We thank Ms. Danae Sharp and Ms. Sheena Daignault for technical assistance. We thank Dr. Atsushi Miyawaki, RIKEN, Wako-city, Japan, for providing the FUCCI constructs, Dr. Meenhard Herlyn and Ms. Patricia Brafford, The Wistar Institute, Philadelphia, for providing cell lines, the Imaging and Flow Cytometry Facility at the Centenary Institute for outstanding technical support. We thank Mr. Chris Johnson and Dr. Andrew Barlow for Volocity software technical support. N.K.H. is a Cameron fellow of the Melanoma and Skin Cancer Research Institute, Australia. K.A.B. is a fellow of the Cancer Institute New South Wales (13/ECF/1-39). W.W. is a fellow of the Cancer Institute New South Wales (11/CDF/3-39). This work was supported by project grants RG 09-08 and RG 13-06 (Cancer Council New South Wales), 570778 and 1051996 (Priority-driven collaborative cancer research scheme/Cancer Australia/Cure Cancer Australia Foundation), 08/RFG/1-27 (Cancer Institute New South Wales), and APP1003637 and APP1084893 (National Health and Medical Research Council).

1. FUCCI Transduction and Cell Culture
<ol>
	<li>FUCCI transduction
	<ol>
		<li>Create cell lines stably expressing the FUCCI constructs mKO2-hCdt1 (30-120) and mAG-hGem (1-100) 15 using lentivirus co-transduction as previously described 7. 
		Note: The FUCCI system is now commercially available.</li>
		<li>Generate sub-clones with bright fluorescence by single-cell sorting. Sort single cells positive for both AG and KO (yellow) by fluorescence activated cell sorting into a 96-well plate as previously described 7,16.</li>
	</ol>
	</li>
	<li>Melanoma cell culture
	<ol>
		<li>Culture C8161 human melanoma cells as previously described 7,17.</li>
	</ol>
	</li>
</ol>
2. 3D Spheroid Formation (as previously described 3,9)
<ol>
	<li>Agarose plate preparation
	<ol>
		<li>Dissolve 1.5% agarose (or noble agar) in 100 ml of Hank&#8217;s balanced salt solution (HBSS) or phosphate buffered saline (PBS) by boiling in the microwave for 3-5 min with swirling. Make sure the agarose is fully dissolved.</li>
		<li>Immediately dispense 100 &#956;l of the agarose solution per well to a flat-bottomed 96-well tissue culture plate using a multi-channel pipette. 
		Note: Agarose may solidify in the tips after a short period of time, to overcome this problem tips must be changed between plates if making more than one agarose plate.</li>
		<li>Leave 96-well plate on a flat surface to harden agarose for at least 1 hr.</li>
	</ol>
	</li>
	<li>Cell preparation and overlay onto agarose
	<ol>
		<li>Grow cells to approximately 80% confluency in a T75 flask. Wash with 10 ml of HBSS.</li>
		<li>Detach cells using 1.5 ml of 0.05% trypsin/ethylenediaminetetraacetic acid (EDTA) and resuspend in 10 ml of normal medium.</li>
		<li>Count cells using a hemocytometer 18 or other automated counting method.</li>
		<li>Resuspend cells to a final concentration of 25,000 cells/ml in normal medium.</li>
		<li>Overlay agarose wells with 200 &#956;l of the cell suspension for a final number of 5,000 cells per well.</li>
		<li>Return plates to the cell culture incubator (5% CO2 and 37 &#730;C) to form spheroids over approximately 3 days. 
		Note: The time taken to form a spheroid varies between different cell lines. Some cell lines do not form spheroids using this method at all.</li>
		<li>Image spheroid morphology with an inverted microscope using a 4X&#160;objective and a phase contrast filter. A cell line that successfully forms spheroids will produce compact, roughly spherical cell aggregates, and there should be only one spheroid per well. 
		Note: Optional: Once spheroids have formed, they can be transplanted into collagen or other matrix for further analysis of growth and invasion 3,7,17. To remove spheroids from collagen, treat with 500 &#956;l of 2 mg/ml collagenase at 37 &#176;C until the collagen is dissolved enough for the spheroids to come free into the media (approximately 30 min). Gently remove spheroids using a 1 ml pipette.</li>
		<li>For sectioning/imaging fix spheroids (either isolated from collagen or grown for 3-5 days on agarose) in 10% neutral buffered formalin (CAUTION: Formalin should be used in a fume cupboard) for at least 2 hr at room temperature (RT), or overnight (O/N) at 4 &#176;C. Spheroids may be stored in HBSS at 4 &#176;C for several days.</li>
	</ol>
	</li>
</ol>
3. Spheroid Vibratome Sectioning
<ol>
	<li>Dissolve 5 g of low melting point agarose in 100 ml of HBSS in a 500 ml glass bottle in a microwave. Use a medium heat setting with swirling. CAUTION: Keep the lid loose when boiling the solution so that the pressure can be released. Use protective heatproof gloves to protect hands from burns when handling the hot glass bottle.</li>
	<li>Wait until the agarose cools slightly &#8211; so the bottle can be touched without burning hands .</li>
	<li>Pour approximately 2 ml of agarose into the bottom of a Coulter counter cup or similar plastic mold. Immediately aspirate a fixed spheroid (see section 2.2.8) using a 1 ml pipette in the smallest volume of liquid possible. Add spheroid to the agarose. A few spheroids (up to 10) may be added per cup.</li>
	<li>Cover the spheroids with 2 ml more of agarose. Do this quickly to avoid the agarose hardening before the second layer is added.</li>
	<li>Allow the agarose to harden at RT in the dark for at least 3 hr. At this point cups may be stored for a short time at 4 &#176;C with 2-3 ml of HBSS overlaid to prevent dehydration.</li>
