Name: physiologic patient derived 3d spheroids for anti-neoplastic drug screening to target cancer stem cells
Uploaded: 2019-07-05T12:30:00
Description: Watch this Scientific Journal Video about Physiologic Patient Derived 3D Spheroids for Anti-neoplastic Drug Screening to Target Cancer Stem Cells at JoVE.com

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.

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
<ol>
	<li>Place the hanging drop plate in a sonicator filled with sterile deionized (DI) water and sonicate for 20 min.</li>
	<li>With a gloved hand, remove the plate from the sonicator and wash it with running DI water.</li>
	<li>Allow the pla...

<ol>
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A., 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=Aldehyde+dehydrogenase+in+combination+with+CD133+defines+angiogenic+ovarian+cancer+stem+cells+that+portend+poor+patient+survival.">Aldehyde dehydrogenase in combination with CD133 defines angiogenic ovarian cancer stem cells that portend poor patient survival.</a> Cancer Research. 71, 3991-4001 (2011).</li><li>Pulaski, H. L., 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=Identifying+alemtuzumab+as+an+anti-myeloid+cell+antiangiogenic+therapy+for+the+treatment+of+ovarian+cancer.">Identifying alemtuzumab as an anti-myeloid cell antiangiogenic therapy for the treatment of ovarian cancer.</a> Journal of Translational Medicine. 7, 49 (2009).</li><li>Jager, L. 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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&#160;co-culture ratios, extracellular components, and medium composi...

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 &#8216;organ-on-a-chip&#8217; 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.

