Login processing...

Trial ends in Request Full Access Tell Your Colleague About Jove

Cancer Research

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

doi: 10.3791/59696 Published: July 5, 2019
* These authors contributed equally


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


In this protocol, we outline the procedure for generation of tumor spheroids within 384-well hanging droplets to allow for high-throughput screening of anti-cancer therapeutics in a physiologically representative microenvironment. We outline the formation of patient derived cancer stem cell spheroids, as well as, the manipulation of these spheroids for thorough analysis following drug treatment. Specifically, we describe collection of spheroid morphology, proliferation, viability, drug toxicity, cell phenotype and cell localization data. This protocol focuses heavily on analysis techniques that are easily implemented using the 384-well hanging drop platform, making it ideal for high throughput drug screening. While we emphasize the importance of this model in ovarian cancer studies and cancer stem cell research, the 384-well platform is amenable to research of other cancer types and disease models, extending the utility of the platform to many fields. By improving the speed of personalized drug screening and the quality of screening results through easily implemented physiologically representative 3D cultures, this platform is predicted to aid in the development of new therapeutics and patient-specific treatment strategies, and thus have wide-reaching clinical impact.


or Start trial to access full content. Learn more about your institution’s access to JoVE content here

Worldwide cancer-related mortality reached a toll of 9.8 million deaths in 20181, highlighting the need for the development of improved therapeutics. Unfortunately, the cost of developing cancer drugs is increasing, with the development of a single drug costing approximately 650 million USD2 indicating the need for improved strategies to develop new anti-cancer drugs. Cancer stem cells (CSCs), which are characterized by increased chemoresistance3, the capacity to self-renew, and the ability to seed new tumors4 are thought to be responsible for tumor recurrence4, metastasis5, and chemoresistance4,6, which all contribute to the malignant capacity of the tumor and thus the high death toll. In ovarian cancer, these cells are found enriched in the malignant ascites fluid in the peritoneal cavity, a condition associated with poor clinical outcomes1. As a result of the malignant capabilities of CSCs, there has been a push to develop new CSC targeting drugs to use in conjunction with traditional chemotherapies. There are several challenges that accompany the development of CSC targeting drugs including: 1) difficulty in expanding and maintaining CSCs in vitro; 2) scarcity of patient samples; 3) physiological relevance of the culture platform; and 4) heterogeneity in drug sensitivity between patients. This protocol outlines the implementation of a high throughput 3D culture platform that can overcome each of these challenges. In particular, this system allows for rapid drug screening using small numbers of patient-derived ovarian CSCs, and is highly amenable to downstream analysis techniques. While ideal for studying ovarian cancer and CSCs, our platform is also valuable in studying other cancers and differentiated cell types in complex 3D environments.

Complex 3-dimensional (3D) models are critical in studying the tumor microenvironment (TME), which is a 3D niche made up of cancer cells, non-cancer supporting cells, and extracellular matrix (ECM) proteins4. This 3D environment results in unique cell morphology, cell-cell and cell-matrix interactions, cell differentiation, cell migration, cell density, and diffusion gradients compared to traditional 2D cell culture in vitro4. All of these factors culminate in differential drug response within 3D cultures, exhibiting increased drug resistance and physiological relevance7,8. Due to the role of the 3D TME in CSC differentiation and chemoresistance, it is vital to screen for CSC targeting drugs in physiologic microenvironments. Improving the physiological relevance of CSC drug screening platforms has the potential to improve patient specific drug screening, drug development, formulation of treatment strategies, and ultimately clinical outcomes. It is equally important that the platform used for drug screening be high-throughput and compatible with downstream analysis methods to minimize cost, time, and clinical translation time of promising drugs9.

Currently, the complex TME is best maintained for drug screening applications through in vivo models such as murine syngeneic tumor models, cell line-derived xenografts, and patient-derived xenograft (PDX) models12, as they provide physiologic conditions. However, the low-throughput nature of these models, as well as, the cost, time, and technical skill sets that they require limits their utility in rapid, high throughput drug screening applications13. As alternatives to these in vivo models, many in vitro 3D models utilizing hydrogels8, culture within microfluidic devices or ‘organ-on-a-chip’ devices10,14, and non-adherent cultures3,8 have also been developed, due to their low barrier to entry in terms of cost, time, and required skillset.

Hydrogel culture platforms are advantageous in the fine control afforded over the matrix composition, mechanical properties, and matrix structure15; however, they can inhibit high density cell culture14. Additionally, harvesting cells from hydrogels can complicate downstream analysis, due to potentially harmful effects of harvesting methods15. Microfluidic devices, on the other hand, are microscale devices that allow for output detection within the same device and for cell culture at physiologically relevant scales with minimal consumption of reagents, decreased reaction time, minimized waste, and rapid diffusion14. These characteristics make them promising platforms for investigating drug toxicity, efficacy, and pharmacokinetics. However, the challenges of efficient, quantifiable, reproducible, and user-friendly 3D cell culture, as well as, bulky and costly pumping systems have restricted microfluidic applications in high-throughput research10. Efficient detection setups and potentially difficult implementation across fields have also hindered widespread adoption of microfluidic systems10.

Contrarily, spheroids generated in non-adherent conditions in rotating mixers (nutators), ultra-low attachment plates, and hanging droplets do not include user-defined matrix components. These methodologies are especially relevant for studying ovarian cancer as the non-adherent conditions are representative of the conditions in which spheroids grow within the peritoneal cavity5. Within these non-adherent culture methods, nutator and hanging drop spheroids have been shown to exhibit higher compaction, remodeling, and chemoresistance compared to spheroids generated in ultra-low attachment plates, suggesting increased physiological relevance16,17,18,19. Due to increased capacity for high-throughput screening from smaller well sizes and minimal required cell numbers, spheroid generation in hanging drop plates is an ideal platform for drug screening. Here, we present a tunable 3D physiologic platform in 384-well hanging drop plates, that is easy to implement and highly amenable to downstream analysis, making it ideal for high throughput drug screening of ovarian cancer and ovarian CSCs.

