Uppsala University sees new details of anti-cancer therapies

A project at Uppsala University has developed a way to create 3D clusters of cancer cells and then image the individual cells within them, for a better understanding of how drug therapy operates.

Published in Nature Communications the study could allow researchers to see how different anti-cancer drugs that appear to have the same therapeutic effects in flat cell cultures can operate differently in real-world 3D environments.

The Uppsala project adapted the image-based assay method termed Cell Painting, and combined it with a means of turning 3D cell clusters transparent for imaging purposes.

Cell Painting, originally developed in 2016, combines multiple fluorescent dyes and imaging channels to differentiate between cellular components or organelles. Subsequent data analysis can reveal a large number of distinct morphological features distinguished by size, shape or optical intensity.

The technique has to date been applied to 2D flat cell cultures, noted the Uppsala team, rather than the 3D structures which would more closely the natural environments experienced by the cells. While advances have been made towards scalable profiling in 3D, current methods do not capture single-cell level phenotypic variations, and light scattering in samples more than a few cell layers thick poses a major hurdle.

"Cells behave differently when they grow in three dimensions, but most screening methods either use flat cultures or collapse a whole 3D sample into one picture," commented Christa Ringers from Uppsala University. "We wanted to keep the detail of single cells while still being able to test many drugs at once."

The Uppsala workflow involved first growing uniform spheroids of cells in suitable microplates and then applying an aqueous clearing solution of fructose and glycerol to render the spheroids transparent, analogous to the larger-scale optical clearing operations developed for animal organs or whole specimens.

Testing 52 anti-cancer drugs

A spinning-disk confocal imaging technique then carried out optical sectioning of the 3D cell structures, effectively imaging individual cells within the cleared spheroids. A customized detection algorithm assessed the orientation of each spheroid prior to imaging, compensating for positional errors that could otherwise interfere with comparisons - the first application of open-source on-the-fly detection tailored to high-content imaging, noted the project.

The team then tested 52 drugs used in or developed for cancer treatment, and noted that drug effects could be resolved more robustly than in flattened or broader views. In particular the effect of two drugs, the chemotherapy treatment 5-fluorouracil and the targeted cancer drug olaparib, were nearly indistinguishable in flat cultures but clearly different in minispheres.

These differences only became apparent when the researchers looked at each cell separately rather than each minisphere as a whole, said the Uppsala group. Follow-up experiments revealed new details of drug action, whereby 5-fluorouracil caused less DNA damage than olaparib but was better at stopping cells from dividing; potentially valuable data for improved cancer therapies.

The next steps will include applying this new imaging method to more complex 3D models, or to particular models known to be difficult to capture in 2D such as liver cell cultures. 

"Together with colleagues at AstraZeneca, we also ran the method outside the lab where it was developed," noted Ola Spjuth, professor at the Department of Pharmaceutical Biosciences, Uppsala University. "That kind of collaboration is a valuable test of whether a new method can be used by others."