Name: Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer (Video) | JoVE Journal
Uploaded: 2024-01-05T14:20:00.000+00:00
Duration: 9 min 13 s
Description: Learn multiplexed live-cell imaging for drug response assessment in patient-derived tumor organoid models. This method enables simultaneous phenotypic monitoring and molecular profiling to prioritize therapies for clinical trials.

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We are grateful to the Tissue Procurement Core and Dr. Kristen Coleman at the University of Iowa for providing patient tumor specimens and to Dr. Sofia Gabrilovich in the Department of Obstetrics and Gynecology for assisting with PDO model generation. We also thank Dr. Valerie Salvatico (Agilent, USA) for critical analysis of the manuscript. We acknowledge the following funding sources: NIH/NCI CA263783 and DOD CDMRP CA220729P1 to KWT; Cancer Research UK, Prostate Cancer UK, Prostate Cancer Foundation and Medical Research Council to JSdB. The funders had no role in the design or analysis of experiments or decision to publish.

Automated Kinetic Imaging for Drug Assessment in Patient-Derived Tumor Organoids

<ol><li>Drost, J., Clevers, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Organoids+in+cancer+research%5BTitle%5D)+AND+%22Nat+Rev+Cancer%22%5BJournal%5D)">Organoids in cancer research.</a> Nat Rev Cancer. 18 (7), 407-418 (2018).</li>
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<li>Driehuis, E., Kretzschmar, K., Clevers, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Establishment+of+patient-derived+cancer+organoids+for+drug-screening+applications%5BTitle%5D)+AND+%22Nat+Protoc%22%5BJournal%5D)">Establishment of patient-derived cancer organoids for drug-screening applications.</a> Nat Protoc. 15 (10), 3380-3409 (2020).</li>
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<li>Tamura, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Evaluation+of+anticancer+agents+using+patient-derived+tumor+organoids+characteristically+similar+to+source+tissues%29%5BTitle%5D)+AND+%22Oncol+Rep%22%5BJournal%5D)">Evaluation of anticancer agents using patient-derived tumor organoids characteristically similar to source tissues).</a> Oncol Rep. 40 (2), 635-646 (2018).</li>
<li>Le Compte, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Multiparametric+tumor+organoid+drug+screening+using+widefield+live-cell+imaging+for+bulk+and+single-organoid+analysis%5BTitle%5D)+AND+%22J+Vis+Exp%22%5BJournal%5D)">Multiparametric tumor organoid drug screening using widefield live-cell imaging for bulk and single-organoid analysis.</a> J Vis Exp. 190, 64434(2022).</li>
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<li>Isherwood, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Live+cell+in+vitro+and+in+vivo+imaging+applications%3A+accelerating+drug+discovery%5BTitle%5D)+AND+%22Pharmaceutics%22%5BJournal%5D)">Live cell in vitro and in vivo imaging applications: accelerating drug discovery.</a> Pharmaceutics. 3 (2), 141-170 (2011).</li>
<li>Bi, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Successful+patient-derived+organoid+culture+of+gynecologic+cancers+for+disease+modeling+and+drug+sensitivity+testing%5BTitle%5D)+AND+%22Cancers+%28Basel%29%22%5BJournal%5D)">Successful patient-derived organoid culture of gynecologic cancers for disease modeling and drug sensitivity testing.</a> Cancers (Basel). 13 (12), 2901(2021).</li>
<li>Binaschi, M., Zunino, F., Capranico, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Mechanism+of+action+of+DNA+topoisomerase+inhibitors%5BTitle%5D)+AND+%22Stem+Cells%22%5BJournal%5D)">Mechanism of action of DNA topoisomerase inhibitors.</a> Stem Cells. 13 (4), 369-379 (1995).</li>
<li>Park, Y. Y., Ahn, J. H., Cho, M. G., Lee, J. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((ATP+depletion+during+mitotic+arrest+induces+mitotic+slippage+and+APC%2FC%28Cdh1%29-dependent+cyclin+B1+degradation%5BTitle%5D)+AND+%22Exp+Mol+Med%22%5BJournal%5D)">ATP depletion during mitotic arrest induces mitotic slippage and APC/C(Cdh1)-dependent cyclin B1 degradation.</a> Exp Mol Med. 50 (4), 1-14 (2018).</li>
<li>Lukonin, I., Zinner, M., Liberali, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Organoids+in+image-based+phenotypic+chemical+screens%5BTitle%5D)+AND+%22Exp+Mol+Med%22%5BJournal%5D)">Organoids in image-based phenotypic chemical screens.</a> Exp Mol Med. 53 (10), 1495-1502 (2021).</li>
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<li>Ramm, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((High-throughput+live+and+fixed+cell+imaging+method+to+screen+matrigel-embedded+organoids%5BTitle%5D)+AND+%22Organoids%22%5BJournal%5D)">High-throughput live and fixed cell imaging method to screen matrigel-embedded organoids.</a> Organoids. 2 (1), 1-19 (2023).</li>
<li>Dekkers, J. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((High-resolution+3D+imaging+of+fixed+and+cleared+organoids%5BTitle%5D)+AND+%22Nat+Protoc%22%5BJournal%5D)">High-resolution 3D imaging of fixed and cleared organoids.</a> Nat Protoc. 14 (6), 1756-1771 (2019).</li>
<li>Van Hemelryk, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Viability+analysis+and+high-content+live-cell+imaging+for+drug+testing+in+prostate+cancer+xenograft-derived+organoids%5BTitle%5D)+AND+%22Cells%22%5BJournal%5D)">Viability analysis and high-content live-cell imaging for drug testing in prostate cancer xenograft-derived organoids.</a> Cells. 12 (10), 1377(2023).</li>
<li>Bi, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Advantages+of+tyrosine+kinase+anti-angiogenic+cediranib+over+bevacizumab%3A+Cell+cycle+abrogation+and+synergy+with+chemotherapy%5BTitle%5D)+AND+%22Pharmaceuticals+%28Basel%29%22%5BJournal%5D)">Advantages of tyrosine kinase anti-angiogenic cediranib over bevacizumab: Cell cycle abrogation and synergy with chemotherapy.</a> Pharmaceuticals (Basel). 14 (7), 682(2021).</li>
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KWT is a co-owner of Immortagen Inc. CJD is an employee of Agilent. JSdB has served on advisory boards and received fees from Amgen, Astra Zeneca, Astellas, Bayer, Bioxcel Therapeutics, Boehringer Ingelheim, Cellcentric, Daiichi, Eisai, Genentech/Roche, Genmab, GSK, Harpoon, ImCheck Therapeutics, Janssen, Merck Serono, Merck Sharp &amp; Dohme, Menarini/Silicon Biosystems, Orion, Pfizer, Qiagen, Sanofi Aventis, Sierra Oncology, Taiho, Terumo, and Vertex Pharmaceuticals; is an employee of the Institute of Cancer Research (ICR), which have received funding or other support for his research work from AZ, Astellas, Bayer, Cellcentric, Daiichi, Genentech, Genmab, GSK, Janssen, Merck Serono, MSD, Menarini/Silicon Biosystems, Orion, Sanofi Aventis, Sierra Oncology, Taiho, Pfizer, and Vertex, and which has a commercial interest in abiraterone, PARP inhibition in DNA repair defective cancers, and PI3K/AKT pathway inhibitors (no personal income); was named as an inventor, with no financial interest for patent 8 822 438, submitted by Janssen that covers the use of abiraterone acetate with corticosteroids; has been the CI/PI of many industry-sponsored clinical trials; and is a National Institute for Health Research (NIHR) Senior Investigator. No other authors have any potential conflicts of interest to disclose.