Our 3D physiologic platform provides all of the advantages of 3D culture, including physiological cell-cell contacts, diffusion gradients, cell densities, and naturally produced ECM proteins, which may contribute to realistic drug responses16,17,18,19. Additionally, by generating these spheroids with patient-derived CSCs, we are able to determine patient specific responses to drugs1 with many technical replicates simultaneously, to overcome heterogeneity that may be found within patient tumor samples20. Furthermore, 3D culture has been shown to enhance maintenance of CSC populations3,16 and thus is representative of enriched CSC populations in the ascites7. This combined with easy downstream analysis, including flow cytometry analysis of viability and CSC proportions allows for optimal evaluation of CSC targeting drug efficacy. Finally, this physiologic platform is compatible with imaging at multiple time points during the experiment, evaluation of cell death and proliferation, cell organization and morphology with immunohistochemistry, soluble signaling with ELISA on conditioned medium, cell phenotypes with flow cytometry, and gene expression following PCR.

Subscription Required. Please recommend JoVE to your librarian.


or Start trial to access full content. Learn more about your institution’s access to JoVE content here

All patient samples are collected under an approved IRB protocol from consenting patients, whose samples are de-identified after tumor debulking and ascites collection.

1. Generation of Spheroids from Small Cell Numbers in 384-well Hanging Drop Plates

  1. Place the hanging drop plate in a sonicator filled with sterile deionized (DI) water and sonicate for 20 min.
  2. With a gloved hand, remove the plate from the sonicator and wash it with running DI water.
  3. Allow the plate to sit in a bath of 0.1% Pluronic acid for 24 h to prevent protein adsorption and spheroid adherence to the wells.
  4. Remove plates with a gloved hand and rinse both sides of the plate with running DI water thoroughly.
  5. Vigorously tap or shake the plate inside a biosafety cabinet to remove water from the wells in a sterile environment.
  6. Place the plate under UV light for 30–60 min on each side to sterilize the plates and minimize contamination.
    NOTE: The plate can also be exposed to ethylene oxide gas in a chamber for sterilization.
  7. Fill each well of a 6-well plate with 4–5 mL of sterile autoclaved DI water and sandwich the hanging drop plate between the lid and the bottom of the 6-well plate. Add 800–1,000 μL of sterile DI water around the rim of the hanging drop plate to provide a humid, stable, and sterile environment to minimize volume lost to evaporation (Figure 1 A-C).
  8. For 2D grown cells, aspirate medium covering cells in their log phase of growth and wash with 1x phosphate buffered saline (PBS) to remove traces of fetal bovine serum (FBS) in the growth medium, as it hampers the action of trypsin.
  9. Aspirate the PBS and add 1.5-2 mL of 0.25% trypsin-EDTA to the 100 mm tissue culture dish. Incubate cells for 5 min in an incubator set to 37 °C.
    NOTE: Cells may detach at different rates, so plates should be checked on a benchtop light microscope to ensure cell detachment after 5 min. Adjust detachment protocol per vendor instructions when using a cell line.
  10. Add 6–8 mL of cellular medium containing FBS or any serum to the dish to neutralize the trypsin, collect cells with a 10 mL serological pipet, and deposit them in a 15 mL conical tube.
  11. Count cells by loading 10 μL of the cell suspension on each side of a hemocytometer and follow the associated counting protocol.
  12. For patient-derived cells collected from primary or metastatic solid tumors or from ascites that have not been 2D cultured, prepare single cell suspensions in serum free medium (SFM) described previously3.
  13. Process tumor tissues as previously described and store single cell suspensions for later use in appropriate freezing medium21,22.
    1. For solid tumor tissue, mince mechanically with a razor blade and filter resulting solution through a 40 μm filter before isolating desired cells from a density gradient21,22.
    2. For ascites samples, concentrate cells by centrifugation, lyse red blood cells in ammonium-chloride-potassium (ACK) buffer, wash in 1x PBS, and then pass through a 40 μm filter and a 28 G needle 4 times22.
  14. For isolation of ovarian CSCs, sort cells with flow cytometry as described below in detail.
  15. Freshly isolated single cells are frozen for storage and thawed when needed for experimentation.
  16. To prepare the cell suspension for plating, calculate the desired volume of cell solution required for plating: 20 μL per drop X total number of droplets = total solution volume needed.
  17. Dilute cell concentration to the desired cell concentration per 20 μL (i.e., 100 cells in a 20 μL drop).
  18. Mix the cell suspension gently using a pipet before before plating to ensure homogeneous distribution of cells and improve uniformity between droplets.
    NOTE: Overmixing of the cell suspension may lead to cell death and debris in the hanging drop spheroids.
  19. Place the tip of the pipette in the well at an angle of approximately 45° and pipet 20 μL of the cell solution into each hanging drop well.
    NOTE: Plating patterns can be adjusted depending on number of spheroids needed. Plating spheroids in every other well is safer when large quantities of spheroids are not needed in an experiment, because it prevents accidental merging of the droplets (Figure 1D, E). If large quantities of spheroids are needed for an experiment, plate every well leaving one row of border wells on all sides (Figure 1F).
  20. Place the lid of the 6-well plate back on top of the hanging drop plate and use a stretchy thermoplastic strip that is insensitive to moisture loss, to seal the edges and prevent additional evaporation of droplets. Incubate in a standard CO2 humidified incubator (5% CO2, 37 °C).
  21. Feed hanging drops once every 2–3 days to replenish cell culture medium for necessary nutrients by adding 2–3 μL to each spheroid containing well.
    NOTE: After imaging, it is always advised to feed the hanging drops, as air exposure during imaging leads to evaporation.

2. Adding Cell Culture Medium to Hanging Drop Spheroid Plates

  1. Remove the thermoplastic strip and lid within a biosafety cabinet and add 2–3 μL of the appropriate culture medium to each well containing a hanging drop.
    NOTE: The volume added will depend on drop size and the amount of time between feedings.
  2. After feeding, cover the plate with the top lid and apply fresh thermoplastic strip to the outside edges before putting the plate back in the incubator.

3. Phase Contrast Imaging of Spheroid Morphology

  1. Remove the thermoplastic strip from around the edges of the plate in a biosafety cabinet.
  2. Carefully remove the 384-well hanging drop spheroids plate from the biosafety cabinet with the lid still in place and place it in the microscope tray at an epifluorescent microscope.
  3. Use the live imaging option in the imaging software at 4x, 10x or 20x to observe the hanging drop spheroids and take desired images.
  4. After saving the images, take the plate back to the biosafety cabinet and feed cells as described above.
  5. Reseal plate with a fresh thermoplastic strip and place the sealed plate back in the incubator.

