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The Promises and Challenges of 3D Models

by Jordan Villanueva

There’s something beautiful about the tiny ball I’m looking at through the microscope. It’s only about 200—250 microns in diameter, smaller than a single grain of salt. As I bump the plate with my finger, the ball rolls around the 1mm well. To me, it may just look like a dark spot within an illuminated circle, but many scientists feel it could represent the future of oncology research and drug discovery.

It’s a Friday afternoon, and I’m staring at a spheroid of roughly 1,000 human liver cells. Promega Research Scientist Mike Valley heard that I was interested in 3-dimensional cell culture models, so he invited me over to his lab in the Research and Development Center to check out the spheroids for myself. Mike is developing a new assay, and with recent trends in cell biology research, he knows it’s crucial to optimize that assay for use with 3D cultures.

“I’m not sure what percentage it is, but there is definitely a shift in research going towards 3D models now,” Mike tells me.


Representing tumor biology in vivo

As I dig in to learn more about 3D models, I find a growing mountain of evidence that the differences in biology between 2D and 3D cultures could lead to different, sometimes opposite conclusions in research, and that the 3D models often better represent how cells behave in vivo.

“You can argue that 3D is not absolutely physiologically relevant,” says Research Scientist Drew Niles, “But it’s a step forward. That’s what we’re always doing with models: Trying to get them closer to being representative. I think everyone recognizes that 3D is a step forward.”

“That’s what we’re always doing with models: Trying to get them closer to being representative. I think everyone recognizes that 3D is a step forward.”

“All models are wrong, but some are useful,” says Sr. Product Manager Terry Riss, referencing statistician George Box.

In 2D culture, cells are typically plated in a flat monolayer. One-sided attachment induces a polarity that is unnatural for many cells. It also means that each cell is getting equal access to nutrients and oxygen, resulting in uniform growth and proliferation. Each cell is likely at the same metabolic state, which is rare in the body. Tumors, in contrast, show high levels of heterogeneity, with some cells actively proliferating, others quiescent, and some necrotic. This issue is less prevalent in 3D spheroids, where nutrient gradients emerge gradually as the diameter increases. As the spheroid grows, the cells in the core begin to experience reduced oxygen exposure. This results in a hypoxia gradient, which can lead inner layers to quiescence and even necrosis.

2D and 3D cultures also differ in the properties of their extracellular matrix (ECM). While ECM does form in 2D cultures, it fails to recapitulate the distribution and complexity of the tumor microenvironment seen in vivo. In 3D cultures, the cells are not only in close proximity to each other, but they develop a thicker, denser ECM that surrounds them and forms a barrier between the cells and the environment. “Attachment dependence is big for cancer cells,” says Drew. “The ECM sticks the cells together and makes it more like a true tumor mass.” The makeup and distribution of that ECM provides a more realistic representation of how cell:ECM interactions in solid tumors influence cell behaviors such as proliferation, differentiation and migration.

In addition to the nutrient gradients and ECM formation, 3D models can reflect the variety of cells surrounding a tumor in the body. Researchers can add immune cells and any other relevant cell types to the culture of cancer cells to get a better idea of how these interactions influence the biology of the tumor itself.

“Some cancers are really good at co-opting the activities of other cells,” says Drew. “I think that right now it’s really difficult for 2D models to recapitulate that tumor model, but in 3D, there can be multiple cell lineages in the sphere itself, which more or less simulates the actual tumor that’s present in a tissue.”

Challenges for assay development

As researchers increasingly turned to 3D, Promega scientists recognized the need to formulate assays that would be effective in these systems. The ECM coating in a 3D model often prevents reagents from penetrating to the center of the spheroid. For example, the CellTiter-Glo® Cell Viability Assay is a bioluminescent assay based on ATP detection, so incomplete lysis meant that much of the ATP present in the system was not measured, producing inaccurate results.

“With the original CellTiter-Glo® product, we noticed that as structures got larger and larger, there was a deviation between how much ATP we were extracting with acid compared to how much we would get with just following the original procedure,” says Terry. “That’s actually what led to reformulating the ATP detection range to make CellTiter-Glo® 3D.”

In the case of CellTiter-Glo®, Promega scientists discovered that the lytic reagent was failing to reach the cells in the center of the spheroid. They increased the lytic capacity of the reagent by adding more detergent and increasing the exposure time, resulting in deeper penetration and more complete lysis. The same logic may not apply to every assay, though. In some cases, no changes to the reagent composition are necessary, such as in the RealTime-Glo™ MT Cell Viability Assay.