	<li>Remove agarose from the cup. Trim the agarose containing the spheroids so that it fits onto the vibratome metal block, and spheroids are close to the top of the agarose. Spheroids can be seen as small white objects inside the agarose. Super glue the agarose to the block. &#160;</li>
	<li>Fill the vibratome with distilled water and mount the block in the vibratome. Set the vibratome to cut 100 &#181;m sections using low speed (setting 2) and high vibration (setting 8). Set the cutting blade angle to 16&#176;. Turn vibratome on, turn on the vibratome light and cut sections from the top of the agarose until 100 &#181;m spheroid sections are cut. Place cut spheroid sections into HBSS in a 24-well plate.</li>
	<li>Choose middle sections for image analysis. Mount sections on slides by transferring the section flat onto the slide using tweezers. Fill a 10 ml syringe barrel with vacuum grease; add a thin line of vacuum grease around the edges of the section in order to prevent the mounting media from running off the edges of the slide and help seal the section under the coverslip. Cover the section with mounting medium and a coverslip. Seal edges of coverslip with nail polish. Store slides at 4 &#176;C before imaging.</li>
</ol>
4. Confocal Image Acquisition
<ol>
	<li>Take a z-slice image of a middle FUCCI spheroid section using a 10X&#160;or 20X&#160;objective as previously described 7. Make sure no overlap or crosstalk occurs between the Kusabira Orange2 and Azami Green. If comparing image analysis between multiple spheroid sections, keep laser power and other settings the same between samples.</li>
</ol>
5. Hoechst Dye Diffusion Assay for Flow Sorting
<ol>
	<li>Transfer live spheroids (3-5 days after agarose seeding) to a 15 ml tube. Let spheroids gravity settle to the bottom of the tube. Several spheroids may be stained per tube. Approximately 20 spheroids are needed to gain sufficient cell numbers for flow cytometry.</li>
	<li>Remove excess medium and add 1 ml of 10 &#956;M Hoechst diluted in normal medium. Incubate spheroids at 37 &#176;C for approximately 1 hr. Use gentle flicking to resuspend the spheroids once or twice during incubation. 
	Note: The incubation time may be varied to alter how far the Hoechst dye penetrates into the spheroids. This will vary based on the spheroid size, density and cell line. For some large/dense spheroids there may be a maximum dye penetration that is less than 100%.</li>
	<li>Wash the spheroids gently with 5 ml of HBSS using gravity settling.
	<ol>
		<li>Optional: For imaging of dye penetration: Fix spheroids with 10% neutral buffered formalin for at least 2 hr at RT or O/N at 4 &#176;C. Prepare vibratome sections, mount on slides and image on the confocal as described in steps 3 and 4 above.</li>
	</ol>
	</li>
	<li>To prepare cells for flow cytometry, trypsinize spheroids with 1 ml of 0.05% trypsin/EDTA at 37 &#176;C for approximately 30 min with flicking every 10 min to break the spheroids apart. 
	Note: Spheroids are difficult to get into single cell suspension, conditions may need to be optimized. Viability of C8161 4 day old spheroids after this process is approximately 95%.</li>
	<li>Stain cells with a near-infrared live/dead stain according to the manufacturers protocol. Wash with HBSS then fix with 1 ml of 10% neutral buffered formalin for approximately 30 min. Cells may be stored in HBSS at 4 &#176;C for several days before flow analysis.</li>
</ol>
6. Flow Cytometry Analysis of Hoechst Stained FUCCI Spheroids
<ol>
	<li>Ensure cells are not clumped together by passing them through a cell strainer. Resuspend the Hoechst stained FUCCI spheroids in ice cold FACS wash (PBS with 5% Fetal Calf Serum) at a concentration of 1-5 x 106 cells/ml. Transfer 200 &#181;l of sample to 5 ml round bottom tubes.</li>
	<li>Prepare the following single colour control samples as described in 6.1: un-stained melanoma cells; adherent melanoma cells stained with 10 &#181;M Hoechst for 1 hr; Azami Green only expressing melanoma cells; and Kusabira Orange only expressing melanoma cells. 
	Note: Single colour controls may be fixed in formalin and stored in FACS wash with 0.1% Sodium Azide at 4 &#176;C for weeks or even months.</li>
	<li>Run single cell suspensions on a flow cytometry analyzer with appropriate lasers and single colour/unstained controls as previously described 7,16.</li>
	<li>Use commercial cytometry software such as FlowJo to analyze the inner vs. outer spheroid cells as follows:
	<ol>
		<li>Remove debris by gating on the main cell population in Forward Scattered Light (FSC) vs. Side Scattered Light (SSC).</li>
		<li>Remove doublets by gating on single cells using FSC (Area) vs. FSC (Height)</li>
		<li>Gate for live cells by gating on the live/dead low population.</li>
		<li>Define Hoechst high cells, gated based on the positive signal from the adherent cells stained with Hoechst, as &#8220;outer&#8221; cells.</li>
		<li>Define Hoechst low or negative cells, gated based on the signal from the un-stained control, as &#8220;inner&#8221; cells.</li>
		<li>After gating for the inner and outer populations, cells may be further gated for FUCCI red (G1), yellow (early S), green (S/G2/M) or negative (early G1). 
		Note: Compensation using the single colour controls may be required to properly define the FUCCI red, yellow, green and negative populations.</li>
