Gotowa bibliografia na temat „Tumoroïdes”
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Artykuły w czasopismach na temat "Tumoroïdes"
Thorel, Lucie, Romane Florent, Marion Perréard, Audrey Vincent, Laurent Poulain i Louis-Bastien Weiswald. "Les tumoroïdes, modèles précliniques en plein essor pour l’oncologie". médecine/sciences 38, nr 11 (listopad 2022): 880–87. http://dx.doi.org/10.1051/medsci/2022148.
Pełny tekst źródłaPerréard, Marion, Romane Florent, Lucie Thorel, Audrey Vincent, Louis-Bastien Weiswald i Laurent Poulain. "Les organoïdes dérivés de tumeurs (ou tumoroïdes), des outils de choix pour la médecine de précision en oncologie". médecine/sciences 38, nr 11 (listopad 2022): 888–95. http://dx.doi.org/10.1051/medsci/2022149.
Pełny tekst źródłaHabanjar, O., A. C. Maurin, C. Vituret, C. Vachias, C. Decombat, M. Diab-Assaf, F. Caldefie-Chezet i L. Delort. "Obésité et progression tumorale : optimisation d’un modèle 3D de tumoroïdes bicellulaires fluorescents mimant le cancer canalaire in situ dans un microenvironnement adipeux et inflammatoire". Nutrition Clinique et Métabolisme 37, nr 2 (maj 2023): e76-e77. http://dx.doi.org/10.1016/j.nupar.2023.03.140.
Pełny tekst źródłaRozprawy doktorskie na temat "Tumoroïdes"
Tourbez, Arthur. "Développement et caractérisation d'organoïdes de tumeurs cérébrales pédiatriques utilisés en recherche fondamentale et translationnelle". Electronic Thesis or Diss., Lyon 1, 2023. https://n2t.net/ark:/47881/m6416x50.
Pełny tekst źródłaPediatric high-grade gliomas (pHGG) and posterior fossa type A ependymomas (EPN-PFA) remain one of the biggest challenges in pediatric oncology. They exhibit vast inter- and intra-tumoral heterogeneity, complicating the development of effective therapeutic strategies. Then to improve their clinical outcome, we absolutely need pre-clinical models that recapitulate key features of their corresponding parental tumors. During my PhD, I developed an optimized protocol for the establishment and biobanking of pHGG organoids (pHGG_O) and EPN-PFA organoids (EPN-PFA_O). These models can be grown long-term and comprehensive histological and molecular analyses showed that they recapitulate inter- and intra-tumoral heterogeneity of their parental tumor even after several passages and cryopreservation as 3D cultures. I further showed that they can be employed to test responses to standard of care therapy as well as new therapeutic options, including drugs from clinical trials as they accurately capture the clinical phenotypes of their respective parental tumors. Moreover, these models led to the identification of the DRD2 inhibitor ONC201 as an unexpected potential therapeutic agent for H3K27M non-altered pediatric brain tumors and helped identify combination strategies to increase the therapeutic response to ONC201. Thus, those models are positioned to support powerful and innovative preclinical studies, particularly those related to personalized assessments of treatment response profiles and identification of novel efficient drug combinations
Seitlinger, Joseph. "Optimisation d’un modèle d’organoïde de cancer du poumon vascularisé dérivé de patient à des fins de médecine de précision". Electronic Thesis or Diss., Strasbourg, 2022. http://www.theses.fr/2022STRAJ022.
Pełny tekst źródłaDespite numerous recent advances, lung cancer is the leading cause of cancer mortality worldwide. Every year, new therapeutic drugs are developed to fight this disease whose prognosis remains poor. The development of precision medicine should make it possible to improve its effectiveness. In this perspective, we have optimized an organoid model derived from lung cancer patients. In this work, we were able to show that our model is reproducible and that it mimics the patient's tumor. Finally, the formation of a vascular network at the level of the organoid is possible : it can infiltrate the formed organoid but can also grow from the organoid to infiltrate the microenvironment. The model that we put forward thus meets the specifications of a patient Avatar model. The tests of therapeutic drugs or irradiation that we are currently carrying out will allow us to define if this model is compatible with a future use in clinical practice to improve the management of patients diagnosed with lung cancer