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Harnessing preclinical models for the interrogation of ovarian cancer

Ovarian cancer (OC) is a heterogeneous malignancy with various etiology, histopathology, and biological feature. Despite accumulating understanding of OC in the post-genomic era, the preclinical knowledge still undergoes limited translation from bench to beside, and the prognosis of ovarian cancer h...

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Autores principales: Qin, Tianyu, Fan, Junpeng, Lu, Funian, Zhang, Li, Liu, Chen, Xiong, Qiyue, Zhao, Yang, Chen, Gang, Sun, Chaoyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9479310/
https://www.ncbi.nlm.nih.gov/pubmed/36114548
http://dx.doi.org/10.1186/s13046-022-02486-z
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author Qin, Tianyu
Fan, Junpeng
Lu, Funian
Zhang, Li
Liu, Chen
Xiong, Qiyue
Zhao, Yang
Chen, Gang
Sun, Chaoyang
author_facet Qin, Tianyu
Fan, Junpeng
Lu, Funian
Zhang, Li
Liu, Chen
Xiong, Qiyue
Zhao, Yang
Chen, Gang
Sun, Chaoyang
author_sort Qin, Tianyu
collection PubMed
description Ovarian cancer (OC) is a heterogeneous malignancy with various etiology, histopathology, and biological feature. Despite accumulating understanding of OC in the post-genomic era, the preclinical knowledge still undergoes limited translation from bench to beside, and the prognosis of ovarian cancer has remained dismal over the past 30 years. Henceforth, reliable preclinical model systems are warranted to bridge the gap between laboratory experiments and clinical practice. In this review, we discuss the status quo of ovarian cancer preclinical models which includes conventional cell line models, patient-derived xenografts (PDXs), patient-derived organoids (PDOs), patient-derived explants (PDEs), and genetically engineered mouse models (GEMMs). Each model has its own strengths and drawbacks. We focus on the potentials and challenges of using these valuable tools, either alone or in combination, to interrogate critical issues with OC.
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spelling pubmed-94793102022-09-17 Harnessing preclinical models for the interrogation of ovarian cancer Qin, Tianyu Fan, Junpeng Lu, Funian Zhang, Li Liu, Chen Xiong, Qiyue Zhao, Yang Chen, Gang Sun, Chaoyang J Exp Clin Cancer Res Review Ovarian cancer (OC) is a heterogeneous malignancy with various etiology, histopathology, and biological feature. Despite accumulating understanding of OC in the post-genomic era, the preclinical knowledge still undergoes limited translation from bench to beside, and the prognosis of ovarian cancer has remained dismal over the past 30 years. Henceforth, reliable preclinical model systems are warranted to bridge the gap between laboratory experiments and clinical practice. In this review, we discuss the status quo of ovarian cancer preclinical models which includes conventional cell line models, patient-derived xenografts (PDXs), patient-derived organoids (PDOs), patient-derived explants (PDEs), and genetically engineered mouse models (GEMMs). Each model has its own strengths and drawbacks. We focus on the potentials and challenges of using these valuable tools, either alone or in combination, to interrogate critical issues with OC. BioMed Central 2022-09-16 /pmc/articles/PMC9479310/ /pubmed/36114548 http://dx.doi.org/10.1186/s13046-022-02486-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Review
Qin, Tianyu
Fan, Junpeng
Lu, Funian
Zhang, Li
Liu, Chen
Xiong, Qiyue
Zhao, Yang
Chen, Gang
Sun, Chaoyang
Harnessing preclinical models for the interrogation of ovarian cancer
title Harnessing preclinical models for the interrogation of ovarian cancer
title_full Harnessing preclinical models for the interrogation of ovarian cancer
title_fullStr Harnessing preclinical models for the interrogation of ovarian cancer
title_full_unstemmed Harnessing preclinical models for the interrogation of ovarian cancer
title_short Harnessing preclinical models for the interrogation of ovarian cancer
title_sort harnessing preclinical models for the interrogation of ovarian cancer
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9479310/
https://www.ncbi.nlm.nih.gov/pubmed/36114548
http://dx.doi.org/10.1186/s13046-022-02486-z
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