We thank Raymond Briones and Wen H. Shen (Weill Cornell Medical College, New York, NY, USA) for their help with the development of this protocol. This work has been supported by a Transformative Breast Cancer Consortium Grant from the US DoD BCRP (#W81XWH2120034, PI: Formenti).

The reagents and equipment used in the study are listed in the Table of Materials.
1. Organoid culture
NOTE: TNBC#1 PDTOs were established in our lab based on tumor tissue surgically removed from a patient with triple-negative breast cancer (TNBC) who provided informed consent to participate in a biobanking protocol (IRB21-06023682). After validation by histology and RNA sequencing (RNAseq), TNBC#1 PDTOs are cultured in 66% matrigel drops (so-called &#39;domes&#39;) in enriched DMEM/F12 culture medium (Table 1) and passaged every 2-3 weeks at a 1:2-1:10 ratio28.
<ol>
	<li>Seed PDTOs at a 1:2-1:10 ratio about 2 weeks before irradiation in separate, non-adherent 6-well plates, one per each radiation dose tested (plus negative controls, which will be provided by PDTOs not exposed to ionizing radiation).</li>
	<li>Add 3 mL of fresh enriched DMEM/F12 culture medium to the PDTOs every 3-4 days. 
	NOTE: Seeding and culture conditions may require some adaptation to prevent PDTOs from acquiring a very recognizable, ring-like appearance that is indicative of core necrosis under the microscope and to ensure optimal viability at irradiation.</li>
</ol>
2. Radiation
<ol>
	<li>PDTOs are ready for irradiation once they reach the average size (approximately 100 &#181;m, as preliminary determined under bright field microscopy with a scale reference) and dome occupancy (approximately 80%). Passage the PDTOs at this stage to avoid overcrowding.</li>
	<li>Radiate the PDTO-containing domes using the Small Animal Research Radition Platform (SARRP) irradiator (or an alternative irradiator for in vitro or in vivo applications) in open field mode (no collimator), delivering single doses of 2 Gy, 4 Gy, 6 Gy, 8 Gy, and 10 Gy. Non-irradiated PDTOs provide appropriate negative control conditions. 
	NOTE: Dosimetry testing calibration should be performed prior to each experiment to ensure that Matrigel-enclosed PDTOs receive the planned radiation dose. These doses were chosen based on preliminary assessments of the radiosensitivity of TNBC#1 PDTOs and, hence, may require adjustments for other PDTOs.</li>
</ol>
3. Dissociation
<ol>
	<li>Immediately after irradiation, wash each PDTO-containing matrigel dome with 2 mL of enriched DMEM/F12 culture medium and resuspend them in 1-3 mL of TrypL-E using a p1000 micropipette. Repeat about 30 times for each well.</li>
	<li>Collect the cell suspension in a 50 mL centrifuge tube and incubate for ~5 min in a water bath at 37 &#176;C.</li>
	<li>Pellet the cells by centrifuging them at 800 x g for 5 min at room temperature.</li>
	<li>Remove excess TrypL-E&#160;to leave ~1 mL in the tube and add 3x the original enzyme volume (see step 3.1) of enriched DMEM/F12 medium to wash the cells.</li>
	<li>Filter the cell suspension using a 40 &#181;m mesh filter. This step ensures that no cell clusters remain at plating and that each new PDTO originates from a single cell.</li>
	<li>Count the cells in an automated cell counter upon staining with 10% trypan blue in PBS, and resuspend them to have 800 cells in 50 &#181;L of enriched DMEM/F12 medium plus 66% matrigel at 4 &#176;C (conditions for 1 dome).</li>
	<li>Plate each dome in an individual well from a live imaging-compatible 48-well culture plate while avoiding the formation of bubbles. Technical triplicates for each radiation dose are recommended.</li>
	<li>Place the plates in a cell culture incubator (37 &#176;C, 5% CO2) for 30 min to solidify the matrigel.</li>
	<li>Add 0.5-1 mL of enriched DMEM/F12 medium, remove potential bubbles, and place plates in the live imaging system inside a cell culture incubator. Let the plate equilibrate to the set temperature for about 30 min before imaging. 
	NOTE: Matrigel solidifies at temperatures &#62;4 &#176;C, implying that this temperature should be preserved until solidification is required.</li>
</ol>
4. Live imaging
<ol>
	<li>On the Incucyte software, select Schedule to Aquire.</li>
	<li>Click on the plus sign in the upper left corner of Launch Add Vessel.</li>
	<li>To scan repeatedly or once, select Scan on Schedule, and then click on Next.</li>
	<li>To create or restore vessel, select Create Vessel New, and then click on Next.</li>
	<li>To select the scan Type, select Organoid, and then click on Next.</li>
	<li>Scan settings: Choose QC &#60; &#39; Phase + Brightfield Image Channels. &#39;4x Objective&#39; is automatically selected. Then click on Next.</li>