PDO cultures are becoming an increasingly popular in vitro model system due to their ability to reflect cellular responses and behaviors2. Significant advances have been made in PDO generation, culture, and expansion techniques, yet methods to analyze therapeutic responses have lagged. Commercially available 3D viability kits are lytic endpoint assays, missing out on potentially valuable kinetic response data and limiting subsequent analyses by other methods8. Emerging studies are applying live-cell imaging to assess drug responses in PDO models. Here, we present a method to assess PDO therapeutic responses over time utilizing multiplexed fluorescent live-cell imaging. Multiplexing fluorescent dyes allows for different cellular responses to be quantified simultaneously. In addition to apoptosis and cytotoxicity, we envision that this approach can be expanded in future studies to examine other phenotypic effects in PDOs.
The protocol presented herein is designed to acquire kinetic bright-field and fluorescent images of PDOs plated as domes in a 96-well plate. Key steps include 1) plating, 2) treating with dye and drug, 3) defining imaging parameters, 4) image preprocessing and analysis at the completion of kinetic image acquisition, and 5) data export for analysis in other statistical software (Figure 1). Intact PDOs are plated in a 96-well plate as 5 &#181;L BME domes composed of a predefined ratio of BME and Organoid Culture Media (typically 1:1). The protocol presented herein uses UltiMatrix as the BME due to minimal batch-to-batch variability and superior optical properties for imaging. Modifications for harvesting PDOs cultured in other BMEs, such as Matrigel, may be necessary, as well as for models that are clumpy and difficult to dissociate (see examples Supplementary Figure 4). Next, fluorescent dyes are added to the Organoid Culture Media at the time of plating (Day -1) at a 2x concentration in a 100 &#181;L volume and incubated overnight to determine baseline cell death. The following day (Day 0), drugs or other treatments are added to Organoid Culture Media at a 2x concentration in a 100 &#181;L volume, and then added to each well for a final volume of 200 &#181;L. The final volume of 200 &#181;L reduces the meniscus effect with imaging. Kinetic images are acquired using the Cytation 5 plate reader partnered with the BioSpa tabletop incubator. The BioSpa incubator allows for the incubation of experimental plates at a fixed temperature of 37 &#176;C and 5% CO2 environment. Up to 8 plates can be stored in the BioSpa and thereby, 8 experiments can be simultaneously conducted. Imaging parameters for each plate are set up in the Gen5 software using &#34;Imager Manual Mode&#34; and saved as a Protocol. The Protocol is then loaded into the scheduling software (BioSpa OnDemand). The BioSpa OnDemand software automates the workflow for kinetic image acquisition, including the physical transfer of the plate from the BioSpa incubator into Cytation 5 and dictating which protocol to run in Gen5 for data collection. Images are analyzed using the Cellular Analysis function in the Gen5 software (Figure 2). We describe specific methods to analyze Z Projections of fluorescent and bright field images. Specific methods to analyze single Z planes and/or only bright field images are provided in Supplementary File 1. Finally, users can define specific data features, such as PDO area, number, and mean fluorescence intensity, to export as an Excel spreadsheet for subsequent statistical analysis of drug effects.
Given that PDO models are a relatively new model system to interrogate drug effects, methods to accommodate the culture conditions, in particular growth in BME, are still emerging16. The bulk of studies assessing PDO response to drug treatment rely on ATP-based endpoint assays as a surrogate for cell health (CellTiter-Glo 3D). This method requires cell lysis, thus precluding subsequent downstream analyses. Alternative endpoint assays, such as fluorescent staining, single timepoint imaging, and morphologic tracking, have provided other metrics to characterize drug response while allowing for sample use for additional purposes. For example, in-plate endpoint fixation protocols have been applied for high-throughput analysis of drug effects17,18. An advantage of this method is that it circumvents the extensive processing required in typical immunohistochemistry and immunofluorescent imaging19 and is particularly useful when sample is limited, as is the case for PDO models. It is also amenable to high-resolution imaging with confocal microscopy. Another endpoint assay that does not require cell lysis is live-cell imaging with reagents such as propidium iodide or acridine orange. Our comparative analysis of CellTiter-Glo 3D and AOPI, the latter of which does not require cell lysis, for assessment of cell viability and death (Figure 6C) highlights the advantages of using live-cell imaging dyes in PDO models. This method has been applied by several groups, including ours, to assess phenotypic effects at the conclusion of an experiment18,19,20. However, kinetic data acquisition using either the in-well fixation or endpoint live-cell imaging methods requires significant sample. Label-free morphologic assessment of PDOs over time in part overcomes this limitation and can be assessed using a wide range of imaging modalities8,10,17,18, yet changes in morphology may not be representative of the spectrum of potential drug effects such as apoptosis and changes in cell viability. We have observed significant model-to-model variability in morphologic changes in response to drugs. For example, some PDOs will increase in area as they are undergoing apoptosis, whereas other models may shrink. Kinetic morphologic assessments have been multiplexed with either fixed or live-cell fluorescent endpoint assays in a limited number of studies18,20. The methods presented herein are among the first to multiplex different fluorescent dyes to simultaneously assess multiple cellular effects in a high-throughput system.
