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Experimental and computational modeling for signature and biomarker discovery of renal cell carcinoma progression

hal.structure.identifierLaboratoire Angiogenèse et Micro-environnement des Cancers [LAMC]
dc.contributor.authorCOOLEY, Lindsay
hal.structure.identifierLaboratoire Angiogenèse et Micro-environnement des Cancers [LAMC]
hal.structure.identifierCentre de Bioinformatique de Bordeaux [CBIB]
dc.contributor.authorRUDEWICZ, Justine
hal.structure.identifierLaboratoire Angiogenèse et Micro-environnement des Cancers [LAMC]
dc.contributor.authorSOULEYREAU, Wilfried
hal.structure.identifierLaboratoire Angiogenèse et Micro-environnement des Cancers [LAMC]
dc.contributor.authorEMANUELLI, Andrea
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
hal.structure.identifierMathematical Oncology Laboratory [Ciudad Real] [MôLAB]
dc.contributor.authorALVAREZ-ARENAS, Arturo
hal.structure.identifierUniversity of Liverpool
dc.contributor.authorCLARKE, Kim
hal.structure.identifierUniversity of Liverpool
dc.contributor.authorFALCIANI, Francesco
hal.structure.identifierCentre Scientifique de Monaco [CSM]
hal.structure.identifierInstitut de Recherche sur le Cancer et le Vieillissement [IRCAN]
dc.contributor.authorDUFIES, Maeva
hal.structure.identifierLeuven Center for Cancer Biology [VIB-KU-CCB]
dc.contributor.authorLAMBRECHTS, Diether
hal.structure.identifierLeuven Center for Cancer Biology [VIB-KU-CCB]
dc.contributor.authorMODAVE, Elodie
hal.structure.identifierInstitut de biochimie et génétique cellulaires [IBGC]
hal.structure.identifierImmunology from Concept and Experiments to Translation = Immunologie Conceptuelle, Expérimentale et Translationnelle [ImmunoConcept]
hal.structure.identifierCentre de Bioinformatique de Bordeaux [CBIB]
dc.contributor.authorCHALOPIN-FILLOT, Domitille
hal.structure.identifierUniversité de Bordeaux [UB]
dc.contributor.authorPINEAU, Raphael
hal.structure.identifierHôpital Pasteur [Nice] [CHU]
dc.contributor.authorAMBROSETTI, Damien
hal.structure.identifierservice d'urologie [CHU Bordeaux]
dc.contributor.authorBERNHARD, Jean-Christophe
hal.structure.identifierCentre Hospitalier Universitaire de Bordeaux [CHU Bordeaux]
dc.contributor.authorRAVAUD, Alain
hal.structure.identifierCentre Léon Bérard [Lyon]
dc.contributor.authorNÉGRIER, Sylvie
hal.structure.identifierCentre de Lutte contre le Cancer Antoine Lacassagne [Nice] [UNICANCER/CAL]
dc.contributor.authorFERRERO, Jean-Marc
hal.structure.identifierCentre Scientifique de Monaco [CSM]
hal.structure.identifierInstitut de Recherche sur le Cancer et le Vieillissement [IRCAN]
dc.contributor.authorPAGÈS, Gilles
hal.structure.identifierMéthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique [COMPO]
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorBENZEKRY, Sebastien
hal.structure.identifierInstitut de biochimie et génétique cellulaires [IBGC]
hal.structure.identifierCentre de Bioinformatique de Bordeaux [CBIB]
dc.contributor.authorNIKOLSKI, Macha
hal.structure.identifierLaboratoire Angiogenèse et Micro-environnement des Cancers [LAMC]
dc.contributor.authorBIKFALVI, Andreas
dc.date.accessioned2024-04-04T02:44:40Z
dc.date.available2024-04-04T02:44:40Z
dc.date.issued2021-12
dc.identifier.issn1476-4598
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/191427
dc.description.abstractEnAbstract Background Renal Cell Carcinoma (RCC) is difficult to treat with 5-year survival rate of 10% in metastatic patients. Main reasons of therapy failure are lack of validated biomarkers and scarce knowledge of the biological processes occurring during RCC progression. Thus, the investigation of mechanisms regulating RCC progression is fundamental to improve RCC therapy. Methods In order to identify molecular markers and gene processes involved in the steps of RCC progression, we generated several cell lines of higher aggressiveness by serially passaging mouse renal cancer RENCA cells in mice and, concomitantly, performed functional genomics analysis of the cells. Multiple cell lines depicting the major steps of tumor progression (including primary tumor growth, survival in the blood circulation and metastatic spread) were generated and analyzed by large-scale transcriptome, genome and methylome analyses. Furthermore, we performed clinical correlations of our datasets. Finally we conducted a computational analysis for predicting the time to relapse based on our molecular data. Results Through in vivo passaging, RENCA cells showed increased aggressiveness by reducing mice survival, enhancing primary tumor growth and lung metastases formation. In addition, transcriptome and methylome analyses showed distinct clustering of the cell lines without genomic variation. Distinct signatures of tumor aggressiveness were revealed and validated in different patient cohorts. In particular, we identified SAA2 and CFB as soluble prognostic and predictive biomarkers of the therapeutic response. Machine learning and mathematical modeling confirmed the importance of CFB and SAA2 together, which had the highest impact on distant metastasis-free survival. From these data sets, a computational model predicting tumor progression and relapse was developed and validated. These results are of great translational significance. Conclusion A combination of experimental and mathematical modeling was able to generate meaningful data for the prediction of the clinical evolution of RCC.
dc.language.isoen
dc.publisherBioMed Central
dc.title.enExperimental and computational modeling for signature and biomarker discovery of renal cell carcinoma progression
dc.typeArticle de revue
dc.identifier.doi10.1186/s12943-021-01416-5
dc.subject.halInformatique [cs]/Bio-informatique [q-bio.QM]
bordeaux.journalMolecular Cancer
bordeaux.volume20
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue1
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-03390517
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03390517v1
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