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Esteban-Medina M, de la Oliva Roque VM, Herráiz-Gil S, Peña-Chilet M, Dopazo J, Loucera C. drexml: A command line tool and Python package for drug repurposing. Comput Struct Biotechnol J 2024; 23:1129-1143. [PMID: 38510973 PMCID: PMC10950807 DOI: 10.1016/j.csbj.2024.02.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 02/27/2024] [Accepted: 02/27/2024] [Indexed: 03/22/2024] Open
Abstract
We introduce drexml, a command line tool and Python package for rational data-driven drug repurposing. The package employs machine learning and mechanistic signal transduction modeling to identify drug targets capable of regulating a particular disease. In addition, it employs explainability tools to contextualize potential drug targets within the functional landscape of the disease. The methodology is validated in Fanconi Anemia and Familial Melanoma, two distinct rare diseases where there is a pressing need for solutions. In the Fanconi Anemia case, the model successfully predicts previously validated repurposed drugs, while in the Familial Melanoma case, it identifies a promising set of drugs for further investigation.
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Affiliation(s)
- Marina Esteban-Medina
- Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Seville, Spain
| | - Víctor Manuel de la Oliva Roque
- Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Seville, Spain
| | - Sara Herráiz-Gil
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER-ISCIII), U714, Madrid, Spain
- Departamento de Bioingeniería, Universidad Carlos III de Madrid (UC3M), Madrid, Spain
- Regenerative Medicine and Tissue Engineering Group, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital (IIS-FJD), Madrid, Spain
- Epithelial Biomedicine Division, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain
| | - María Peña-Chilet
- Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Platform of Big Data, AI and Biostatistics, Health Research Institute La Fe (IISLAFE), Valencia, Spain
| | - Joaquín Dopazo
- Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Seville, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER-ISCIII), U715, Seville, Spain
- FPS/ELIXIR-es, Hospital Virgen del Rocío, Seville, Spain
| | - Carlos Loucera
- Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Seville, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER-ISCIII), U715, Seville, Spain
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2
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Niarakis A, Ostaszewski M, Mazein A, Kuperstein I, Kutmon M, Gillespie ME, Funahashi A, Acencio ML, Hemedan A, Aichem M, Klein K, Czauderna T, Burtscher F, Yamada TG, Hiki Y, Hiroi NF, Hu F, Pham N, Ehrhart F, Willighagen EL, Valdeolivas A, Dugourd A, Messina F, Esteban-Medina M, Peña-Chilet M, Rian K, Soliman S, Aghamiri SS, Puniya BL, Naldi A, Helikar T, Singh V, Fernández MF, Bermudez V, Tsirvouli E, Montagud A, Noël V, Ponce-de-Leon M, Maier D, Bauch A, Gyori BM, Bachman JA, Luna A, Piñero J, Furlong LI, Balaur I, Rougny A, Jarosz Y, Overall RW, Phair R, Perfetto L, Matthews L, Rex DAB, Orlic-Milacic M, Gomez LCM, De Meulder B, Ravel JM, Jassal B, Satagopam V, Wu G, Golebiewski M, Gawron P, Calzone L, Beckmann JS, Evelo CT, D’Eustachio P, Schreiber F, Saez-Rodriguez J, Dopazo J, Kuiper M, Valencia A, Wolkenhauer O, Kitano H, Barillot E, Auffray C, Balling R, Schneider R. Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches. Front Immunol 2024; 14:1282859. [PMID: 38414974 PMCID: PMC10897000 DOI: 10.3389/fimmu.2023.1282859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 12/22/2023] [Indexed: 02/29/2024] Open
Abstract
Introduction The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.
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Affiliation(s)
- Anna Niarakis
- Université Paris-Saclay, Laboratoire Européen de Recherche pour la Polyarthrite rhumatoïde - Genhotel, Univ Evry, Evry, France
- Lifeware Group, Inria, Saclay-île de France, Palaiseau, France
| | - Marek Ostaszewski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Alexander Mazein
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Inna Kuperstein
- Institut Curie, P.S.L. Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | - Martina Kutmon
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, Netherlands
| | - Marc E. Gillespie
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- St. John’s University, Queens, NY, United States
| | - Akira Funahashi
- Department of Biosciences and Informatics, Keio University, Kanagawa, Japan
| | - Marcio Luis Acencio
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Ahmed Hemedan
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Michael Aichem
- Department of Computer and Information Science, University of Konstanz, Konstanz, Germany
| | - Karsten Klein
- Department of Computer and Information Science, University of Konstanz, Konstanz, Germany
| | - Tobias Czauderna
- Faculty of Applied Computer Sciences & Biosciences, University of Applied Sciences Mittweida, Mittweida, Germany
| | - Felicia Burtscher
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Takahiro G. Yamada
- Department of Biosciences and Informatics, Keio University, Kanagawa, Japan
| | - Yusuke Hiki
- Center for Biosciences and Informatics, Graduate School of Fundamental Science and Technology, Keio University, Kanagawa, Japan
| | - Noriko F. Hiroi
- Faculty of Creative Engineering, Kanagawa Institute of Technology, Kanagawa, Japan
- Keio University School of Medicine, Tokyo, Japan
| | - Finterly Hu
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, Netherlands
- Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, Netherlands
| | - Nhung Pham
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, Netherlands
- Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, Netherlands
| | - Friederike Ehrhart
- Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, Netherlands
| | - Egon L. Willighagen
- Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, Netherlands
| | - Alberto Valdeolivas
- Institute for Computational Biomedicine, Heidelberg University, Faculty of Medicine, Heidelberg University Hospital, Bioquant, Heidelberg, Germany
| | - Aurelien Dugourd
- Institute for Computational Biomedicine, Heidelberg University, Faculty of Medicine, Heidelberg University Hospital, Bioquant, Heidelberg, Germany
| | - Francesco Messina
- Department of Epidemiology, Preclinical Research and Advanced Diagnostic, National Institute for Infectious Diseases’ Lazzaro Spallanzani’ - IRCCS, Rome, Italy
| | - Marina Esteban-Medina
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Sevilla, Spain
| | - Maria Peña-Chilet
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Sevilla, Spain
- Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocio, Seville, Spain
| | - Kinza Rian
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
| | - Sylvain Soliman
- Lifeware Group, Inria, Saclay-île de France, Palaiseau, France
| | - Sara Sadat Aghamiri
- Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE, United States
| | - Bhanwar Lal Puniya
- Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE, United States
| | - Aurélien Naldi
- Lifeware Group, Inria, Saclay-île de France, Palaiseau, France
| | - Tomáš Helikar
- Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE, United States
| | - Vidisha Singh
- Université Paris-Saclay, Laboratoire Européen de Recherche pour la Polyarthrite rhumatoïde - Genhotel, Univ Evry, Evry, France
| | | | - Viviam Bermudez
- Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Eirini Tsirvouli
- Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Arnau Montagud
- Barcelona Supercomputing Center (BSC.), Barcelona, Spain
| | - Vincent Noël
- Institut Curie, P.S.L. Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | | | | | | | - Benjamin M. Gyori
- Harvard Medical School, Laboratory of Systems Pharmacology, Boston, MA, United States
| | - John A. Bachman
- Harvard Medical School, Laboratory of Systems Pharmacology, Boston, MA, United States
| | - Augustin Luna
- Computational Biology Branch, National Library of Medicine, Bethesda, MD, United States
- Department of Systems Biology, Harvard Medical School, Boston, MA, United States
| | - Janet Piñero
- Medbioinformatics Solutions SL, Barcelona, Spain
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Dept. of Medicine and Life Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Laura I. Furlong
- Medbioinformatics Solutions SL, Barcelona, Spain
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Dept. of Medicine and Life Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Irina Balaur
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - 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
| | - Yohan Jarosz
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Rupert W. Overall
- Institute for Biology, Humboldt University of Berlin, Berlin, Germany
| | - Robert Phair
- Integrative Bioinformatics, Inc., Mountain View, CA, United States
| | - Livia Perfetto
- Department of Biology and Biotechnology Charles Darwin, Sapienza University of Rome, Rome, Italy
| | - Lisa Matthews
- Department of Biochemistry & Molecular Pharmacology, NYU. Langone Medical Center, New York, NY, United States
| | | | | | - Luis Cristobal Monraz Gomez
- Institut Curie, P.S.L. Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | | | - Jean Marie Ravel
- Institut Curie, P.S.L. Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | - Bijay Jassal
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Venkata Satagopam
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
- Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universität Frankfurt, Frankfurt am Main, Germany
| | - Guanming Wu
- Oregon Health Sciences University, Portland, OR, United States
| | - Martin Golebiewski
- Heidelberg Institute for Theoretical Studies (HITS), Heidelberg, Germany
| | - Piotr Gawron
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Laurence Calzone
- Institut Curie, P.S.L. Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | | | - Chris T. Evelo
- Department of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, Maastricht, Netherlands
| | - Peter D’Eustachio
- Department of Biochemistry & Molecular Pharmacology, NYU. Langone Medical Center, New York, NY, United States
| | - Falk Schreiber
- Department of Computer and Information Science, University of Konstanz, Konstanz, Germany
- Faculty of Information Technology, Monash University, Clayton, Victoria, VIC, Australia
| | - Julio Saez-Rodriguez
- Institute for Computational Biomedicine, Heidelberg University, Faculty of Medicine, Heidelberg University Hospital, Bioquant, Heidelberg, Germany
| | - Joaquin Dopazo
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Sevilla, Spain
- Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocio, Seville, Spain
- FPS/ELIXIR-es, Hospital Virgen del Rocío, Sevilla, Spain
| | - Martin Kuiper
- Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Alfonso Valencia
- Barcelona Supercomputing Center (BSC.), Barcelona, Spain
- I.C.R.E.A., Pg. Lluís Companys 23, Barcelona, Spain
| | - Olaf Wolkenhauer
- Department of Systems Biology & Bioinformatics, University of Rostock, Rostock, Germany
- Leibniz Institute for Food Systems Biology, at the Technical University Munich, Munich, Germany
| | | | - Emmanuel Barillot
- Institut Curie, P.S.L. Research University, Paris, France
- INSERM, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | | | - Rudi Balling
- Institute of Molecular Psychiatry, University of Bonn, Bonn, Germany
| | - Reinhard Schneider
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
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Esteban-Medina M, Loucera C, Rian K, Velasco S, Olivares-González L, Rodrigo R, Dopazo J, Peña-Chilet M. The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery. J Transl Med 2024; 22:139. [PMID: 38321543 PMCID: PMC10848380 DOI: 10.1186/s12967-024-04911-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 01/20/2024] [Indexed: 02/08/2024] Open
Abstract
BACKGROUND Retinitis pigmentosa is the prevailing genetic cause of blindness in developed nations with no effective treatments. In the pursuit of unraveling the intricate dynamics underlying this complex disease, mechanistic models emerge as a tool of proven efficiency rooted in systems biology, to elucidate the interplay between RP genes and their mechanisms. The integration of mechanistic models and drug-target interactions under the umbrella of machine learning methodologies provides a multifaceted approach that can boost the discovery of novel therapeutic targets, facilitating further drug repurposing in RP. METHODS By mapping Retinitis Pigmentosa-related genes (obtained from Orphanet, OMIM and HPO databases) onto KEGG signaling pathways, a collection of signaling functional circuits encompassing Retinitis Pigmentosa molecular mechanisms was defined. Next, a mechanistic model of the so-defined disease map, where the effects of interventions can be simulated, was built. Then, an explainable multi-output random forest regressor was trained using normal tissue transcriptomic data to learn causal connections between targets of approved drugs from DrugBank and the functional circuits of the mechanistic disease map. Selected target genes involvement were validated on rd10 mice, a murine model of Retinitis Pigmentosa. RESULTS A mechanistic functional map of Retinitis Pigmentosa was constructed resulting in 226 functional circuits belonging to 40 KEGG signaling pathways. The method predicted 109 targets of approved drugs in use with a potential effect over circuits corresponding to nine hallmarks identified. Five of those targets were selected and experimentally validated in rd10 mice: Gabre, Gabra1 (GABARα1 protein), Slc12a5 (KCC2 protein), Grin1 (NR1 protein) and Glr2a. As a result, we provide a resource to evaluate the potential impact of drug target genes in Retinitis Pigmentosa. CONCLUSIONS The possibility of building actionable disease models in combination with machine learning algorithms to learn causal drug-disease interactions opens new avenues for boosting drug discovery. Such mechanistically-based hypotheses can guide and accelerate the experimental validations prioritizing drug target candidates. In this work, a mechanistic model describing the functional disease map of Retinitis Pigmentosa was developed, identifying five promising therapeutic candidates targeted by approved drug. Further experimental validation will demonstrate the efficiency of this approach for a systematic application to other rare diseases.