	<li>Vessel Selection: Choose the appropriate software-validated plate according to the catalog number.</li>
	<li>Vessel Location: Select the location of the plate on the instrument according to the layout, and then click on Next.</li>
	<li>Scan Pattern: Select wells according to the plate layout, then click on Next.</li>
	<li>Vessel Notebook: Name plate (Optional: name Cell Type and Passage). Create a plate Map by clicking on the plus sign in the upper right corner of the plate layout, &#39;Create plate map&#39;.</li>
	<li>In the Plate Map Editor, indicate cell type by clicking on the Create New Cell icon in the Cells section, apply to appropriate wells by clicking on the plus icon, and select the appropriate wells. Optional: The number of seeded cells and passages can be indicated. Repeat for each cell line.</li>
	<li>Indicate the treatment by clicking on the Create New Cell icon in the Growth Conditions section, apply to appropriate wells by clicking on the plus icon, and select the appropriate wells. Repeat for each experimental condition. Next, click on Okay &#62;&#160;Next.</li>
	<li>Analysis Setup: &#39;Defer analysis until later&#39; is automatically selected; click on Next.</li>
	<li>Scan Schedule: Choose to scan twice a day, indefinitely. Click on Next. Monitor the darkness of control PDTOs for ideal endpoint, as they tend to collapse when overgrown.</li>
	<li>Summary: Check the summary and click on Add to Schedule. 
	NOTE: Scan properties can be visualized, and the schedule can be edited if needed by right-clicking on the scanning timeline.</li>
</ol>
5. Analysis
<ol>
	<li>On the compatible software, select View. This can also be operated from a computer connected to the system via intranet.</li>
	<li>Select the desired experiment by double-clicking on it.</li>
	<li>Select the Launch Analysis icon.</li>
	<li>Select the Create New Analysis Definition, and then click on Next.</li>
	<li>Analysis Type: Select Organoid, and click on Next.</li>
	<li>Image Channels: &#39;Phase + Brightfield&#39; is selected by default, click &#39;Next&#39;.</li>
	<li>Select a set of representative images for analysis. Click on Next. It is recommended to choose early and late time points and different treatment conditions, e.g., control and different radiation doses.</li>
	<li>Perform Analysis Definition for TNBC#1 following the steps below:
	<ol>
		<li>On image: Select Preview Current or &#39;Preview All&#39; to visualize the default mask of current or selected images. Repeat as analysis parameters are changed to update the mask.</li>
		<li>Segmentation: Set the Radius to 300, Sensitivity Background to 80, Edge Split to ON, and Edge Sensitivity to 70.</li>
		<li>Cleanup: Set Hole Fill to 5E+05 &#181;m2 and Adjust Size to 0 pixels.</li>
		<li>Filters: Set no min or max Area, min Eccentricity set to 0.19, and no max Eccentricity. Click on Next.</li>
	</ol>
	</li>
	<li>Scan times and wells: Select all desired scan time points and wells. Click on Next. Optional: Select Analyze Future Scans.</li>
	<li>Save and Apply Analysis Definition: Enter the Definition Name, and click on Next.</li>
	<li>Visualize the Summary, and click on Finish.</li>
	<li>A pop-up window appears to inform the user that the analysis has entered the Analysis Queue. Click on Okay. Once the Analysis Queue window opens, the remaining tasks can be visualized.</li>
	<li>If necessary, retrieve the completed analysis in View by selecting the blue arrow in the Analyses column, next to the Vessel Name, and right-clicking on the Analysis Definition Name. Next, either visualize the raw data on the software by clicking on Graph analysis Metrics, or export for further analysis by selecting Export Analysis Definition. 
	NOTE: Raw data exportation can be customized in the Graph analysis Metrics window. Organoid Count, Total Area, Average Eccentricity, and Darkness can be separately exported, and data organized in the Select Grouping roll-down menu by clicking on None, Columns, Rows or plate Map Replicates. For TNBC#1, for raw data exportation, Graph Analysis Metrics, and for the Select Grouping roll-down option, the option None was chosen. These import parameters were chosen based on preliminary assessments with TNBC#1 PDTOs. They hence may require adjustments for other PDTOs, which is possible on the software based on the &#34;Preview&#34; features. We recommend adapting import parameters on (1) early images that mostly contain single cells or small PDTOs, and (2) images collected at late time points to ensure that large PDTOs are also acquired in both control and treated conditions.</li>
</ol>

