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Title: | Developing Organoids from Ovarian Cancer as Experimental and Preclinical Models | Authors: | Maenhoudt, Nina Defraye, Charlotte Boretto, Matteo Jan, Ziga Heremans, Ruben Boeckx, Bram HERMANS, Florian ARIJS, Ingrid Cox, Benoit Van Nieuwenhuysen, Els Vergote, Ignace Van Rompuy, Anne-Sophie Lambrechts, Diether Timmerman, Dirk Vankelecom, Hugo |
Issue Date: | 2020 | Publisher: | CELL PRESS | Source: | Stem cell reports, 14 (4) , p. 717 -729 | Abstract: | Ovarian cancer (OC) represents the most dismal gynecological cancer. Pathobiology is poorly understood, mainly due to lack of appropriate study models. Organoids, defined as self-developing three-dimensional in vitro reconstructions of tissues, provide powerful tools to model human diseases. Here, we established organoid cultures from patient-derived OC, in particular from the most prevalent high-grade serous OC (HGSOC). Testing multiple culture medium components identified neuregulin-1 (NRG1) as key factor in maximizing OC organoid development and growth, although overall derivation efficiency remained moderate (36% for HGSOC patients, 44% for all patients together). Established organoid lines showed patient tumor-dependent morphology and disease characteristics, and recapitulated the parent tumor's marker expression and mutational landscape. Moreover, the organoids displayed tumor-specific sensitivity to clinical HGSOC chemotherapeutic drugs. Patient-derived OC organoids provide powerful tools for the study of the cancer's pathobiology (such as importance of the NRG1/ERBB pathway) as well as advanced preclinical tools for (personalized) drug screening and discovery. | Keywords: | Tumor-Suppressor;Serous Tumors;Expression;Disease;Survival;Cultures;Cells;Mutations;Biobank;Breast | Document URI: | http://hdl.handle.net/1942/31183 | ISSN: | 2213-6711 | e-ISSN: | 2213-6711 | DOI: | 10.1016/j.stemcr.2020.03.004 | ISI #: | WOS:000526941200017 | Rights: | This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2021 |
Appears in Collections: | Research publications |
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Maenhoudt_N_2020.pdf | Published version | 2.88 MB | Adobe PDF | View/Open |
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