4. Quantification of Proliferation and Viability within Spheroids

  1. Plate spheroids in a sufficient number of wells to obtain >10 technical replicates for each time point (i.e., day 1 and day 7) that is to be examined.
    NOTE: Wells that are used for this assay are generally not used again due to potential contaminants from the resazurin dye.
  2. Add 2 μL of filtered resazurin-based solution to the wells designated for proliferation analysis as if feeding those wells and incubate for a pre-determined incubation period.
    NOTE: This incubation time can vary based on cell type and the number of cells in the spheroid. It is advised to determine the required incubation time needed prior to beginning proliferation experiments by beginning measurements after 1 hour incubation and then re-measuring every 30 min until the signal readouts in control wells plateau. Assay readings can be taken as many times as desired. Incubation is typically 4 h for spheroids initiated with 100 cancer cells.
  3. Turn on the microplate reader first followed by the associated plate reader software at least 15 min prior to first reading to allow for the machine to warm up and secure the internal temperature at 22 °C as temperature can affect the readings.
  4. Open a 384-well plate protocol set with 530/25 nm excitation and 590/35 nm emission wavelengths with Optics set to Bottom, Gain set to 35, Read Speed set to Normal, and read type set to Fluorescence.
  5. After the incubation period, open the hanging drop sandwich in a biosafety cabinet and bring the 384-well plate with the lid still in place to the plate reader.
  6. Place the 384-well plate with the lid still in place in the plate reader tray, which will be extended once the machine is warmed up and click Ok to read the plate.
  7. Return the well plate to the 6-well base and place it in the incubator. If all time points have been read for the day, reseal the plate before placing it back in the incubator.
  8. Save the experiment in the pop-up window and then click Yes when prompted Do you want to execute PowerExports for Plate 1 to output data from the plate reader software into a spreadsheet for organization.
  9. Average fluorescence values for each condition and normalize by the average of the control condition to report fold change in proliferation in various experimental conditions.
  10. When comparing day 1 to day 7, normalize by dividing by day 1 average fluorescence to obtain fold change in proliferation over time.
  11. Calculate error bars using standard error of the mean and determine statistical significance between experimental groups with an appropriate statistical test, like the student’s two-tailed T test.

5. Evaluation of Drug Toxicity in Spheroids

  1. Drug administration
    1. At any time following spheroid formation, deliver drug diluted to the desired concentration such that a 2 μL dose contains 10x the desired final drug concentration.
      NOTE: This is assuming an evaporation of 2 μL from the droplet so that the ending volume post drug treatment is 20 μL. For example, a 50 μM dose of cisplatin will have a prepared solution of 500 μM. If droplets contain more than 20 μL, the concentration of drug and/or the volume added should be adjusted accordingly.
    2. Treat control samples with 2 μL of cell culture medium.
      NOTE: Cisplatin is solubilized in water. Therefore, controls are 2 μL of cell culture medium; however, if the drug vehicle is a different solvent (e.g., DMSO), then controls should be cell culture medium with an equal concentration of DMSO as used in the drug treatment.
    3. Continue to monitor the drug treated and the control spheroids throughout the drug incubation period with phase microscopy to have a visual record of the effect of drug toxicity as well as with resazurin dye as described above to monitor cellular viability.
      NOTE: Typically, the drugs are added after 5–7 days in the hanging drops and toxicity measured after 48–-72 hs but this can be varied depending on the experiment. Drugs can be added as soon as stable spheroids have formed, usually between 1–4 days.
  2. Drug toxicity quantification by cell counting
    1. At the end time point of drug treatment, collect 10 spheroids each from control and drug treated wells using a 1,000 μL pipet and deposit each set of spheroids into its own microcentrifuge tube.
    2. Break down the spheroids into single cells by repeated pipetting.
      NOTE: To reduce potential cell damage due to repeated pipetting, enzymatic digestion with an enzyme such as trypsin can be performed to facilitate generation of single cell solutions prior to pipetting23. Minimization of cell death due to pipetting will depend on the cell type and should be optimized accordingly. If concerned about death due to disaggregation, refer to analysis with resazurin dye and the cytotoxicity assay for alternative methods that do not require spheroid disaggregation.
    3. Centrifuge the tubes for 5 min at 400 x g to collect cells at the bottom of microcentrifuge tubes and aspirate the supernatant.
    4. Add 20 μL of fresh media or 1x PBS to each tube and mix well.
    5. Add Trypan blue at a ratio of 2 μL of Trypan blue stain to 20 μL of cell suspension.
    6. Load 10 μL of cells and Trypan blue suspension into each chamber of the hemocytometer and count cells under a light microscope, with blue stained cells representing dead cells and unstained cells representing live cells.
      1. The live cell % = (Number of live cells ÷ total number of cells) x 100.

6. Spheroid Characterization with Histological Techniques

NOTE: There are two mold options 3D printed in a biocompatible polymer to replicate spheroid array molds made by Ivanov et al.24: 1) 20 well mold that can hold 28 μL per well and 2) 63 well mold that can hold 9 μL per well (Figure 2D).