Radiation Response in Patient-Derived Tumor Organoids Using a Clonogenic Assay

<ol>
	<li>De Ruysscher, D., 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=Radiotherapy+toxicity.">Radiotherapy toxicity.</a> Nat Rev Dis Primers. 5 (1), 13 (2019).</li><li>Bates, J. E., Sanders, T., Arnone, A., Elmore, S. N. C., Royce, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Geographic+density+of+linear+accelerators+and+receipt+of+radiation+therapy+for+prostate+cancer.">Geographic density of linear accelerators and receipt of radiation therapy for prostate cancer.</a> Int J Radiat Oncol Biol Phys. 111, e351-e352 (2021).</li><li>Harmenberg, U., Hamdy, F. C., Widmark, A., Lennern&#228;s, B., Nilsson, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Curative+radiation+therapy+in+prostate+cancer.">Curative radiation therapy in prostate cancer.</a> Acta Oncol. 50, 98-103 (2011).</li><li>Nakano, T., Ohno, T., Ishikawa, H., Suzuki, Y., Takahashi, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Current+advancement+in+radiation+therapy+for+uterine+cervical+cancer.">Current advancement in radiation therapy for uterine cervical cancer.</a> J Radiat Res. 51 (1), 1-8 (2010).</li><li>Spencer, K., Parrish, R., Barton, R., Henry, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Palliative+radiotherapy.">Palliative radiotherapy.</a> BMJ. 360, k821 (2018).</li><li>Price, J. M., Prabhakaran, A., West, C. M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Predicting+tumour+radiosensitivity+to+deliver+precision+radiotherapy.">Predicting tumour radiosensitivity to deliver precision radiotherapy.</a> Nat Rev Clin Oncol. 20 (2), 83-98 (2023).</li><li>McLaughlin, 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=Inflammatory+microenvironment+remodelling+by+tumour+cells+after+radiotherapy.">Inflammatory microenvironment remodelling by tumour cells after radiotherapy.</a> Nat Rev Cancer. 20 (4), 203-217 (2020).</li><li>Rodriguez-Ruiz, M. E., Vitale, I., Harrington, K. J., Melero, I., Galluzzi, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immunological+impact+of+cell+death+signaling+driven+by+radiation+on+the+tumor+microenvironment.">Immunological impact of cell death signaling driven by radiation on the tumor microenvironment.</a> Nat Immunol. 21 (2), 120-134 (2020).</li><li>Cytlak, U. 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=Immunomodulation+by+radiotherapy+in+tumour+control+and+normal+tissue+toxicity.">Immunomodulation by radiotherapy in tumour control and normal tissue toxicity.</a> Nat Rev Immunol. 22 (2), 124-138 (2022).</li><li>Hanahan, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hallmarks+of+Cancer:+New+Dimensions.">Hallmarks of Cancer: New Dimensions.</a> Cancer Discov. 12 (1), 31-46 (2022).</li><li>Groelly, F. J., Fawkes, M., Dagg, R. A., Blackford, A. N., Tarsounas, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeting+DNA+damage+response+pathways+in+cancer.">Targeting DNA damage response pathways in cancer.</a> Nat Rev Cancer. 23 (2), 78-94 (2023).</li><li>Renaudin, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reactive+oxygen+species+and+DNA+damage+response+in+cancer.">Reactive oxygen species and DNA damage response in cancer.</a> Int Rev Cell Mol Biol. 364, 139-161 (2021).</li><li>Klapp, V., 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=The+DNA+damage+response+and+inflammation+in+cancer.">The DNA damage response and inflammation in cancer.</a> Cancer Discov. 13 (7), 1521-1545 (2023).</li><li>Constanzo, J., Garcia-Prada, C. D., Pouget, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clonogenic+assay+to+measure+bystander+cytotoxicity+of+targeted+alpha-particle+therapy.">Clonogenic assay to measure bystander cytotoxicity of targeted alpha-particle therapy.</a> Methods Cell Biol. 174, 137-149 (2023).</li><li>Serrano-Mendioroz, I., Garate-Soraluze, E., Rodriguez-Ruiz, M. E. <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+method+to+assess+clonogenic+survival+of+irradiated+cancer+cells.">A simple method to assess clonogenic survival of irradiated cancer cells.</a> Methods Cell Biol. 174, 127-136 (2023).</li><li>Petroni, G., 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=Radiotherapy+delivered+before+CDK4/6+inhibitors+mediates+superior+therapeutic+effects+in+ER(+)+breast+cancer.">Radiotherapy delivered before CDK4/6 inhibitors mediates superior therapeutic effects in ER(+) breast cancer.</a> Clin Cancer Res. 27 (7), 1855-1863 (2021).</li><li>Alvarez-Abril, B., 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=Cytofluorometric+assessment+of+acute+cell+death+responses+driven+by+radiation+therapy.">Cytofluorometric assessment of acute cell death responses driven by radiation therapy.</a> Methods Cell Biol. 172, 17-36 (2022).</li><li>Bodey, R. K., Evans, P. M., Flux, G. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Application+of+the+linear-quadratic+model+to+combined+modality+radiotherapy.">Application of the linear-quadratic model to combined modality radiotherapy.</a> Int J Radiat Oncol Biol Phys. 59 (1), 228-241 (2004).</li><li>Unkel, S., Belka, C., Lauber, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+the+analysis+of+clonogenic+survival+data:+Statistical+alternatives+to+the+linear-quadratic+model.">On the analysis of clonogenic survival data: Statistical alternatives to the linear-quadratic model.</a> Radiat Oncol. 11, 11 (2016).</li><li>Zitvogel, L., Pitt, J. M., Daill&#232;re, R., Smyth, M. J., Kroemer, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mouse+models+in+oncoimmunology.">Mouse models in oncoimmunology.</a> Nat Rev Cancer. 16 (12), 759-773 (2016).</li><li>Buqu&#233;, A., Galluzzi, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+Tumor+immunology+and+immunotherapy+in+mice.">Modeling Tumor immunology and immunotherapy in mice.</a> Trends Cancer. 4 (9), 599-601 (2018).</li><li>Lee, S. Y., 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=A+Functionally+robust+phenotypic+screen+that+identifies+drug+resistance-associated+genes+using+3D+cell+culture.">A Functionally robust phenotypic screen that identifies drug resistance-associated genes using 3D cell culture.</a> Bio Protoc. 8 (22), e3083 (2018).</li><li>Mina, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bissell:+Context+Matters.">Bissell: Context Matters.</a> Trends Cancer. 1 (1), 6-8 (2015).</li><li>Drost, J., 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=Organoids+in+cancer+research.">Organoids in cancer research.</a> Nat Rev Cancer. 18 (7), 407-418 (2018).</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> Nat Rev Mol Cell Biol. 21 (10), 571-584 (2020).</li><li>van Renterghem, A. W. J., van de Haar, J., Voest, E. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+precision+oncology+using+patient-derived+assays:+Bridging+genotype+and+phenotype.">Functional precision oncology using patient-derived assays: Bridging genotype and phenotype.</a> Nat Rev Clin Oncol. 20 (5), 305-317 (2023).</li><li>Vitale, I., Manic, G., De Maria, R., Kroemer, G., Galluzzi, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+damage+in+stem+cells.">DNA damage in stem cells.</a> Mol Cell. 66 (3), 306-319 (2017).</li><li>Sachs, 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+Living+biobank+of+breast+cancer+organoids+captures+disease+heterogeneity.">A Living biobank of breast cancer organoids captures disease heterogeneity.</a> Cell. 172 (1-2), 373-386 (2018).</li><li>Zhou, 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=Harnessing+3D+in+vitro+systems+to+model+immune+responses+to+solid+tumours:+A+step+towards+improving+and+creating+personalized+immunotherapies.">Harnessing 3D in vitro systems to model immune responses to solid tumours: A step towards improving and creating personalized immunotherapies.</a> Nat Rev Immunol. 24, 18-32 (2024).</li></ol>

Unrelated to this work, SCF is/has been holding research contracts with Merck, Varian, Bristol Myers Squibb, Celldex, Regeneron, Eisai, and Eli-Lilly, and has received consulting/advisory honoraria from Bayer, Bristol Myers Squibb, Varian, Elekta, Regeneron, Eisai, AstraZeneca, MedImmune, Merck US, EMD Serono, Accuray, Boehringer Ingelheim, Roche, Genentech, AstraZeneca, View Ray and Nanobiotix. Unrelated to this work, SD has received consulting/advisory honoraria from Lytix Biopharma, EMD Serono, Ono Pharmaceutical, Genentech, and Johnson &amp; Johnson Enterprise Innovation Inc., and is/has been holding research contracts with Lytix Biopharma, Nanobiotix and Boehringer-Ingelheim. Unrelated to this work, LG is/has been holding research contracts with Lytix Biopharma, Promontory and Onxeo, has received consulting/advisory honoraria from Boehringer Ingelheim, AstraZeneca, OmniSEQ, Onxeo, The Longevity Labs, Inzen, Imvax, Sotio, Promontory, Noxopharm, EduCom, and the Luke Heller TECPR2 Foundation, and holds Promontory stock options.

