Identification of Deregulated Mechanisms ...
Type de document :
Compte-rendu et recension critique d'ouvrage
PMID :
Titre :
Identification of Deregulated Mechanisms Specific to Bladder Cancer Subtypes
Auteur(s) :
Champion, Magali [Auteur]
Mathématiques Appliquées Paris 5 [MAP5 - UMR 8145]
Chiquet, Julien [Auteur]
Mathématiques et Informatique Appliquées [MIA Paris-Saclay]
Neuvial, Pierre [Auteur]
Institut de Mathématiques de Toulouse UMR5219 [IMT]
Elati, Mohamed [Auteur]
Hétérogénéité, Plasticité et Résistance aux Thérapies des Cancers = Cancer Heterogeneity, Plasticity and Resistance to Therapies - UMR 9020 - U 1277 [CANTHER]
Radvanyi, François [Auteur]
Centre de recherche de l'Institut Curie [Paris]
Birmelé, Etienne [Auteur]
Institut de Recherche Mathématique Avancée [IRMA]
Mathématiques Appliquées Paris 5 [MAP5 - UMR 8145]
Mathématiques Appliquées Paris 5 [MAP5 - UMR 8145]
Chiquet, Julien [Auteur]
Mathématiques et Informatique Appliquées [MIA Paris-Saclay]
Neuvial, Pierre [Auteur]
Institut de Mathématiques de Toulouse UMR5219 [IMT]
Elati, Mohamed [Auteur]
Hétérogénéité, Plasticité et Résistance aux Thérapies des Cancers = Cancer Heterogeneity, Plasticity and Resistance to Therapies - UMR 9020 - U 1277 [CANTHER]
Radvanyi, François [Auteur]
Centre de recherche de l'Institut Curie [Paris]
Birmelé, Etienne [Auteur]
Institut de Recherche Mathématique Avancée [IRMA]
Mathématiques Appliquées Paris 5 [MAP5 - UMR 8145]
Titre de la revue :
Journal of Bioinformatics and Computational Biology
Éditeur :
World Scientific Publishing
Date de publication :
2021
ISSN :
0219-7200
Mot(s)-clé(s) en anglais :
Cancer systems biology
Deregulations
Gene regulatory network
Deregulations
Gene regulatory network
Discipline(s) HAL :
Mathématiques [math]/Statistiques [math.ST]
Sciences du Vivant [q-bio]/Cancer
Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
Sciences du Vivant [q-bio]/Cancer
Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
Résumé en anglais : [en]
In many cancers, mechanisms of gene regulation can be severely altered. Identification of deregulated genes, which do not follow the regulation processes that exist between transcription factors and their target genes, is ...
Lire la suite >In many cancers, mechanisms of gene regulation can be severely altered. Identification of deregulated genes, which do not follow the regulation processes that exist between transcription factors and their target genes, is of importance to better understand the development of the disease. We propose a methodology to detect deregulation mechanisms with a particular focus on cancer subtypes. This strategy is based on the comparison between tumoral and healthy cells. First, we use gene expression data from healthy cells to infer a reference gene regulatory network. Then, we compare it with gene expression levels in tumor samples to detect deregulated target genes. We finally measure the ability of each transcription factor to explain these deregulations. We apply our method on a public bladder cancer data set derived from The Cancer Genome Atlas project and confirm that it captures hallmarks of cancer subtypes. We also show that it enables the discovery of new potential biomarkers.Lire moins >
Lire la suite >In many cancers, mechanisms of gene regulation can be severely altered. Identification of deregulated genes, which do not follow the regulation processes that exist between transcription factors and their target genes, is of importance to better understand the development of the disease. We propose a methodology to detect deregulation mechanisms with a particular focus on cancer subtypes. This strategy is based on the comparison between tumoral and healthy cells. First, we use gene expression data from healthy cells to infer a reference gene regulatory network. Then, we compare it with gene expression levels in tumor samples to detect deregulated target genes. We finally measure the ability of each transcription factor to explain these deregulations. We apply our method on a public bladder cancer data set derived from The Cancer Genome Atlas project and confirm that it captures hallmarks of cancer subtypes. We also show that it enables the discovery of new potential biomarkers.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
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