaux, Luxembourg
| | - Andreas Kremer
- ITTM Information Technology for Translational Medicine, Esch-sur-Alzette, Luxemburg
| | - Reinhard Schneider
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
- ELIXIR Luxembourg, Belvaux, Luxembourg
| | - Marek Ostaszewski
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
- ELIXIR Luxembourg, Belvaux, Luxembourg
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3
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Mechanisms of Vitamin C Regulating Immune and Inflammation Associated with Neonatal Hypoxic-Ischemic Encephalopathy Based on Network Pharmacology and Molecular Simulation Technology. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:4904325. [PMID: 35198034 PMCID: PMC8860524 DOI: 10.1155/2022/4904325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 01/02/2022] [Accepted: 01/19/2022] [Indexed: 11/29/2022]
Abstract
Background There are still controversies about the curative effect of vitamin C in treating HIE, and its mechanism of action is not entirely clear. This study is designed to explore the potential molecular mechanism of vitamin C in treating neonatal hypoxic ischemic encephalopathy (HIE). Methods The effect targets of vitamin C and the pathogenic targets of neonatal HIE were obtained via retrieval of public databases to screen out the molecular targets of vitamin C acting on neonatal HIE. Gene Ontology (GO) functional annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the main targets. Vitamin C and the optimum target structural components are subjected to molecular docking and molecular dynamics simulation analysis via computer software so as to verify their binding activity and stability. Result Based on 16 overlapping targets of vitamin C and HIE, seven main targets were identified in this study. According to GO and KEGG analysis, molecular functions (top 25 items) and signal pathways (21 items) related to inflammatory reaction, immune response, and cell transcriptional control may be potential pathways for vitamin C to treat neonatal HIE. Molecular docking and molecular dynamics simulation were adopted to definitively determine the 4 optimum core target spots. Conclusion The efficacy of vitamin C on HIE is involved in the immunoregulation and inflammation-related functional processes and signal pathways. These molecular mechanisms, including core targets, will contribute to the clinical practice of neonatal HIE in the future.
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Mo YN, Cheng F, Yang Z, Shang XF, Liang JP, Shang RF, Hao BC, Wang XH, Zhang HJ, Wali A, Lu CF, Liu Y. Antioxidant Activity and the Potential Mechanism of the Fruit From Ailanthus altissima Swingle. Front Vet Sci 2021; 8:784898. [PMID: 34966812 PMCID: PMC8710717 DOI: 10.3389/fvets.2021.784898] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/15/2021] [Indexed: 11/23/2022] Open
Abstract
The fruits of Ailanthus altissima Swingle (AS) possess a variety of pharmacological activities. Its antioxidant activity and the potential mode of action have not yet been investigated. In in vitro studies, AS revealed the strong reducing power and DPPH scavenging effect, but hydroxyl radical scavenging activity and ferrous ions-chelating ability were not strong. Meanwhile, the oxidative stress RAW264.7 cell injury model was established, the low and medium-doses of AS showed significant protective effects on the viability of H2O2-treated cells by CCK-8 method. Besides, three doses of AS all increased the activities of SOD, CAT, and GSH-Px and decreased the MDA level compared with the H2O2 group, suggesting it significantly relieved oxidative stress of cells. The active ingredients and related targets of AS were collected by HERB and Swiss Target Prediction database, the common targets of drugs and diseases database were conducted by GeneCards database platform and the Venny platform. We screened the core targets of AS like threonine kinase1 (AKT1), mitogen-activated protein kinase 1 (MAPK1), sirtuin-1 (SIRT1), mechanistic target of rapamycin kinase (MTOR) by STRING database, and the key pathways involved PI3K-AKT and FoxO signaling pathway by KEGG pathway enrichment analysis. Besides, qRT-PCR revealed AS preconditioning significantly up-regulated the expression level of AKT1, SIRT1, MAPK1, and MTOR in model cells, and the effect was related to the regulation of FoxO and PI3K/AKT signaling pathway. In summary, AS showed significant antioxidant activity and its potential mechanism was regulating FoxO and PI3K/AKT signaling pathway.
