Name: ovarian cancer patient-derived organoid models for pre-clinical drug testing
Uploaded: 2023-09-15T15:00:00
Description: Watch this Scientific Journal Video about Ovarian Cancer Patient-Derived Organoid Models for Pre-Clinical Drug Testing at JoVE.com

Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA243511. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors thank Deborah Frank for her editorial comments.

The collection of human specimens for this research was approved by the Washington University School of Medicine Institutional Review Board. All eligible patients over the age of 18 years had a diagnosis or presumed diagnosis of high-grade serous ovarian cancer and were willing and able to provide informed consent. The tumor tissue from either primary or metastatic sites, in addition to ascites and pleural fluid, were obtained from consented patients at the time of care.
1. Selection of ...

<ol>
	<li>Matulonis, U. A., Sood, A. K., Fallowfield, L., Howitt, B. E., Sehouli, J. m., Karlan, B. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ovarian+cancer.">Ovarian cancer.</a> Nature Reviews Disease Primers. 2 (1), 16061 (2016).</li><li>Siegel, R. L., Miller, K. D., Jemal, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cancer+statistics,+2019.">Cancer statistics, 2019.</a> CA: A Cancer Journal for Clinicians. 69 (1), 7-34 (2019).</li><li>Christie, E. L., Bowtell, D. D. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acquired+chemotherapy+resistance+in+ovarian+cancer.">Acquired chemotherapy resistance in ovarian cancer.</a> Annals of Oncology. 28 (suppl_8), viii13-viii15 (2017).</li><li>Wang, L., Wang, Q., Xu, Y., Cui, M., Han, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+the+treatment+of+ovarian+cancer+using+PARP+inhibitors+and+the+underlying+mechanism+of+resistance.">Advances in the treatment of ovarian cancer using PARP inhibitors and the underlying mechanism of resistance.</a> Current Drug Targets. 21 (2), 167-178 (2020).</li><li>Wang, Q., Peng, H., Qi, X., Wu, M., Zhao, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeted+therapies+in+gynecological+cancers:+a+comprehensive+review+of+clinical+evidence.">Targeted therapies in gynecological cancers: a comprehensive review of clinical evidence.</a> Signal Transduction and Targeted Therapy. 5 (1), 137 (2020).</li><li>Hofer, M., Lutolf, M. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Engineering+organoids.">Engineering organoids.</a> Nature Reviews Materials. 6 (5), 402-420 (2021).</li><li>Lancaster, M. A., Knoblich, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Organogenesis+in+a+dish:+Modeling+development+and+disease+using+organoid+technologies.">Organogenesis in a dish: Modeling development and disease using organoid technologies.</a> Science. 345 (6194), 1247125 (2014).</li><li>Sato, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Long-term+expansion+of+epithelial+organoids+from+human+colon,+adenoma,+adenocarcinoma,+and+barrett's+epithelium.">Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and barrett's epithelium.</a> Gastroenterology. 141 (5), 1762-1772 (2011).</li><li>Sato, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single+Lgr5+stem+cells+build+crypt-villus+structures+in+vitro+without+a+mesenchymal+niche.">Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche.</a> Nature. 459 (7244), 262-265 (2009).</li><li>Spence, J. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Directed+differentiation+of+human+pluripotent+stem+cells+into+intestinal+tissue+in+vitro.">Directed differentiation of human pluripotent stem cells into intestinal tissue in vitro.</a> Nature. 470 (7332), 105-109 (2011).</li><li>Schutgens, F., Clevers, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Human+organoids:+Tools+for+understanding+biology+and+treating+diseases.">Human organoids: Tools for understanding biology and treating diseases.