H2020Индивидуална стипендия2020–2022

RESIST3D · Targeting drug resistance in ovarian cancer through large-scale drug-response profiling in physiologically relevant cancer organoids

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период
2020-09-01 → 2022-08-31
Финансиране от ЕС
207 312 €
Участници
1
Схема
MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Ракът на яйчниците се изследва чрез 3D модели (органоиди), за да се открият малки групи клетки, които устояват на лекарствата. Това помага за създаването на индивидуално лечение, което да се справи с повторното проявяване на болестта.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

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

Ovarian cancer is the fifth leading cause of cancer death among women in Europe. Despite the fact that standard chemotherapeutic agents, used as a first-line therapy, are very effective in eliminating a vast majority of bulk ovarian cancer cells thereby inducing remission, 80% of women diagnosed with stage III or IV ovarian cancer later die due to relapse of the disease. In recent years, it has been shown that the relapsed cancer lesions emerge from relatively small subpopulations of surviving cells that exhibit drug resistance, likely driven by both genetic and non-genetic mechanisms. Tailoring individualized therapeutic approaches for each patient (i.e. precision cancer medicine) has recently gained substantial attention as a way to improve cancer care. It is usually applied either by therapeutically targeting specific genetic mutations identified in cancers or by performing functional drug response profiling by exposing cancer cells derived directly from patients to a panel of cancer drugs and, based on the drug responses, informing therapeutic decisions in the clinic. However, as both genomic and functional precision medicine analyses are typically performed on bulk tumour mass, neither of these approaches address the challenge in ovarian cancer therapy (as well as many other types of cancers) where small drug-resistant cell subpopulations are responsible for relapses. Thus, there is a need for a method that would enable both identification of pre-existing drug-resistant cancer cell subpopulations and evaluation of therapies that could be used to target these subpopulations. Organoids – patient-derived, stem cell-driven three-dimensional (3D) cell cultures – have been described as in vitro models that reproduce cellular heterogeneity, cell subpopulation representation and drug resistance of original tumours more closely than standard cell cultures. Organoids from several cancer types (e.g. colon, pancreas or prostate) have been recently applied for in vitro profiling of drug responses. So far, however, no large-scale endeavour utilizing ovarian cancer organoids derived directly from patient samples has been reported. Moreover, using non-physiologic growth-promoting culture media (e.g. abundant in glucose, growth factors and with non- physiological pH) in culture of cancer organoids has recently been questioned, as they can result in exaggerated cell growth rates, distorted cellular phenotypes and, likely, non-physiologic drug responses. Furthermore, drug responses of cells in commonly used in vitro culture conditions often do not reflect drug responses in vivo. Therefore, we hypothesized that by culturing ovarian cancer organoids in physiologic-like in vitro conditions, we would enrich the models in drug-resistant cell subpopulations and enable identification of compounds targeting drug-resistant cancer cells through drug-response profiling. The project aimed to address following objectives: • Objective 1: Apply an ovarian cancer organoid model, cultured in physiologic medium and enriched in drug-resistant cells, for large-scale drug response profiling • Objective 2: Validate the most effective screening hits in patient-derived mouse xenografts (PDX)

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

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.

Оригинален текст от CORDIS (на английски).

Участници

  • KOBENHAVNS UNIVERSITET · KOBENHAVNКоординаторДания

Връзки

Данни: CORDIS, © Европейски съюз