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Affiliation(s)
- Marina Esteban-Medina
- Andalusian Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Systems and Computational Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013, Seville, Spain
| | - Carlos Loucera
- Andalusian Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Systems and Computational Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013, Seville, Spain
| | - Kinza Rian
- Andalusian Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Systems and Computational Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013, Seville, Spain
| | - Sheyla Velasco
- Group of Pathophysiology and Therapies for Vision Disorders, Príncipe Felipe Research Center (CIPF), 46012, Valencia, Spain
| | - Lorena Olivares-González
- Group of Pathophysiology and Therapies for Vision Disorders, Príncipe Felipe Research Center (CIPF), 46012, Valencia, Spain
| | - Regina Rodrigo
- Group of Pathophysiology and Therapies for Vision Disorders, Príncipe Felipe Research Center (CIPF), 46012, Valencia, Spain
- Biomedical Research Networking Center in Rare Diseases (CIBERER), Health Institute Carlos III, 28029, Madrid, Spain
- Department of Physiology, University of Valencia (UV), 46100, Burjassot, Spain
- Department of Anatomy and Physiology, Catholic University of Valencia San Vicente Mártir, 46001, Valencia, Spain
- Joint Research Unit on Endocrinology, Nutrition and Clinical Dietetics UV-IIS La Fe, 46026, Valencia, Spain
| | - Joaquin Dopazo
- Andalusian Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain.
- Systems and Computational Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013, Seville, Spain.
- Biomedical Research Networking Center in Rare Diseases (CIBERER), Health Institute Carlos III, 28029, Madrid, Spain.
| | - Maria Peña-Chilet
- Andalusian Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain.
- Systems and Computational Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013, Seville, Spain.
- Biomedical Research Networking Center in Rare Diseases (CIBERER), Health Institute Carlos III, 28029, Madrid, Spain.
- BigData, AI, Biostatistics & Bioinformatics Platform, Health Research Institute La Fe (IISLaFe), 46026, Valencia, Spain.
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Loucera C, Carmona R, Esteban-Medina M, Bostelmann G, Muñoyerro-Muñiz D, Villegas R, Peña-Chilet M, Dopazo J. Real-world evidence with a retrospective cohort of 15,968 COVID-19 hospitalized patients suggests 21 new effective treatments. Virol J 2023; 20:226. [PMID: 37803348 PMCID: PMC10559601 DOI: 10.1186/s12985-023-02195-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 09/27/2023] [Indexed: 10/08/2023] Open
Abstract
PURPOSE Despite the extensive vaccination campaigns in many countries, COVID-19 is still a major worldwide health problem because of its associated morbidity and mortality. Therefore, finding efficient treatments as fast as possible is a pressing need. Drug repurposing constitutes a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent, as is the case with COVID-19. METHODS Using data from a central registry of electronic health records (the Andalusian Population Health Database), the effect of prior consumption of drugs for other indications previous to the hospitalization with respect to patient outcomes, including survival and lymphocyte progression, was studied on a retrospective cohort of 15,968 individuals, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020. RESULTS Covariate-adjusted hazard ratios and analysis of lymphocyte progression curves support a significant association between consumption of 21 different drugs and better patient survival. Contrarily, one drug, furosemide, displayed a significant increase in patient mortality. CONCLUSIONS In this study we have taken advantage of the availability of a regional clinical database to study the effect of drugs, which patients were taking for other indications, on their survival. The large size of the database allowed us to control covariates effectively.
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Affiliation(s)
- Carlos Loucera
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain
| | - Rosario Carmona
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS. Hospital Virgen del Rocio, Sevilla, Spain
| | - Marina Esteban-Medina
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain
| | - Gerrit Bostelmann
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
| | - Dolores Muñoyerro-Muñiz
- Subdirección Técnica Asesora de Gestión de la Información. Servicio Andaluz de Salud, Sevilla, Spain
| | - Román Villegas
- Subdirección Técnica Asesora de Gestión de la Información. Servicio Andaluz de Salud, Sevilla, Spain
| | - María Peña-Chilet
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain
- Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS. Hospital Virgen del Rocio, Sevilla, Spain
| | - Joaquín Dopazo
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain.
- Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, Sevilla, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS. Hospital Virgen del Rocio, Sevilla, Spain.
- FPS/ELIXIR-ES, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocio, Sevilla, Spain.
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5
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Payá-Milans M, Peña-Chilet M, Loucera C, Esteban-Medina M, Dopazo J. Functional Profiling of Soft Tissue Sarcoma Using Mechanistic Models. Int J Mol Sci 2023; 24:14732. [PMID: 37834179 PMCID: PMC10572617 DOI: 10.3390/ijms241914732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 09/08/2023] [Accepted: 09/26/2023] [Indexed: 10/15/2023] Open
Abstract
Soft tissue sarcoma is an umbrella term for a group of rare cancers that are difficult to treat. In addition to surgery, neoadjuvant chemotherapy has shown the potential to downstage tumors and prevent micrometastases. However, finding effective therapeutic targets remains a research challenge. Here, a previously developed computational approach called mechanistic models of signaling pathways has been employed to unravel the impact of observed changes at the gene expression level on the ultimate functional behavior of cells. In the context of such a mechanistic model, RNA-Seq counts sourced from the Recount3 resource, from The Cancer Genome Atlas (TCGA) Sarcoma project, and non-diseased sarcomagenic tissues from the Genotype-Tissue Expression (GTEx) project were utilized to investigate signal transduction activity through signaling pathways. This approach provides a precise view of the relationship between sarcoma patient survival and the signaling landscape in tumors and their environment. Despite the distinct regulatory alterations observed in each sarcoma subtype, this study identified 13 signaling circuits, or elementary sub-pathways triggering specific cell functions, present across all subtypes, belonging to eight signaling pathways, which served as predictors for patient survival. Additionally, nine signaling circuits from five signaling pathways that highlighted the modifications tumor samples underwent in comparison to normal tissues were found. These results describe the protective role of the immune system, suggesting an anti-tumorigenic effect in the tumor microenvironment, in the process of tumor cell detachment and migration, or the dysregulation of ion homeostasis. Also, the analysis of signaling circuit intermediary proteins suggests multiple strategies for therapy.
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Affiliation(s)
- Miriam Payá-Milans
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, 41013 Sevilla, Spain; (M.P.-M.); (M.P.-C.); (C.L.); (M.E.-M.)
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocío, 41013 Seville, Spain
- Institute of Biomedicine of Seville, IBiS/University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Sevilla, Spain
| | - María Peña-Chilet
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, 41013 Sevilla, Spain; (M.P.-M.); (M.P.-C.); (C.L.); (M.E.-M.)