	</ol>
	</li>
	<li>Once the assay has been optimized and Hoechst penetration validated via confocal microscopy, run cells without fixing on a flow cell sorter as previously described 7,16 for further analysis of live cell sub-populations.</li>
</ol>
7. Image Analysis of FUCCI Spheroid Sections
<ol>
	<li>Open software e.g. Volocity, choose the Quantitation ONLY configuration.</li>
	<li>Create a new library. Import the FUCCI spheroid confocal image file into the software by dragging the raw data file from the confocal into the library. Alternatively, use the File &#62;Import&#160;command.</li>
	<li>Go to the measurements tab to build an image analysis protocol. The Protocol is built by dragging and dropping the appropriate commands in the correct order as follows in the protocol window.</li>
	<li>Find objects in the green channel: Drag the find objects command (found in &#8216;Finding&#8217;) into the protocol window, select the correct channel in the find objects protocol.Add an open command (found in &#8216;Processing&#8217;), then a separate touching objects command (found in &#8216;Processing&#8217; - this will separate cells). Exclude objects by size &#60;50 &#956;m (found in &#8216;Filtering&#8217; - this will exclude small non-cellular objects). 
	Note: Variables such as the find objects threshold, number of open iterations, the size of objects to be separated and the size of objects to exclude must be manually optimized until the object masks match the image.</li>
	<li>Find objects in the red channel: Repeat find objects as above for the red channel. Green and red protocols may need to be adjusted separately. 
	Note: Due to nuclei being in G2, green nuclei are often slightly larger.</li>
	<li>Confirm objects found are accurate: Confirm red and green objects match the red and green nuclei in the image by turning off and on the green and red channels (using the hide or show channel command) while displaying the red and green masks found by the protocol. Feedback options (Measurements &#62;Feedback options) may be used to modify the appearance of the object masks.</li>
	<li>Find yellow objects (early S phase cells): To find yellow cells, add an intersect red with green cells command (found in &#8216;Combining&#8217;). Exclude objects by size (&#60;50 &#956;m, found in &#8216;Filtering&#8217;) to exclude any small non-cellular objects.</li>
	<li>Find exclusively red objects (G1 phase cells): To find exclusively red nuclei, subtract the yellow cells from the red cells (found in &#8216;Combining&#8217;). Exclude objects by size &#60;50 &#956;m, (found in &#8216;Filtering&#8217;) to remove any small non-cellular objects created.</li>
	<li>Find exclusively green objects (S/G2/M phase cells): Repeat for the green channel to find exclusively green. 
	Note: If there are still non-cellular objects remaining, a filter population command may be added to the Exclusive green or Exclusive red protocols (found in &#8216;Filtering&#8217;) to retain only objects with a shape factor greater than 0.25. This will remove non-circular objects.</li>
	<li>Find the spheroid outline: Find the spheroid outline using a find objects command (found in &#8216;Finding&#8217;) with the green or red channel (whichever has more cells around the edge of the spheroid). A much lower threshold (found in the find objects variables) will need to be used to find the spheroid outline compared to individual cells.
	<ol>
		<li>Use a close command to join objects (found in &#8216;Processing&#8217;), then fill holes in objects (found in &#8216;Processing&#8217;), then use a fine filter (found in &#8216;Filtering&#8217;) to remove noise from objects. Finally, exclude objects by size to remove smaller objects &#60;30,000 &#956;m (depending on the spheroid size). 
		Note: This protocol will need to be optimized manually till the spheroid outline is accurate. A brightfield image may also be used &#8211; however this is usually less accurate with a spheroid section, and an invert command (found in &#8216;Combining&#8217;) will need to be used.</li>
	</ol>
	</li>
	<li>Measure distances of nuclei to spheroid outline: Measure distances (found in &#8216;Relating&#8217;) from the yellow, exclusively green and exclusively red populations from the cell centroid to the edge of the spheroid outline.To visualize the minimum distances, which should be from the cell to the nearest spheroid edge, turn on show distances in the relationships tab in feedback options (Measurements &#62;Feedback options &#62;Relationships).</li>
	<li>Save the protocol. This protocol may be re-applied to other images using the Measurements &#62;Restore protocol command.</li>
	<li>Create a measurements item (Measurements &#62;Make Measurement Item). Data may be analyzed using the analysis functions.
	<ol>
		<li>Go to the analysis tab in the measurements item. Go to the Analysis menu (Analysis &#62;Analyze) and analyze the minimum distance from the cell centroid (red, green or yellow) to the spheroid edge, summarized by count and organized by population.</li>
		<li>To count the number of cells found at a certain distance from the edge create a filter (Analysis &#62;Filter). The filter for minimum distance in Figure 2 is based on Hoechst penetration (e.g. minimum distance is less than 80 gives the &#8220;outer&#8221; population). Alternatively, export raw data to a spreadsheet for further analysis.</li>
	</ol>
	</li>
</ol>