One of the greatest improvements provided by kinetic live-cell imaging is that it overcomes key limitations associated with endpoint assays. For example, plating an equal number of PDOs&#160;per well is technically difficult because most automated cell counters are gated for objects smaller than 60 &#181;m. Live-cell imaging allows for normalization to PDO number or area at time 0 h in each well, which can then be used to adjust for variation in plating amongst wells. The gold standard endpoint assay for PDOs is the CellTiter-Glo 3D kit, which measures ATP as a surrogate for cell viability. We have extensively used this assay in our studies of gynecologic and prostate cancer PDOs13,21,22,23,24. In addition to requiring cell lysis for ATP measures, drugs&#160;and other therapeutic modalities can alter ATP levels, potentially providing an inaccurate assessment of therapeutic response. Utilizing live-cell imaging dyes allows for quantification of a wider scope of specific cellular responses, such as apoptosis and cytotoxicity. Importantly, these reagents do not perturb cell viability or induce DNA damage, as is the case with propidium iodide; this allows for repeated assessment of PDO response over time. While we have not explored the use of acridine orange (AO) for kinetic measures, the mechanism of action for AO should not preclude such application in the future.
Tumors consist of several distinct cell populations with varying genomic profiles and morphologies. Due to the complex heterogeneity of PDO models, individual PDO&#160;responses may vary, and tracking these responses is challenging. Our protocol provides a method to assess multiple PDO response metrics on a well-by-well basis. However, certain technical considerations still apply to live-cell imaging. The number of wells of a 24-well plate needed to seed a 96-well plate will depend upon the density and growth rate of each PDO model. Because clumping can confound image analysis (Supplementary Figure 4), PDO models may need additional processing steps prior to plating. If necessary, PDOs may be mechanically sheared during processing through vigorous pipetting with a non-wide bore p200 tip. Enzymatic digestion using TrypLE Express may also be employed prior to plating to promote PDO dissociation and decreased clumping. In our experience, we have noted that the length of TrypLE incubation is highly variable depending upon the model. Therefore, TrypLE incubation should be optimized for each model, particularly if researchers wish to obtain single cell suspensions. Recovery time prior to beginning treatment may be necessary for PDO models that are particularly sensitive to enzymatic digestion.
We present methods for specific live-cell imaging reagents. A limitation in the broad applicability of the methods presented herein is a paucity of reagents that are compatible with BME. For other dyes/reagents that have not yet been optimized for use in PDOs, additional troubleshooting may be necessary to determine the optimal concentration and minimize solvent effects. Depending on the readout of interest (e.g., apoptosis or cytotoxicity), treatment with a compound known to induce cell death, such as staurosporine or daunorubicin13 should be used to optimize reagent conditions. An additional consideration is the optimal time for dye integration into the BME dome. In our experiments, we perform an overnight incubation prior to treatment to allow for complete uptake of the dye into the domes as well as determine baseline cell health. Since signal intensity will increase over time, researchers should perform pilot studies with the dyes to determine the ideal exposure time at the end of the experiment to avoid overexposed images. Finally, reagents should not interfere with cellular processes. For example, dyes that intercalate into DNA are not compatible with kinetic imaging. However, live-cell imaging can be used for data normalization in endpoint assays. Indeed, we present a supplementary method to quantify cell viability and the viable: dead cell ratio using AOPI. In this experiment, the fluorescent signal is normalized to PDO number for each well as determined by live-cell imaging on day 0 (day of treatment, Figure 6).