  1. Sterilize histology mold and its border by wiping them down with 70% ethanol and attach the border firmly around the mold and lay the mold upright. Both molds fit approximately 3 mL of fluid (3.203 mL for the 20 spheroid array and 3.196 mL for the 63 spheroid array).
  2. Lightly coat the spheroid array with 10,000 cSt Si oil using a pointed cotton swab to facilitate removal of the specimen processing gel cast in subsequent steps.
  3. Warm up specimen processing gel until liquefied via microwave for 10–20 s with the cap loosened.
  4. Add between 2.6 and 2.8 mL of molten processing gel into the mold until approximately level with the top of the border.
  5. In a few minutes, once solidified, remove the processing gel cast by separating the border from the mold and then inverting the array mold.
  6. Insert tweezer tip between mold and the border to carefully separate them and then use a cell scraper to help dislodge the cast from the mold if it does not detach right away.
  7. Harvest the spheroids from the hanging drop plate by pipetting the contents of a single well onto a 100 or 150 mm cell petri dish with a 1,000 μL pipet, and isolate the spheroid visually.
  8. Pipet 5 μL of the well contents including the identified spheroid into one of the array wells, until the array is filled.
  9. Wait 3 min to ensure spheroids have settled to the bottom of the array before gently pipetting molten processing gel into each of the wells being careful not to disturb the spheroids.
  10. Add additional processing gel to level off the top of the array and once cooled, place the solidified spheroid array into a labeled cassette for processing.
  11. Submerge labeled cassette in 4% formalin overnight to fix the spheroids at 4 °C and then store in 70% ethanol at 4 °C until ready for processing.
  12. Process with standard 1 h paraffin program and then embed the spheroid arrays such that the processed arrays are facing upright with the bottom of the wells closest to the block face.
  13. Ensure that the arrays are embedded as flat as possible, with the bottom face flush with the bottom of the block and place blocks on ice.
  14. Load the block onto the microtome and adjust the block such that the blade is parallel with the loaded block face.
  15. Cut array (sample depth = 15 μm) until the bottom of the array wells are reached making sure that the circular wells are visible on cut samples.
  16. Switch to a 5 μm sample depth and continue to slice and collect ribbons. Check under the microscope every few slices to determine if spheroid depth has been reached. Once spheroids are reached collect each subsequent slide until the spheroids are no longer visible.
  17. Stain each slide with standard H&E protocol.

7. Live Dead Cytotoxicity Assay

  1. To each hanging drop, add the live cell dye, calcein-AM to the final concentration of 2 μM, and the dead cell dye, ethidium homodimer-1 to the final concentration of 4 μM, keeping in mind that the drop volume is 20 μL.
    NOTE: Try to keep volumes added to a minimum, and typically add 2 μL of the dyes combined.
  2. Place plates back in incubator sandwiched in a 6-well plate with a lid and incubate the spheroids for 45 min at 37 °C.
    NOTE: Depending on the size of spheroids, this incubation time significantly varies. For example, spheroids under 400 μm typically only require 30–45 min of incubation time, whereas larger spheroids closer to 800 μm have required up to 90 min of incubation time. Incubation times must be optimized for an individual’s experiment.
  3. For subsequent imaging, harvest spheroids with a 1,000 μL pipet in a biosafety cabinet and deposit each spheroid onto pre-cleaned glass microscope slides.
  4. Image spheroids through the glass, on an inverted confocal microscope.
    NOTE: Depending on the proximity of the confocal microscope to the lab in which spheroids are harvested, the spheroids can either be imaged in the original droplet of medium placed on the slide or encased in 2% agarose if more stability is required for spheroid transport.
  5. Using the Multidimensional Acquisition mode in the microscope software, locate the spheroid using DIC illumination at 10x magnification and then scan the z-plane to identify the heights encompassing the spheroid.
  6. Click on Z Series and set the upper and lower limit of the z-scan slightly higher than the top of the spheroid and slightly lower than the bottom of the spheroid.
  7. Excite the spheroids at 488 nm for calcein-AM (live cells; green) and 561 nm for ethidium homodimer-1 (dead cells; red) with the step size recommended by the software, maximal gain and minimal exposure for each color.
  8. Click Acquire to obtain a composite z-stack image of live and dead cells within the spheroid.
  9. Quantify live/dead proportions using image processing software to quantify a percentage of pixel intensity from the channel corresponding to live cells versus the percentage of pixel intensity from the channel corresponding to dead cells from the composite z-projection images.
    NOTE: Due to the limitations in quantifying a 3D structure with a 2D projection, an alternative method to quantify live versus dead fluorescence, within the hanging drop plates is to use a plate reader following the protocol included with the calcein-AM and ethidium homodimer-1 kit.

8. Immunofluorescence

  1. Heat a low melting 2% agarose solution, so the solution is viscous and just above melting point and place on a microscope slide to create a soft bed of agarose
  2. Harvest spheroids by pushing 20 μL of PBS through the drop onto the soft bed of 2% agarose.
    NOTE: This should be done quickly so that agarose does not solidify before spheroids are embedded.
  3. Once the agarose cools and gels with the harvested spheroid trapped within (under 5 min), add 4% neutral buffered formalin to fix the spheroids. Alternately, add ice cold methanol, and fix the agarose-embedded spheroids at -20 °C for 30 min.
  4. Wash 3x for 5 min each with 1x PBS, discarding PBS after each wash.
  5. Block for 1 h at RT with 10% serum (i.e., horse serum) and 0.15% soap solution (Triton X-100) in 1x PBS.
  6. Wash 3x for 5 min each with 1x PBS, discarding PBS after each wash.
  7. Stain spheroids with desired fluorescent antibody at recommended or pre-determined antibody dilution (i.e., fluorescently labeled phalloidin at a 1:100 dilution), incubating for at least 90 min at room temperature, covered from light.
    NOTE: Protocols will vary depending on antibody and target and antibody dilution may need to be optimized depending on the experiment.
  8. Visualize fluorescently stained spheroids with the inverted confocal microscope using methods outlined in the previous section for imaging spheroids.
  9. Composite z-stack images will demonstrate 3D morphology in the spheroids.