<table>
	<tbody>
		<tr>
			<td>0.25% trypsin-EDTA</td>
			<td>Gibco</td>
			<td>ILT25200056</td>
			<td></td>
		</tr>
		<tr>
			<td>10 mL serological pipet</td>
			<td>Fisher Scientific</td>
			<td>13-678-11E</td>
			<td></td>
		</tr>
		<tr>
			<td>10,000 cSt Si oil</td>
			<td>Millipore Sigma</td>
			<td>63148-62-9</td>
			<td>Used to coat spheroid array mold to facilitate removal of tissue processing gels, like Histogel, from the mold.</td>
		</tr>
		<tr>
			<td>100 mm tissue culture dish</td>
			<td>Thermo Scientific</td>
			<td>130182</td>
			<td></td>
		</tr>
		<tr>
			<td>15 ml conical tube</td>
			<td>Celltreat</td>
			<td>FL4021</td>
			<td></td>
		</tr>
		<tr>
			<td>1X DMEM for Serum Free Medium</td>
			<td>Gibco</td>
			<td>11965-092</td>
			<td></td>
		</tr>
		<tr>
			<td>1X F12 for Serum Free Medium</td>
			<td>Gibco</td>
			<td>11765-054</td>
			<td></td>
		</tr>
		<tr>
			<td>1X phosphate buffered saline (PBS)</td>
			<td>Gibco</td>
			<td>ILT10010023</td>
			<td></td>
		</tr>
		<tr>
			<td>4&#8217;,6-diamidino-2-phenylindole (DAPI)</td>
			<td>Thermo Fisher</td>
			<td>D1306</td>
			<td></td>
		</tr>
		<tr>
			<td>40 &#181;m filter</td>
			<td>Fisher Scientific</td>
			<td>22363547</td>
			<td></td>
		</tr>
		<tr>
			<td>6-well plate</td>
			<td>Fisher Scientific</td>
			<td>353046</td>
			<td></td>
		</tr>
		<tr>
			<td>Accutase</td>
			<td>Innovative Cell Technologies Inc.</td>
			<td>1449</td>
			<td>A gentle cell detachment enzyme composed of proteolytic and collagenolytic enzymes.</td>
		</tr>
		<tr>
			<td>ACK Lysing Buffer</td>
			<td>Thermo Scientific</td>
			<td>A1049201</td>
			<td></td>
		</tr>
		<tr>
			<td>alamarBlue</td>
			<td>Invitrogen</td>
			<td>DAL1025</td>
			<td>Resazurin dye used to measure viability and proliferation of cells based on their ability to reduce resazurin to resorufin, which is highly fluorescent.</td>
		</tr>
		<tr>
			<td>ALDEFLUOR assay kit</td>
			<td>Stem Cell Tech</td>
			<td>1700</td>
			<td>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.</td>
		</tr>
		<tr>
			<td>ALDEFLUOR Diethylaminobenzaldehyde (DEAB)</td>
			<td>Stem Cell Tech</td>
			<td>1705</td>
			<td>Diethylaminobenzaldehyde (DEAB) is an inhibitor of ALDH isozymes, used to determine non-specific ALDH staining.</td>
		</tr>
		<tr>
			<td>Andor iXon x3 CCD Camera</td>
			<td>Oxford Instruments</td>
			<td>-</td>
			<td></td>
		</tr>
		<tr>
			<td>Antibiotics and Antimycotics</td>
			<td>Gibco</td>
			<td>15240-062</td>
			<td></td>
		</tr>
		<tr>
			<td>APC-isotype IgG2b</td>
			<td>Miltenyi biotec</td>
			<td>130-092-217</td>
			<td>Isotype control to quantify non-specific staining of IgG2b antibodies.</td>
		</tr>
		<tr>
			<td>B27 Supplement</td>
			<td>Gibco</td>
			<td>17504044</td>
			<td></td>
		</tr>
		<tr>
			<td>basic Fibroblast Growth Factor</td>
			<td>Stem Cell Technologies</td>
			<td>78003.1</td>
			<td></td>
		</tr>
		<tr>
			<td>BD Lo-Dose U-100 Insulin Syringes</td>
			<td>Fisher Scientific</td>
			<td>14-826-79</td>
			<td></td>
		</tr>
		<tr>
			<td>BioTek Synergy HT Microplate Reader</td>
			<td>BioTek</td>
			<td>7091000</td>
			<td></td>
		</tr>
		<tr>
			<td>CD133-APC</td>
			<td>Miltenyi biotec</td>
			<td>130-113-184</td>
			<td>Fluorescent antibody targeting CD133, a cancer stem cell marker.</td>
		</tr>
		<tr>
			<td>cellSens Dimension Software</td>