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocío, 41013 Seville, Spain
- Institute of Biomedicine of Seville, IBiS/University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Sevilla, Spain
| | - Carlos Loucera
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, 41013 Sevilla, Spain; (M.P.-M.); (M.P.-C.); (C.L.); (M.E.-M.)
- Institute of Biomedicine of Seville, IBiS/University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Sevilla, Spain
| | - Marina Esteban-Medina
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, 41013 Sevilla, Spain; (M.P.-M.); (M.P.-C.); (C.L.); (M.E.-M.)
- Institute of Biomedicine of Seville, IBiS/University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Sevilla, Spain
| | - Joaquín Dopazo
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, 41013 Sevilla, Spain; (M.P.-M.); (M.P.-C.); (C.L.); (M.E.-M.)
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocío, 41013 Seville, Spain
- Institute of Biomedicine of Seville, IBiS/University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Sevilla, Spain
- FPS/ELIXIR-ES, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocío, 41013 Sevilla, Spain
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6
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Gawron P, Hoksza D, Piñero J, Peña-Chilet M, Esteban-Medina M, Fernandez-Rueda JL, Colonna V, Smula E, Heirendt L, Ancien F, Groues V, Satagopam VP, Schneider R, Dopazo J, Furlong LI, Ostaszewski M. Visualization of automatically combined disease maps and pathway diagrams for rare diseases. Front Bioinform 2023; 3:1101505. [PMID: 37502697 PMCID: PMC10369067 DOI: 10.3389/fbinf.2023.1101505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 05/05/2023] [Indexed: 07/29/2023] Open
Abstract
Introduction: Investigation of molecular mechanisms of human disorders, especially rare diseases, require exploration of various knowledge repositories for building precise hypotheses and complex data interpretation. Recently, increasingly more resources offer diagrammatic representation of such mechanisms, including disease-dedicated schematics in pathway databases and disease maps. However, collection of knowledge across them is challenging, especially for research projects with limited manpower. Methods: In this article we present an automated workflow for construction of maps of molecular mechanisms for rare diseases. The workflow requires a standardized definition of a disease using Orphanet or HPO identifiers to collect relevant genes and variants, and to assemble a functional, visual repository of related mechanisms, including data overlays. The diagrams composing the final map are unified to a common systems biology format from CellDesigner SBML, GPML and SBML+layout+render. The constructed resource contains disease-relevant genes and variants as data overlays for immediate visual exploration, including embedded genetic variant browser and protein structure viewer. Results: We demonstrate the functionality of our workflow on two examples of rare diseases: Kawasaki disease and retinitis pigmentosa. Two maps are constructed based on their corresponding identifiers. Moreover, for the retinitis pigmentosa use-case, we include a list of differentially expressed genes to demonstrate how to tailor the workflow using omics datasets. Discussion: In summary, our work allows for an ad-hoc construction of molecular diagrams combined from different sources, preserving their layout and graphical style, but integrating them into a single resource. This allows to reduce time consuming tasks of prototyping of a molecular disease map, enabling visual exploration, hypothesis building, data visualization and further refinement. The code of the workflow is open and accessible at https://gitlab.lcsb.uni.lu/minerva/automap/.
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Affiliation(s)
- Piotr Gawron
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, Luxembourg
| | - David Hoksza
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, Luxembourg
- Faculty of Mathematics and Physics, Charles University, Prague, Czechia
| | - Janet Piñero
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), Barcelona, Spain
- MedBioinformatics Solutions SL, Barcelona, Spain
| | - Maria Peña-Chilet
- Computational Medicine Platform, Fundacion Progreso y Salud, Sevilla, Spain
- Spanish Network of Research in Rare Diseases (CIBERER), Sevilla, Spain
| | | | | | - Vincenza Colonna
- Institute of Genetics and Biophysics, National Research Council of Italy, Naples, Rome
- Department of Genetics, Genomics and Informatics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Ewa Smula
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, Luxembourg
| | - Laurent Heirendt
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, Luxembourg
| | - François Ancien
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, Luxembourg
| | - Valentin Groues
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, Luxembourg
| | - Venkata P. Satagopam
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, Luxembourg
| | - Reinhard Schneider
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, Luxembourg
| | - Joaquin Dopazo
- Computational Medicine Platform, Fundacion Progreso y Salud, Sevilla, Spain
- Spanish Network of Research in Rare Diseases (CIBERER), Sevilla, Spain
| | - Laura I. Furlong
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), Barcelona, Spain
- MedBioinformatics Solutions SL, Barcelona, Spain
| | - Marek Ostaszewski
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, Luxembourg
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7
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Olivares-González L, Velasco S, Gallego I, Esteban-Medina M, Puras G, Loucera C, Martínez-Romero A, Peña-Chilet M, Pedraz JL, Rodrigo R. An SPM-Enriched Marine Oil Supplement Shifted Microglia Polarization toward M2, Ameliorating Retinal Degeneration in rd10 Mice. Antioxidants (Basel) 2022; 12:antiox12010098. [PMID: 36670960 PMCID: PMC9855087 DOI: 10.3390/antiox12010098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 12/03/2022] [Accepted: 12/13/2022] [Indexed: 01/04/2023] Open
Abstract
Retinitis pigmentosa (RP) is the most common inherited retinal dystrophy causing progressive vision loss. It is accompanied by chronic and sustained inflammation, including M1 microglia activation. This study evaluated the effect of an essential fatty acid (EFA) supplement containing specialized pro-resolving mediators (SPMs), on retinal degeneration and microglia activation in rd10 mice, a model of RP, as well as on LPS-stimulated BV2 cells. The EFA supplement was orally administered to mice from postnatal day (P)9 to P18. At P18, the electrical activity of the retina was examined by electroretinography (ERG) and innate behavior in response to light were measured. Retinal degeneration was studied via histology including the TUNEL assay and microglia immunolabeling. Microglia polarization (M1/M2) was assessed by flow cytometry, qPCR, ELISA and histology. Redox status was analyzed by measuring antioxidant enzymes and markers of oxidative damage. Interestingly, the EFA supplement ameliorated retinal dysfunction and degeneration by improving ERG recording and sensitivity to light, and reducing photoreceptor cell loss. The EFA supplement reduced inflammation and microglia activation attenuating M1 markers as well as inducing a shift to the M2 phenotype in rd10 mouse retinas and LPS-stimulated BV2 cells. It also reduced oxidative stress markers of lipid peroxidation and carbonylation. These findings could open up new therapeutic opportunities based on resolving inflammation with oral supplementation with SPMs such as the EFA supplement.
