Real-time viability and apoptosis kinetic detection method of 3D multicellular tumor spheroids using the Celigo Image Cytometer.

The development of three-dimensional (3D) multicellular tumor spheroid models for cancer drug discovery research has increased in the recent years. The use of 3D tumor spheroid models may be more representative of the complex in vivo tumor microenvironments in comparison to two-dimensional (2D) assays. Currently, viability of 3D multicellular tumor spheroids has been commonly measured on standard plate-readers using metabolic reagents such as CellTiter-Glo® for end point analysis. Alternatively, high content image cytometers have been used to measure drug effects on spheroid size and viability. Previously, we have demonstrated a novel end point drug screening method for 3D multicellular tumor spheroids using the Celigo Image Cytometer. To better characterize the cancer drug effects, it is important to also measure the kinetic cytotoxic and apoptotic effects on 3D multicellular tumor spheroids. In this work, we demonstrate the use of PI and caspase 3/7 stains to measure viability and apoptosis for 3D multicellular tumor spheroids in real-time. The method was first validated by staining different types of tumor spheroids with PI and caspase 3/7 and monitoring the fluorescent intensities for 16 and 21 days. Next, PI-stained and nonstained control tumor spheroids were digested into single cell suspension to directly measure viability in a 2D assay to determine the potential toxicity of PI. Finally, extensive data analysis was performed on correlating the time-dependent PI and caspase 3/7 fluorescent intensities to the spheroid size and necrotic core formation to determine an optimal starting time point for cancer drug testing. The ability to measure real-time viability and apoptosis is highly important for developing a proper 3D model for screening tumor spheroids, which can allow researchers to determine time-dependent drug effects that usually are not captured by end point assays. This would improve the current tumor spheroid analysis method to potentially better identify more qualified cancer drug candidates for drug discovery research.