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<li>Minchinton, A. I., Tannock, I. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Drug+penetration+in+solid+tumours%5BTitle%5D)+AND+%22Nature+reviews.+Cancer%22%5BJournal%5D)">Drug penetration in solid tumours.</a> Nature reviews. Cancer. 6, 583-592 (2006).</li>
<li>Giesbrecht, J. L., Wilson, W. R., Hill, R. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Radiobiological+studies+of+cells+in+multicellular+spheroids+using+a+sequential+trypsinization+technique%5BTitle%5D)+AND+%22Radiation+research%22%5BJournal%5D)">Radiobiological studies of cells in multicellular spheroids using a sequential trypsinization technique.</a> Radiation research. 86, 368-386 (1981).</li>
</ol>

PerkinElmer contributed to the costs of publication.

Semi-automated image analysis identified the spheroid inner G1 arrested region, and proliferating outer layers. This method may be used on live spheroids using an optical section, or in fixed spheroid sections, to identify changes in not only the cell cycle but marker expression (via immunofluorescence), cell death, or cell morphology in these different regions. Cell motility within different spheroid regions may also be quantified &#8211; if live confocal time lapse imaging along with a cell tracking image analysis step...

Multicellular 3D spheroids have been known as a tumor model for decades, however it is only recently that they have come into more common usage as an in vitro model for many solid cancers. They are increasingly being used in high-throughput drug discovery screens as an intermediate between complex, expensive and time-consuming in vivo models and the simple, low cost 2D monolayer model 1-6. Studies in 2D culture are often unable to be replicated in vivo. Spheroid models of many types of cancer are able to mimic the growth characteristics, drug sensitivity, drug penetration, cell-cell interactions, restricted availability of oxygen and nutrients and development of necrosis that is seen in vivo in solid tumors 6-11. Spheroids develop a necrotic core, a quiescent or G1 arrested region surrounding the core, and proliferating cells at the periphery of the spheroid 7. The development of these regions may vary depending on the cell density, proliferation rate and the size of the spheroid 12. It has been hypothesized that the cellular heterogeneity seen in these different sub-regions may contribute to cancer therapy resistance 13,14. Therefore the ability to analyze cells in these regions separately is crucial to understanding tumor drug responses.
The fluorescence ubiquitination cell cycle indicator (FUCCI) system is based on the red (Kusabira Orange &#8211; KO) and green (Azami Green &#8211; AG) fluorescent tagging of Cdt1 and geminin, which are degraded in different phases of the cell cycle 15. Thus cell nuclei appear red in G1, yellow in early S and green in S/G2/M phase. We describe here two complementary methods both using FUCCI to identify the cell cycle, along with the use of imaging software or a dye diffusion flow cytometry assay to determine whether cells reside in the G1 arrested center or the outer proliferating ring, and the distance of individual cells from the edge of the spheroid. These methods were developed in our previous publication, where we demonstrated that melanoma cells in hypoxic regions in the center of the spheroid or/and in the presence of targeted therapies are able to remain in G1 arrest for extended periods of time, and can re-enter the cell cycle when more favorable conditions arise 7.