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Affiliation(s)
- Ya-Nan Mo
- Key Laboratory of New Animal Drug Project of Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, China
| | - Feng Cheng
- Key Laboratory of New Animal Drug Project of Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, China.,Key Laboratory of Plant Resources and Chemistry in Arid Regions, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, China
| | - Zhen Yang
- Key Laboratory of New Animal Drug Project of Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, China
| | - Xiao-Fei Shang
- Key Laboratory of New Animal Drug Project of Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, China
| | - Jian-Ping Liang
- Key Laboratory of New Animal Drug Project of Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, China
| | - Ruo-Feng Shang
- Key Laboratory of New Animal Drug Project of Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, China
| | - Bao-Cheng Hao
- Key Laboratory of New Animal Drug Project of Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, China
| | - Xue-Hong Wang
- Key Laboratory of New Animal Drug Project of Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, China
| | - Hong-Juan Zhang
- Key Laboratory of New Animal Drug Project of Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, China
| | - Ahmidin Wali
- Key Laboratory of Plant Resources and Chemistry in Arid Regions, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, China
| | - Chun-Fang Lu
- Key Laboratory of Plant Resources and Chemistry in Arid Regions, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, China
| | - Yu Liu
- Key Laboratory of New Animal Drug Project of Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, China.,College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
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5
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Mazein A, Rougny A, Karr JR, Saez-Rodriguez J, Ostaszewski M, Schneider R. Reusability and composability in process description maps: RAS-RAF-MEK-ERK signalling. Brief Bioinform 2021; 22:6217719. [PMID: 33834185 PMCID: PMC8425390 DOI: 10.1093/bib/bbab103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 03/05/2021] [Accepted: 03/08/2021] [Indexed: 12/05/2022] Open
Abstract
Detailed maps of the molecular basis of the disease are powerful tools for interpreting data and building predictive models. Modularity and composability are considered necessary network features for large-scale collaborative efforts to build comprehensive molecular descriptions of disease mechanisms. An effective way to create and manage large systems is to compose multiple subsystems. Composable network components could effectively harness the contributions of many individuals and enable teams to seamlessly assemble many individual components into comprehensive maps. We examine manually built versions of the RAS–RAF–MEK–ERK cascade from the Atlas of Cancer Signalling Network, PANTHER and Reactome databases and review them in terms of their reusability and composability for assembling new disease models. We identify design principles for managing complex systems that could make it easier for investigators to share and reuse network components. We demonstrate the main challenges including incompatible levels of detail and ambiguous representation of complexes and highlight the need to address these challenges.
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Affiliation(s)
- Alexander Mazein
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.,European Institute for Systems Biology and Medicine, CIRI UMR5308, CNRS-ENS-UCBL-INSERM, Université de Lyon, 50 Avenue Tony Garnier, 69007 Lyon, France
| | - Adrien Rougny
- Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Aomi, Tokyo, Japan.,Com. Bio Big Data Open Innovation Lab. (CBBD-OIL), AIST, Aomi, Tokyo, Japan
| | - Jonathan R Karr
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, 10029, NY, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, 10029, NY, USA
| | - Julio Saez-Rodriguez
- Joint Research Centre for Computational Biomedicine (JRC-COMBINE), RWTH Aachen University, Faculty of Medicine, 52074 Aachen, Germany.,Institute for Computational Biomedicine, Heidelberg University Hospital and Heidelberg University, Faculty of Medicine, Bioquant Heidelberg, Heidelberg 69120, Germany
| | - Marek Ostaszewski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Reinhard Schneider
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
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6
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Touré V, Dräger A, Luna A, Dogrusoz U, Rougny A. The Systems Biology Graphical Notation: Current Status and Applications in Systems Medicine. SYSTEMS MEDICINE 2021. [DOI: 10.1016/b978-0-12-801238-3.11515-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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7
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MINERVA, A Platform for the Exploration of Disease Maps. SYSTEMS MEDICINE 2021. [DOI: 10.1016/b978-0-12-801238-3.11685-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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8
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Mazein A, Ivanova O, Balaur I, Ostaszewski M, Berzhitskaya V, Serebriyskaya T, Ligon T, Hasenauer J, De Meulder B, Overall RW, Roy L, Knowles RG, Wheelock CE, Dahlen SE, Chung KF, Adcock IM, Roberts G, Djukanovic R, Pellet J, Gawron P, Balling R, Maitland-van der Zee AH, Schneider R, Sterk PJ, Auffray C. AsthmaMap: An interactive knowledge repository for mechanisms of asthma. J Allergy Clin Immunol 2020; 147:853-856. [PMID: 33309742 DOI: 10.1016/j.jaci.2020.11.032] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 10/17/2020] [Accepted: 11/10/2020] [Indexed: 10/22/2022]
Affiliation(s)
- Alexander Mazein
- European Institute for Systems Biology and Medicine, Université de Lyon, Lyon, France; Institute of Cell Biophysics, Russian Academy of Sciences, Pushchino, Moscow, Russia; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.
