A rapid 3D tumor spheroid analysis method using the Celigo Imaging Cytometry
Leo L. Chan, Scott Cribbes, Sarah Kessel, Olivier Dery, Catherine Swingler, Dmitry Kuksin, Tim Smith, Jean Qiu, Maria Vinci, Lisa Patterson, and Sue Eccles
The current 2D methods for cancer drug discovery have had some difficulty in identifying potential drug candidates that can be used for clinical testing. To overcome this challenge, there has been an increase in research of 3D tissue culture, which has facilitated the development of new in-vitro tumor model assays. Traditional 2D and 3D analysis method relied heavily on visual observation using microscopy. However, the method is time-consuming and has high variations. Automated plate-based imaging cytometry can be employed to rapidly analyze and characterize 3D tumor spheroids, which can be used to generate both quantitative and qualitative results. In this work, we
demonstrate a novel 3D tumor spheroid analysis method using the Celigo imaging cytometer for spheroid counting, size analysis, tumor migration and invasion, tumor viability, and dose response of drug induced/inhibited tumor growth. The plate-based imaging cytometer utilizes bright-field and three fluorescence channels (Blue, Green, and Red) for multi-channel analyses. By utilizing the F theta lens technology, uniform bright-field image are captured for more accurate counting of the entire well. In addition, Celigo analysis software is used to report numerous parameters allowing detailed spheroid characterization. In addition to direct spheroid counting in the well, the use of specific fluorescent dyes and probes allow the user to define viable and hypoxic areas within spheroids and monitor migration and invasion on or into supporting cells and/or tissues. The results showed that Celigo imaging cytometer can accurately count and measure spheroid sizes in response to drug induction. Furthermore, tumor migration and invasion were clearly observed and quantified in the captured images. By utilizing the 3D spheroid imaging cytometry method, researchers can quickly characterize and quantify tumor spheroids, which can improve the efficiency of identification of potential cancer drug candidates