9. Collection and Analysis of Cancer Stem Cell Populations with Flow Cytometry

  1. Preparing spheroids for flow cytometry analysis
    1. Collect spheroids from each well in the hanging drop plates using a 1,000 µL pipet and deposit them into a 15 mL centrifuge tube for disaggregation with repeated pipetting.
    2. Count viable cells on a hemocytometer using Trypan Blue to determine cell number and concentration as outlined above.
    3. Aliquot cell suspension into five microcentrifuge tubes such that each contains a minimum of 50,000 cells.
    4. Centrifuge all tubes at 400 x g for 5 min in a microcentrifuge.
    5. Aspirate the supernatant from each tube and resuspend pellets in 100 μL of buffer.
    6. Label tubes “Unstained”, “DAPI”, “APC-iso”, “DEAB”, and “ALDH/CD133”, respectively.
    7. Add 0.5 μL of APC-isotype antibody to the APC-iso tube and 1 μL of CD133 antibody to the ALDH/CD133 tube as determined by serial dilution and manufacturers recommendation.
    8. Add 5 μL of DEAB Reagent and 0.5 μL of ALDH to the DEAB tube, and 1 μL of ALDH to the ALDH/CD133 tube.
    9. Vortex all tubes for approximately 2 s and incubate at 37 °C for 45 min.
    10. Vortex all tubes again and centrifuge at 400 x g for 5 min in a microcentrifuge.
    11. Label FACS tubes “Unstained”, “DAPI”, “APC-iso”, “DEAB”, and “ALDH/CD133” and fill an insulated foam container to set aside.
    12. Aspirate supernatant and resuspend the “unstained” control in 400 μL FACS Buffer (1x PBS with 2% FBS) and all other tubes in 400 μL of FACS DAPI Buffer (FACS Buffer with 300 μM 4’,6-diamidino-2-phenylindole).
    13. Place tubes in container with ice until analyzed on a flow cytometer.
      NOTE: To sort for ovarian cancer stem cells, collect all cells that the cytometer measures to be ALDH+ and CD133+ with gates set to include 0.5% non-specific APC signal and 0.15% non-specific ALDH+ signal. At least 10,000 cells need to be analyzed for reliable results. Additional details can be found in recent publications3,17.
  2. Analysis of ALDH+/CD133+ populations in FlowJo
    1. Double click the FlowJo icon to open the program and drag .fcs files obtained from flow cytometry software into the workspace.
    2. Double click the unstained file and set the y-axis to side scatter height (SSC-H) and the x-axis to forward scatter height (FSC-H).
    3. Click the T button next to each axis to adjust the scale and transformation to maximize the separation between different cell populations.
    4. Click on the Polygon gating button and draw a polygon gate around the cell population and label the population ‘Cells’.
    5. Double click the Cells population in the workspace to view only the cells within the ‘Cells’ population and then click on the FSC axis to change the axis channel to FSC-width and then click on the SSC axis and change the axis channel to the FSC-H.
    6. Choose the Rectangle gate tool and draw a rectangle around the left-most dense population of cells spanning the entirety of the y-axis to exclude potential doublets toward the right of the window and label this gate ‘Single Cells’.
    7. Right click and copy the Cells and the nested Single Cells gate and paste them under each sample in the workspace.
    8. Double click the Single Cells gate nested under the DAPI sample in the workspace to view the single cell population from that sample tube and click on the FSC axis and change the axis channel to the DAPI - Area channel.
    9. Click on the SSC axis and change the axis channel to Histogram.
      NOTE: The live cells will be towards the left as they exclude DAPI, while dead cells will take in the DAPI and appear towards the right of the graph.
    10. Click on the T button next to the DAPI axis and click on Customize Axis to adjust the scale to maximize separation between DAPI positive and DAPI negative peaks.
      NOTE: A window will pop up with scaling options. Often times, setting the Scale field to Biex and adjusting the Extra Negative Decades and Width Basis will yield the greatest separation.
    11. Click Apply in the pop-up window to apply scaling changes, choose the Range gate button, and spread it over the DAPI negative peak, corresponding to the live cell population.
    12. Label this gate ‘Live Cells’ and right click to copy the ‘Live Cells’ gate to paste it under the ‘Single Cells’ gate under the ‘APC-iso, ‘DEAB’, and ‘ALDH/CD133’ tubes to select the same portion of live cells in each sample tube.
    13. Then double click the Live Cells population nested under the APC-iso sample file and switch the x-axis to the ALDH — Area channel and the y-axis to the APC — Area channel.
    14. Again, adjust the axis scale by clicking the T button and Customize Axis of each axis so that the events are localized in the bottom left region of the plot and select the Quad gate option and click the plot window to establish a quadrant gate.
    15. Adjust the intersection of the gate such that approximately 0.5% of the population lies in the upper left of the plot window or ‘APC positive’ quadrant.
      NOTE: This 0.5% represents the non-specific staining of the APC isotype.
    16. Right click each quadrant label individually in the workspace and rename them appropriately. Control or Command click each quadrant gate label in the workspace and copy them.
      NOTE: ‘Q1’ represents CD133+ cells; ‘Q2’ represents CD133+ and ALDH+’ cells; ‘Q3’ represents ALDH+ cells; and ‘Q4’ represents CD133- and ALDH- cells.
    17. Paste the quadrant gates onto the Live Cells population nested under the ‘DEAB’ file. Adjust the vertical line such that approximately 0.15% of the cell population lies within the ‘ALDH+’ quadrant taking care not to move the horizontal line.
      NOTE: This 0.15% represents non-specific ALDH signal.
      1. To ensure that the horizontal line did not change position, copy the new quadrant gates nested under the DEAB file and paste them onto the Live Cells under the APC iso file. Select Yes when asked to replace existing quadrant gate.
      2. Verify in the workspace that the ‘CD133+’ percent is still approximately 0.5 under the ‘APC-iso’ file.
    18. Copy and paste the quadrant gates to the ‘ALDH/CD133’ file’s ‘Live Cells’ population.
      NOTE: The percentage of the viable cell population present in the top right quadrant will be the percentage of ALDH+ and CD133+ double positive CSCs within the sample.

Subscription Required. Please recommend JoVE to your librarian.

Representative Results

or Start trial to access full content. Learn more about your institution’s access to JoVE content here

Spheroids formed with cell lines or patient-derived CSCs can be formed with a range of small cell numbers within hanging droplets (Figure 2A). Spheroids form reliably with as few as 10 cells per well, which allows for conservation of rare patient samples. Cells within these spheroids are surrounded by other cells in 3 dimensions as they would be in vivo, allowing for physiologic cell-cell contacts and diffusion rates. Tumor cells within the spheroids proliferate causing the spheroids to expand in size over time (Figure 2B). As more aggressive patient cells or cell lines grow faster than their counterparts, it is important to quantify the proliferation capacity of each sample and examine how drug treatment affects the proliferation of each sample. To do this, a metabolic activity assay, such as a resazurin based fluorescence assay, can be easily performed with the 384-well physiologic platform, without any requirement for harvesting spheroids, the results of which can be seen in Figure 2C. Multiple spheroids can also be harvested, fixed, sectioned, and stained with hematoxylin and eosin or immunofluorescent antibodies at the same time to identify cell morphologies and organization within spheroids, as well as, the distribution of cell types and ECM proteins (Figure 2D, E).