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Affiliation(s)
- Lorena Olivares-González
- Group of Pathophysiology and Therapies for Vision Disorders, Príncipe Felipe Research Center (CIPF), 46012 Valencia, Spain
| | - Sheyla Velasco
- Group of Pathophysiology and Therapies for Vision Disorders, Príncipe Felipe Research Center (CIPF), 46012 Valencia, Spain
| | - Idoia Gallego
- NanoBioCel Group, Laboratory of Pharmaceutics, School of Pharmacy, University of the Basque Country (UPV/EHU), 01006 Vitoria-Gasteiz, Spain
- Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Health Institute Carlos III, 01006 Vitoria-Gasteiz, Spain
- Bioaraba, NanoBioCel Research Group, 01006 Vitoria-Gasteiz, Spain
| | - Marina Esteban-Medina
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS Hospital Virgen del Rocío, 41013 Seville, Spain
- Systems and Computational Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
| | - Gustavo Puras
- NanoBioCel Group, Laboratory of Pharmaceutics, School of Pharmacy, University of the Basque Country (UPV/EHU), 01006 Vitoria-Gasteiz, Spain
- Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Health Institute Carlos III, 01006 Vitoria-Gasteiz, Spain
- Bioaraba, NanoBioCel Research Group, 01006 Vitoria-Gasteiz, Spain
| | - Carlos Loucera
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS Hospital Virgen del Rocío, 41013 Seville, Spain
- Systems and Computational Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
| | | | - María Peña-Chilet
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS Hospital Virgen del Rocío, 41013 Seville, Spain
- Systems and Computational Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocio, 41013 Seville, Spain
| | - José Luis Pedraz
- NanoBioCel Group, Laboratory of Pharmaceutics, School of Pharmacy, University of the Basque Country (UPV/EHU), 01006 Vitoria-Gasteiz, Spain
- Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Health Institute Carlos III, 01006 Vitoria-Gasteiz, Spain
- Bioaraba, NanoBioCel Research Group, 01006 Vitoria-Gasteiz, Spain
| | - Regina Rodrigo
- Group of Pathophysiology and Therapies for Vision Disorders, Príncipe Felipe Research Center (CIPF), 46012 Valencia, Spain
- Biomedical Research Networking Center in Rare Diseases (CIBERER), Health Institute Carlos III, 28029 Madrid, Spain
- Department of Physiology, University of Valencia (UV), 46100 Burjassot, Spain
- Department of Anatomy and Physiology, Catholic University of Valencia San Vicente Mártir, 46001 Valencia, Spain
- Joint Research Unit on Endocrinology, Nutrition and Clinical Dietetics UV-IIS La Fe, 46026 Valencia, Spain
- Correspondence: ; Tel.: +34-96-328-96-80
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8
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Puerto-Camacho P, Díaz-Martín J, Olmedo-Pelayo J, Bolado-Carrancio A, Salguero-Aranda C, Jordán-Pérez C, Esteban-Medina M, Álamo-Álvarez I, Delgado-Bellido D, Lobo-Selma L, Dopazo J, Sastre A, Alonso J, Grünewald TGP, Bernabeu C, Byron A, Brunton VG, Amaral AT, Álava ED. Endoglin and MMP14 Contribute to Ewing Sarcoma Spreading by Modulation of Cell–Matrix Interactions. Int J Mol Sci 2022; 23:ijms23158657. [PMID: 35955799 PMCID: PMC9369355 DOI: 10.3390/ijms23158657] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 07/14/2022] [Accepted: 07/22/2022] [Indexed: 01/26/2023] Open
Abstract
Endoglin (ENG) is a mesenchymal stem cell (MSC) marker typically expressed by active endothelium. This transmembrane glycoprotein is shed by matrix metalloproteinase 14 (MMP14). Our previous work demonstrated potent preclinical activity of first-in-class anti-ENG antibody-drug conjugates as a nascent strategy to eradicate Ewing sarcoma (ES), a devastating rare bone/soft tissue cancer with a putative MSC origin. We also defined a correlation between ENG and MMP14 expression in ES. Herein, we show that ENG expression is significantly associated with a dismal prognosis in a large cohort of ES patients. Moreover, both ENG/MMP14 are frequently expressed in primary ES tumors and metastasis. To deepen in their functional relevance in ES, we conducted transcriptomic and proteomic profiling of in vitro ES models that unveiled a key role of ENG and MMP14 in cell mechano-transduction. Migration and adhesion assays confirmed that loss of ENG disrupts actin filament assembly and filopodia formation, with a concomitant effect on cell spreading. Furthermore, we observed that ENG regulates cell–matrix interaction through activation of focal adhesion signaling and protein kinase C expression. In turn, loss of MMP14 contributed to a more adhesive phenotype of ES cells by modulating the transcriptional extracellular matrix dynamics. Overall, these results suggest that ENG and MMP14 exert a significant role in mediating correct spreading machinery of ES cells, impacting the aggressiveness of the disease.
