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 con...

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 border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>40 &#181;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&#160;</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&#160;</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&#160;</td>
			<td>100-19</td>
			<td></td>
		</tr>
		<tr>
			<td>GlutaMax</td>
			<td>Invitrogen&#160;</td>
			<td>35050061</td>
			<td></td>
		</tr>
		<tr>
			<td>Hepes</td>
			<td>Invitrogen&#160;</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&#160;</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&#160;</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&#160;</td>
			<td>S7067</td>
			<td></td>
		</tr>
		<tr>
			<td>PBS</td>
			<td>Corning&#160;</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)&#160;</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 ...

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

Research

JoVE Journal

Cancer Research

722 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 ...

Drug Screening of Primary Patient Derived Tumor Xenografts in Zebrafish

Patient derived xenograft models are critical in defining how different cancers respond to drug treatment in an in vivo system. Mouse models are the standard in the field, but zebrafish have emerged as an alternative model with several advantages, including the ability for high-throughput and low-cost drug screening. Zebrafish also allow for in vivo drug screening with large replicate numbers that were previously only obtainable with in vitro systems. The ability to rapidly perform large scale drug screens may open up the possibility for personalized medicine with rapid translation of results back to clinic. Zebrafish xenograft models could also be used to rapidly screen for actionable mutations based on tumor response to targeted therapies or to identify new anti-cancer compounds from large libraries. The current major limitation in the field has been quantifying and automating the process so that drug screens can be done on a larger scale and be less labor-intensive. We have developed a workflow for xenografting primary patient samples into zebrafish larvae and performing large scale drug screens using a fluorescence microscope equipped imaging unit and automated sampler unit. This method allows for standardization and quantification of engrafted tumor area and response to drug treatment across large numbers of zebrafish larvae. Overall, this method is advantageous over traditional cell culture drug screening as it allows for growth of tumor cells in an in vivo environment throughout drug treatment, and is more practical and cost-effective than mice for large scale in vivo drug screens.

Zebrafish xenograft models allow for high-throughput drug screening and fluorescent imaging of human cancer cells in an in vivo microenvironment. We developed a workflow for large scale, automated drug screening on patient-derived leukemia samples in zebrafish using an automated fluorescence microscope equipped imaging unit.

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

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

An understanding of drug resistance and the development of novel strategies to sensitize highly resistant cancers rely on the availability of suitable preclinical models that can accurately predict patient responses. One of the disadvantages of existing preclinical models is the inability to contextually preserve the human tumor microenvironment (TME) and accurately represent intratumoral heterogeneity, thus limiting the clinical translation of data. By contrast, by representing the culture of live fragments of human tumors, the patient-derived explant (PDE) platform allows drug responses to be examined in a three-dimensional (3D) context that mirrors the pathological and architectural features of the original tumors as closely as possible. Previous reports with PDEs have documented the ability of the platform to distinguish chemosensitive from chemoresistant tumors, and it has been shown that this segregation is predictive of patient responses to the same chemotherapies. Simultaneously, PDEs allow the opportunity to interrogate molecular, genetic, and histological features of tumors that predict drug responses, thereby identifying biomarkers for patient stratification as well as novel interventional approaches to sensitize resistant tumors. This paper reports PDE methodology in detail, from collection of patient samples through to endpoint analysis. It provides a detailed description of explant derivation and culture methods, highlighting bespoke conditions for particular tumors, where appropriate. For endpoint analysis, there is a focus on multiplexed immunofluorescence and multispectral imaging for the spatial profiling of key biomarkers within both tumoral and stromal regions. By combining these methods, it is possible to generate quantitative and qualitative drug response data that can be related to various clinicopathological parameters and thus potentially be used for biomarker identification.

This paper describes methods for the generation, drug treatment, and analysis of patient-derived explants for assessing tumor drug responses in a live, patient-relevant, preclinical model system.

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

High-Throughput In Vitro Assay using Patient-Derived Tumor Organoids

Patient-derived tumor organoids (PDOs) are expected to be a preclinical cancer model with better reproducibility of disease than traditional cell culture models. PDOs have been successfully generated from a variety of human tumors to recapitulate the architecture and function of tumor tissue accurately and efficiently. However, PDOs are unsuitable for an in vitro high-throughput assay system (HTS) or cell analysis using 96-well or 384-well plates when evaluating anticancer drugs because they are heterogeneous in size and form large clusters in culture. These cultures and assays use extracellular matrices, such as Matrigel, to create tumor tissue scaffolds. Therefore, PDOs have a low throughput and high cost, and it has been difficult to develop a suitable assay system. To address this issue, a simpler and more accurate HTS was established using PDOs to evaluate the potency of anticancer drugs and immunotherapy. An in vitro HTS was created that uses PDOs established from solid tumors cultured in 384-well plates. An HTS was also developed for assessment of antibody-dependent cellular cytotoxicity activity to represent the immune response using PDOs cultured in 96-well plates.

