Personalized medicine in ovarian cancer: Design and development of a tool for re...
Personalized medicine in ovarian cancer: Design and development of a tool for response prediction to targeted platinated nanocarrier-based treatments
Personalized treatments are considered major challenges in clinical practice. They become particularly critical for diseases with poor prognoses diagnosed at later stages, such as ovarian cancer. Here, the vague symptoms, the lack...
Personalized treatments are considered major challenges in clinical practice. They become particularly critical for diseases with poor prognoses diagnosed at later stages, such as ovarian cancer. Here, the vague symptoms, the lack of reliable screening tools and the treatment resistances have made this cancer the most lethal gynaecological malignancy (40% 5-year survival rate; 50-90% recurrence rate). Thus, ovarian cancer patients would certainly benefit from improved therapies and appropriate treatment choices. In this regard, the present OvaCTool project aims at developing a highly sensitive mass cytometer-based tool for the prediction of treatment response against newly designed targeted nanocarriers for platinum (Pt)-based chemotherapy in ovarian cancer. Specifically, diverse iron-based nanocarriers for Pt (IV) prodrugs targeting ovarian cancer cells will be evaluated. Such assessment will also include the understanding of ovarian cancer proteome changes after therapy. All this information will then be integrated to define biomarkers of treatment response which will be combined in a mass cytometry panel (up to 50 markers) together with proteins to identify other cells from the tumour microenvironment aiming at the stratification of patients into responders vs non-responders to the newly designed drugs. Likewise, protein corona formation on the nanostructures will be investigated to recognize potential challenges after intravenous injection of the drug in the clinical setting. In summary, this project will provide potential enhanced anticancer drugs and a prediction tool for targeted treatment choices which will help towards better survival rates for this malignant disease.ver más
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