To examine the effect of drug treatment on spheroid morphology, spheroids can be easily visualized by phase contrast imaging (Figure 3A). More quantitatively, the effect of drug treatment on tumor cell or CSC proliferation can also be measured by resazurin dye fluorescence readings in control untreated spheroids compared to in the drug treated spheroids (Figure 3B). As a validation of cell death following drug treatment, viability within control and drug treated spheroids can easily be determined via the addition of calcein-AM and ethidium homodimer-1 to multiple spheroids for each condition (Figure 3C). Following incubation time, stained spheroids can be harvested with a pipette and imaged on a confocal microscope.

Finally, by harvesting spheroids and dispersing them into single cell suspensions, the presence of CSCs and other cell phenotype markers can be analyzed with flow cytometry (Figure 4). Comparison of viable CSCs between different drug treatments within the same patient, as well as, between patients can help to discern the effectiveness of various CSC targeting drugs in a patient specific manner.

Figure 1
Figure 1: 3D high throughput 384 hanging drop spheroid plate storage and plating layouts. (A) Hanging drop plate is placed on the bottom of a 6 well plate partially filled with water. (B) Lid of 6 well plate is placed on top of hanging drop plate to create sterile hydration chamber. (C) 6-well plate stack to be sealed with a thermoplastic strip for protection from moisture loss and contaminants. (D) Alternating plating pattern for hanging drop plate. Pink squares indicate wells filled with cells and medium mixture. Blue areas indicate water chambers for hydration. Gray boxes indicate blank wells that act as a border between hydration chambers and spheroid droplets. (E) Live image of hanging drop plate plated with the alternating well pattern. (F) All well plating pattern layout utilized for high throughput hanging drop spheroids experiments. Pink squares indicate cell plated wells and blue areas indicate water filled chambers for increased hydration. Gray squares indicate border wells that act as boundary between hydration sections and cell culture areas. Please click here to view a larger version of this figure.

Figure 2
Figure 2: Patient derived CSC spheroids morphology and proliferation within 3D hanging drops. (A) Live image of prepared 384-hanging drop spheroid plate as viewed from the bottom. (B) Progressive light microscope images of patient derived CSC spheroid growth after 2, 3, and 5 days in a hanging drop. Scale bars = 100 µm. (C) Resazurin fluorescence intensity shows significant increase after 7 days of hanging drop culture, correlating to proliferation and growth of the hanging drop patient derived CSC spheroids (Unpaired two tailed t-test, p <0.0001, n >10). (D) Picture of spheroid array mold used to create a cast for collection of spheroids for histology sectioning. (E) H&E image of a spheroid cultured with primary ovarian cancer stem cells, mesenchymal stem cells, endothelial cells, and donor peripheral blood mononuclear cells collected in the spheroid array. Scare bar = 100 µm. Please click here to view a larger version of this figure.

Figure 3
Figure 3: Drug treatment analysis of patient derived CSC spheroids hanging drops. (A) Patient derived CSC spheroids seeded at 50 cells/drop treated with increasing concentrations of paclitaxel after 5 days of growth. Representative images taken 48 h after drug treatment. (B) Quantification of cellular viability via resazurin fluorescence at increasing concentrations of paclitaxel treatment. All samples have a significant reduction in viability compared to control. (One-way ANOVA, p <0.0001, n> 8). (C) Confocal imaging of live (calcein-AM) and dead (ethidium homodimer-1) cells within hanging drop spheroid. Green color indicates live cells and red color indicates dead cell population. Scale bar = 100 µm. Please click here to view a larger version of this figure.

Figure 4
Figure 4: Quantification of CSCs in patient derived CSC spheroids generated and maintained on the 384-hanging drop platform. (A) In analyzing the flow cytometry data, the cell population is first selected using a polygon gate to eliminate any events attributable to debris. (B) The single cells are then selected to eliminate potential doublet signals which may obscure results. (C) All of the single live cells are then selected based on DAPI exclusion. (D) The vertical axis of a quadrant gate is adjusted in the DEAB control to allow for about 0.15% non-specific ALDH staining. (E) The horizontal axis of the quadrant gate is adjusted in the APC ISO control to allow for about 0.5% non-specific APC staining. (F) The quadrant gate is then used to determine the percent of CD133+, ALDH+, and CD133+/ALDH+ cells are present in the live cell population in the experimental CD133 plus ALDH condition. Please click here to view a larger version of this figure.

Subscription Required. Please recommend JoVE to your librarian.


or Start trial to access full content. Learn more about your institution’s access to JoVE content here

The 384-well hanging drop plate platform for 3D spheroid formation is an easily implemented tool for any cell biology or cancer biology labs. This physiologic platform enables the study of cell lines, as well as, primary patient samples within physiologically relevant 3D cultures while allowing for high throughput drug screening. The platform also ensures that the culture conditions are highly tunable, enabling tight control over plating densities, cell co-culture ratios, extracellular components, and medium composition. Furthermore, this physiologic platform allows experiments to be highly amenable to downstream analysis techniques requiring large or small cell counts such as qRT-PCR, FACS, and various imaging methods. While ease of utilization comes with experience, new trainees become successful quickly, once speed and ease of pipetting are mastered. Thus, this physiologic platform is highly applicable for personalized 3D drug screening, CSC biology and chemoresistance investigations.

Some points of concern when newly implementing this platform include plate transfer and drug treatment. When transferring plates from one location to another as required for routine feeding, imaging, and analysis, careful precautions should be taken to avoid unnecessary jostling. Grip the plates from the outer edges keeping them as level as possible and take care to avoid jarring movements when placing the plate down. This helps to avoid droplet loss or merging of neighboring drops. Similarly, vigilant attention should be given to the task of drug treating hanging drop spheroids to avoid incorrect dosing of any one hanging drop spheroid. As with any technique, confidence and accuracy with these tasks arrive with practice.

A few limitations are innate to this 3D physiologic platform. First, droplet instability may be of issue at long term culture time points, if care is not taken to maintain correct total droplet volume. Furthermore, as mentioned above, transport and storage of plates must be done carefully to avoid loss or merging of droplets. Additionally, the size for this 3D environment is dictated by innate stable droplet size of 20 µL, though many replicates can be produced for enhanced cell counts.

Modifications to this 3D physiologic platform can be utilized to increase throughput and alter physiological characteristics. For instance, droplet layout can be altered to include every well within the 384 well plate to increase throughput. Additionally, the 3D hanging drop platform is highly conducive to co-culture investigations by simple inclusion of multiple cell types in each well. To generate and maintain spheroids successfully, cell culture medium and initial cell seeding density can be easily modulated, to tightly regulate spheroid size. With these highly tunable variables countless investigations are possible within the realm of 3D physiological patient derived spheroids.

