Project description
Targeting pre-existing subpopulations of drug-resistant ovarian cancer cells
Ovarian cancer is the fifth most deadly cancer type in Europe. Standard chemotherapy is effective in eliminating tumour masses, but most patients diagnosed with advanced ovarian cancer die after new lesions emerge from small subpopulations of surviving drug-resistant cells. The EU-funded RESIST3D project is developing new directions in precision cancer medicine by targeting small pre-existing subpopulations of drug-resistant cells instead of the bulk of the tumour. The research utilises 3D patient-derived ovarian cancer organoids to search for new strategies to eradicate drug-resistant cancer cells. The models for drug response profiling will assist in the identification of treatment that eradicates pre-existing drug-resistant cells to be applied in combination with standard chemotherapy.
Objective
Ovarian cancer is the fifth most deadly cancer type among women in Europe. Despite the fact that standard chemotherapy is usually effective in eliminating bulk tumour mass, thereby inducing remission, most patients diagnosed with advanced ovarian cancer die from the disease, as relapsed lesions emerge from small subpopulations of surviving drug-resistant cells.
Precision medicine aims to improve cancer care through tailoring individualized therapies based on genomic or functional profiling of human cancers. However, as these approaches are usually performed on bulk tumour cells, the small pre-existing drug-resistant cell subpopulations remain untargeted.
In the RESIST3D project, I will utilize ovarian cancer organoids – a patient-derived, three-dimensional cell cultures – to search for new strategies to eradicate drug-resistant cancer cells. I will use two organoid models developed for the same patient – one model derived from tumour material taken before chemotherapeutic treatment and one from a post-treatment sample, typically enriched in drug-resistant cells. I will further enrich the organoids in quiescent, drug-resistant cells by maintaining them in physiologic-like culture medium. I will then apply the models for drug-response profiling in order to identify agents that eradicate pre-existing drug-resistant cells, which could be combined with standard chemotherapy. Finally, I will assess whether the selected combinations prevent relapses in patient-derived xenograft mouse models.
RESIST3D sets a new direction in precision cancer medicine, as it focuses on targeting small pre-existing subpopulations of drug-resistant cells rather than bulk tumour mass. Through combining organoid model, paired samples for each patient and physiologic culture conditions, I expect to identify new ways to target drug-resistant ovarian cancer cells. Moreover, RESIST3D will provide me with new research expertise and a scientific network that will enhance my research career.
Fields of science
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Keywords
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
1165 Kobenhavn
Denmark