			<td>Olympus</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Cisplatin</td>
			<td>Sigma-Aldrich</td>
			<td>P4394</td>
			<td>Platinum based chemotherapy agent that functions as an alkylating agent that disrupts DNA.</td>
		</tr>
		<tr>
			<td>DAPI (4&#39;,6-Diamidino-2-Phenylindole, Dihydrochloride)</td>
			<td>Invitrogen</td>
			<td>D1306</td>
			<td></td>
		</tr>
		<tr>
			<td>Epidermal Growth Factor</td>
			<td>Gibco</td>
			<td>PHG0311</td>
			<td></td>
		</tr>
		<tr>
			<td>EVOS XL Core Cell Imaging System</td>
			<td>Life Technologies</td>
			<td>AME3300</td>
			<td></td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum - premium (FBS)</td>
			<td>Atlanta Biologicals</td>
			<td>S11150</td>
			<td></td>
		</tr>
		<tr>
			<td>Ficoll 400</td>
			<td>Sigma-Aldrich</td>
			<td>F4375</td>
			<td></td>
		</tr>
		<tr>
			<td>Hemacytometer</td>
			<td>Hausser Scientific</td>
			<td>1490</td>
			<td></td>
		</tr>
		<tr>
			<td>Histogel</td>
			<td>Thermo Scientific</td>
			<td>HG-4000-012</td>
			<td>Tissue processing gel that can penetrate and hold the specimen within the gel while preventing discoloration around the specimen upon staining.</td>
		</tr>
		<tr>
			<td>Human Adipose-Derived Mesenchymal Stem Cells</td>
			<td>Lonza</td>
			<td>PT-5006</td>
			<td></td>
		</tr>
		<tr>
			<td>Human Microvascular Endothelial Cells</td>
			<td>Lonza</td>
			<td>CC2543</td>
			<td></td>
		</tr>
		<tr>
			<td>Insulin-Transferrin-Selenium Supplement</td>
			<td>Gibco</td>
			<td>51500-056</td>
			<td></td>
		</tr>
		<tr>
			<td>Live/Dead viability kit</td>
			<td>Invitrogen</td>
			<td>L3224</td>
			<td>Kit for the fluorescence based detection of live (calcein-AM) and dead cells (Ethidium Homodimer-1).</td>
		</tr>
		<tr>
			<td>MEM Non-essential Amino Acids</td>
			<td>Gibco</td>
			<td>11140-050</td>
			<td></td>
		</tr>
		<tr>
			<td>MetaMorph 7.8 Software</td>
			<td>Molecular Devices</td>
			<td>-</td>
			<td></td>
		</tr>
		<tr>
			<td>Olympus IX81 Inverted Confocal Microscope</td>
			<td>Olympus</td>
			<td>-</td>
			<td></td>
		</tr>
		<tr>
			<td>Olympus IX83 Research Inverted Microscope</td>
			<td>Olympus</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Parafilm M</td>
			<td>Thomas Scientific</td>
			<td>7315D35</td>
			<td>Thermoplastic polymer strips that serve to limit droplet evaporation in hanging drop plates while still allowing for gas exchange.</td>
		</tr>
		<tr>
			<td>Perfecta 3D 384 Well Hanging Drop Plates</td>
			<td>3D Biomatrix</td>
			<td>HDP1384-8</td>
			<td>Available through Sigma-Aldrich</td>
		</tr>
		<tr>
			<td>phalloidin AlexaFluor488</td>
			<td>Invitrogen</td>
			<td>A12379</td>
			<td>Phalloidin is a peptide to fluorescently label F-actin in fixed cells.</td>
		</tr>
		<tr>
			<td>ProJet 3500 HD Max</td>
			<td>3D Systems</td>
			<td>-</td>
			<td>3D printer</td>
		</tr>
		<tr>
			<td>Sterile DI water</td>
			<td>Fisher Scientific</td>
			<td>353046</td>
			<td></td>
		</tr>
		<tr>
			<td>Trypan Blue</td>
			<td>Gibco</td>
			<td>15250061</td>
			<td>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.</td>
		</tr>
		<tr>
			<td>VisiJet M3 Crystal</td>
			<td>3D Systems</td>
			<td>-</td>
			<td>A biocompatible polymer material for 3D printing.</td>
		</tr>
		<tr>
			<td>Yokogawa CSU-X1 Confocal Scanner Unit</td>
			<td>Yokogawa</td>
			<td>-</td>
			<td></td>
		</tr>
	</tbody>
</table>

