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Targeting drug resistance in ovarian cancer through large-scale drug-response profiling in physiologically relevant cancer organoids

Total Cost €


EC-Contrib. €






Project "RESIST3D" data sheet

The following table provides information about the project.


Organization address
address: NORREGADE 10
postcode: 1165

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Denmark [DK]
 Total cost 207˙312 €
 EC max contribution 207˙312 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2020
 Duration (year-month-day) from 2020-09-01   to  2022-08-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KOBENHAVNS UNIVERSITET DK (KOBENHAVN) coordinator 207˙312.00


 Project 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.

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The information about "RESIST3D" are provided by the European Opendata Portal: CORDIS opendata.

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