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Current Status of Patient-Derived Ovarian Cancer Models

Department of Molecular Carcinogenesis, Chiba Cancer Center Research Institute, Chiba 260-8717, Japan
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Author to whom correspondence should be addressed.
Cells 2019, 8(5), 505; https://doi.org/10.3390/cells8050505
Received: 30 April 2019 / Revised: 17 May 2019 / Accepted: 23 May 2019 / Published: 25 May 2019
Ovarian cancer (OC) is one of the leading causes of female cancer death. Recent studies have documented its extensive variations as a disease entity, in terms of cell or tissue of origin, pre-cancerous lesions, common mutations, and therapeutic responses, leading to the notion that OC is a generic term referring to a whole range of different cancer subtypes. Despite such heterogeneity, OC treatment is stereotypic; aggressive surgery followed by conventional chemotherapy could result in chemo-resistant diseases. Whereas molecular-targeted therapies will become shortly available for a subset of OC, there still remain many patients without effective drugs, requiring development of groundbreaking therapeutic agents. In preclinical studies for drug discovery, cancer cell lines used to be the gold standard, but now this has declined due to frequent failure in predicting therapeutic responses in patients. In this regard, patient-derived cells and tumors are gaining more attention in precise and physiological modeling of in situ tumors, which could also pave the way to implementation of precision medicine. In this article, we comprehensively overviewed the current status of various platforms for patient-derived OC models. We highly appreciate the potentials of organoid culture in achieving high success rate and retaining tumor heterogeneity. View Full-Text
Keywords: ovarian cancer; patient-derived cells; organoid; spheroid; xenograft; pre-clinical model; precision medicine; drug discovery ovarian cancer; patient-derived cells; organoid; spheroid; xenograft; pre-clinical model; precision medicine; drug discovery
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Maru, Y.; Hippo, Y. Current Status of Patient-Derived Ovarian Cancer Models. Cells 2019, 8, 505.

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