Here, we describe an adaptation of conventional clonogenic assays that harnesses breast cancer PDTOs and live imaging to quantify PDTO radiosensitivity based on (1) the persistence of PTDO-forming stem-like cells upon PDTO irradiation in vitro, and (2) the growth rate of the PDTOs these cells (may) generate. Critical steps of this protocol include (1) the establishment of PDTOs to a dome occupancy enabling good viability, (2) PDTO exposure to ionizing irradiation at different doses, including mock irradiated control conditions; (3) PDTO dissociation into single cells; (4) replating of PDTO-derived single cells; and (5) live imaging until a predefined dome occupancy in control conditions.
With minimal modifications, mostly linked to PDTO-forming efficiency and PDTO growth rate in control conditions (which are likely to vary considerably across different PDTOs), we expect this protocol to be adaptable to multiple commercially available live imaging platforms, as well as to numerous PDTOs, of both mammary and non-mammary derivation. On the one hand, baseline PDTO-forming efficiency upon single-cell dispersion is expected to influence the number of single cells to be reseeded to obtain new PDTOs at a density that enables not only image-based PDTO quantification but also the normal growth of untreated PDTOs. On the other hand, the PDTO growth rate is expected to affect the duration of the assay, as the merging of adjacent PDTOs should be avoided to preserve optimal analytical capacities. Thus, determining PDTO-forming efficiency and PDTO growth rate in control conditions for each individual PDTO is critical for the correct implementation of this protocol.
While this method is found to be fairly straightforward, it has some limitations. First, an excessively low number of PDTO-forming cells may impair the regeneration of normally growing PDTOs upon single-cell dissociation. Indeed, while routine PDTO passaging can be achieved by incomplete dissociation, quantitative assessments, as offered by this protocol, rely on the generation of a single-cell suspension (which can be visually confirmed during counting). Second, an excessively slow growth rate may considerably extend the duration of the assay and potentially result in an imprecise estimation of radiosensitivity. It is indeed conceivable that an extended culture time as required for slow-growing PDTOs to reach an endpoint-compatible size may offer extra chances for sublethally irradiated PDTO-forming cells to recover from stress and restore&#160;detectable (though slow-growing) PDTOs. Finally, dissociating PDTOs shortly after irradiation is expected to impose added stress on PDTO-forming cells, potentially increasing radiosensitivity as a result of altered cell-cell communications in the early phases of recovery. Delaying dissociation of 24-72 h may provide insights into the relative contribution of preserved cell-cell communications to the ability of PDTO-forming cells to recover from macromolecular damage as imposed by RT.
While live imaging platforms offer a convenient method to monitor PDTO formation and growth longitudinally, single endpoint images can also be used for the same objective. In this case, attention should be paid to ensure that adjacent PDTOs do not merge prior to imaging, and growth rate can be assessed as a function of PDTO size normalized to the duration of the assay.
In the era of personalized cancer medicine, assessing the sensitivity of individual tumors to treatment is of the utmost importance as it provides some hints for the design of individualized therapeutic strategies with improved efficacy29. The protocol described herein fits into this endeavor by providing a convenient approach to estimating the cellular sensitivity of individual PDTOs to ionizing radiation (alone or combined with other therapeutic modalities). That said, whether measuring cancer cell radiosensitivity from PDTOs accurately predicts the response of individual patients with cancer to focal RT remains to be demonstrated. Correlating the radiosensitivity of distinct PDTOs to irradiation with the clinical response to RT of their respective donors will provide important insights into this possibility.

External beam radiation therapy (RT) is one of the mainstays of modern oncology, reflecting not only a pronounced anticancer activity associated with a well-defined spectrum of generally manageable side effects1, but also an exceptionally widespread clinical availability (most cancer centers in developed countries are equipped with modern linear accelerators for external beam RT)2. In line with this notion, RT is globally employed with success for both curative purposes, generally in the context of early-stage disease3,4, and palliative applications, to contain symptoms (e.g., pain) from metastatic tumors5. That said, not all malignancies are equally sensitive to RT, reflecting a number of cancer cell-intrinsic and microenvironmental features6,7,8,9. As a standalone example, various cancer-associated genetic and epigenetic alterations influencing DNA repair and redox homeostasis have been associated with increased or decreased intrinsic radiosensitivity, largely reflecting the ability of RT to kill cancer cells by causing direct and reactive oxygen species (ROS)-dependent damage to DNA and other macromolecules10,11,12,13.
Over the past decades, clonogenic assays have been routinely employed to assess the radiosensitivity of cultured human and murine cancer cells14,15,16. Indeed, while chemotherapeutics and other stressors often kill malignant cells in a fairly rapid manner, RT employed at clinically relevant doses most often elicit a delayed form of cell death that cannot be simply quantified with short-term flow cytometry- or microscopy-assisted techniques, such as measuring the cellular uptake of vital dyes (which selectively stain dead cells) 24-72 h after exposure to a cytotoxic stimulus17. Besides being straightforward and relying on rather inexpensive reagents, clonogenic assays have been particularly convenient as they allow for the implementation of the so-called &#34;linear quadratic&#34; model, which is a fairly simple mathematical tool for the quantitative analysis of RT dose response18,19. Along similar lines, cultured cancer cells (including established cell lines as well as primary, patient-derived cells) have provided a convenient platform for testing various aspects of cancer biology, including (but not limited to) sensitivity to treatment in a rather straightforward but simplified manner, one major limitation being the absence of a structured tumor microenvironment (TME)20,21. Indeed, two-dimensional cancer cell cultures are intrinsically unable to recapitulate cell-cell communications and interactions with the extracellular matrix and as they occur in cancer22,23. Patient-derived tumor organoids (PDTOs) have emerged as tumor models that at least in part circumvent such limitation24,25,26.
Unfortunately, conventional clonogenic assays cannot be employed to assess the radiosensitivity of PDTOs. On the one hand, irradiating established PDTOs may not necessarily compromise their growth as a multicellular unit, unless their stem-like compartment - which is responsible for the formation and maturation of PDTOs but exhibits increased resistance to DNA damage as compared to more differentiated PDTO-composing cells27- is completely eradicated. On the other hand, irradiating PDTO-derived single-cell suspensions may not properly recapitulate the radiosensitivity of PDTO-composing (including stem-like) cells as exhibited in the context of formed PDTOs. Here, we detail a technique that harnesses live imaging of breast cancer PDTOs to monitor the PDTO-forming efficacy and growth rate of PDTO-derived cells previously exposed to ionizing irradiation compared to their unirradiated counterparts. With required variations largely reflecting the differential biology of individual PDTOs (e.g., culture media requirements, growth rate), we expect this protocol to be suitable for the study of radiosensitivity in a wide panel of PTDOs of both mammary and non-mammary origin.