Another limitation of this methods paper is the reliance on manual pipetting for experiments, which can lead to greater variance in technical replicates. Further improvements in data reproducibility can be achieved with the addition of automation to other steps of the experimental process, such as the use of an automated liquid handler for plating and drug dispensing, as has been demonstrated by others8,10. However, this addition requires an additional investment in research infrastructure that may not be available to all investigators. Given the heterogeneity in PDO area for each model, normalizing results to the initial PDO number or area at time 0 h is still a useful approach with automated seeding.
A key advantage of Cytation 5 over other live-cell imaging platforms is the ability to customize image and analysis features. However, the Cytation 5/Gen5 software has a steep learning curve and assumes that users have a foundational knowledge of imaging. One of the goals of this methods paper is to provide step-by-step instructions to decrease the barrier for other researchers to incorporate sophisticated live-cell imaging techniques in their PDO research programs. While the specific analysis steps presented herein are for one system, users can apply the multiplexing principles to other platforms, with the understanding that downstream analysis may necessitate the use of third-party software, such as NIH ImageJ.
Analysis metrics should be chosen based on both experimental goals and plating conditions. For example, if the experiment is conducted using a fluorescent dye to quantify cell death, fluorescence intensity is an effective readout. The most effective fluorescence metric (Total Fluorescence vs. Object Mean Intensity) will depend on the plating conditions (Supplementary Figure 4). If PDOs are evenly dispersed and have a more circular, cohesive morphology, fluorescence can be determined in a defined PDO subpopulation. The specific function in the Gen5 software is Cellular Analysis, and the output is Object Mean Intensity. However, if the PDO model is clumpy or has a discohesive morphology, we recommend quantifying the fluorescence signal at the image level; this function can be found under Image Statistics, and the output is Total Fluorescence Intensity. While this method is useful for observing changes at the individual well level, this metric is not specific for objects of interest and could change erroneously if the PDOs move outside of the designated plug over the duration of the experiment. In scenarios in which there is significant debris or dead single cells, use of the Cellular Analysis is suggested to gate out any fluorescent signal that is not specifically associated with a PDO. An example of differential results using Cellular Analysis vs. Image Statistics is presented in Supplementary Figure 5.
To determine the optimal threshold for the Image Statistics function, the line tool may be utilized. Using the line tool, users can determine the range of fluorescence intensity within an image. We set the lower threshold as the 25% value of the peak intensity within the image. To view the fluorescent areas that are included in the designated threshold, check the &#34;Threshold Outliers&#34; box. Additional fine-tuning of the lower threshold value may be necessary.
A significant challenge in live-cell imaging is storing the massive amount of data generated with each experiment. This is particularly relevant in the case of PDO cultures, where Z-Stacks are used to image across several focal planes and generate a Z Projection. There are multiple methods to overcome this issue. First, ensure adequate storage capacity. We have installed three solid-state hard drives with a total of 17 TB. Other options include transferring experimental files to external hard drives or networked storage. It is not recommended to directly write files to cloud based storage. To analyze data that has been stored on an external drive, simply transfer the experiment and the image files to a computer equipped with Gen5 software (NOTE: large files may take extended periods of time to transfer). Before analysis, the images must be relinked to the experiment. Open the experiment file, click Protocol in the toolbar, select Protocol Options. Click Image Save Options and click Select new image folder. Locate the image file and click Select Folder to relink.
Depending on the goals of the experiment, it may also be suitable to use the binning feature within Gen5. Binning decreases file size by lowering the number of pixels, which leads to lower image resolution (see step 3.5.3.2). Therefore, binning is not recommended if high-resolution images are required. When using the binning feature, the exposure settings will need to be adjusted. Once the experimental file has been created, double click on the Image section, and click the microscope icon to reopen Imager Manual Mode. Use the Auto-expose function or manually adjust exposure as needed.
In summary, we present methods for assessing apoptosis and cell health of PDOs in response to cytotoxic agents. Future studies are necessary to optimize methods and develop additional analysis strategies for kinetic imaging of PDOs, such as other phenotypes and effects of drugs that are cytostatic rather than cytotoxic. A major roadblock is the commercial availability of dyes and reagents that are compatible with BME. There is still more work necessary to better understand how kinetic live-cell imaging can be fully utilized to extract the most data from these models.