</a> Annual Review of Pathology: Mechanisms of Disease. 15 (1), 211-234 (2020).</li><li>Zhao, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Organoids.">Organoids.</a> Nature Reviews Methods Primers. 2 (1), 94 (2022).</li><li>Barker, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lgr5(+ve)+stem+cells+drive+self-renewal+in+the+stomach+and+build+long-lived+gastric+units+in+vitro.">Lgr5(+ve) stem cells drive self-renewal in the stomach and build long-lived gastric units in vitro.</a> Cell Stem Cell. 6 (1), 25-36 (2010).</li><li>Corr&#242;, C., Novellasdemunt, L., Li, V. S. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+brief+history+of+organoids.">A brief history of organoids.</a> American Journal of Physiology-Cell Physiology. 319 (1), C151-C165 (2020).</li><li>Kim, J., Koo, B. K., Knoblich, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Human+organoids:+model+systems+for+human+biology+and+medicine.">Human organoids: model systems for human biology and medicine.</a> Nature Reviews Molecular Cell Biology. 21 (10), 571-584 (2020).</li><li>Simian, M., Bissell, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Organoids:+A+historical+perspective+of+thinking+in+three+dimensions.">Organoids: A historical perspective of thinking in three dimensions.</a> Journal of Cell Biology. 216 (1), 31-40 (2017).</li><li>Graham, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Generation+and+culturing+of+high-grade+serous+ovarian+cancer+patient-derived+organoids.">Generation and culturing of high-grade serous ovarian cancer patient-derived organoids.</a> Journal of Visualized Experiments. 191, e64878 (2023).</li><li>Liu, C., Qin, T., Huang, Y., Li, Y., Chen, G., Sun, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Drug+screening+model+meets+cancer+organoid+technology.">Drug screening model meets cancer organoid technology.</a> Translational Oncology. 13 (11), 100840 (2020).</li><li>Driehuis, E., Kretzschmar, K., Clevers, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Establishment+of+patient-derived+cancer+organoids+for+drug-screening+applications.">Establishment of patient-derived cancer organoids for drug-screening applications.</a> Nature Protocols. 15 (10), 3380-3409 (2020).</li><li>Zhou, Z., Cong, L., Cong, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Patient-derived+organoids+in+precision+medicine:+drug+screening,+organoid-on-a-chip+and+living+organoid+biobank.">Patient-derived organoids in precision medicine: drug screening, organoid-on-a-chip and living organoid biobank.</a> Frontiers in Oncology. 11, 762184 (2021).</li><li>Costa, E. C., Moreira, A. F., de Melo-Diogo, D., Gaspar, V. M., Carvalho, M. P., Correia, I. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+tumor+spheroids:+an+overview+on+the+tools+and+techniques+used+for+their+analysis.">3D tumor spheroids: an overview on the tools and techniques used for their analysis.</a> Biotechnology Advances. 34 (8), 1427-1441 (2016).</li><li>Foo, M. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clinical+translation+of+patient-derived+tumour+organoids-+bottlenecks+and+strategies.">Clinical translation of patient-derived tumour organoids- bottlenecks and strategies.</a> Biomarker Research. 10 (1), 10 (2022).</li><li>Kapa&#322;czy&#324;ska, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=2D+and+3D+cell+cultures+-+a+comparison+of+different+types+of+cancer+cell+cultures.">2D and 3D cell cultures - a comparison of different types of cancer cell cultures.</a> Archives of Medical Science. 14 (4), 910-919 (2018).</li><li>Bergdorf, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+drug+screening+of+fine-needle+aspiration-derived+cancer+organoids.">High-throughput drug screening of fine-needle aspiration-derived cancer organoids.</a> STAR Protocols. 