<table><tbody><tr><td>Hoechst 33342</td><td>Life Technologies</td><td>H3570</td><td></td></tr><tr><td>agarose low melting point</td><td>Life Technologies</td><td>16520-050</td><td>For sectioning</td></tr><tr><td>noble agar&amp;nbsp;</td><td>Sigma</td><td>A5431</td><td>For making spheroids</td></tr><tr><td>agarose for spheroids</td><td>Fisher Scientific</td><td>BP1356-100</td><td>For making spheroids</td></tr><tr><td>0.05% trypsin/EDTA</td><td>Life Technologies</td><td>25300-054</td><td></td></tr><tr><td>HBSS</td><td>Life Technologies</td><td>14175-103</td><td></td></tr><tr><td>10% formalin</td><td>Sigma</td><td>HT5014-1CS</td><td>CAUTION: Harmful, corrosive. Use Personal Protective Equipment, do &amp;nbsp;not breath fumes (open in a fume cupboard).</td></tr><tr><td>live/dead near IR</td><td>Life Technologies</td><td>L10119</td><td></td></tr><tr><td>vibratome</td><td>Technical Products International, Inc</td><td></td><td></td></tr><tr><td>coulture cup</td><td>Thermo-Fisher Scientific</td><td>SIE936</td><td>Mold for sectioning spheroids</td></tr><tr><td>hemocytometer</td><td>Sigma</td><td>Z359629</td><td></td></tr><tr><td>96-well tissue culture plate</td><td>Invitro</td><td>FAL353072</td><td></td></tr><tr><td>collagenase</td><td>Sigma</td><td>C5138&amp;nbsp;</td><td></td></tr><tr><td>confocal microscope</td><td>Leica</td><td>TCS SP5</td><td></td></tr><tr><td>Flow cytometer analyser</td><td>Becton Dickinson</td><td>LSRFortessa</td><td></td></tr><tr><td>volocity</td><td>PerkinElmer</td><td></td><td>Imaging software</td></tr><tr><td>flowjo</td><td>Tree Star</td><td></td><td>Flow cytometry software</td></tr><tr><td>Vaccuum grease</td><td>Sigma</td><td>Z273554</td><td></td></tr><tr><td>Mounting media</td><td>Vector Laboratories</td><td>H1000</td><td></td></tr><tr><td>FUCCI (commercial constructs)</td><td>Life Technologies</td><td>P36238</td><td>Transient transfection only</td></tr><tr><td>Cell strainer 70 &amp;#956;m</td><td>In Vitro</td><td>FAL352350</td><td></td></tr><tr><td>Round bottom 5 ml tubes (sterile)</td><td>In Vitro</td><td>FAL352003</td><td></td></tr><tr><td>Round bottom 5 ml tubes (non-sterile)</td><td>In Vitro</td><td>FAL352008</td><td></td></tr></tbody></table>

imaging- and flow cytometry-based analysis of cell position and the cell cycle in 3d melanoma spheroids

Three-dimensional (3D) tumor spheroids are utilized in cancer research as a more accurate model of the in vivo tumor microenvironment, compared to traditional two-dimensional (2D) cell culture. The spheroid model is able to mimic the effects of cell-cell interaction, hypoxia and nutrient deprivation, and drug penetration. One characteristic of this model is the development of a necrotic core, surrounded by a ring of G1 arrested cells, with proliferating cells on the outer layers of the spheroid. Of interest in the cancer field is how different regions of the spheroid respond to drug therapies as well as genetic or environmental manipulation. We describe here the use of the fluorescence ubiquitination cell cycle indicator (FUCCI) system along with cytometry and image analysis using commercial software to characterize the cell cycle status of cells with respect to their position inside melanoma spheroids. These methods may be used to track changes in cell cycle status, gene/protein expression or cell viability in different sub-regions of tumor spheroids over time and under different conditions.

There are several methods of producing tumor spheroids, this protocol uses the non-adherent growth method, where cells are cultured on agar or agarose 3,7,9. Figure 1 shows an example of a C8161 melanoma spheroid after 3 days on agar. C8161 spheroids form regular sized spheroids with a diameter of 500 - 600 &#956;m (mean = 565, SD = 19, n = 3) after 3 days. Other melanoma cell lines that will form spheroids include: WM793, WM983C, WM983B, WM164, 1205lu (spheroids formed with this cell line are...

Watch this Scientific Journal Video about Imaging- and Flow Cytometry-based Analysis of Cell Position and the Cell Cycle in 3D Melanoma Spheroids at JoVE.com

Imaging- and Flow Cytometry-based Analysis of Cell Position and the Cell Cycle in 3D Melanoma Spheroids

We describe two complementary methods using the fluorescence ubiquitination cell cycle indicator (FUCCI) and image analysis or flow cytometry to identify and isolate cells in the inner G1 arrested and outer proliferating regions of 3D spheroids.

Three-dimensional (3D) tumor spheroids are utilized in cancer research as a more accurate model of the in vivo tumor microenvironment, compared to ...

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13.0K Views.  The Centenary Institute. We describe two complementary methods using the fluorescence ubiquitination cell cycle indicator (FUCCI) and image analysis or flow cytometry to identify and isolate cells in the inner G1 arrested and outer proliferating regions of 3D spheroids. 

