Descripción del proyecto
Recrear el ecosistema tumoral de un paciente con impresión 3D fomentará la precisión de los tratamientos
Uno de los problemas fundamentales de la experimentación en los sistemas modelo es la idoneidad de los mismos a la hora de recapitular enfermedades o trastornos humanos que tienen que ser evaluados. En el caso del cáncer, ha quedado claro que la interacción de las células tumorales con su mircoentorno es fundamental para el avance de la enfermedad, la metástasis y la respuesta a terapias. 3DCanPredict está desarrollando un sistema analítico novedoso empleando un modelo tumoral bioimprimido en 3D que aprovecha matrices de hidrogel y las células tumorales del propio paciente. El sistema, que posee vasos sanguíneos funcionales que pueden impregnarse con suero del paciente a través de una bomba, no solo imita el microentorno tumoral, sino que abre la puerta a la medicina oncológica personalizada.
Objetivo
Predicting clinical response to novel and existing anticancer drugs remains a major hurdle for successful cancer treatment. Studies indicate that the tumor ecosystem, resembling an organ-like structure, can limit the predictive power of current therapies that were evaluated solely on tumor cells. The interactions of tumor cells with their adjacent microenvironment are required to promote tumor progression and metastasis, determining drug responsiveness. Such interactions do not form in standard research techniques, where cancer cells grow on 2D plastic dishes. Hence, there is a need to develop new cancer models that better mimic the physio-pathological conditions of tumors. Here, we create 3D-bioprinted tumor models based on a library of hydrogels we developed as scaffold for different tumor types, designed according to the mechanical properties of the tissue of origin. As PoC, we bioprinted a vascularized 3D brain tumor model from brain tumor cells co-cultured with stromal cells and mixed with our hydrogels, that resemble the biophysics of the tumor and its microenvironment. Our patient-derived models consist of cells from a biopsy, constructed according to CT/MRI scans, and include functional vessels allowing for patients' serum to flow when connected to a pump. These models will facilitate reproducible, reliable and rapid results, determining which treatment suits best the specific patient's tumor. Taken together, this 3D-printed model could be the basis for potentially replacing cell and animal models. We predict that this powerful platform will be used in translational research for preclinical evaluation of new therapies and for clinical drug screening, which will save critical time, reduce toxicity and significantly decrease costs generating a major societal benefit. Our platform offers a highly attractive business case, as pharmaceutical and biotech companies heavily invest in preclinical predictive tools for novel personalized drug screening strategies.
Ámbito científico
CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural.
CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural.
Programa(s)
Régimen de financiación
ERC-POC-LS - ERC Proof of Concept Lump Sum PilotInstitución de acogida
69978 Tel Aviv
Israel