Many researchers have published using RealTime-Glo™ MT Cell Viability Assay with 3D models, and Promega scientists have verified that the viability results are reliable in the cell models tested so far. However, it's important to remember that a specific assay may not have been tested with every available model or cell type. “With all of these assays, there’s a caveat in that different cells behave differently," says Terry. "The spheroids may be looser or more tightly packed, so we always say, ‘This is a recommendation, but you need to validate it with your own cells.’”

Promega currently offers 13 assays that have been tested with 3D cultures, but scientists like Mike and Drew are constantly working to keep up with the trend. As Promega receives an increasing number of requests related to applying assays to 3D cultures, they continue to develop more recommendations for getting answers from these complex systems.

Learn more about the CellTiter-Glo® 3D Cell Viability Assay

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“Some things you only discover when you roll up your sleeves and do the work.”

“More art than science”

A few days after my first visit, I’m back in the lab with Mike. He’s getting ready to assay the cells that I had previously examined. As I watch Mike remove the media from the two plates, I realize that this is the slowest I have ever seen someone transfer only 70µl of liquid. He’s using an electronic 8-channel pipetter, but it takes around 7 seconds to empty each row of wells.

“You have to be careful about how fast you pipette because the microtissues will move around,” Mike tells me. “We actually had to buy pipetters that can run at less than 10µl per second. We go as slowly as possible.”

It’s so slow that it’s almost painful to watch. I easily could have finished the same task in less time using only a single-channel manual pipetter, and I can’t imagine the tedium of working at that speed every day, but Mike insists that it’s safer this way.

“I gave some advice to other people in R&D, other people who were working with microtissues, but I forgot to tell them about the speed. They did their experiments and, at the end, they were just missing the tissues. I’m like, ‘That’s my fault, and I’m sorry, but that’s funny.’”

All of the Promega scientists I talk to share stories about unexpected issues they discovered while working with 3D models for the first time. “It’s more art than science, to be honest,” says Drew. “Some things you only discover when you roll up your sleeves and do the work.” Research scientist Natascha Karassina mentions one set of experiments in which the cells failed to come together into a spheroid and even the company that provided the plates and cells was unable to explain why. Terry describes scenarios where researchers new to 3D models have been confused by spheroids being visible following cell lysis, suggesting that the lysis was ineffective. He explains that the membranes could be lysed, releasing the ATP, but the ECM and other cell:cell interactions could hold the overall structure of the spheroid together so that it remained visible.

Above all, there’s a widespread belief that these methods need to be standardized to ensure replicability and minimize variability. There’s currently no one-size-fits-all method for producing 3D structures, largely because every tumor cell type is different. “Some people may just do 2D because it’s easier for them,” says Drew, “But I think that everyone will ultimately embrace 3D to some extent.”


The future of 3D models

These 3D systems are attractive to scientists working in drug discovery, because they will often produce a more accurate reflection of how the drug will affect cells in vivo. For example, Kota et al (2018) used a high-throughput screening approach with 3D spheroids of pancreatic epithelial tumor cells and found a potential drug candidate (Proscillaridin A) that would not have been identified as a selective hit in a traditional 2D approach. They describe differences in drug penetration, cell:cell interactions and hypoxia that they believe contribute to the contrasting results.

Outside of the drug discovery process, 3D models could revolutionize clinical approaches to cancer treatment. Every cancer is genetically distinct, and even single mutations could influence drug responses. Researchers are developing methods of using tumor samples from patients to create 3D organoids, called patient-derived organoids (PDOs). When a panel of compounds with known efficacy profiles is applied to these PDOs, the results have high predictability to the clinical response. These results could guide clinical decisions, and the genome sequences of the organoids could help researchers find correlations between specific mutations and responses to different drugs. All of this could someday streamline treatment regimen development and help patients gain quicker access to the drugs that could likely be most effective for their specific cancer.

As scientists continue improving 3D models, it will be crucial to address questions about standardization and replicability, as well as the financial challenges of widespread implementation. With the right conditions, perhaps these systems could spark a revolution in how we study and treat cancer. Every advance in recapitulating tumor biology in vivo represents massive potential for improving medicine and patient care, but from the researcher’s perspective, these advances are made one tiny spheroid and one excruciatingly slow pipet at a time.

Image credits: Spheroid image provided by Insphero, all other photographs by Wesley Bishop.