Using interactive platforms to encode, manage and explore immune-related adverse outcome pathways

We address the need for modelling and predicting adverse outcomes in immunotoxicology to improve non-clinical assessments of immunomodulatory therapy safety and efficacy. The integrated approach includes, first, the adverse outcome pathway concept established in the toxicology field, and, second, the systems medicine disease map approach for describing molecular mechanisms involved in a particular pathology. The proposed systems immunotoxicology workflow is demonstrated with CAR T cell treatment as a use case. To this end, the linear adverse outcome pathway (AOP) is expanded into a molecular interaction model in standard systems biology formats. Then it is shown how knowledge related to immunotoxic events can be integrated, encoded, managed and explored to benefit the research community. The map is accessible online via the MINERVA Platform for browsing, commenting and data visualisation (https://minerva.pages.uni.lu). Our work transforms a graphical illustration of an AOP into a digitally structured and standardised form, featuring precise and controlled vocabulary and supporting reproducible computational analyses. Because of annotations to source literature and databases, the map can be further expanded to match the evolving knowledge and research questions.

[1]  Alexander R. Pico,et al.  COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms , 2021, Molecular systems biology.

[2]  Ugur Dogrusoz,et al.  Newt: a comprehensive web-based tool for viewing, constructing and analyzing biological maps , 2020, Bioinform..

[3]  Marek Ostaszewski,et al.  Reusability and composability in process description maps: RAS–RAF–MEK–ERK signalling , 2020, bioRxiv.

[4]  Thomas S. Ligon,et al.  AsthmaMap: an interactive knowledge repository for mechanisms of asthma. , 2020, The Journal of allergy and clinical immunology.

[5]  Anna Niarakis,et al.  Automated inference of Boolean models from molecular interaction maps using CaSQ , 2020, Bioinform..

[6]  J. Myklebust,et al.  Tuning the Antigen Density Requirement for CAR T Cell Activity. , 2020, Cancer discovery.

[7]  Piotr Gawron,et al.  RA-map: building a state-of-the-art interactive knowledge base for rheumatoid arthritis , 2020, Database J. Biol. Databases Curation.

[8]  Marek Ostaszewski,et al.  Closing the gap between formats for storing layout information in systems biology , 2019, Briefings Bioinform..

[9]  C. Reinhardt,et al.  Physiological Roles of the von Willebrand Factor-Factor VIII Interaction. , 2020, Sub-cellular biochemistry.

[10]  J. Bergh,et al.  The European Medicines Agency Review of Kymriah (Tisagenlecleucel) for the Treatment of Acute Lymphoblastic Leukemia and Diffuse Large B-Cell Lymphoma. , 2019, The oncologist.

[11]  Piotr Gawron,et al.  MINERVA API and plugins: opening molecular network analysis and visualization to the community , 2019, Bioinform..

[12]  I. Flinn,et al.  Long-term safety and activity of axicabtagene ciloleucel in refractory large B-cell lymphoma (ZUMA-1): a single-arm, multicentre, phase 1-2 trial. , 2019, The Lancet. Oncology.

[13]  Victoria McGilligan,et al.  New models of atherosclerosis and multi-drug therapeutic interventions , 2018, Bioinform..

[14]  Marek Ostaszewski,et al.  Community-driven roadmap for integrated disease maps , 2018, Briefings Bioinform..

[15]  Users' Handbook supplement to the Guidance Document for developing and assessing Adverse Outcome Pathways , 2019 .

[16]  Viktoriya Zvoda,et al.  Construction and Data Analysis , 2018 .

[17]  Craig W. Freyer Tisagenlecleucel: The First CAR on the Highway to Remission for Acute Lymphoblastic Leukemia , 2018, Journal of the advanced practitioner in oncology.

[18]  C. Auffray,et al.  Systems medicine disease maps: community-driven comprehensive representation of disease mechanisms , 2018, npj Systems Biology and Applications.

[19]  M. Sadelain,et al.  CAR T cell–induced cytokine release syndrome is mediated by macrophages and abated by IL-1 blockade , 2018, Nature Medicine.

[20]  Inna Kuperstein,et al.  Signalling maps in cancer research: construction and data analysis , 2018, Database J. Biol. Databases Curation.

[21]  David S. Wishart,et al.  DrugBank 5.0: a major update to the DrugBank database for 2018 , 2017, Nucleic Acids Res..