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Affiliation(s)
- Pilar Puerto-Camacho
- Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital/CSIC/University of Sevilla/CIBERONC, Molecular Pathology of Sarcomas, 41013 Seville, Spain
| | - Juan Díaz-Martín
- Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital/CSIC/University of Sevilla/CIBERONC, Molecular Pathology of Sarcomas, 41013 Seville, Spain
- Department of Normal and Pathological Cytology and Histology, School of Medicine, University of Seville, 41009 Seville, Spain
| | - Joaquín Olmedo-Pelayo
- Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital/CSIC/University of Sevilla/CIBERONC, Molecular Pathology of Sarcomas, 41013 Seville, Spain
- Department of Normal and Pathological Cytology and Histology, School of Medicine, University of Seville, 41009 Seville, Spain
| | - Alfonso Bolado-Carrancio
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Carmen Salguero-Aranda
- Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital/CSIC/University of Sevilla/CIBERONC, Molecular Pathology of Sarcomas, 41013 Seville, Spain
- Department of Normal and Pathological Cytology and Histology, School of Medicine, University of Seville, 41009 Seville, Spain
| | - Carmen Jordán-Pérez
- Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital/CSIC/University of Sevilla/CIBERONC, Molecular Pathology of Sarcomas, 41013 Seville, Spain
| | - Marina Esteban-Medina
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocío, 41013 Seville, Spain
| | - Inmaculada Álamo-Álvarez
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocío, 41013 Seville, Spain
| | - Daniel Delgado-Bellido
- Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital/CSIC/University of Sevilla/CIBERONC, Molecular Pathology of Sarcomas, 41013 Seville, Spain
| | - Laura Lobo-Selma
- Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital/CSIC/University of Sevilla/CIBERONC, Molecular Pathology of Sarcomas, 41013 Seville, Spain
- Department of Normal and Pathological Cytology and Histology, School of Medicine, University of Seville, 41009 Seville, Spain
| | - Joaquín Dopazo
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocío, 41013 Seville, Spain
| | - Ana Sastre
- Unidad Hemato-oncología Pediátrica, Hospital Infantil Universitario La Paz, 28046 Madrid, Spain
| | - Javier Alonso
- Unidad Hemato-oncología Pediátrica, Hospital Infantil Universitario La Paz, 28046 Madrid, Spain
- Unidad de Tumores Sólidos Infantiles, Instituto de Investigación de Enfermedades Raras, Instituto de Salud Carlos III (IIER-ISCIII), 28029 Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, Instituto de Salud Carlos III (CB06/07/1009; CIBERER-ISCIII), 28029 Madrid, Spain
| | - Thomas G. P. Grünewald
- Division of Translational Pediatric Sarcoma Research, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
- Hopp-Children’s Cancer Center Heidelberg (KiTZ), 69120 Heidelberg, Germany
- Institute of Pathology, Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Carmelo Bernabeu
- Division of Translational Pediatric Sarcoma Research, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), 69120 Heidelberg, Germany
- Centro de Investigaciones Biológicas Margarita Salas, Consejo Superior de Investigaciones Científicas (CSIC), 28040 Madrid, Spain
| | - Adam Byron
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
- Division of Molecular and Cellular Function, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, UK
| | - Valerie G. Brunton
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Ana Teresa Amaral
- Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital/CSIC/University of Sevilla/CIBERONC, Molecular Pathology of Sarcomas, 41013 Seville, Spain
- Department of Normal and Pathological Cytology and Histology, School of Medicine, University of Seville, 41009 Seville, Spain
- Correspondence: (A.T.A.); (E.D.Á.)
| | - Enrique De Álava
- Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital/CSIC/University of Sevilla/CIBERONC, Molecular Pathology of Sarcomas, 41013 Seville, Spain
- Department of Normal and Pathological Cytology and Histology, School of Medicine, University of Seville, 41009 Seville, Spain
- Correspondence: (A.T.A.); (E.D.Á.)
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9
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Ostaszewski M, Niarakis A, Mazein A, Kuperstein I, Phair R, Orta-Resendiz A, Singh V, Aghamiri SS, Acencio ML, Glaab E, Ruepp A, Fobo G, Montrone C, Brauner B, Frishman G, Monraz Gómez LC, Somers J, Hoch M, Kumar Gupta S, Scheel J, Borlinghaus H, Czauderna T, Schreiber F, Montagud A, Ponce de Leon M, Funahashi A, Hiki Y, Hiroi N, Yamada TG, Dräger A, Renz A, Naveez M, Bocskei Z, Messina F, Börnigen D, Fergusson L, Conti M, Rameil M, Nakonecnij V, Vanhoefer J, Schmiester L, Wang M, Ackerman EE, Shoemaker JE, Zucker J, Oxford K, Teuton J, Kocakaya E, Summak GY, Hanspers K, Kutmon M, Coort S, Eijssen L, Ehrhart F, Rex DAB, Slenter D, Martens M, Pham N, Haw R, Jassal B, Matthews L, Orlic-Milacic M, Senff-Ribeiro A, Rothfels K, Shamovsky V, Stephan R, Sevilla C, Varusai T, Ravel JM, Fraser R, Ortseifen V, Marchesi S, Gawron P, Smula E, Heirendt L, Satagopam V, Wu G, Riutta A, Golebiewski M, Owen S, Goble C, Hu X, Overall RW, Maier D, Bauch A, Gyori BM, Bachman JA, Vega C, Grouès V, Vazquez M, Porras P, Licata L, Iannuccelli M, Sacco F, Nesterova A, Yuryev A, de Waard A, Turei D, Luna A, Babur O, Soliman S, Valdeolivas A, Esteban-Medina M, Peña-Chilet M, Rian K, Helikar T, Puniya BL, Modos D, Treveil A, Olbei M, De Meulder B, Ballereau S, Dugourd A, Naldi A, Noël V, Calzone L, Sander C, Demir E, Korcsmaros T, Freeman TC, Augé F, Beckmann JS, Hasenauer J, Wolkenhauer O, Willighagen EL, Pico AR, Evelo CT, Gillespie ME, Stein LD, Hermjakob H, D'Eustachio P, Saez-Rodriguez J, Dopazo J, Valencia A, Kitano H, Barillot E, Auffray C, Balling R, Schneider R. COVID-19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms. Mol Syst Biol 2021; 17:e10851. [PMID: 34939300 PMCID: PMC8696085 DOI: 10.15252/msb.202110851] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 12/07/2021] [Indexed: 11/19/2022] Open
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10
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Loucera C, Peña-Chilet M, Esteban-Medina M, Muñoyerro-Muñiz D, Villegas R, Lopez-Miranda J, Rodriguez-Baño J, Túnez I, Bouillon R, Dopazo J, Quesada Gomez JM. Real world evidence of calcifediol or vitamin D prescription and mortality rate of COVID-19 in a retrospective cohort of hospitalized Andalusian patients. Sci Rep 2021; 11:23380. [PMID: 34862422 PMCID: PMC8642445 DOI: 10.1038/s41598-021-02701-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 11/19/2021] [Indexed: 12/12/2022] Open
Abstract
COVID-19 is a major worldwide health problem because of acute respiratory distress syndrome, and mortality. Several lines of evidence have suggested a relationship between the vitamin D endocrine system and severity of COVID-19. We present a survival study on a retrospective cohort of 15,968 patients, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020. Based on a central registry of electronic health records (the Andalusian Population Health Database, BPS), prescription of vitamin D or its metabolites within 15–30 days before hospitalization were recorded. The effect of prescription of vitamin D (metabolites) for other indication previous to the hospitalization was studied with respect to patient survival. Kaplan–Meier survival curves and hazard ratios support an association between prescription of these metabolites and patient survival. Such association was stronger for calcifediol (Hazard Ratio, HR = 0.67, with 95% confidence interval, CI, of [0.50–0.91]) than for cholecalciferol (HR = 0.75, with 95% CI of [0.61–0.91]), when prescribed 15 days prior hospitalization. Although the relation is maintained, there is a general decrease of this effect when a longer period of 30 days prior hospitalization is considered (calcifediol HR = 0.73, with 95% CI [0.57–0.95] and cholecalciferol HR = 0.88, with 95% CI [0.75, 1.03]), suggesting that association was stronger when the prescription was closer to the hospitalization.