Patient-derived tumor organoids (PDOs) are rapidly emerging as a robust model system to study cancer development and therapeutic responses. PDOs are three-dimensional (3D) cell culture systems that recapitulate the complex genomic profile and architecture of the primary tumor1,2. Unlike traditional two-dimensional (2D) cultures of immortalized cancer cell lines, PDOs capture and maintain intratumoral heterogeneity3,4, making them a valuable tool for both mechanistic and translational research. Although PDOs are becoming an increasingly popular model system, commercially available reagents and analysis methods for cellular effects that are compatible with PDO cultures are limited.
The lack of robust methods to analyze subtle changes in treatment response hinders clinical translation. The gold standard cell health reagent in 3D cultures, CellTiter-Glo 3D, utilizes ATP levels as a determinant of cell viability5,6. While this reagent is useful for endpoint assays, there are several caveats, most notably the inability to use samples for other purposes after completion of the assay.
Live-cell imaging is a sophisticated form of kinetic microscopy that, when combined with fluorescent reagents, has the capacity to quantify a variety of cell health readouts within PDO models, including apoptosis7,8,9 and cytotoxicity10. Indeed, live-cell imaging has been integral to high throughput screening of compounds in 2D platforms11,12. Systems such as the Incucyte have made the technology affordable and thus accessible to research groups in a variety of settings. However, the application of these systems to analyze 3D cultures is still in its infancy.
Herein, we describe a method to assess drug response in PDO models of cancer using multiplexed live-cell imaging (Figure 1). Through analysis of bright field images, changes in PDO&#160;size and morphology can be kinetically monitored. Furthermore, cellular processes can be simultaneously quantified over time using fluorescent reagents, such as Annexin V Red Dye for apoptosis and Cytotox Green Dye for cytotoxicity. The methods presented are optimized for the Cytation 5 live-cell imaging system, but this protocol may be adapted across different live-cell imaging platforms.