1 (3), 100212 (2020).</li><li>Phan, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+simple+high-throughput+approach+identifies+actionable+drug+sensitivities+in+patient-derived+tumor+organoids.">A simple high-throughput approach identifies actionable drug sensitivities in patient-derived tumor organoids.</a> Communications Biology. 2 (1), 78 (2019).</li><li>Putker, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Medium-throughput+drug-+and+radiotherapy+screening+assay+using+patient-derived+organoids.">Medium-throughput drug- and radiotherapy screening assay using patient-derived organoids.</a> Journal of Visualized Experiments. 170, e62495 (2021).</li><li>Dahlin, J. L., Inglese, J., Walters, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mitigating+risk+in+academic+preclinical+drug+discovery.">Mitigating risk in academic preclinical drug discovery.</a> Nature Reviews Drug Discovery. 14 (4), 279-294 (2015).</li><li>Honkala, A., Malhotra, S. V., Kummar, S., Junttila, M. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Harnessing+the+predictive+power+of+preclinical+models+for+oncology+drug+development.">Harnessing the predictive power of preclinical models for oncology drug development.</a> Nature Reviews Drug Discovery. 21 (2), 99-114 (2022).</li><li>de Witte, C. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Patient-derived+ovarian+cancer+organoids+mimic+clinical+response+and+exhibit+heterogeneous+inter-+and+intrapatient+drug+responses.">Patient-derived ovarian cancer organoids mimic clinical response and exhibit heterogeneous inter- and intrapatient drug responses.</a> Cell Reports. 31 (11), 107762 (2020).</li><li>Hill, S. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prediction+of+DNA+repair+inhibitor+response+in+short-term+patient-derived+ovarian+cancer+organoids.">Prediction of DNA repair inhibitor response in short-term patient-derived ovarian cancer organoids.</a> Cancer Discovery. 8 (11), 1404-1421 (2018).</li><li>Kopper, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+organoid+platform+for+ovarian+cancer+captures+intra-+and+interpatient+heterogeneity.">An organoid platform for ovarian cancer captures intra- and interpatient heterogeneity.</a> Nature Medicine. 25 (5), 838-849 (2019).</li><li>Maenhoudt, N., Vankelecom, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protocol+for+establishing+organoids+from+human+ovarian+cancer+biopsies.">Protocol for establishing organoids from human ovarian cancer biopsies.</a> STAR Protocols. 2 (2), 100429 (2021).</li><li>Nanki, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Patient-derived+ovarian+cancer+organoids+capture+the+genomic+profiles+of+primary+tumours+applicable+for+drug+sensitivity+and+resistance+testing.">Patient-derived ovarian cancer organoids capture the genomic profiles of primary tumours applicable for drug sensitivity and resistance testing.</a> Scientific Reports. 10 (1), 12581 (2020).</li><li>Hafner, M., Niepel, M., Chung, M., Sorger, P. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth+rate+inhibition+metrics+correct+for+confounders+in+measuring+sensitivity+to+cancer+drugs.">Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs.</a> Nat Methods. 13 (6), 521-527 (2016).</li><li>Clark, N. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=GRcalculator:+an+online+tool+for+calculating+and+mining+dose-response+data.">GRcalculator: an online tool for calculating and mining dose-response data.</a> BMC Cancer. 17 (1), 698 (2017).</li><li>Senkowski, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+platform+for+efficient+establishment+and+drug-response+profiling+of+high-grade+serous+ovarian+cancer+organoids.">A platform for efficient establishment and drug-response profiling of high-grade serous ovarian cancer organoids.</a> Developmental Cell. 58 (12), 1106.e7-1121.e7 (2023).</li></ol>