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Affiliation(s)
- Carlos Loucera
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocio, 41013, Seville, Spain.,Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Seville, Spain
| | - María Peña-Chilet
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocio, 41013, Seville, Spain.,Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Seville, Spain.,Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocio, 41013, Seville, Spain
| | - Marina Esteban-Medina
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocio, 41013, Seville, Spain.,Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Seville, Spain
| | - Dolores Muñoyerro-Muñiz
- Subdirección Técnica Asesora de Gestión de la Información, Servicio Andaluz de Salud, Seville, Spain
| | - Román Villegas
- Subdirección Técnica Asesora de Gestión de la Información, Servicio Andaluz de Salud, Seville, Spain
| | - Jose Lopez-Miranda
- Internal Medicine Department, IMIBIC/Reina Sofia University Hospital/University of Cordoba, 14004, Córdoba, Spain.,CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - Jesus Rodriguez-Baño
- Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Seville, Spain.,Unidad Clínica de Enfermedades Infecciosas, Microbiología y Medicina Preventiva, Hospital Universitario Virgen Macarena, Seville, Spain.,Departamento de Medicina, Universidad de Sevilla, Seville, Spain
| | - Isaac Túnez
- Departamento de Bioquimica y Biología Molecular, Facultad de Medicina y Enfermería, Universidad de Córdoba, Córdoba, Spain.,Instituto Maimónides de Investigacion Biomédica de Córdoba (IMIBIC), 14004, Córdoba, Spain.,G. Técnico de Expertos de Andalucía para Estudios de Suplementos e Intervención Nutricional Frente a Covid-19, SGIDIS, Consejería de Salud y Familias, Junta de Andalucia, Seville, Spain.,Secretaria General de Investigación, Desarrollo e Innovación en Salud, Consejería de Salud y Familias de la Junta de Andalucía, Seville, Spain
| | - Roger Bouillon
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KULeuven, Herestraat, 3000, Leuven, Belgium
| | - Joaquin Dopazo
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocio, 41013, Seville, Spain. .,Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Seville, Spain. .,Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocio, 41013, Seville, Spain. .,FPS/ELIXIR-ES, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocio, 41013, Seville, Spain.
| | - Jose Manuel Quesada Gomez
- Instituto Maimónides de Investigacion Biomédica de Córdoba (IMIBIC), 14004, Córdoba, Spain. .,CIBER de Fragilidad y Envejecimiento Saludable (CIBERFES), Hospital Universitario Reina Sofía, Universidad de Córdoba, Menéndez Pidal s/n, 14004, Córdoba, Spain.
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11
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Rian K, Hidalgo MR, Çubuk C, Falco MM, Loucera C, Esteban-Medina M, Alamo-Alvarez I, Peña-Chilet M, Dopazo J. Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data. Comput Struct Biotechnol J 2021; 19:2968-2978. [PMID: 34136096 PMCID: PMC8170118 DOI: 10.1016/j.csbj.2021.05.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 04/21/2021] [Accepted: 05/11/2021] [Indexed: 12/13/2022] Open
Abstract
Genome-scale mechanistic models of pathways are gaining importance for genomic data interpretation because they provide a natural link between genotype measurements (transcriptomics or genomics data) and the phenotype of the cell (its functional behavior). Moreover, mechanistic models can be used to predict the potential effect of interventions, including drug inhibitions. Here, we present the implementation of a mechanistic model of cell signaling for the interpretation of transcriptomic data as an R/Bioconductor package, a Cytoscape plugin and a web tool with enhanced functionality which includes building interpretable predictors, estimation of the effect of perturbations and assessment of the effect of mutations in complex scenarios.
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Affiliation(s)
- Kinza Rian
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla 41013, Spain
- Laboratory of Innovative Technologies (LTI), National School of Applied Sciences in Tangier, UAE, Morocco
| | - Marta R. Hidalgo
- Bioinformatics and Biostatistics Unit, Centro de Investigación Príncipe Felipe (CIPF), 46012 Valencia, Spain
| | - Cankut Çubuk
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla 41013, Spain
| | - Matias M. Falco
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla 41013, Spain
- Bioinformatics in RareDiseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Sevilla 41013, Spain
| | - Carlos Loucera
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla 41013, Spain
- Computational Systems Medicine. Institute of Biomedicine of Seville (IBiS), Sevilla 41013, Spain
| | - Marina Esteban-Medina
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla 41013, Spain
- Computational Systems Medicine. Institute of Biomedicine of Seville (IBiS), Sevilla 41013, Spain
| | - Inmaculada Alamo-Alvarez
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla 41013, Spain
- Computational Systems Medicine. Institute of Biomedicine of Seville (IBiS), Sevilla 41013, Spain
| | - María Peña-Chilet
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla 41013, Spain
- Bioinformatics in RareDiseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Sevilla 41013, Spain
- Computational Systems Medicine. Institute of Biomedicine of Seville (IBiS), Sevilla 41013, Spain
| | - Joaquín Dopazo
- Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla 41013, Spain
- Bioinformatics in RareDiseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Sevilla 41013, Spain
- Computational Systems Medicine. Institute of Biomedicine of Seville (IBiS), Sevilla 41013, Spain
- Functional Genomics Node (INB-ELIXIR-es), Sevilla, Spain
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12
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Rian K, Esteban-Medina M, Hidalgo MR, Çubuk C, Falco MM, Loucera C, Gunyel D, Ostaszewski M, Peña-Chilet M, Dopazo J. Mechanistic modeling of the SARS-CoV-2 disease map. BioData Min 2021; 14:5. [PMID: 33478554 PMCID: PMC7817765 DOI: 10.1186/s13040-021-00234-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 01/05/2021] [Indexed: 12/13/2022] Open
Abstract
Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral infection, covering from the entry and replication mechanisms to the downstream consequences as inflammation and antigenic response, can be inferred from gene expression experiments. Moreover, the effect of potential interventions, such as knock-downs, or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied. This freely available tool not only provides an unprecedentedly detailed view of the mechanisms of viral invasion and the consequences in the cell but has also the potential of becoming an invaluable asset in the search for efficient antiviral treatments.
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Affiliation(s)
- Kinza Rian
- Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain
| | - Marina Esteban-Medina
- Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Sevilla, Spain
| | - Marta R Hidalgo
- Bioinformatics and Biostatistics Unit, Centro de Investigación Príncipe Felipe (CIPF), 46012, Valencia, Spain
| | - Cankut Çubuk
- Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain
| | - Matias M Falco
- Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain
- Bioinformatics in RareDiseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Sevilla, Spain
| | - Carlos Loucera
- Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Sevilla, Spain
| | - Devrim Gunyel
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4367, Belvaux, Luxembourg
| | - Marek Ostaszewski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4367, Belvaux, Luxembourg
| | - María Peña-Chilet
- Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain.