Video: Imaging- and Flow Cytometry-based Analysis of Cell Position and the Cell Cycle in 3D Melanoma Spheroids

A 3D Organotypic Melanoma Spheroid Skin Model

Malignant transformation of melanocytes, the pigment cells of human skin, causes formation of melanoma, a highly aggressive cancer with increased metastatic potential. Recently, mono-chemotherapies continue to improve by melanoma specific combination therapies with targeted kinase inhibitors. Still, metastatic melanoma remains a life-threatening disease because tumors exhibit primary resistance or develop resistance to novel therapies, thereby regaining tumorigenic capacity. In order to improve the therapeutic success of malignant melanoma, the determination of molecular mechanisms conferring resistance against conventional treatment approaches is necessary; however, it requires innovative cellular in vitro models. Here, we introduce an in vitro three-dimensional (3D) organotypic melanoma spheroid model that can portray the in vivo architecture of malignant melanoma and may warrant new insights into intra-tumoral as well as tumor-host interactions. The model incorporates defined numbers of mature and differentiated melanoma spheroids in a 3D human full skin reconstruction model consisting of primary skin cells. The cellular composition and differentiation status of the embedded melanoma spheroids is similar to the one of cutaneous melanoma metastasis in vivo. Using this organotypic melanoma spheroid model as a drug screening platform may support the identification of responders to selected combination therapies, while sparing the unnecessary treatment burden for non-responders, thereby increasing the benefit of therapeutic interventions.

Here, we present a protocol to generate a 3D organotypic melanoma spheroid skin model that recapitulates both the architecture and multicellular complexity of an organ/tumor in vivo but at the same time accommodates systematic experimental intervention.

Malignant transformation of melanocytes, the pigment cells of human skin, causes formation of melanoma, a highly aggressive cancer with increased ...

Cancer Research

Longitudinal Morphological and Physiological Monitoring of Three-dimensional Tumor Spheroids Using Optical Coherence Tomography

Tumor spheroids have been developed as a three-dimensional (3D) cell culture model in cancer research and anti-cancer drug discovery. However, currently, high-throughput imaging modalities utilizing bright field or fluorescence detection, are unable to resolve the overall 3D structure of the tumor spheroid due to limited light penetration, diffusion of fluorescent dyes and depth-resolvability. Recently, our lab demonstrated the use of optical coherence tomography (OCT), a label-free and non-destructive 3D imaging modality, to perform longitudinal characterization of multicellular tumor spheroids in a 96-well plate. OCT was capable of obtaining 3D morphological and physiological information of tumor spheroids growing up to about 600 &#181;m in height. In this article, we demonstrate a high-throughput OCT (HT-OCT) imaging system that scans the whole multi-well plate and obtains 3D OCT data of tumor spheroids automatically. We describe the details of the HT-OCT system and construction guidelines in the protocol. From the 3D OCT data, one can visualize the overall structure of the spheroid with 3D rendered and orthogonal slices, characterize the longitudinal growth curve of the tumor spheroid based on the morphological information of size and volume, and monitor the growth of the dead-cell regions in the tumor spheroid based on optical intrinsic attenuation contrast. We show that HT-OCT can be used as a high-throughput imaging modality for drug screening as well as characterizing biofabricated samples.

Optical coherence tomography (OCT), a three-dimensional imaging technology, was used to monitor and characterize the growth kinetics of multicellular tumor spheroids. Precise volumetric quantification of tumor spheroids using a voxel counting approach, and label-free dead tissue detection in the spheroids based on intrinsic optical attenuation contrast, were demonstrated.

Tumor spheroids have been developed as a three-dimensional (3D) cell culture model in cancer research and anti-cancer drug discovery. However, currently, ...

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.

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 ...

Assessing Cell Viability and Death in 3D Spheroid Cultures of Cancer Cells

Three-dimensional spheroids of cancer cells are important tools for both cancer drug screens and for gaining mechanistic insight into cancer cell biology. The power of this preparation lies in its ability to mimic many aspects of the in vivo conditions of tumors while being fast, cheap, and versatile enough to allow relatively high-throughput screening. The spheroid culture conditions can recapitulate the physico-chemical gradients in a tumor, including the increasing extracellular acidity, increased lactate, and decreasing glucose and oxygen availability, from the spheroid periphery to its core. Also, the mechanical properties and cell-cell interactions of in vivo tumors are in part mimicked by this model. The specific properties and consequently the optimal growth conditions, of 3D spheroids, differ widely between different types of cancer cells. Furthermore, the assessment of cell viability and death in 3D spheroids requires methods that differ in part from those employed for 2D cultures. Here we describe several protocols for preparing 3D spheroids of cancer cells, and for using such cultures to assess cell viability and death in the context of evaluating the efficacy of anticancer drugs.

Here, we present several simple methods for evaluating viability and death in 3D cancer cell spheroids, which mimic the physico-chemical gradients of in vivo tumors much better than the 2D culture. The spheroid model, therefore, allows evaluation of the cancer drug efficacy with improved translation to in vivo conditions.

Three-dimensional spheroids of cancer cells are important tools for both cancer drug screens and for gaining mechanistic insight into cancer cell biology. ...