This article describes a method that can be used to assess the therapeutic effects of conventional or novel drugs on ovarian cancer PDOs. Researchers must consider several issues before conducting the viability assay in the PDO model.
First, when selecting a PDO to use in the viability assay, one must determine the ideal organoid type (tumor vs. ascites) and passage number for their needs. In our experience, ascites-derived PDOs grow more rapidly and are easier to generate than tumor-...

Although rare, ovarian cancer is one of the most lethal gynecological cancers1,2. A challenge in developing new treatments is that ovarian cancer is heterogeneous, and the tumor microenvironment differs greatly among patients. Additionally, many ovarian cancers develop resistance to platinum-based chemotherapy and poly (ADP-ribose) polymerase inhibitors, highlighting the need for greater therapeutic options3,4,5.
One approach that may be useful in identifying new therapeutics is using patient-derived organoids (PDOs). Organoids are three-dimensional clusters of multiple cell types that self-organize and form in vitro&#160;&#34;mini-organs&#34;6,7,8,9,10. Organoids can recapitulate important tissue morphology and gene expression profiles11,12. Some of the first organoids were derived from intestinal, gastric, and colon cancer cells from both mice and humans8,9,13. Long-lived organoid cultures have been established from a wide range of benign and malignant tissues, including the bladder, colon, stomach, pancreas, brain, retina, and liver14,15,16. We previously demonstrated methods to establish PDOs from ovarian cancer tumors and ascites samples17. PDOs can be used to study molecular characteristics, cellular mechanisms, and novel drug treatments18,19,20. PDOs have several advantages over traditional two-dimensional primary cell cultures for drug screening. Although primary two-dimensional cultures are a low-cost method for drug screens, primary cell cultures are single-cell types and lack the three-dimensional architecture of tumors21,22,23. Nevertheless, PDOs are a precious resource, and cost-effective protocols are needed to optimize their use in therapeutic drug screening.
This article describes an in vitro method to use ovarian cancer PDOs to test the effects of known or candidate drugs. Whereas current medium- and high-throughput drug screens using PDOs require expensive automated dispensing instruments24,25,26, this cost-effective method uses readily available basic lab supplies and an ATP-based cell viability assay in a standard 96-well plate format (Figure 1A). This method will facilitate preliminary tests of novel ovarian cancer drugs prior to scaling up to larger screens27,28. Although ovarian cancer PDOs are used here, this method can be applied to other cancer organoid models.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1.5 mL Plastic Tubes</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL Plastic Tubes</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>96 well Flat Black Plates</td>
			<td>MidSci</td>
			<td>781968</td>
			<td></td>
		</tr>
		<tr>
			<td>Advance Organoid Media&#160;</td>
			<td></td>
			<td></td>
			<td>see Graham et al 2022 (Jove)</td>
		</tr>
		<tr>
			<td>Advanced DMEM/F12</td>
			<td>Thermo Fisher</td>
			<td>12634028</td>
			<td></td>
		</tr>
		<tr>
			<td>Automated Cell Counter</td>
			<td>Thermo Fisher</td>
			<td>AMQAX1000</td>
			<td></td>
		</tr>
		<tr>
			<td>Brightfield Microscope</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Carboplatin&#160;</td>
			<td>Teva&#160;Pharmaceuticals&#160;USA</td>
			<td>NDC&#160;00703-4246-01</td>
			<td></td>
		</tr>
		<tr>
			<td>CellTiter-Glo 3D Viability&#160;</td>
			<td>Promega</td>
			<td>G9681</td>
			<td></td>
		</tr>
		<tr>
			<td>Cultrex</td>
			<td>R &#38; D Systems</td>
			<td>3533-010-02</td>
			<td></td>
		</tr>
		<tr>
			<td>DMSO</td>
			<td>Sigma Aldrich</td>
			<td>D2650-100ML</td>
			<td></td>
		</tr>
		<tr>
			<td>Glutamax</td>
			<td>Life Technologies</td>
			<td>35050061</td>
			<td></td>
		</tr>
		<tr>
			<td>GR Calculator&#160;</td>
			<td>http://www.grcalculator.org</td>
			<td></td>
			<td>Online calculator</td>
		</tr>
		<tr>
			<td>GraphPad Prism</td>
			<td>GraphPad Software, Inc.</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>Life Technologies</td>
			<td>15630080</td>
			<td></td>
		</tr>
		<tr>
			<td>Matrigel</td>
			<td>Corning</td>
			<td>354230</td>
			<td></td>
		</tr>
		<tr>
			<td>Microsoft Excel</td>
			<td>Microsoft</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Penicillin-Streptomycin</td>
			<td>Thermo Fisher</td>
			<td>15140122</td>
			<td></td>
		</tr>
		<tr>
			<td>Plate Rocker</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sterile P10, P200, and P1000 Barrier Sterile Pipette Tips</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Sterile P10, P200, and P1000 Pipettes</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Tecan Infinte 200Pro Plate Reader; i-Control Software</td>
			<td>Tecan</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>TrypLE</td>
			<td>Thermo Fisher</td>
			<td>12605010</td>
			<td>Organoid dissociation reagent</td>
		</tr>
	</tbody>
</table>