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Sevilla, Spain.
- Bioinformatics in RareDiseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Sevilla, Spain.
| | - Joaquín Dopazo
- Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, Sevilla, Spain.
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, 41013, Sevilla, Spain.
- Bioinformatics in RareDiseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Sevilla, Spain.
- Functional Genomics Node (INB-ELIXIR-es), Sevilla, Spain.
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Puerto-Camacho P, Amaral AT, Diaz-Martin J, Bolado-Carrancio A, Jordan-Perez C, Salguero-Aranda C, Esteban-Medina M, Alamo-Alvarez I, Dopazo J, Bernabeu C, Byron A, Brunton VG, de Álava E. Abstract 6158: The relevance of endoglin and MMP14 to the metastatic potential of Ewing sarcoma cells. Cancer Res 2020. [DOI: 10.1158/1538-7445.am2020-6158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Ewing sarcoma (ES) is a developmental bone/soft tissue neoplasia, for which mesenchymal stem cell (MSC) is the putative cell of origin. Although the outcome of ES patients bearing primary tumors has improved significantly, patients with metastatic ES still have a poor prognosis. The MSC marker endoglin/CD105 (ENG) and the ENG-shedding protease MMP14 have been, respectively, described as cell migration and invasion regulators. In our attempt to better understand the mechanism of ES progression, we are focusing on the role of ENG and MMP14 in ES cells.
Methods: In vitro ENG-knockdown (ENG-KD; RM82 and SKNMC cell lines) and ENG-overexpressing (pENG; TC71 cell lines) models were generated by shRNA technology and pDisplay vectors, respectively, and confirmed by qRT-PCR, western blotting and flow cytometry. In vitro MMP14-knockout (MMP14-KO; RM82 and SKNMC) models were generated by CRISPR-Cas9 and confirmed by western blotting and Sanger sequencing. Transwell migration/invasion, adhesion, clonogenicity and proliferation assays were performed in vitro. Actin filament organization was evaluated by immunofluorescence. Extracellular vesicles (EVs) were isolated by ultracentrifugation and density gradient separation. Transcriptomic profiling was performed by Clarion S Human arrays followed by Gene Set Enrichment Analysis. HiPathia tool was used to recode the transcriptomic data into measurements of cell activity by applying mechanistic models. Reverse Phase Protein Array (RPPA) analysis was evaluated on the ENG-KD RM82 model. ENG-targeting immunoprecipitations (IP) from wild type RM82 protein extracts were analyzed by mass spectrometry (MS).
Results: The impaired clonogenic potential of ENG-KD RM82 and SKNMC models suggests a role of ENG on the stemness capacity of ES, without affecting the proliferation rate. The reduced migratory and adhesive phenotype of the ENG-KD RM82 model and the transcriptomic profiling of both ENG-KD RM82 and SKNMC cells, suggest a role of ENG in ES cell migration and adhesion. The altered organization of actin filaments in ENG-KD and pENG models could support a role of ENG in actin filament remodeling. The transcriptomic profiling of ENG-KD models and the RPPA results underscore the regulation of FAK signaling by ENG. The IP-MS analysis of ENG partners identifies Integrin-Linked Kinase-Associated serine/threonine Phosphatase (ILKAP) as one of the main interactors of ENG in RM82 cells, suggesting its possible association with the focal adhesion member ILK. ENG is enriched in EVs from different ES cell lines. The transcriptomic profiling of MMP14-KO SKNMC cells highlights the involvement of MMP14 activity in the extracellular matrix organization of ES cells.
Conclusion: ENG favors a pro-migratory phenotype in ES cells. These findings help to better understand the molecular landscape of tumoral cells from ES patients, and might have potential clinical implications.
Citation Format: Pilar Puerto-Camacho, Ana Teresa Amaral, Juan Diaz-Martin, Alfonso Bolado-Carrancio, Carmen Jordan-Perez, Carmen Salguero-Aranda, Marina Esteban-Medina, Inmaculada Alamo-Alvarez, Joaquin Dopazo, Carmelo Bernabeu, Adam Byron, Valerie G. Brunton, Enrique de Álava. The relevance of endoglin and MMP14 to the metastatic potential of Ewing sarcoma cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6158.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Adam Byron
- 2MRC Institute of Genetics & Molecular Medicine, Edinburgh, United Kingdom
| | - Valerie G. Brunton
- 2MRC Institute of Genetics & Molecular Medicine, Edinburgh, United Kingdom
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Esteban-Medina M, Peña-Chilet M, Loucera C, Dopazo J. Exploring the druggable space around the Fanconi anemia pathway using machine learning and mechanistic models. BMC Bioinformatics 2019; 20:370. [PMID: 31266445 PMCID: PMC6604281 DOI: 10.1186/s12859-019-2969-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 06/25/2019] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND In spite of the abundance of genomic data, predictive models that describe phenotypes as a function of gene expression or mutations are difficult to obtain because they are affected by the curse of dimensionality, given the disbalance between samples and candidate genes. And this is especially dramatic in scenarios in which the availability of samples is difficult, such as the case of rare diseases. RESULTS The application of multi-output regression machine learning methodologies to predict the potential effect of external proteins over the signaling circuits that trigger Fanconi anemia related cell functionalities, inferred with a mechanistic model, allowed us to detect over 20 potential therapeutic targets. CONCLUSIONS The use of artificial intelligence methods for the prediction of potentially causal relationships between proteins of interest and cell activities related with disease-related phenotypes opens promising avenues for the systematic search of new targets in rare diseases.
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Affiliation(s)
- Marina Esteban-Medina
- Clinical Bioinformatics Area. Fundación Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013 Sevilla, Spain
| | - María Peña-Chilet
- Clinical Bioinformatics Area. Fundación Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013 Sevilla, Spain
- Bioinformatics in Rare Diseases (BiER). Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocío, 41013 Sevilla, Spain
| | - Carlos Loucera
- Clinical Bioinformatics Area. Fundación Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013 Sevilla, Spain
| | - Joaquín Dopazo
- Clinical Bioinformatics Area. Fundación Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, 41013 Sevilla, Spain
- Bioinformatics in Rare Diseases (BiER). Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocío, 41013 Sevilla, Spain
- INB-ELIXIR-es, FPS, Hospital Virgen del Rocío, 42013 Sevilla, Spain
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