<table><tbody><tr><td>1.5 mL microcentrfuge tube</td><td>Dot Scientific Inc</td><td>1008113</td><td></td></tr><tr><td>15 mL conical centrifuge tube</td><td>Sarstedt</td><td>62.554.100</td><td></td></tr><tr><td>554 NM LED Cube</td><td>Agilent</td><td>1225012</td><td></td></tr><tr><td>96-well plate</td><td>Corning Costar</td><td>3596</td><td>Prewarmed to 37 &amp;deg;C</td></tr><tr><td>96-well plate</td><td>Agilent</td><td>204626-100</td><td>Prewarmed to 37 &amp;deg;C</td></tr><tr><td>A83-01</td><td>Tocris</td><td>2939</td><td>Final concentration is 500 nM (component of organoid culture media)</td></tr><tr><td>Advanced DMEM/F-12</td><td>Gibco</td><td>12634-010</td><td>component of organoid culture media</td></tr><tr><td>B27 Supplement</td><td>Gibco</td><td>17504044</td><td>Final concentration is 1x (component of organoid culture media)</td></tr><tr><td>BioTek BioSpa 8 Automated Incubator</td><td>Agilent</td><td>BIOSPAG-SN</td><td>Tabletop incubator; BioSpa OnDemand scheduling software comunicates with Gen5 to transfer plates between the BioSpa and the Cytation 5 for imaging (this protocol uses version 1.01.10)</td></tr><tr><td>BioTek Cytation 5 Cell Imaging Multimode Reader</td><td>Agilent</td><td>CYT5PW-SN</td><td>Plate reader; Gen5 software is used for this device (this protocol uses version 3.12.08)</td></tr><tr><td>Cultrex UltiMatrix Reduced Growth Factor Basement Membrane Extract</td><td>R&amp;amp;D Systems</td><td>BME001-10</td><td></td></tr><tr><td>Daunorubicin HCl</td><td>Sigma-Aldrich</td><td>S3035</td><td>Reconstituted in DMSO</td></tr><tr><td>Dimethyl sulfoxide</td><td>Sigma-Aldrich</td><td>D2438</td><td></td></tr><tr><td>EDTA (0.5 M)</td><td>Thermo Fisher</td><td>AM9260G</td><td></td></tr><tr><td>Forskolin</td><td>Tocris</td><td>1099</td><td>Final concentration is 10 &amp;micro;M (component of organoid culture media)</td></tr><tr><td>Glutamax</td><td>Gibco</td><td>35050-061</td><td>Final concentration is 1x (component of organoid culture media)</td></tr><tr><td>HEPES</td><td>Gibco</td><td>15630-080</td><td>Final concentration is 10 mM (component of organoid culture media)</td></tr><tr><td>Human EGF, Animal-Free Recombinant Protein</td><td>Gibco</td><td>AF-100-15-1MG</td><td>Final concentration is 0.5 ng/mL (component of organoid culture media)</td></tr><tr><td>Human FGF-10 Recombinant Protein</td><td>Gibco</td><td>100-26-1MG</td><td>Final concentration is 10 ng/mL (component of organoid culture media)</td></tr><tr><td>Human R-Spondin 1 Recombinant Protein</td><td>Gibco</td><td>120-38-5UG</td><td>Final concentration is 250 ng/mL (component of organoid culture media)</td></tr><tr><td>Hydrocortisone Stock Solution</td><td>StemCell Technologies</td><td>7926</td><td>Final concentration is 500 ng/mL (component of organoid culture media)</td></tr><tr><td>Imaging Filter Cube- GFP</td><td>Agilent</td><td>1225101</td><td></td></tr><tr><td>Imaging Filter Cube- TRITC</td><td>Agilent</td><td>1225125</td><td></td></tr><tr><td>Imaging LED GFP/CFP</td><td>Agilent</td><td>1225001</td><td></td></tr><tr><td>Incucyte Annexin V Red Dye</td><td>Sartorius</td><td>4641</td><td>Reconstituted in organoid culture media</td></tr><tr><td>Incucyte Cytotox Green Dye</td><td>Sartorius</td><td>4633</td><td>DMSO solution</td></tr><tr><td>N-Acetyl-L-cysteine</td><td>Sigma-Aldrich</td><td>A7250</td><td>Final concentration is 1.25 mM (component of organoid culture media)</td></tr><tr><td>Nexcelom Bioscience ViaStain AOPI Staining Solution</td><td>Fisher-Scientific</td><td>13366169</td><td>Add 1:50 volume</td></tr><tr><td>Nicotinamide</td><td>Sigma-Aldrich</td><td>N0636</td><td>Final concentration is 10 mM (component of organoid culture media)</td></tr><tr><td>Noggin</td><td>R&amp;amp;D Systems</td><td>6057-NG</td><td>Final concentration is 100 ng/mL (component of organoid culture media)</td></tr><tr><td>Penicillin-Streptomycin</td><td>Gibco</td><td>15140122</td><td>Final concentration is 10 units/mL (component of organoid culture media)</td></tr><tr><td>Phosphate Buffered Saline (1x)</td><td>Gibco</td><td>14190-144</td><td></td></tr><tr><td>Primocin</td><td>InvivoGen</td><td>ant-pm-05</td><td>Final concentration is 100 &amp;micro;g/mL (component of organoid culture media)</td></tr><tr><td>Recombinant Human Heregulin&amp;beta;-1</td><td>Pepro Tech</td><td>100-03</td><td>Final concentration is 37.5 ng/mL (component of organoid culture media)</td></tr><tr><td>Staurosporine solution from Streptomyces sp.</td><td>Sigma-Aldrich</td><td>S6942</td><td></td></tr><tr><td>TrypLE Express</td><td>Life Technologies</td><td>12604013</td><td></td></tr><tr><td>Y-27632, CAS 331752-47-7</td><td>Sigma-Aldrich</td><td>688000</td><td>Final concentration is 5 &amp;micro;M (component of organoid culture media)</td></tr><tr><td>&amp;beta;-Estradiol</td><td>Sigma-Aldrich</td><td>E2758</td><td>Final concentration is 100 nM (component of organoid culture media)</td></tr></tbody></table>