ovarian cancer patient-derived organoid models for pre-clinical drug testing

Ovarian cancer is a fatal gynecologic cancer and the fifth leading cause of cancer death among women in the United States. Developing new drug treatments is crucial to advancing healthcare and improving patient outcomes. Organoids are in-vitro three-dimensional multicellular miniature organs. Patient-derived organoid (PDO) models of ovarian cancer may be optimal for drug screening because they more accurately recapitulate tissues of interest than two-dimensional cell culture models and are inexpensive compared to patient-derived xenografts. In addition, ovarian cancer PDOs mimic the variable tumor microenvironment and genetic background typically observed in ovarian cancer. Here, a method is described that can be used to test conventional and novel drugs on PDOs derived from ovarian cancer tissue and ascites. A luminescence-based adenosine triphosphate (ATP) assay is used to measure viability, growth rate, and drug sensitivity. Drug screens in PDOs can be completed in 7-10 days, depending on the rate of organoid formation and drug treatments.

These results illustrate the response of two PDOs to the chemotherapy drug carboplatin, which is used to treat ovarian cancer. Organoids were derived from tumor biopsy (PDO #1) and from ascites (PDO #2). These organoids were selected based on their perceived doubling time (1-2 days) and morphological appearance (formation of many large organoids). Both PDO #1 and PDO #2 were plated on Day -2, at passage two, and carboplatin was added on Day 0. We tested the following carboplatin concentrations diluted in Advance Organoid...

Watch this Scientific Journal Video about Ovarian Cancer Patient-Derived Organoid Models for Pre-Clinical Drug Testing at JoVE.com

Ovarian Cancer Patient-Derived Organoid Models for Pre-Clinical Drug Testing

We present a protocol that can be used to conduct therapeutic drug testing with patient-derived ovarian cancer organoids.

Ovarian cancer is a fatal gynecologic cancer and the fifth leading cause of cancer death among women in the United States. Developing new drug treatments ...

This protocol describes a low cost method for performing drug viability assays using patient-derived ovarian cancer organoids. The main advantages of this technique are the use of low cost and readily available materials and lab equipment. This method can be used before undertaking expensive high-throughput drug screens.Although the method deals with performing drug viability assays in patient-derived ovarian cancer organoids, it can be applied to any organoid system, including those that are murine derived. To begin, observe the basement membrane extract or BME containing organoids under a brightfield microscope to ensure 70 to 90%confluency. Using a pipette, add one to two milliliters of prewarmed base media to the well containing the organoids and mechanically dissociate the organoids by pipetting them up and down.Transfer the entire organoid suspension to a 15-milliliter conical tube and vortex the tube for five to 10 seconds to further disaggregate the cells. Then, centrifuge the cells at 1, 107 G for five minutes at room temperature. Using a single-channel pipette, aspirate and discard the supernatant.Resuspend the pellet in one milliliter of organoid dissociation reagent prewarmed to 37 degrees Celsius, and transfer the suspension to a 1.5-milliliter micro centrifuge tube. Incubate the sample for seven minutes at 37 degrees Celsius. Then centrifuge the result in cell suspension at 1, 107 G for five minutes at room temperature.After discarding the supernatant, resuspend the cell pellet in one milliliter of prewarmed base media. Reconstitute the cells in a mix of base media and BME, maintaining a final concentration of 20, 000 cells per 10 microliters. Plate one three-microliter droplet of the resuspended cells per well of a black opaque 96 well plate.Incubate the plate in a cell culture incubator at 37 degrees Celsius for 15 minutes. Finally, add 100 microliters of prewarmed advanced organoid media to each well before incubating the plate at 37 degrees Celsius for 24 to 72 hours. Perform drug treatment of the organoids two days after plating them.Perform viability assay on the organoids seven days after drug treatment. Add 100 microliters of viability assay reagent to each well, bringing the total volume to 200 microliters, and shake the plate at 80 RPM for five minutes. Then allow the plate to incubate at room temperature for an additional 25 minutes.Meanwhile, switch on the bioluminescence plate reader and open the eye control software. Navigate to connect to instrument"and select Infinite 200Pro"Select luminescence"and default script"Next from the dropdown menu, choose BD 96 FB Falcon BD Falcon 96 Flat Black"as the plate type to set the luminescence parameters. Assign attenuation as none.Integration time as 1000 milliseconds and settle time as zero milliseconds. Finally, uncover the plate, load it onto the plate reader, and press start"to begin. Brightfield images were acquired for the two different patient-derived organoids, or PDOs, used in the protocol.PDO one, derived from a tumor biopsy and PDO two derived from ascites. Results of the viability assay revealed the percentage of live cells in PDO one and PDO two after both were treated with varying concentrations of carboplatin. The calculated growth rate, or GR values, were plotted against the corresponding carboplatin concentrations, and the GR metrics revealed that the GR50 value for PDO one was much higher than that for PDO two.This indicated that PDO one was more resistant to platinum chemotherapy While plating, it is crucial that the three-microliter droplet of the cell suspension is placed directly in the center of the well. If the droplet is placed to close to the edge of the well, it may cause the droplet to collapse, affecting the assay results.

