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.
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.
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
2. Adding Cell Culture Medium to Hanging Drop Spheroid Plates
3. Phase Contrast Imaging of Spheroid Morphology
4. Quantification of Proliferation and Viability within Spheroids
5. Evaluation of Drug Toxicity in Spheroids
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).
7. Live Dead Cytotoxicity Assay
8. Immunofluorescence
9. Collection and Analysis of Cancer Stem Cell Populations with Flow Cytometry
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: 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: 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: 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: 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.
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.
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.
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 | – |