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<\/span><\/p>\n ESR13<\/strong><\/p>\n Project Title<\/span>: Microfluidic bone chip to personalize the therapeutic regimen of bone metastatic tumours.<\/p>\n Objectives<\/span>: the aim of the project is to design a patient-specific bone tumor-on-chip model, based on cells isolated from patients. Presently, chemotherapeutic treatment of patients with bone tumors is based on standardized protocols, with consecutive cycles of different drugs, with unsatisfying success rates and many side effects. The possibility to customize the treatment for each patient, based on a predictive in vitro model of treatment efficacy, will greatly enhance patient quality of life. In the project, a bone tumor model will be generated, exploiting advanced biofabrication techniques, aiming at recreating a bone microenvironment with tailored matrix microarchitecture. Multiple human bone cell populations will be co-cultured in the matrix to recreate the bone microenvironment and bone tumor cells will be injected to mimic the tumor growth. Following model development and validation, different anti-tumor drugs and combinations will be tested in the chip platform and associated to genomic analyses, to better stratify the patients following known biomarkers for bone cancer.<\/p>\n Expected Results<\/span>: At the end of the project a personalized in vitro screening platform will be obtained. The developed chip will allow to estimate the efficacy of single drugs and drug combinations against bone tumor on patients\u2019 own cells, in view of a personalized therapeutic strategy. Furthermore, the association between drug efficacy and patient stratification will allow to indicate effective treatments for different classes of patients.<\/p>\n Host<\/span>: EOC<\/strong><\/p>\n Main Supervisor<\/span>: Matteo Moretti (EOC)<\/p>\n Duration<\/span>: 36 months<\/p>\n Planned Secondment<\/span>: IOG (2 months) and UNIBAS (2 months) the first year, to learn how to setup the model of tumor\/tumor on chip, in the third year he\/she will be at EIO (5M) to perform genetic analyses on patient cells.<\/p>\n