<table><tbody><tr><td>40 &amp;micro;m mesh filter</td><td>Thomas Scientific</td><td>1164H35</td><td></td></tr><tr><td>B27</td><td>Invitrogen</td><td>17504-044</td><td></td></tr><tr><td>Cellometer Auto T4 Bright Field Cell Counter</td><td>Nexcelom</td><td></td><td></td></tr><tr><td>DMEM F/12</td><td>Corning&amp;nbsp;</td><td>12634-010</td><td></td></tr><tr><td>Epidermal Growth Factor hEGF</td><td>Peprotech</td><td>AF-100-15</td><td></td></tr><tr><td>EVOS FL Digital Inverted Fluorescence Microscope&amp;nbsp;</td><td>Thermo Fisher Scientific</td><td>12-563-460</td><td></td></tr><tr><td>FGF10</td><td>Peprotech</td><td>100-26</td><td></td></tr><tr><td>FGF7</td><td>Peprotech&amp;nbsp;</td><td>100-19</td><td></td></tr><tr><td>GlutaMax</td><td>Invitrogen&amp;nbsp;</td><td>35050061</td><td></td></tr><tr><td>Hepes</td><td>Invitrogen&amp;nbsp;</td><td>15630-080</td><td></td></tr><tr><td>IncuCyte software 2021A</td><td>Sartorius</td><td></td><td>version: 2021A</td></tr><tr><td>Incucyte SX1</td><td>Sartorius</td><td></td><td>model SX1</td></tr><tr><td>Incucyte validated 48 well plate</td><td>Corning&amp;nbsp;</td><td>3548</td><td></td></tr><tr><td>Matrigel</td><td>Discovery Labware</td><td>354230</td><td></td></tr><tr><td>nAc</td><td>Sigma Aldrich&amp;nbsp;</td><td>A9165-5G</td><td></td></tr><tr><td>Nicotinamide</td><td>Sigma-Aldrich</td><td>N0636</td><td></td></tr><tr><td>Noggin</td><td></td><td></td><td>Purchased from the Englander Institute for Precision Medicine, Weill Cornell, NY, USA</td></tr><tr><td>Non-treated 6 well plate</td><td>Cellstar</td><td>657 185</td><td></td></tr><tr><td>NR (Heregulin)</td><td>Peprotech</td><td>100-03</td><td></td></tr><tr><td>p38 MAP inhibitor p38i SB202190</td><td>Sigma Aldrich&amp;nbsp;</td><td>S7067</td><td></td></tr><tr><td>PBS</td><td>Corning&amp;nbsp;</td><td>21-040-CV</td><td></td></tr><tr><td>PenStrep</td><td>Invitrogen</td><td>15140-122</td><td></td></tr><tr><td>Primocin</td><td>Invivogen</td><td>ant-pm-1</td><td></td></tr><tr><td>Rspondin Media</td><td></td><td></td><td>Purchased from the Englander Institute for Precision Medicine, Weill Cornell, NY, USA</td></tr><tr><td>Small Animal Radiation Research Platform (SARRP)&amp;nbsp;</td><td>Xstrahl Ltd</td><td></td><td></td></tr><tr><td>TGFbeta Receptor Inhibitor A83-01</td><td>Tocris</td><td>2939</td><td></td></tr><tr><td>Trypan blue Stain (0.4%)</td><td>Gibco</td><td>15250-61</td><td></td></tr><tr><td>TrypLE</td><td>Gibco</td><td>112605-028</td><td></td></tr><tr><td>Y-27632 (RhoKi)</td><td>Selleck</td><td>S1049</td><td></td></tr></tbody></table>

live imaging to quantify cellular radiosensitivity in patient-derived tumor organoids

Radiation therapy (RT) is one of the mainstays of modern clinical cancer management. However, not all cancer types are equally sensitive to irradiation, often (but not always) because of differences in the ability of malignant cells to repair oxidative DNA damage as elicited by ionizing rays. Clonogenic assays have been employed for decades to assess the sensitivity of cultured cancer cells to ionizing irradiation, largely because irradiated cancer cells often die in a delayed manner that is difficult to quantify with short-term flow cytometry- or microscopy-assisted techniques. Unfortunately, clonogenic assays cannot be employed as such for more complex tumor models, such as patient-derived tumor organoids (PDTOs). Indeed, irradiating established PDTOs may not necessarily abrogate their growth as multicellular units, unless their stem-like compartment is completely eradicated. Moreover, irradiating PDTO-derived single-cell suspensions may not properly recapitulate the sensitivity of malignant cells to RT in the context of established PDTOs. Here, we detail an adaptation of conventional clonogenic assays that involves exposure of established PDTOs to ionizing radiation, followed by single-cell dissociation, replating in suitable culture conditions and live imaging. Non-irradiated (control) PDTO-derived stem-like cells reform growing PDTOs with a PDTO-specific efficiency, which is negatively influenced by irradiation in a dose-dependent manner. In these conditions, PDTO-forming efficiency and growth rate can be quantified as a measure of radiosensitivity on time-lapse images collected until control PDTOs achieve a predefined space occupancy.