Research

JoVE Journal

Cancer Research

Physiologic Patient Derived 3D Spheroids for Anti-neoplastic Drug Screening to Target Cancer Stem Cells

In this protocol, we outline the procedure for generation of tumor spheroids within 384-well hanging droplets to allow for high-throughput screening of ...

Establishment of Gastric Cancer Patient-derived Xenograft Models and Primary Cell Lines

The use of preclinical models to advance our understanding of tumor biology and investigate the efficacy of therapeutic agents is key to cancer research. ...

Isolation and Characterization of Patient-derived Pancreatic Ductal Adenocarcinoma Organoid Models

Pancreatic ductal adenocarcinoma (PDAC) is amongst the most lethal malignancies. Recently, next-generation organoid culture methods enabling the ...

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts

We present here an integrative approach for testing efficacy of targeted therapies that combines the next generation sequencing technolo-gies, therapeutic ...

Drug Screening of Primary Patient Derived Tumor Xenografts in Zebrafish

Patient derived xenograft models are critical in defining how different cancers respond to drug treatment in an in vivo system. Mouse models are the ...

Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients

An understanding of drug resistance and the development of novel strategies to sensitize highly resistant cancers rely on the availability of suitable ...

Generation and Culturing of High-Grade Serous Ovarian Cancer Patient-Derived Organoids

Organoids are 3D dynamic tumor models that can be grown successfully from patient-derived ovarian tumor tissue, ascites, or pleural fluid and aid in the ...

Visualizing DNA Damage Repair Proteins in Patient-Derived Ovarian Cancer Organoids via Immunofluorescence Assays

Visualizing DNA Damage Repair Proteins in Patient-Derived Ovarian Cancer Organoids via Immunofluorescence Assays

Immunofluorescence is one of the most widely used techniques to visualize target antigens with high sensitivity and specificity, allowing for the accurate ...

Establishment of Zebrafish Patient-Derived Xenografts from Pancreatic Cancer for Chemosensitivity Testing

Cancer is one of the main causes of death worldwide, and the incidence of many types of cancer continues to increase. Much progress has been made in terms ...

Optimizing HCC Organoid Formation for Target Identification and Drug Development

Development and Optimization of A Human Hepatocellular Carcinoma Patient-Derived Organoid Model for Potential Target Identification and Drug Discovery

Author Spotlight: Investigating Liver Cancer Pathogenesis Using Patient-Derived Organoids 

Hepatocellular carcinoma (HCC) is a highly prevalent and lethal tumor worldwide and its late discovery and lack of effective specific therapeutic agents ...