| | - Olga Ivanova
- European Institute for Systems Biology and Medicine, Université de Lyon, Lyon, France; Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Respiratory Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Irina Balaur
- European Institute for Systems Biology and Medicine, Université de Lyon, Lyon, France
| | - Marek Ostaszewski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | | | | | - Thomas Ligon
- Faculty of Physics and Center for NanoScience (CeNS), Ludwig-Maximilians-Universität, Munich, Germany
| | - Jan Hasenauer
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany; Faculty of Mathematics and Natural Sciences, University of Bonn, Endenicher, Bonn, Germany
| | - Bertrand De Meulder
- European Institute for Systems Biology and Medicine, Université de Lyon, Lyon, France
| | - Rupert W Overall
- Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden, Dresden, Germany; German Center for Neurodegenerative Diseases (DZNE) Dresden, Dresden, Germany
| | - Ludovic Roy
- European Institute for Systems Biology and Medicine, Université de Lyon, Lyon, France
| | - Richard G Knowles
- Knowles Consulting, Stevenage Bioscience Catalyst, Stevenage, United Kingdom
| | - Craig E Wheelock
- Division of Physiological Chemistry 2, Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden
| | - Sven-Erik Dahlen
- Unit for Experimental Asthma and Allergy Research, Institute of Environmental Medicine (IMM), Karolinska Institutet, Solna, Sweden
| | - Kian Fan Chung
- National Heart & Lung Institute, Imperial College London, London, United Kingdom
| | - Ian M Adcock
- National Heart & Lung Institute, Imperial College London, London, United Kingdom
| | - Graham Roberts
- Clinical and Experimental Sciences and Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom; NIHR Southampton Biomedical Research Centre, Southampton, United Kingdom
| | - Ratko Djukanovic
- Clinical and Experimental Sciences, University of Southampton Faculty of Medicine, University of Southampton, Southampton, United Kingdom; NIHR Southampton Respiratory Biomedical Research Unit, Southampton University Hospital, Southampton, United Kingdom
| | - Johann Pellet
- European Institute for Systems Biology and Medicine, Université de Lyon, Lyon, France
| | - Piotr Gawron
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Rudi Balling
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Anke H Maitland-van der Zee
- Respiratory Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Reinhard Schneider
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Peter J Sterk
- Respiratory Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Charles Auffray
- European Institute for Systems Biology and Medicine, Université de Lyon, Lyon, France
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9
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Li R, Guo C, Li Y, Liang X, Yang L, Huang W. Therapeutic target and molecular mechanism of vitamin C-treated pneumonia: a systematic study of network pharmacology. Food Funct 2020; 11:4765-4772. [PMID: 32420559 DOI: 10.1039/d0fo00421a] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Vitamin C (VC), a well-reported antioxidant, is found with beneficial actions of preventing and treating pneumonia.
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Affiliation(s)
- Rong Li
- Guangxi Key Laboratory of Tumor Immunology and Microenvironmental Regulation
- Guilin Medical University
- Guilin
- China
| | - Chao Guo
- Department of Pharmacy
- Guigang City People's Hospital
- The Eighth Affiliated Hospital of Guangxi Medical University
- Guigang
- PR China
| | - Yu Li
- College of Pharmacy
- Guilin Medical University
- Guilin
- PR China
| | - Xiao Liang
- Guangxi Key Laboratory of Tumor Immunology and Microenvironmental Regulation
- Guilin Medical University
- Guilin
- China
| | - Lu Yang
- Guangxi Key Laboratory of Tumor Immunology and Microenvironmental Regulation
- Guilin Medical University
- Guilin
- China
| | - Wenjun Huang
- Guangxi Key Laboratory of Tumor Immunology and Microenvironmental Regulation
- Guilin Medical University
- Guilin
- China
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10
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Kondratova M, Czerwinska U, Sompairac N, Amigorena SD, Soumelis V, Barillot E, Zinovyev A, Kuperstein I. A multiscale signalling network map of innate immune response in cancer reveals cell heterogeneity signatures. Nat Commun 2019; 10:4808. [PMID: 31641119 PMCID: PMC6805895 DOI: 10.1038/s41467-019-12270-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 08/02/2019] [Indexed: 12/14/2022] Open
Abstract
The lack of integrated resources depicting the complexity of the innate immune response in cancer represents a bottleneck for high-throughput data interpretation. To address this challenge, we perform a systematic manual literature mining of molecular mechanisms governing the innate immune response in cancer and represent it as a signalling network map. The cell-type specific signalling maps of macrophages, dendritic cells, myeloid-derived suppressor cells and natural killers are constructed and integrated into a comprehensive meta map of the innate immune response in cancer. The meta-map contains 1466 chemical species as nodes connected by 1084 biochemical reactions, and it is supported by information from 820 articles. The resource helps to interpret single cell RNA-Seq data from macrophages and natural killer cells in metastatic melanoma that reveal different anti- or pro-tumor sub-populations within each cell type. Here, we report a new open source analytic platform that supports data visualisation and interpretation of tumour microenvironment activity in cancer. The complexity of the innate immune response to cancer makes interpretation of large data sets challenging. Here, the authors provide an integrated multi-scale map of signalling networks representing the different immune cells and their interactions and show its utility for data interpretation.
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Affiliation(s)
- Maria Kondratova
- Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, 75005, Paris, France
| | - Urszula Czerwinska
- Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, 75005, Paris, France.,Université Paris Descartes, Centre de Recherches Interdisciplinaires, Paris, France
| | - Nicolas Sompairac
- Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, 75005, Paris, France.,Université Paris Descartes, Centre de Recherches Interdisciplinaires, Paris, France
| | | | - Vassili Soumelis
- Institut Curie, PSL Research University, Inserm, U932, 75005, Paris, France
| | - Emmanuel Barillot
- Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, 75005, Paris, France
| | - Andrei Zinovyev
- Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, 75005, Paris, France
| | - Inna Kuperstein
- Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, 75005, Paris, France.
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