physiologic patient derived 3d spheroids for anti-neoplastic drug screening to target cancer stem cells

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.

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 expa...

Watch this Scientific Journal Video about Physiologic Patient Derived 3D Spheroids for Anti-neoplastic Drug Screening to Target Cancer Stem Cells at JoVE.com

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

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&#8217; 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 ...

Our protocol provides a simple method for 3D cell culture and is highly amenable to downstream analysis. This facilitates the evaluation of heterogeneous patient samples and their specific drug responses. The advantage of this technique is that spheroids can be formed from small cell numbers, allowing for both preservation of scarce primary samples, and high throughput screening for patient-specific drug responses.The hanging drop model creates a physiological environment with 3D drug diffusion and does responses corresponding to tumor stage. This allows for the development of targeted therapies and patient-specific treatments. This method is ideal for studying ovarian cancer, heterogeneity and the development of chemo resistance.However, it can also be used to study other cancers and drug-resistant cell populations. When plating spheroids, it is important to pipette precise volumes. This ensures consistency between spheroids.The spheroids and their respective droplets are inherently fragile and easily lost without proper handling, therefore we will show how to appropriately plate, maintain and analyze a hanging drop plate. Demonstrating this procedure will be Michael Bregenzer, a graduate student from our laboratory. Start by filling each well of the six-well plate with four to five milliliters of autoclave deionized water and sandwiching the hanging drop plate between the lid and the bottom of the plate.Add 800 to 1000 microliters of water around the rim of the hanging drop plate to provide a humid environment and minimize evaporation. Next, collect 2D grown cells by detaching them with trypsin, and then adding six or eight milliliters of medium containing FBS. Aspirate the cells with the 10 milliliters serological pipette, and deposit them in a 15 milliliter conical tube.Use a hemocytometer to count the cells. Prepare cell suspension according to manuscript directions, and mix gently with the pipette to ensure homogenous distribution. Place the tip of the pipette in the well at an angle of 45 degrees and pipette 20 microliters of suspension into each hanging drop well.Place the lid of the six-well plate back on and use a stretchy thermoplastic strip to seal the edges. Incubate in a standard carbon dioxide humidified incubator and feed the hanging drops every two to three days by adding two to three microliters of cell culture medium to each spheroid-containing well. To quantify proliferation and viability of the cells, add two microliters of filtered resazurin-based solution to the wells designated for proliferation analysis and incubate according to manuscript direction.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. Place it in the plate reader and read the plate. Save the experiment in the popup window and export the data into a spreadsheet.Return the plate back to the six-well base and place it in the incubator. Once all time points have been read for the day, reseal the plate before incubating. To prepare spheroids for flow cytometry analysis, use a 1000 microliter pipette to collect them from each well and deposit them into a 15 milliliter conical tube for disaggregation.Aliquot cell suspension into five micro centrifuge tubes so that each tube contains at least 50, 000 cells. Centrifuge the tubes at 400 times G for five minutes in a microcentrifuge, then aspirate the supernatant and re-suspend pellets in 100 microliters of Aldefluor buffer. Label the tubes according to manuscript directions.Add 0.5 microliters of APC isotype antibody to the APC ISO tube and one microliter of CD133 antibody to the ALDH CD133 tube. Then add five microliters of DEAB reagent and 0.5 microliters of ALDH to the DEAB tube and one microliter of ALDH to the ALDH CD133 tube. Vortex all tubes for a few seconds and incubate them at 37 degrees celsius for 45 minutes.After the incubation, vortex all tubes again and centrifuge them at 400 times G for five minutes. Label FACS tubes according to manuscript directions and fill an insulated foam container with ice. Aspirate the supernatant from the microcentrifuge tubes.Then re-suspend the unstained control in 400 microliters of FACS buffer and the rest of the cells in 400 microliters of FACS DAPI buffer. Place the tubes on the ice until they can be analyzed on a flow cytometer. Use FlowJo to analyze the data from the flow cytometer.Double click the unstained file and set the Y-axis to side scatter height or SSCH and the X-axis to forward scatter height or FSCH. Click the T button next to each axis to adjust the scale and maximize separation between different cell populations. Next, click on the Polygon Gating button, draw polygon gate around the cell population and label the population Cells.Double click the cell's population in the workspace, and then change the FSC axis to FSC width and the SSC axis to the FSC height. Choose the rectangle gate to only draw a rectangle around the leftmost dense population of cells, spanning the entire Y-axis. Label this gate Single Cells.Then right click and copy this Cells in the nested Single Cells gate and paste them under each sample in the workspace. Double click the Single Cells gate nested under the DAPI sample to view the single cell population from that sample tube. Change the FSC axis channel to the DAPI area channel and change the SSC axis channel to histogram.Click on the T button next to the DAPI axis and click on Customize Axis to adjust the scale and maximize separation between DAPI positive and DAPI negative peaks. Click Apply in the popup window and choose the Range Gate button. Spread it over the DAPI negative peak and label this gate Live Cells.Copy the Live Cells gate and 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 tube. Then double click the Live Cells population nested under the APC ISO sample file, and switch the X-axis to ALDH area and the Y-axis to APC area. Apply Quadrant Gate and adjust the intersection of the gate such as that approximately 0.5%of the population lies in the upper left of the plot window.Then name the quadrants as desired, then copy and paste the quadrant gates onto the live cells population nested under the DEAB file and adjust the vertical line so that approximately 0.15%of the cell population lies within the ALDH positive quadrant. Finally, copy and paste the quadrant gates to the ALDH CD133 files Live Cells population and evaluation cancer stem cell proportions based on ALDH and CD133 proportions. This protocol can be used for high throughput analysis of patient-derived cancer stem cells.As little as 10 cells per well can form reliable spheroids and as the cells proliferate, the spheroids expand in size. Proliferation capacity can be easily quantified with a resazurin-based florescence assay. The effect of drugs on spheroid morphology can be visualized with phase contrast imaging and quantified by comparing resazurin florescence in untreated and treated cells.Cell death can be validated via addition of Calcein-AM and ethidium homodimer I to spheroids, followed by imaging on a confocal microscope. Finally, spheroids can be harvested and dispersed into a single cells suspension for analysis with flow cytometry, which makes it possible to discern the effectiveness of different drug treatments on specific cell populations. To avoid droplet loss, medium evaporation and variation in spheroid size, it is important to handle your plates carefully, pipette with precision and completely seal your hanging drop plates.To evaluate changes in gene expression and soluble signaling due to drug treatment, single cell RNA sequencing and enzyme-linked immunosorbent assays, can be used to facilitate the development of therapeutics. This technique allows researches in oncology, precision medicine and drug development to explore intra and inter patient heterogeneity as well chemo resistance through high throughput drug screening of small biopsies. When performing this protocol, be sure to wear all standard personal protective equipment.Including gloves, safety glasses, lab coats, pants and close-toed shoes.