[22]  John Kunze,et al.  Uniform resolution of compact identifiers for biomedical data , 2017, Scientific Data.

[23]  Inna Kuperstein,et al.  Application of Atlas of Cancer Signalling Network in pre-clinical studies , 2017, bioRxiv.

[24]  K. Mansfield,et al.  Cytokine release syndrome associated with chimeric-antigen receptor T-cell therapy: clinicopathological insights. , 2017, Blood.

[25]  Daniel Li,et al.  Kinetics and biomarkers of severe cytokine release syndrome after CD19 chimeric antigen receptor-modified T-cell therapy. , 2017, Blood.

[26]  S. H. Bennekou,et al.  Adverse outcome pathways: opportunities, limitations and open questions , 2017, Archives of Toxicology.

[27]  D. Teachey,et al.  Monocyte lineage-derived IL-6 does not affect chimeric antigen receptor T-cell function. , 2017, Cytotherapy.

[28]  Piotr Gawron,et al.  MINERVA—a platform for visualization and curation of molecular interaction networks , 2016, npj Systems Biology and Applications.

[29]  Sharon Munn,et al.  Adverse outcome pathway development from protein alkylation to liver fibrosis , 2016, Archives of Toxicology.

[30]  G. Wertheim,et al.  Identification of Predictive Biomarkers for Cytokine Release Syndrome after Chimeric Antigen Receptor T-cell Therapy for Acute Lymphoblastic Leukemia. , 2016, Cancer discovery.

[31]  Denis Thieffry,et al.  Logical Modeling and Dynamical Analysis of Cellular Networks , 2016, Front. Genet..

[32]  M. Wurfel,et al.  Biomarkers of Endothelial Activation Are Associated with Poor Outcome in Critical Illness , 2015, PloS one.

[33]  E. Barillot,et al.  Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps , 2015, Oncogenesis.

[34]  Pamela A Shaw,et al.  Chimeric antigen receptor T cells for sustained remissions in leukemia. , 2014, The New England journal of medicine.

[35]  S. Riddell,et al.  The Nonsignaling Extracellular Spacer Domain of Chimeric Antigen Receptors Is Decisive for In Vivo Antitumor Activity , 2014, Cancer Immunology Research.

[36]  D. Teachey,et al.  Managing Cytokine Release Syndrome Associated With Novel T Cell-Engaging Therapies , 2014, Cancer journal.

[37]  Hong Wang,et al.  An evolving new paradigm: endothelial cells – conditional innate immune cells , 2013, Journal of Hematology & Oncology.

[38]  H. Kitano,et al.  Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map , 2013, Molecular Neurobiology.

[39]  T. Helikar,et al.  A Cell Simulator Platform: The Cell Collective , 2013, Clinical pharmacology and therapeutics.

[40]  Michel Sadelain,et al.  The basic principles of chimeric antigen receptor design. , 2013, Cancer discovery.

[41]  Alex Madrahimov,et al.  The Cell Collective: Toward an open and collaborative approach to systems biology , 2012, BMC Systems Biology.

[42]  John P. Overington,et al.  ChEMBL: a large-scale bioactivity database for drug discovery , 2011, Nucleic Acids Res..

[43]  Falk Schreiber,et al.  Editing, validating and translating of SBGN maps , 2010, Bioinform..

[44]  M. Sadelain,et al.  Treatment of chronic lymphocytic leukemia with genetically targeted autologous T cells: case report of an unforeseen adverse event in a phase I clinical trial. , 2010, Molecular therapy : the journal of the American Society of Gene Therapy.

[45]  Daniel L Villeneuve,et al.  Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment , 2010, Environmental toxicology and chemistry.

[46]  Sarala M. Wimalaratne,et al.  The Systems Biology Graphical Notation , 2009, Nature Biotechnology.

[47]  Hugh D. Spence,et al.  Minimum information requested in the annotation of biochemical models (MIRIAM) , 2005, Nature Biotechnology.

[48]  C. Wouters,et al.  Macrophage activation syndrome: characteristic findings on liver biopsy illustrating the key role of activated, IFN-gamma-producing lymphocytes and IL-6- and TNF-alpha-producing macrophages. , 2005, Blood.

[49]  Hiroaki Kitano,et al.  The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models , 2003, Bioinform..