multiplexed live-cell imaging for drug responses in patient-derived organoid models of cancer

Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell lines. PDO models can be generated by culturing patient tumor cells in extracellular basement membrane extracts (BME) and plating them as three-dimensional domes. However, commercially available reagents that have been optimized for phenotypic assays in monolayer cultures often are not compatible with BME. Herein, we describe a method to plate PDO models and assess drug effects using an automated live-cell imaging system. In addition, we apply fluorescent dyes that are compatible with kinetic measurements to quantify cell health and apoptosis simultaneously. Image capture can be customized to occur at regular time intervals over several days. Users can analyze drug effects in individual Z-plane images or a Z Projection of serial images from multiple focal planes. Using masking, specific parameters of interest are calculated, such as PDO number, area, and fluorescence intensity. We provide proof-of-concept data demonstrating the effect of cytotoxic agents on cell health, apoptosis, and viability. This automated kinetic imaging platform can be expanded to other phenotypic readouts to understand diverse therapeutic effects in PDO models of cancer.

Patient-derived tumor organoids are a sophisticated model system for basic and translational research. This methods article details the use of multiplexed fluorescent live-cell imaging for simultaneous kinetic assessment of different organoid phenotypes.

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell ...

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Research

JoVE Journal

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The Drosophila Imaginal Disc Tumor Model: Visualization and Quantification of Gene Expression and Tumor Invasiveness Using Genetic Mosaics

This protocol describes generation of patient-derived spheroids, and downstream analysis including quantification of proliferation, cytotoxicity testing, flow cytometry, immunofluorescence staining and confocal imaging, in order to assess drug candidates’ potential as anti-neoplastic therapeutics. This protocol supports precision medicine with identification of specific drugs for each patient and stage of disease.

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Learn multiplexed live-cell imaging for drug response assessment in patient-derived tumor organoid models. This method enables simultaneous phenotypic monitoring and molecular profiling to prioritize therapies for clinical trials.

Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer

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