A 3D Spheroid Model as a More Physiological System for Cancer-Associated Fibroblasts Differentiation and Invasion In Vitro Studies

Defining the ideal model for an in vitro study is essential, mainly if studying physiological processes such as differentiation of cells. In the tumor stroma, host fibroblasts are stimulated by cancer cells to differentiate. Thus, they acquire a phenotype that contributes to the tumor microenvironment and supports tumor progression. By using the spheroid model, we have set up such a 3D in vitro model system, in which we analyzed the role of laminin-332 and its receptor integrin &#945;3&#946;1 in this differentiation process. This spheroid model system not only reproduces the tumor microenvironment conditions in a more accurate way, but also is a very versatile model since it allows different downstream studies, such as immunofluorescent staining of both intra- and extracellular markers, as well as deposited extracellular matrix proteins. Moreover, transcriptional analyses by qPCR, flow cytometry and cellular invasion can be studied with this model. Here, we describe a protocol of a spheroid model to assess the role of CAFs&#39; integrin &#945;3&#946;1 and its ectopically deposited ligand, laminin-332, in differentiation and in supporting the invasion of pancreatic cancer cells.

The goal of this protocol is to establish a 3D in vitro model to study the differentiation of cancer-associated fibroblasts (CAFs) in a tumor bulk-like environment, which can be addressed in different analysis systems, such as immunofluorescence, transcriptional analysis and life cell imaging.

Defining the ideal model for an in vitro study is essential, mainly if studying physiological processes such as differentiation of cells. In the tumor ...

A Novel Stromal Fibroblast-Modulated 3D Tumor Spheroid Model for Studying Tumor-Stroma Interaction and Drug Discovery

Tumor-stroma interactions play an important role in cancer progression. Three-dimensional (3D) tumor spheroid models are the most widely used in vitro model in the study of cancer stem/initiating cells, preclinical cancer research, and drug screening. The 3D spheroid models are superior to conventional tumor cell culture and reproduce some important characters of real solid tumors. However, conventional 3D tumor spheroids are made up exclusively of tumor cells. They lack the participation of tumor stromal cells and have insufficient extracellular matrix (ECM) deposition, thus only partially mimicking the in vivo conditions of tumor tissues. We established a new multicellular 3D spheroid model composed of tumor cells and stromal fibroblasts that better mimics the in vivo heterogeneous tumor microenvironment and its native desmoplasia. The formation of spheroids is strictly regulated by the tumor stromal fibroblasts and is determined by the activity of certain crucial intracellular signaling pathways (e.g., Notch signaling) in stromal fibroblasts. In this article, we present the techniques for coculture of tumor cells-stromal fibroblasts, time-lapse imaging to visualize cell-cell interactions, and confocal microscopy to display the 3D architectural features of the spheroids. We also show two examples of the practical application of this 3D spheroid model. This novel multicellular 3D spheroid model offers a useful platform for studying tumor-stroma interaction, elucidating how stromal fibroblasts regulate cancer stem/initiating cells, which determine tumor progression and aggressiveness, and exploring involvement of stromal reaction in cancer drug sensitivity and resistance. This platform can also be a pertinent in vitro model for drug discovery.

A novel three-dimensional spheroid model based on the heterotypic interaction of tumor cells and stromal fibroblasts is established. Here, we present coculture of tumor cells and stromal fibroblasts, time-lapse imaging, and confocal microscopy to visualize the formation of spheroids. This three-dimensional model offers a pertinent platform to study tumor-stroma interactions and test cancer therapeutics.

Tumor-stroma interactions play an important role in cancer progression. Three-dimensional (3D) tumor spheroid models are the most widely used in vitro ...

Rapid Optical Clearing for Semi-High-Throughput Analysis of Tumor Spheroids

Tumor spheroids are fast becoming commonplace in basic cancer research and drug development. Obtaining data regarding protein expression within the spheroid at the cellular level is important for analysis, yet existing techniques are often expensive, laborious, use non-standard equipment, cause significant size distortion, or are limited to relatively small spheroids. This protocol presents a new method of mounting and clearing spheroids that address these issues while allowing for confocal analysis of the inner structure of spheroids. In contrast to existing approaches, this protocol provides for rapid mounting and clearing of a large number of spheroids using standard equipment and laboratory supplies. Mounting spheroids in a pH-neutral agarose-PBS gel solution before introducing a refractive-index-matched clearing solution minimizes size distortion common to other similar techniques. This allows for detailed quantitative and statistical analysis where the accuracy of size measurements is paramount. Furthermore, compared to liquid clearing solutions, the agarose gel technique keeps spheroids fixed in place, allowing for the collection of three-dimensional (3D) confocal images. The present article elaborates how the method yields high-quality two- and 3D images that provide information about inter-cell variability and inner spheroid structure.

Tumor spheroids are becoming increasingly utilized to assess tumor cell-microenvironment interactions and therapy response. The present protocol describes a robust but simple method for semi-high-throughput imaging of 3D tumor spheroids using rapid optical clearing.

Tumor spheroids are fast becoming commonplace in basic cancer research and drug development. Obtaining data regarding protein expression within the ...