TNBC#1 PDTOs were exposed to a single radiation dose of 0 (unirradiated controls), 2 Gy, 4 Gy, 6 Gy, 8 Gy, or 10 Gy on day 0. Immediately thereafter, PDTOs were dissociated to obtain a single-cell suspension for each experimental condition. PDTO-derived cells were next seeded in 48-well plates within 66% matrigel domes (50 &#181;L each) deposited at the center of the wells, in 3 technical replicates per condition. Plates were placed in a live imaging system and imaged every 6 h using the organoid module 4X objective for a total of 30 days. Irradiation of TNBC#1 PDTOs with RT in a single dose of 2 Gy significantly delayed PDTO regrowth, while radiation doses &#8805;4 Gy (up to 10 Gy) completed prevented the regeneration of growing PDTOs (Figure 1).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66680/66680fig01.jpg" /> 
Figure 1: Live imaging of patient-derived tumor organoids (PDTOs). Breast cancer TNBC#1 patient-derived tumor organoids (PDTOs) were left untreated or exposed to the indicated radiation dose, shortly followed by dissociation, replating, and imaging with a live cell imaging system. Representative images upon contrast adjustment (A) and quantitative assessments (B, mean &#177; SEM) are reported. Image scale: 1.19 x 1.16 mm (1.38 mm2). Scale bar: 400 &#181;m; insets: 200 &#181;m. ****p &#60; 0.001 (two-way ANOVA, as compared to 0 Gy); ####p &#60; 0.001 (two-way ANOVA, as compared to 2 Gy). <a href="https://www.jove.com/files/ftp_upload/66680/66680fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Component</td>
			<td>Concentration</td>
		</tr>
		<tr>
			<td>DMEM F/12</td>
			<td>1X</td>
		</tr>
		<tr>
			<td>GlutaMax</td>
			<td>1X</td>
		</tr>
		<tr>
			<td>Hepes</td>
			<td>10 mM</td>
		</tr>
		<tr>
			<td>PenStrep</td>
			<td>100 U/mL</td>
		</tr>
		<tr>
			<td>B27</td>
			<td>1X</td>
		</tr>
		<tr>
			<td>nAc</td>
			<td>1.25 mM</td>
		</tr>
		<tr>
			<td>Nicotinamide</td>
			<td>10 mM</td>
		</tr>
		<tr>
			<td>TGFbeta Receptor Inhibitor A83-01</td>
			<td>0.5 &#956;M</td>
		</tr>
		<tr>
			<td>p38 MAP inhibitor p38i SB202190</td>
			<td>1 &#956;M</td>
		</tr>
		<tr>
			<td>Noggin</td>
			<td>10%</td>
		</tr>
		<tr>
			<td>Rspondin Media</td>
			<td>10%</td>
		</tr>
		<tr>
			<td>FGF10</td>
			<td>20 ng/mL</td>
		</tr>
		<tr>
			<td>FGF7</td>
			<td>5 ng/mL</td>
		</tr>
		<tr>
			<td>NR (Heregulin)</td>
			<td>5&#160;nM</td>
		</tr>
		<tr>
			<td>Primocin</td>
			<td>100&#160; &#956;g/mL</td>
		</tr>
		<tr>
			<td>Y-27632 (RhoKi)</td>
			<td>5&#160; &#956;M</td>
		</tr>
		<tr>
			<td>Epidermal Growth Factor hEGF</td>
			<td>5 ng/mL</td>
		</tr>
	</tbody>
</table>
Table 1: PDTO culture medium composition.

Read this Scientific Article Protocol about Live Imaging to Quantify Cellular Radiosensitivity in Patient-Derived Tumor Organoids at JoVE.com

Author Spotlight: Radiotherapy and Clonogenic Assays for Advancing Cancer Research and Personalized Medicine

Here, we detail a straightforward live imaging approach for quantifying the sensitivity of patient-derived tumor organoids to ionizing radiation.

Live Imaging to Quantify Cellular Radiosensitivity in Patient-Derived Tumor Organoids

Radiation therapy (RT) is one of the mainstays of modern clinical cancer management. However, not all cancer types are equally sensitive to irradiation, ...

live-imaging-to-quantify-cellular-radiosensitivity-patient-derived

Nanyang Technological University

Research

JoVE Journal

Cancer Research

727 Views.  Weill Cornell Medical College. Here, we detail a straightforward live imaging approach for quantifying the sensitivity of patient-derived tumor organoids to ionizing radiation. 

Video: Author Spotlight: Radiotherapy and Clonogenic Assays for Advancing Cancer Research and Personalized Medicine

Isolation and Characterization of Tumor-initiating Cells from Sarcoma Patient-derived Xenografts

The existence and importance of tumor-initiating cells (TICs) have been supported by increasing evidence during the past decade. These TICs have been shown to be responsible for tumor initiation, metastasis, and drug resistance. Therefore, it is important to develop specific TIC-targeting therapy in addition to current chemotherapy strategies, which mostly focus on the bulk of non-TICs. In order to further understand the mechanism behind the malignancy of TICs, we describe a method to isolate and to characterize TICs in human sarcomas. Herein, we show a detailed protocol to generate patient-derived xenografts (PDXs) of human sarcomas and to isolate TICs by fluorescence-activated cell sorting (FACS) using human leukocyte antigen class I (HLA-1) as a negative marker. Also, we describe how to functionally characterize these TICs, including a sphere formation assay and a tumor formation assay, and to induce differentiation along mesenchymal pathways. The isolation and characterization of PDX TICs provide clues for the discovery of potential targeting therapy reagents. Moreover, increasing evidence suggests that this protocol may be further extended to isolate and characterize TICs from other types of human cancers.

We describe a detailed protocol for the isolation of tumor-initiating cells from human sarcoma patient-derived xenografts by fluorescence-activated cell sorting, using human leukocyte antigen-1 (HLA-1) as a negative marker, and for the further validation and characterization of these HLA-1-negative tumor-initiating cells.

The existence and importance of tumor-initiating cells (TICs) have been supported by increasing evidence during the past decade. These TICs have been ...

Radionuclide-fluorescence Reporter Gene Imaging to Track Tumor Progression in Rodent Tumor Models

Metastasis is responsible for most cancer deaths. Despite extensive research, the mechanistic understanding of the complex processes governing metastasis remains incomplete. In vivo models are paramount for metastasis research, but require refinement. Tracking spontaneous metastasis by non-invasive in vivo imaging is now possible, but remains challenging as it requires long-time observation and high sensitivity. We describe a longitudinal combined radionuclide and fluorescence whole-body in vivo imaging approach for tracking tumor progression and spontaneous metastasis. This reporter gene methodology employs the sodium iodide symporter (NIS) fused to a fluorescent protein (FP). Cancer cells are engineered to stably express NIS-FP followed by selection based on fluorescence-activated cell sorting. Corresponding tumor models are established in mice. NIS-FP expressing cancer cells are tracked non-invasively in vivo at the whole-body level by positron emission tomography (PET) using the NIS radiotracer [18F]BF4-. PET is currently the most sensitive in vivo imaging technology available at this scale and enables reliable and absolute quantification. Current methods either rely on large cohorts of animals that are euthanized for metastasis assessment at varying time points, or rely on barely quantifiable 2D imaging. The advantages of the described method are: (i) highly sensitive non-invasive in vivo 3D PET imaging and quantification, (ii) automated PET tracer production, (iii) a significant reduction in required animal numbers due to repeat imaging options, (iv) the acquisition of paired data from subsequent imaging sessions providing better statistical data, and (v) the intrinsic option for ex vivo confirmation of cancer cells in tissues by fluorescence microscopy or cytometry. In this protocol, we describe all steps required for routine NIS-FP-afforded non-invasive in vivo cancer cell tracking using PET/CT and ex vivo confirmation of in vivo results. This protocol has applications beyond cancer research whenever in vivo localization, expansion and long-time monitoring of a cell population is of interest.