While most analysis methods described are widely used in scientific research, there are a few limitations specific to analyzing hanging drop generated spheroids with some of these methods. For example, when spheroids are cultured for long periods of time in hanging drop plates, droplet size can increase significantly causing droplets to shake during phase contrast imaging, potentially compromising image quality. This can be ameliorated by taking an equivalent amount of medium out of each well prior to adding fresh medium. Additionally, techniques such as flow cytometry and counting individual viable cells may be affected by the technique used to break apart spheroids, which may be harmful to cells. As such, it is important for each lab to optimize spheroid disaggregation techniques based on their cells and experiment to minimize cell damage while maximizing single cell density. Finally, histological analysis of spheroids can be complicated by their small size and requires practice to obtain successful sections.

Overall, the 3D hanging drop spheroid platform is widely adaptable within cancer and non-cancer research. The system is easy to learn and provides a 3D physiologically relevant environment for cell culture in a high throughput format. Initiation time of this 3D physiological platform is minimal, with few, if any, technical analysis hurdles to overcome. The versatility of this system provides a means for patient specific screening of effective chemotherapeutics for precision medicine, in a more physiologic environment than ever before.

Subscription Required. Please recommend JoVE to your librarian.


The authors have nothing to disclose.


This work is supported primarily by DOD OCRP Early Career Investigator Award W81XWH-13-1-0134(GM), DOD Pilot award W81XWH-16-1-0426 (GM), DOD Investigator Initiated award W81XWH-17-OCRP-IIRA (GM), Rivkin Center for Ovarian Cancer and Michigan Ovarian Cancer Alliance. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award number P30CA046592. CMN is supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1256260. MEB is supported by the Department of Education Graduate Assistance in Areas of National Need (GAANN) Fellowship.


Name Company Catalog Number Comments
0.25% trypsin-EDTA Gibco ILT25200056
10 mL serological pipet Fisher Scientific 13-678-11E
10,000 cSt Si oil Millipore Sigma 63148-62-9 Used to coat spheroid array mold to facilitate removal of tissue processing gels, like Histogel, from the mold.
100 mm tissue culture dish Thermo Scientific 130182
15 mL conical tube Celltreat FL4021
1x DMEM for Serum Free Medium Gibco 11965-092
1x F12 for Serum Free Medium Gibco 11765-054
1x phosphate buffered saline (PBS) Gibco ILT10010023
4’,6-diamidino-2-phenylindole (DAPI) Thermo Fisher D1306
40 µm filter Fisher Scientific 22363547
6-well plate Fisher Scientific 353046
Accutase Innovative Cell Technologies Inc. 1449 A gentle cell detachment enzyme composed of proteolytic and collagenolytic enzymes.
ACK Lysing Buffer Thermo Scientific A1049201
alamarBlue Invitrogen DAL1025 Resazurin dye used to measure viability and proliferation of cells based on their ability to reduce resazurin to resorufin, which is highly fluorescent.
ALDEFLUOR assay kit Stem Cell Tech 1700 Kit to identify stem and progenitor cells that express high levels of aldehyde dehydrogenase , an indicator of cancer stem cells. The kit is composed of ALDEFLUOR Reagent, DEAB, Hydrochloric Acid, Dimethylsulphoxide, and ALDEFLUOR Assay Buffer.
ALDEFLUOR Diethylaminobenzaldehyde (DEAB) Stem Cell Tech 1705 Diethylaminobenzaldehyde (DEAB) is an inhibitor of ALDH isozymes, used to determine non-specific ALDH staining.
Andor iXon x3 CCD Camera Oxford Instruments -
Antibiotics and Antimycotics Gibco 15240-062
APC-isotype IgG2b Miltenyi biotec 130-092-217 Isotype control to quantify non-specific staining of IgG2b antibodies.
B27 Supplement Gibco 17504044
basic Fibroblast Growth Factor Stem Cell Technologies 78003.1
BD Lo-Dose U-100 Insulin Syringes Fisher Scientific 14-826-79
BioTek Synergy HT Microplate Reader BioTek 7091000
CD133-APC Miltenyi biotec 130-113-184 Fluorescent antibody targeting CD133, a cancer stem cell marker.
cellSens Dimension Software Olympus
Cisplatin Sigma-Aldrich P4394 Platinum based chemotherapy agent that functions as an alkylating agent that disrupts DNA.
DAPI (4',6-Diamidino-2-Phenylindole, Dihydrochloride) Invitrogen D1306
Epidermal Growth Factor Gibco PHG0311
EVOS XL Core Cell Imaging System Life Technologies AME3300
Fetal Bovine Serum - premium (FBS) Atlanta Biologicals S11150
Ficoll 400 Sigma-Aldrich F4375
Hemacytometer Hausser Scientific 1490
Histogel Thermo Scientific HG-4000-012 Tissue processing gel that can penetrate and hold the specimen within the gel while preventing discoloration around the specimen upon staining.
Human Adipose-Derived Mesenchymal Stem Cells Lonza PT-5006
Human Microvascular Endothelial Cells Lonza CC2543
Insulin-Transferrin-Selenium Supplement Gibco 51500-056
Live/Dead viability kit Invitrogen L3224 Kit for the fluorescence based detection of live (calcein-AM) and dead cells (Ethidium Homodimer-1).
MEM Non-essential Amino Acids Gibco 11140-050
MetaMorph 7.8 Software Molecular Devices -
Olympus IX81 Inverted Confocal Microscope Olympus -
Olympus IX83 Research Inverted Microscope Olympus
Parafilm M Thomas Scientific 7315D35 Thermoplastic polymer strips that serve to limit droplet evaporation in hanging drop plates while still allowing for gas exchange.
Perfecta 3D 384 Well Hanging Drop Plates 3D Biomatrix HDP1384-8 Available through Sigma-Aldrich
phalloidin AlexaFluor488 Invitrogen A12379 Phalloidin is a peptide to fluorescently label F-actin in fixed cells.
ProJet 3500 HD Max 3D Systems - 3D printer
Sterile DI water Fisher Scientific 353046
Trypan Blue Gibco 15250061 Azo dye used to differentiate between live and dead cells based on its ability to pass through the damaged membrane of dead cells, but not the intact membrane of live cells.
VisiJet M3 Crystal 3D Systems - A biocompatible polymer material for 3D printing.
Yokogawa CSU-X1 Confocal Scanner Unit Yokogawa -