Three-Dimensional (3D) Tumor Spheroid Invasion Assay

Invasion of surrounding normal tissues is generally considered to be a key hallmark of malignant (as opposed to benign) tumors. For some cancers in particular (e.g., brain tumors such as glioblastoma multiforme and squamous cell carcinoma of the head and neck &#8211; SCCHN) it is a cause of severe morbidity and can be life-threatening even in the absence of distant metastases. In addition, cancers which have relapsed following treatment unfortunately often present with a more aggressive phenotype. Therefore, there is an opportunity to target the process of invasion to provide novel therapies that could be complementary to standard anti-proliferative agents. Until now, this strategy has been hampered by the lack of robust, reproducible assays suitable for a detailed analysis of invasion and for drug screening. Here we provide a simple micro-plate method (based on uniform, self-assembling 3D tumor spheroids) which has great potential for such studies. We exemplify the assay platform using a human glioblastoma cell line and also an SCCHN model where the development of resistance against targeted epidermal growth factor receptor (EGFR) inhibitors is associated with enhanced matrix-invasive potential. We also provide two alternative methods of semi-automated quantification: one using an imaging cytometer and a second which simply requires standard microscopy and image capture with digital image analysis.

Three-Dimensional 3D Tumor Spheroid Invasion Assay

Invasion of surrounding normal tissues is a defining characteristic of malignant tumors. We provide here a simple, semi-automated micro-plate assay of invasion into a natural 3D biomatrix that has been exemplified with a number of models of advanced human cancers.

Invasion of surrounding normal tissues is generally considered to be a key hallmark of malignant (as opposed to benign) tumors. For some cancers in ...

Examining Macrophage-Tumor Spheroid Interactions in a 3D Collagen Matrix Setup

A Macrophage-Tumor Spheroid Co-Invasion Assay

The interaction of immune and cancer cells and their respective impact on metastasis represents an important aspect of cancer research. So far, only a few protocols are available that allow an in vitro approximation of the in vivo situation. Here, we present a novel approach to observing the impact of human macrophages on the invasiveness of cancer cells, using tumor spheroids of H1299 non-small cell lung carcinoma cells embedded in a three-dimensional (3D) collagen I matrix. With this co-cultivation setup, we tested the impact of small interfering RNA (siRNA)-based depletion of regulatory factors in macrophages on the 3D invasion of cancer cells from the tumor spheroid compared to controls. This method allows the determination of different parameters, such as spheroid area or the number of invading cancer cells, and thus, to detect differences in cancer cell invasion. In this article, we present the respective setup, discuss the subsequent analysis, as well as the advantages and potential pitfalls of this method.

Here, we present a protocol to investigate the interaction of primary human monocyte-derived macrophages with a tumor spheroid in a three-dimensional (3D) collagen I matrix, with the possibility to compare the impact of soluble and physical properties of the microenvironment on cell invasion.

The interaction of immune and cancer cells and their respective impact on metastasis represents an important aspect of cancer research. So far, only a few ...

Time-Resolved Fluorescence Imaging and Analysis of Cancer Cell Invasion in the 3D Spheroid Model

The invasion of cancer cells from the primary tumor into the adjacent healthy tissues is an early step in metastasis. Invasive cancer cells pose a major clinical challenge because no efficient method exist for their elimination once their dissemination is underway. A better understanding of the mechanisms regulating cancer cell invasion may lead to the development of novel potent therapies. Due to their physiological resemblance to tumors, spheroids embedded in collagen I have been extensively utilized by researchers to study the mechanisms governing cancer cell invasion into the extracellular matrix (ECM). However, this assay is limited by (1) a lack of control over the embedding of spheroids into the ECM; (2) high cost of collagen I and glass bottom dishes, (3) unreliable immunofluorescent labeling, due to the inefficient penetration of antibodies and fluorescent dyes and (4) time-consuming image processing and quantification of the data. To address these challenges, we optimized the three-dimensional (3D) spheroid protocol to image fluorescently labeled cancer cells embedded in collagen I, either using time-lapse videos or longitudinal imaging, and analyze cancer cell invasion. First, we describe the fabrication of a spheroid imaging device (SID) to embed spheroids reliably and in a minimal collagen I volume, reducing the assay cost. Next, we delineate the steps for robust fluorescence labeling of live and fixed spheroids. Finally, we offer an easy-to-use Fiji macro for image processing and data quantification. Altogether, this simple methodology provides a reliable and affordable platform to monitor cancer cell invasion in collagen I. Furthermore, this protocol can be easily modified to fit the users&#8217; needs.

Presented here is a protocol for the fabrication of a spheroid imaging device. This device enables dynamic or longitudinal fluorescence imaging of cancer cell spheroids. The protocol also offers a simple image processing procedure for the analysis of cancer cell invasion.

The invasion of cancer cells from the primary tumor into the adjacent healthy tissues is an early step in metastasis. Invasive cancer cells pose a major ...

Imaging- and Flow Cytometry-based Analysis of Cell Position and the Cell Cycle in 3D Melanoma Spheroids

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