We describe a protocol for preclinical in vivo tracking of cancer metastasis. It is based on a radionuclide-fluorescence reporter combining the sodium iodide symporter, detected by non-invasive [18F]tetrafluoroborate-PET, and a fluorescent protein for streamlined ex vivo confirmation. The method is applicable for preclinical in vivo cell tracking beyond tumor biology.

Metastasis is responsible for most cancer deaths. Despite extensive research, the mechanistic understanding of the complex processes governing metastasis ...

High-sensitivity Detection of Micrometastases Generated by GFP Lentivirus-transduced Organoids Cultured from a Patient-derived Colon Tumor

Despite current advances in human colorectal cancer (CRC) treatment, few radical therapies are effective for the late stages of CRC. To overcome this clinical challenge, tumor xenograft mouse models using long-established human carcinoma cell lines and many transgenic mouse models with tumors have been developed as preclinical models. They partially mimic the features of human carcinomas, but often fail to recapitulate the key aspects of human malignancies including invasion and metastasis. Thus, alternative models that better represent the malignant progression in human CRC have long been awaited.
We herein show generation of patient-derived tumor xenografts (PDXs) by subcutaneous implantation of small CRC fragments surgically dissected from a patient. The colon PDXs develop and histopathologically resemble the CRC in the patient. However, few spontaneous micrometastases are detectable in conventional cross-sections of affected distant organs in the PDX model. To facilitate the detection of metastatic dissemination into distant organs, we extracted the tumor organoid cells from the colon PDXs in culture and infected them with GFP lentivirus prior to injection into highly immunodeficient NOD/Shi-scid IL2R&#947;null (NOG) mice. Orthotopically injected PDX-derived CRC organoid cells consistently form primary tumors positive for GFP in recipient mice. Moreover, spontaneously developing micrometastatic colonies expressing GFP are notably detected in the lungs of these mice by fluorescence microscopy. Moreover, intrasplenic injection of CRC organoids frequently produces hepatic colonization. Taken together, these findings indicate GFP-labelled PDX-derived CRC organoid cells to be visually detectable during a multistep process termed the invasion-metastasis cascade. The described protocols include the establishment of PDXs of human CRC and 3D culture of the corresponding CRC organoid cells transduced by GFP lentiviral particles.

To allow highly sensitive detection of the disseminating human colorectal cancer (CRC) cells colonizing tissues, we herein show a protocol for efficient transduction of green fluorescent protein (GFP) lentiviral particles into PDX-derived CRC organoid cells prior to their injection into recipient mice, with stereo-fluorescence microscopic observation.

Despite current advances in human colorectal cancer (CRC) treatment, few radical therapies are effective for the late stages of CRC. To overcome this ...

Live-Cell Imaging Assays to Study Glioblastoma Brain Tumor Stem Cell Migration and Invasion

Glioblastoma (GBM) is an aggressive brain tumor that is poorly controlled with the currently available treatment options. Key features of GBMs include rapid proliferation and pervasive invasion into the normal brain. Recurrence is thought to result from the presence of radio- and chemo-resistant brain tumor stem cells (BTSCs) that invade away from the initial cancerous mass and, thus, evade surgical resection. Hence, therapies that target BTSCs and their invasive abilities may improve the otherwise poor prognosis of this disease. Our group and others have successfully established and characterized BTSC cultures from GBM patient samples. These BTSC cultures demonstrate fundamental cancer stem cell properties such as clonogenic self-renewal, multi-lineage differentiation, and tumor initiation in immune-deficient mice. In order to improve on the current therapeutic approaches for GBM, a better understanding of the mechanisms of BTSC migration and invasion is necessary. In GBM, the study of migration and invasion is restricted, in part, due to the limitations of existing techniques which do not fully account for the in vitro growth characteristics of BTSCs grown as neurospheres. Here, we describe rapid and quantitative live-cell imaging assays to study both the migration and invasion properties of BTSCs. The first method described is the BTSC migration assay which measures the migration toward a chemoattractant gradient. The second method described is the BTSC invasion assay which images and quantifies a cellular invasion from neurospheres into a matrix. The assays described here are used for the quantification of BTSC migration and invasion over time and under different treatment conditions.

Here, we describe live-cell imaging techniques to quantitatively measure the migration and invasion of glioblastoma brain tumor stem cells over time and under multiple treatment conditions.

Glioblastoma (GBM) is an aggressive brain tumor that is poorly controlled with the currently available treatment options. Key features of GBMs include ...

Measuring Real-time Drug Response in Organotypic Tumor Tissue Slices

Tumor tissues are composed of cancerous cells, infiltrated immune cells, endothelial cells, fibroblasts, and extracellular matrix. This complex milieu constitutes the tumor microenvironment (TME) and can modulate response to therapy in vivo or drug response ex vivo. Conventional cancer drug discovery screens are carried out on cells cultured in a monolayer, a system critically lacking the influence of TME. Thus, experimental systems that integrate sensitive and high-throughput assays with physiological TME will strengthen the preclinical drug discovery process. Here, we introduce ex vivo tumor tissue slice culture as a platform for medium-high-throughput drug screening. Organotypic tissue slice culture constitutes precisely-cut, thin tumor sections that are maintained with the support of a porous membrane in a liquid-air interface. In this protocol, we describe the preparation and maintenance of tissue slices prepared from mouse tumors and tumors from patient-derived xenograft (PDX) models. To assess changes in tissue viability in response to drug treatment, we leveraged a biocompatible luminescence-based viability assay that enables real-time, rapid, and sensitive measurement of viable cells in the tissue. Using this platform, we evaluated dose-dependent responses of tissue slices to the multi-kinase inhibitor, staurosporine, and cytotoxic agent, doxorubicin. Further, we demonstrate the application of tissue slices for ex vivo pharmacology by screening 17 clinical and preclinical drugs on tissue slices prepared from a single PDX tumor. Our physiologically-relevant, highly-sensitive, and robust ex vivo screening platform will greatly strengthen preclinical oncology drug discovery and treatment decision making.&#160;

We introduce a protocol for measuring real-time drug response in organotypic tumor tissue slices. The experimental strategy outlined here provides a platform to carry out medium-high throughput drug screens on tissue slices derived from clinical or mouse tumors in ex vivo conditions.

Tumor tissues are composed of cancerous cells, infiltrated immune cells, endothelial cells, fibroblasts, and extracellular matrix. This complex milieu ...

