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Computational Modelling of Metastasis Development in Renal Cell Carcinoma

hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorBARATCHART, Etienne
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorBENZEKRY, Sébastien
hal.structure.identifierLaboratoire Angiogenèse et Micro-environnement des Cancers [LAMC]
dc.contributor.authorBIKFALVI, Andreas
hal.structure.identifierUniversité de Bordeaux [UB]
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorCOLIN, Thierry
hal.structure.identifierLaboratoire Angiogenèse et Micro-environnement des Cancers [LAMC]
dc.contributor.authorCOOLEY, Lindsay S.
hal.structure.identifierLaboratoire Angiogenèse et Micro-environnement des Cancers [LAMC]
dc.contributor.authorPINEAU, Raphäel
hal.structure.identifierCentre de résonance magnétique des systèmes biologiques [CRMSB]
dc.contributor.authorRIBOT, Emeline J
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorSAUT, Olivier
hal.structure.identifierLaboratoire Angiogenèse et Micro-environnement des Cancers [LAMC]
dc.contributor.authorSOULEYREAU, Wilfried
dc.date.accessioned2024-04-04T03:16:55Z
dc.date.available2024-04-04T03:16:55Z
dc.date.created2015-06-17
dc.date.issued2015-11
dc.identifier.issn1553-734X
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/194260
dc.description.abstractEnTo improve our understanding of the biology of the metastatic colonization process, weconducted a modelling study based on multi-modal data from an orthotopic murine experimentalsystem of metastatic renal cell carcinoma. The standard theory of metastatic colonization usuallyassumes that secondary tumours, once established at a distant site, grow independently from eachother and from the primary tumour. Using a mathematical model describing the metastaticpopulation dynamics under this assumption, we challenged the theory against our data thatincluded: 1) dynamics of primary tumour cells in the kidney and metastatic cells in the lungs,retrieved by green fluorescent protein tracking, and 2) magnetic resonance images (MRI) informingon the number and size of macroscopic lesions. While the model could fit the primary tumour andtotal metastatic burden, the predicted size distribution was not in agreement with the MRIobservations. Moreover, the model was incompatible with the growth rates of individual metastatictumours.To explain the observed metastatic patterns, we hypothesised that metastatic foci derivedfrom one or a few cells could aggregate, resulting in a similar total mass but a smaller number ofmetastases. This was indeed observed in our data and led us to investigate the effect of spatialinteractions on the dynamics of the global metastatic burden. We derived a novel mathematicalmodel for spatial tumour growth, where the intra-tumour increase in pressure is responsible for theslowdown of the growth rate. The model could fit the growth of lung metastasis visualized bymagnetic resonance imaging. As a non-trivial outcome from this analysis, the model predicted thatthe net growth of two neighbouring tumour lesions that enter in contact is considerably impaired (of31% ± 1.5%, mean ± standard deviation), as compared to the growth of two independent tumours.Together, our results have implications for theories of metastatic development and suggest thatglobal dynamics of metastasis development is dependent on spatial interactions between metastaticlesions.
dc.description.sponsorshipTranslational Research and Advanced Imaging Laboratory - ANR-10-LABX-0057
dc.language.isoen
dc.publisherPublic Library of Science
dc.subject.enRenal cell carcinoma
dc.subject.encancer modelling
dc.subject.enmetastasis
dc.title.enComputational Modelling of Metastasis Development in Renal Cell Carcinoma
dc.typeArticle de revue
dc.identifier.doi10.1371/journal.pcbi.1004626
dc.subject.halSciences du Vivant [q-bio]/Cancer
dc.subject.halSciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
bordeaux.journalPLoS Computational Biology
bordeaux.volume11
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue11
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01164834
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01164834v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=PLoS%20Computational%20Biology&rft.date=2015-11&rft.volume=11&rft.issue=11&rft.eissn=1553-734X&rft.issn=1553-734X&rft.au=BARATCHART,%20Etienne&BENZEKRY,%20S%C3%A9bastien&BIKFALVI,%20Andreas&COLIN,%20Thierry&COOLEY,%20Lindsay%20S.&rft.genre=article


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