There is an increasing interest in using three-dimensional (3D) spheroids for modeling cancer and tissue biology to accelerate translation research. Development of higher throughput assays to quantify phenotypic changes in spheroids is an active area of investigation. The goal of this study was to develop higher throughput high-content imaging and analysis methods to characterize phenotypic changes in human cancer spheroids in response to compound treatment. We optimized spheroid cell culture protocols using low adhesion U-bottom 96- and 384-well plates for three common cancer cell lines and improved the workflow with a one-step staining procedure that reduces assay time and minimizes variability. We streamlined imaging acquisition by using a maximum projection algorithm that combines cellular information from multiple slices through a 3D object into a single image, enabling efficient comparison of different spheroid phenotypes. A custom image analysis method was implemented to provide multiparametric characterization of single-cell and spheroid phenotypes. We report a number of readouts, including quantification of marker-specific cell numbers, measurement of cell viability and apoptosis, and characterization of spheroid size and shape. Assay performance was assessed using established anticancer cytostatic and cytotoxic drugs. We demonstrated concentration–response effects for different readouts and measured IC50 values, comparing 3D spheroid results to two-dimensional cell cultures. Finally, a library of 119 approved anticancer drugs was screened across a wide range of concentrations using HCT116 colon cancer spheroids. The proposed methods can increase performance and throughput of high-content assays for compound screening and evaluation of anticancer drugs with 3D cell models.

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