Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models
Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models
Abstract Backgroundin spite of the increasing availability of genomic and transcriptomic data, there is still a gap between the detection of perturbations in gene expression and the understanding of their contribution to the molecular mechanisms that ultimately account for the phenotype studied. Alterations in the metabolism are behind the initiation and progression of many diseases, including cancer. The wealth of available knowledge on metabolic processes can therefore be used to derive mechanistic models that link gene expression perturbations to changes in metabolic activity that provide relevant clues on molecular mechanisms of disease and drug modes of action (MoA). In particular, pathway modules, which recapitulate the main aspects of metabolism, are especially suitable for this type of modeling. Resultswe present Metabolizer, a web-based application that offers an intuitive, easy-to-use interactive interface to analyze differences in pathway module metabolic activities that can also be used for class prediction and in silico prediction of Knock-Out (KO) effects. Moreover, Metabolizer can automatically predict the optimal KO intervention for restoring a diseased phenotype. We provide different types of validations of some of the predictions made by Metabolizer. ConclusionsMetabolizer is a web tool that allows understanding molecular mechanisms of disease or the MoA of drugs within the context of the metabolism by using gene expression measurements. In addition, this tool automatically suggests potential therapeutic targets for individualized therapeutic interventions.Metabolizer can be found at: http://metabolizer.babelomics.org.
Rian Kinza、Hidalgo Marta R.、Dopazo Joaqu¨an、Salavert Francisco、Carbonell-Caballero Jose、Herranz Carmen、Pujana Miguel A.、Mateo Francesca、Amadoz Alicia、?ubuk Cankut
Clinical Bioinformatics Area, Fundaci¨?n Progreso y SaludBioinformatics and Biostatistics Unit, Centro de Investigaci¨?n Pr¨ancipe Felipe (CIPF)Clinical Bioinformatics Area, Fundaci¨?n Progreso y Salud||Bioinformatics in Rare Diseases (BiER), Centro de Investigaci¨?n Biom¨|dica en Red de Enfermedades Raras (CIBERER)||Functional Genomics NodeBioinformatics in Rare Diseases (BiER), Centro de Investigaci¨?n Biom¨|dica en Red de Enfermedades Raras (CIBERER)Chromatin and Gene expression Lab, Gene Regulation, Stem Cells and Cancer Program, Centre de Regulaci¨? Gen¨°mica (CRG). The Barcelona Institute of Science and TechnologyProCURE. Catalan Institute of Oncology. Bellvitge Institute for Biomedical Research (IDIBELL). L?ˉHospitalet del LlobregatProCURE. Catalan Institute of Oncology. Bellvitge Institute for Biomedical Research (IDIBELL). L?ˉHospitalet del LlobregatProCURE. Catalan Institute of Oncology. Bellvitge Institute for Biomedical Research (IDIBELL). L?ˉHospitalet del LlobregatDepartment of BioinformaticsClinical Bioinformatics Area, Fundaci¨?n Progreso y Salud
基础医学生物化学分子生物学
Metabolic pathwaypathway analysismetabolic modulesmodelspredictorstherapeutic targetMoAdisease mechanismsystems biology
Rian Kinza,Hidalgo Marta R.,Dopazo Joaqu¨an,Salavert Francisco,Carbonell-Caballero Jose,Herranz Carmen,Pujana Miguel A.,Mateo Francesca,Amadoz Alicia,?ubuk Cankut.Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models[EB/OL].(2025-03-28)[2025-05-04].https://www.biorxiv.org/content/10.1101/367334.点此复制
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