Medium-Throughput Drug- and Radiotherapy Screening Assay using Patient-Derived Organoids

Patient-derived organoid (PDO) models allow for long-term expansion and maintenance of primary epithelial cells grown in three dimensions and a near-native state. When derived from resected or biopsied tumor tissue, organoids closely recapitulate in vivo tumor morphology and can be used to study therapy response in vitro. Biobanks of tumor organoids reflect the vast variety of clinical tumors and patients and therefore hold great promise for preclinical and clinical applications. This paper presents a method for medium-throughput drug screening using head and neck squamous cell carcinoma and colorectal adenocarcinoma organoids. This approach can easily be adopted for use with any tissue-derived organoid model, both normal and diseased. Methods are described for in vitro exposure of organoids to chemo- and radiotherapy (either as single-treatment modality or in combination). Cell survival after 5 days of drug exposure is assessed by measuring adenosine triphosphate (ATP) levels. Drug sensitivity is measured by the half-maximal inhibitory concentration (IC50), area under the curve (AUC), and growth rate (GR) metrics. These parameters can provide insight into whether an organoid culture is deemed sensitive or resistant to a particular treatment.

We describe detailed protocols to use patient-derived organoids for medium-throughput therapy sensitivity screenings. Therapies tested include chemotherapy, radiotherapy, and chemo-radiotherapy. Adenosine triphosphate levels are used as a functional readout.

Patient-derived organoid (PDO) models allow for long-term expansion and maintenance of primary epithelial cells grown in three dimensions and a ...

Profiling Sensitivity to Targeted Therapies in EGFR-Mutant NSCLC Patient-Derived Organoids

Novel 3D cancer organoid cultures derived from clinical patient specimens represent an important model system to evaluate intratumor heterogeneity and treatment response to targeted inhibitors in cancer. Pioneering work in gastrointestinal and pancreatic cancers has highlighted the promise of patient-derived organoids (PDOs) as a patient-proximate culture system, with an increasing number of models emerging. Similarly, work in other cancer types has focused on establishing organoid models and optimizing culture protocols. Notably, 3D cancer organoid models maintain the genetic complexity of original tumor specimens and thus translate tumor-derived sequencing data into treatment with genetically informed targeted therapies in an experimental setting. Further, PDOs might foster the evaluation of rational combination treatments to overcome resistance-associated adaptation of tumors in the future. The latter focuses on intense research efforts in non-small-cell lung cancer (NSCLC), as resistance development ultimately limits the treatment success of targeted inhibitors. An early assessment of therapeutically targetable mechanisms using NSCLC PDOs could help inform rational combination treatments. This manuscript describes a standardized protocol for the cell culture plate-based assessment of drug sensitivities to targeted inhibitors in NSCLC-derived 3D PDOs, with potential adaptability to combinational treatments and other treatment modalities.

This protocol describes a standardized evaluation of drug sensitivities to targeted signaling inhibitors in NSCLC patient-derived organoid models.

Novel 3D cancer organoid cultures derived from clinical patient specimens represent an important model system to evaluate intratumor heterogeneity and ...

Multiparametric Tumor Organoid Drug Screening Using Widefield Live-Cell Imaging for Bulk and Single-Organoid Analysis

Patient-derived tumor organoids (PDTOs) hold great promise for preclinical and translational research and predicting the patient therapy response from ex vivo drug screenings. However, current adenosine triphosphate (ATP)-based drug screening assays do not capture the complexity of a drug response (cytostatic or cytotoxic) and intratumor heterogeneity that has been shown to be retained in PDTOs due to a bulk readout. Live-cell imaging is a powerful tool to overcome this issue and visualize drug responses more in-depth. However, image analysis software is often not adapted to the three-dimensionality of PDTOs, requires fluorescent viability dyes, or is not compatible with a 384-well microplate format. This paper describes a semi-automated methodology to seed, treat, and image PDTOs in a high-throughput, 384-well format using conventional, widefield, live-cell imaging systems. In addition, we developed viability marker-free image analysis software to quantify growth rate-based drug response metrics that improve reproducibility and correct growth rate variations between different PDTO lines. Using the normalized drug response metric, which scores drug response based on the growth rate normalized to a positive and negative control condition, and a fluorescent cell death dye, cytotoxic and cytostatic drug responses can be easily distinguished, profoundly improving the classification of responders and non-responders. In addition, drug-response heterogeneity can by quantified from single-organoid drug response analysis to identify potential, resistant clones. Ultimately, this method aims to improve the prediction of clinical therapy response by capturing a multiparametric drug response signature, which includes kinetic growth arrest and cell death quantification.

This protocol describes a semi-automated method for medium- to high-throughput organoid drug screenings and microscope-agnostic, automated image analysis software to quantify and visualize multiparametric, single-organoid drug responses to capture intratumor heterogeneity.

Patient-derived tumor organoids (PDTOs) hold great promise for preclinical and translational research and predicting the patient therapy response from ex ...

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

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.

Author Spotlight: Developing Multiplexed Kinetic Assays for Organoid-Based Drug Response Analysis

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 ...

Growth and Characterization of Irradiated Organoids from Mammary Glands

Organoids derived from the digested tissue are multicellular three-dimensional (3D) constructs that better recapitulate in vivo conditions than cell monolayers. Although they cannot completely model in vivo complexity, they retain some functionality of the original organ. In cancer models, organoids are commonly used to study tumor cell invasion. This protocol aims to develop and characterize organoids from the normal and irradiated mouse mammary gland tissue to evaluate the radiation response in normal tissues. These organoids can be applied to future in vitro cancer studies to evaluate tumor cell interactions with irradiated organoids. Mammary glands were resected, irradiated to 20 Gy and digested in a collagenase VIII solution. Epithelial organoids were separated via centrifugal differentiation, and 3D organoids were developed in 96-well low-adhesion microplates. Organoids expressed the characteristic epithelial marker cytokeratin 14. Macrophage interaction with the organoids was observed in co-culture experiments. This model may be useful for studying tumor-stromal interactions, infiltration of immune cells, and macrophage polarization within an irradiated microenvironment.

Organoids developed from mouse mammary glands were irradiated and characterized to assess epithelial traits and interactions with immune cells. Irradiated organoids can be used to better evaluate cell-cell interactions that may lead to tumor cell recruitment in irradiated normal tissue.

Organoids derived from the digested tissue are multicellular three-dimensional (3D) constructs that better recapitulate in vivo conditions than cell ...