High-Throughput In Vitro Assay using Patient-Derived Tumor Organoids

A highly accurate in vitro high-throughput assay system was developed to evaluate anticancer drugs using patient-derived tumor organoids (PDOs), similar to cancer tissues but are unsuitable for in vitro high-throughput assay systems with 96-well and 384-well plates.

Patient-derived tumor organoids (PDOs) are expected to be a preclinical cancer model with better reproducibility of disease than traditional cell culture ...

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 ...

Establishing 3-Dimensional Spheroids from Patient-Derived Tumor Samples and Evaluating their Sensitivity to Drugs

Despite remarkable advances in understanding tumor biology, the vast majority of oncology drug candidates entering clinical trials fail, often due to a lack of clinical efficacy. This high failure rate illuminates the inability of the current preclinical models to predict clinical efficacy, mainly due to their inadequacy in reflecting tumor heterogeneity and the tumor microenvironment. These limitations can be addressed with 3-dimensional (3D) culture models (spheroids) established from human tumor samples derived from individual patients. These 3D cultures represent real-world biology better than established cell lines that do not reflect tumor heterogeneity. Furthermore, 3D cultures are better than 2-dimensional (2D) culture models (monolayer structures) since they replicate elements of the tumor environment, such as hypoxia, necrosis, and cell adhesion, and preserve the natural cell shape and growth. In the present study, a method was developed for preparing primary cultures of cancer cells from individual patients that are 3D and grow in multicellular spheroids. The cells can be derived directly from patient tumors or patient-derived xenografts. The method is widely applicable to solid tumors (e.g., colon, breast, and lung) and is also cost-effective, as it can be performed in its entirety in a typical cancer research/cell biology lab without relying on specialized equipment. Herein, a protocol is presented for generating 3D tumor culture models (multicellular spheroids) from primary cancer cells and evaluating their sensitivity to drugs using two complementary approaches: a cell-viability assay (MTT) and microscopic examinations. These multicellular spheroids can be used to assess potential drug candidates, identify potential biomarkers or therapeutic targets, and investigate the mechanisms of response and resistance.

The present protocol describes generating 3D tumor culture models from primary cancer cells and evaluating their sensitivity to drugs using cell-viability assays and microscopic examinations.

Despite remarkable advances in understanding tumor biology, the vast majority of oncology drug candidates entering clinical trials fail, often due to a ...

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

Organoids are 3D dynamic tumor models that can be grown successfully from patient-derived ovarian tumor tissue, ascites, or pleural fluid and aid in the discovery of novel therapeutics and predictive biomarkers for ovarian cancer. These models recapitulate clonal heterogeneity, the tumor microenvironment, and cell-cell and cell-matrix interactions. Additionally, they have been shown to match the primary tumor morphologically, cytologically, immunohistochemically, and genetically. Thus, organoids facilitate research on tumor cells and the tumor microenvironment and are superior to cell lines. The present protocol describes distinct methods to generate patient-derived ovarian cancer organoids from patient tumors, ascites, and pleural fluid samples with a higher than 97% success rate. The patient samples are separated into cellular suspensions by both mechanical and enzymatic digestion. The cells are then plated utilizing a basement membrane extract (BME) and are supported with optimized growth media containing supplements specific to the culturing of high-grade serous ovarian cancer (HGSOC). After forming initial organoids, the PDOs can sustain long-term culture, including passaging for expansion for subsequent experiments.

Patient-derived organoids (PDO) are a three-dimensional (3D) culture that can mimic the tumor environment in vitro. In high-grade serous ovarian cancer, PDOs represent a model to study novel biomarkers and therapeutics.

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

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

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Rozdziały w tym wideo

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

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

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

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

Drug Screening of Primary Patient Derived Tumor Xenografts in Zebrafish

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

High-Throughput In Vitro Assay using Patient-Derived Tumor Organoids

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

Establishing 3-Dimensional Spheroids from Patient-Derived Tumor Samples and Evaluating their Sensitivity to Drugs

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