Research

JoVE Journal

Cancer Research

Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening

Cancer cells have routinely been cultured in two dimensions (2D) on a plastic surface. This technique, however, lacks the true environment a tumor mass is ...

Modeling Osteosarcoma Using Li-Fraumeni Syndrome Patient-derived Induced Pluripotent Stem Cells

Li-Fraumeni syndrome (LFS) is an autosomal dominant hereditary cancer disorder. Patients with LFS are predisposed to a various type of tumors, including ...

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 ...

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 ...

A Rapid Screening Workflow to Identify Potential Combination Therapy for GBM using Patient-Derived Glioma Stem Cells

The glioma stem cells (GSCs) are a small fraction of cancer cells which play essential roles in tumor initiation, angiogenesis, and drug resistance in ...

Exploring Mitochondrial Energy Metabolism of Single 3D Microtissue Spheroids Using Extracellular Flux Analysis

Three-dimensional (3D) cellular aggregates, termed spheroids, have become the forefront of in vitro cell culture in recent years. In contrast to culturing ...

Pooled shRNA Library Screening to Identify Factors that Modulate a Drug Resistance Phenotype

Understanding clinically relevant driver mechanisms of acquired chemo-resistance is crucial for elucidating ways to circumvent resistance and improve ...

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 ...

Orthotopic Implantation of Patient-Derived Cancer Cells in Mice Recapitulates Advanced Colorectal Cancer

Over the last decade, more sophisticated preclinical colorectal cancer (CRC) models have been established using patient-derived cancer cells and 3D ...

Generation of 3D Tumor Spheroids for Drug Evaluation Studies

In recent decades, in addition to monolayer-cultured cells, three-dimensional tumor spheroids have been developed as a potentially powerful tool for the ...