  1. All cancers Source: Globocan. Globocan. http://gco.iarc.fr/today/data/factsheets/cancers/39-All-cancers-fact-sheet.pdf (2018).
  2. Prasad, V., Mailankody, S. Research and Development Spending to Bring a Single Cancer Drug to Market and Revenues After Approval. JAMA Internal Medicine. 177, 1569-1575 (2017).
  3. Raghavan, S., et al. Personalized Medicine Based Approach to Model Patterns of Chemoresistance and Tumor Recurrence Using Ovarian Cancer Stem Cell Spheroids. Clinical Cancer Research. 23, (22), 6934-6945 (2017).
  4. Jordan, C. T., Guzman, M. L., Noble, M. Cancer Stem Cells. New England Journal of Medicine. 355, 1253-1261 (2006).
  5. Ishiguro, T., et al. Establishment and Characterization of an In Vitro Model of Ovarian Cancer Stem-like Cells with an Enhanced Proliferative Capacity. Cancer Research. 76, 150-160 (2016).
  6. Páez, D., et al. Cancer Dormancy: A Model of Early Dissemination and Late Cancer Recurrence. Clinical Cancer Research. 18, 645-653 (2012).
  7. Ahmed, N., Stenvers, K. L. Getting to Know Ovarian Cancer Ascites: Opportunities for Targeted Therapy-Based Translational Research. Frontiers in Oncology. 3, (2013).
  8. Pradhan, S., Clary, J. M., Seliktar, D., Lipke, E. A. A three-dimensional spheroidal cancer model based on PEG-fibrinogen hydrogel microspheres. Biomaterials. 115, 141-154 (2017).
  9. Varna, M., Bertheau, P., Legrès, L. Tumor Microenvironment in Human Tumor Xenografted Mouse Models. Journal of Analytical Oncology. 3, 159-166 (2014).
  10. Huang, S. B., et al. An integrated microfluidic cell culture system for high-throughput perfusion three-dimensional cell culture-based assays: Effect of cell culture model on the results of chemosensitivity assays. Lab on a Chip. 13, 1133-1143 (2013).
  11. Zang, R., Li, D., Tang, I. C., Wang, J., Yang, S. T. Cell-Based Assays in High-Throughput Screening for Drug Discovery. International Journal of Biotechnology for Wellness Industries. (2012).
  12. Murphy, B., et al. Evaluation of alternative in vivo drug screening methodology: a single mouse analysis. Cancer Research. 76, 5798-5809 (2016).
  13. Hidalgo, M., et al. Patient-derived Xenograft models: An emerging platform for translational cancer research. Cancer Discovery. 4, 998-1013 (2014).
  14. Damiati, S., Kompella, U. B., Damiati, S. A., Kodzius, R. Microfluidic devices for drug delivery systems and drug screening. Genes. 9, (2018).
  15. Caliari, S. R., Burdick, J. A. A Practical Guide to Hydrogels for Cell Culture. Nature Methods. 14, 69-81 (2016).
  16. Mehta, G., Hsiao, A. Y., Ingram, M., Luker, G. D., Takayama, S. Opportunities and challenges for use of tumor spheroids as models to test drug delivery and efficacy. Journal of Control Release. (2012).
  17. Mehta, P., Novak, C., Raghavan, S., Ward, M., Mehta, G. Self-Renewal and CSCs In Vitro Enrichment: Growth as Floating Spheres. Cancer Stem Cells: Methods and Protocols. Papaccio, G., Desiderio, V. Springer. New York. 61-75 (2018).
  18. Raghavan, S., et al. Formation of stable small cell number three-dimensional ovarian cancer spheroids using hanging drop arrays for preclinical drug sensitivity assays. Gynecologic Oncology. 138, 181-189 (2015).
  19. Raghavan, S., et al. Comparative analysis of tumor spheroid generation techniques for differential in vitro drug toxicity. Oncotarget. 7, 16948-16961 (2016).
  20. Kim, S., et al. Evaluating Tumor Evolution via Genomic Profiling of Individual Tumor Spheroids in a Malignant Ascites. Scientific Reports. 8, 1-11 (2018).
  21. Silva, I. A., et al. Aldehyde dehydrogenase in combination with CD133 defines angiogenic ovarian cancer stem cells that portend poor patient survival. Cancer Research. 71, 3991-4001 (2011).
  22. Pulaski, H. L., et al. Identifying alemtuzumab as an anti-myeloid cell antiangiogenic therapy for the treatment of ovarian cancer. Journal of Translational Medicine. 7, 49 (2009).
  23. Jager, L. D., et al. Effect of enzymatic and mechanical methods of dissociation on neural progenitor cells derived from induced pluripotent stem cells. Advances in Medical Sciences. 61, 78-84 (2016).
  24. Ivanov, D. P., Grabowska, A. M. Spheroid arrays for high-throughput single-cell analysis of spatial patterns and biomarker expression in 3D. Scientific Reports. 7, 41160 (2017).
Physiologic Patient Derived 3D Spheroids for Anti-neoplastic Drug Screening to Target Cancer Stem Cells
Play Video

Cite this Article

Bregenzer, M. E., Davis, C., Horst, E. N., Mehta, P., Novak, C. M., Raghavan, S., Snyder, C. S., Mehta, G. Physiologic Patient Derived 3D Spheroids for Anti-neoplastic Drug Screening to Target Cancer Stem Cells. J. Vis. Exp. (149), e59696, doi:10.3791/59696 (2019).More

Bregenzer, M. E., Davis, C., Horst, E. N., Mehta, P., Novak, C. M., Raghavan, S., Snyder, C. S., Mehta, G. Physiologic Patient Derived 3D Spheroids for Anti-neoplastic Drug Screening to Target Cancer Stem Cells. J. Vis. Exp. (149), e59696, doi:10.3791/59696 (2019).

Copy Citation Download Citation Reprints and Permissions
View Video

Get cutting-edge science videos from JoVE sent straight to your inbox every month.

Waiting X
simple hit counter