Three-Dimensional Modelling of Ovarian Cancer: From Cell Lines to Organoids for Discovery and Personalized Medicine

Yee, C; Dickson, K-A; Muntasir, MN; Ma, Y; Marsh, DJ

Three-Dimensional Modelling of Ovarian Cancer: From Cell Lines to Organoids for Discovery and Personalized Medicine

Yee, C Dickson, K-A Muntasir, MN Ma, Y Marsh, DJ

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Publisher:: Frontiers Media SA
Publication Type:: Journal Article
Citation:: Frontiers in Bioengineering and Biotechnology, 2022, 10
Issue Date:: 2022-02-10

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Field	Value	Language
dc.contributor.author	Yee, C
dc.contributor.author	Dickson, K-A
dc.contributor.author	Muntasir, MN
dc.contributor.author	Ma, Y
dc.contributor.author	Marsh, DJ
dc.date.accessioned	2022-02-28T02:46:31Z
dc.date.available	2022-02-28T02:46:31Z
dc.date.issued	2022-02-10
dc.identifier.citation	Frontiers in Bioengineering and Biotechnology, 2022, 10
dc.identifier.issn	2296-4185
dc.identifier.issn	2296-4185
dc.identifier.uri	http://hdl.handle.net/10453/154913
dc.description.abstract	<jats:p>Ovarian cancer has the highest mortality of all of the gynecological malignancies. There are several distinct histotypes of this malignancy characterized by specific molecular events and clinical behavior. These histotypes have differing responses to platinum-based drugs that have been the mainstay of therapy for ovarian cancer for decades. For histotypes that initially respond to a chemotherapeutic regime of carboplatin and paclitaxel such as high-grade serous ovarian cancer, the development of chemoresistance is common and underpins incurable disease. Recent discoveries have led to the clinical use of PARP (poly ADP ribose polymerase) inhibitors for ovarian cancers defective in homologous recombination repair, as well as the anti-angiogenic bevacizumab. While predictive molecular testing involving identification of a genomic scar and/or the presence of germline or somatic <jats:italic>BRCA1</jats:italic> or <jats:italic>BRCA2</jats:italic> mutation are in clinical use to inform the likely success of a PARP inhibitor, no similar tests are available to identify women likely to respond to bevacizumab. Functional tests to predict patient response to any drug are, in fact, essentially absent from clinical care. New drugs are needed to treat ovarian cancer. In this review, we discuss applications to address the currently unmet need of developing physiologically relevant <jats:italic>in vitro</jats:italic> and <jats:italic>ex vivo</jats:italic> models of ovarian cancer for fundamental discovery science, and personalized medicine approaches. Traditional two-dimensional (2D) <jats:italic>in vitro</jats:italic> cell culture of ovarian cancer lacks critical cell-to-cell interactions afforded by culture in three-dimensions. Additionally, modelling interactions with the tumor microenvironment, including the surface of organs in the peritoneal cavity that support metastatic growth of ovarian cancer, will improve the power of these models. Being able to reliably grow primary tumoroid cultures of ovarian cancer will improve the ability to recapitulate tumor heterogeneity. Three-dimensional (3D) modelling systems, from cell lines to organoid or tumoroid cultures, represent enhanced starting points from which improved translational outcomes for women with ovarian cancer will emerge.</jats:p>
dc.language	en
dc.publisher	Frontiers Media SA
dc.relation	Medical Research Future FundAPP1199620
dc.relation	Cancer Institute NSW
dc.relation.ispartof	Frontiers in Bioengineering and Biotechnology
dc.relation.isbasedon	10.3389/fbioe.2022.836984
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0699 Other Biological Sciences, 0903 Biomedical Engineering, 1004 Medical Biotechnology
dc.title	Three-Dimensional Modelling of Ovarian Cancer: From Cell Lines to Organoids for Discovery and Personalized Medicine
dc.type	Journal Article
utslib.citation.volume	10
utslib.for	0699 Other Biological Sciences
utslib.for	0903 Biomedical Engineering
utslib.for	1004 Medical Biotechnology
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Centre for Health Technologies (CHT)
utslib.copyright.status	open_access	*
dc.date.updated	2022-02-28T02:46:30Z
pubs.publication-status	Published online
pubs.volume	10

Abstract:

Ovarian cancer has the highest mortality of all of the gynecological malignancies. There are several distinct histotypes of this malignancy characterized by specific molecular events and clinical behavior. These histotypes have differing responses to platinum-based drugs that have been the mainstay of therapy for ovarian cancer for decades. For histotypes that initially respond to a chemotherapeutic regime of carboplatin and paclitaxel such as high-grade serous ovarian cancer, the development of chemoresistance is common and underpins incurable disease. Recent discoveries have led to the clinical use of PARP (poly ADP ribose polymerase) inhibitors for ovarian cancers defective in homologous recombination repair, as well as the anti-angiogenic bevacizumab. While predictive molecular testing involving identification of a genomic scar and/or the presence of germline or somatic BRCA1 or BRCA2 mutation are in clinical use to inform the likely success of a PARP inhibitor, no similar tests are available to identify women likely to respond to bevacizumab. Functional tests to predict patient response to any drug are, in fact, essentially absent from clinical care. New drugs are needed to treat ovarian cancer. In this review, we discuss applications to address the currently unmet need of developing physiologically relevant in vitro and ex vivo models of ovarian cancer for fundamental discovery science, and personalized medicine approaches. Traditional two-dimensional (2D) in vitro cell culture of ovarian cancer lacks critical cell-to-cell interactions afforded by culture in three-dimensions. Additionally, modelling interactions with the tumor microenvironment, including the surface of organs in the peritoneal cavity that support metastatic growth of ovarian cancer, will improve the power of these models. Being able to reliably grow primary tumoroid cultures of ovarian cancer will improve the ability to recapitulate tumor heterogeneity. Three-dimensional (3D) modelling systems, from cell lines to organoid or tumoroid cultures, represent enhanced starting points from which improved translational outcomes for women with ovarian cancer will emerge.

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http://hdl.handle.net/10453/154913