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Tumor spheroid models have proven useful in the study of cancer cell responses to chemotherapeutic compounds by more closely mimicking the 3-dimensional nature of tumors in situ. Their advantages are often offset, however, by protocols that are long, complicated, and expensive. Efforts continue for the development of high-throughput assays that combine the advantages of 3D models with the convenience and simplicity of traditional 2D monolayer methods. Herein, we describe the development of a breast cancer spheroid image cytometry assay using T47D cells in Aggrewell™400 spheroid plates. Using the Celigo ® automated imaging system, we developed a method to image and individually track thousands of spheroids within the Aggrewell™400 microwell plate over time. We demonstrate the use of calcein AM and propidium iodide staining to study the effects of known anti-cancer drugs Doxorubicin, Everolimus, Gemcitabine, Metformin, Paclitaxel and Tamoxifen. We use the image cytometry results to quantify the fluorescence of calcein AM and PI as well as spheroid size in a dose dependent manner for each of the drugs. We observe a dose-dependent reduction in spheroid size and find that it correlates well with the viability obtained from the CellTiter96 ® endpoint assay. The image cytometry method we demonstrate is a convenient and high-throughput drug-response assay for breast cancer spheroids under 400 μm in diameter, and may lay a foundation for investigating other three-dimensional spheroids, organoids, and tissue samples., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Three-dimensional tumor spheroid models have been increasingly used to investigate and characterize cancer drug compounds. Previously, the Celigo image cytometer has demonstrated its utility in a high-throughput screening manner for evaluating potential drug candidates in a 3D multicellular tumor spheroid (MCTS) primary screen. In addition, we have developed real-time kinetic caspase 3/7 apoptosis and propidium iodide viability 3D MCTS assays, both of which can be used in a secondary screen to better characterize the hit compounds. In this work, we monitored the kinetic apoptotic and cytotoxic effects of 14 compounds in 3D MCTS produced from the glioblastoma cell line U87MG in 384-well plates for 9 days. The kinetic results allowed the categorization of the effects from 14 drug compounds into early and late cytotoxic, apoptotic, cytostatic, and no effects. The real-time apoptosis and viability screening method can serve as an improved secondary screen to better understand the mechanism of action of these potential drug candidates identified from the primary screen, allowing one to identify a more qualified drug candidate and streamline the drug discovery process of research and development.

Oncologists have investigated the effect of protein or chemical-based compounds on cancer cells to identify potential drug candidates. Traditionally, the growth inhibitory and cytotoxic effects of the drugs are first measured in 2D in vitro models, and then further tested in 3D xenograft in vivo models. Although the drug candidates can demonstrate promising inhibitory or cytotoxicity results in a 2D environment, similar effects may not be observed under a 3D environment. In this work, we developed an image-based high-throughput screening method for 3D tumor spheroids using the Celigo image cytometer. First, optimal seeding density for tumor spheroid formation was determined by investigating the cell seeding density of U87MG, a human glioblastoma cell line. Next, the dose-response effects of 17-AAG with respect to spheroid size and viability were measured to determine the IC 50 value. Finally, the developed high-throughput method was used to measure the dose response of four drugs (17-AAG, paclitaxel, TMZ, and doxorubicin) with respect to the spheroid size and viability. Each experiment was performed simultaneously in the 2D model for comparison. This detection method allowed for a more efficient process to identify highly qualified drug candidates, which may reduce the overall time required to bring a drug to clinical trial.

Three-dimensional (3D) tumor models have been increasingly used to investigate and characterize cancer drug compounds. The ability to perform high-throughput screening of 3D multicellular tumor spheroids (MCTS) can highly improve the efficiency and cost-effectiveness of discovering potential cancer drug candidates. Previously, the Celigo Image Cytometer has demonstrated a novel method for high-throughput screening of 3D multicellular tumor spheroids. In this work, we employed the Celigo Image Cytometer to examine the effects of 14 cancer drug compounds on 3D MCTS of the glioblastoma cell line U87MG in 384-well plates. Using parameters such as MCTS diameter and invasion area, growth and invasion were monitored for 9 and 3 d, respectively. Furthermore, fluorescent staining with calcein AM, propidium iodide, Hoechst 33342, and caspase 3/7 was performed at day 9 posttreatment to measure viability and apoptosis. Using the kinetic and endpoint data generated, we created a novel multiparametric drug-scoring system for 3D MCTS that can be used to identify and classify potential drug candidates earlier in the drug discovery process. Furthermore, the combination of quantitative and qualitative image data can be used to delineate differences between drugs that induce cytotoxic and cytostatic effects. The 3D MCTS-based multiparametric scoring method described here can provide an alternative screening method to better qualify tested drug compounds.

Amplification and overexpression of c-Myc is commonly seen in human ovarian cancers, and this could be a potentially novel therapeutic target for this disease. JQ1, a selective small-molecule BET bromodomain (BRDs) inhibitor, has been found to suppress tumor progression in several cancer cell types. Using ovarian cancer cell lines, a transgenic mouse model, and primary cell cultures from human ovarian cancer tissues, we demonstrated that JQ1 significantly suppressed cellular proliferation and induced cell cycle arrest and apoptosis in ovarian cancer cells and mouse model via targeting c-Myc. In addition, JQ1 had multiple influences on cancer metabolism, particularly in the aerobic glycolysis pathway. JQ1 reduced both the activity and phosphorylation of LDHA, inhibited lactate production, and decreased the energy supply to ovarian cancer cell lines and tumors. Taken together, our findings suggest that JQ1 is an efficacious anti-tumor agent in ovarian cancer that is associated with cell cycle arrest, induction of apoptosis and alterations of metabolism.

Epithelial ovarian carcinoma is the most lethal gynecological cancer due to its silent onset and recurrence with resistance to chemotherapy. Overexpression of oncogene c-Myc is one of the most frequently encountered events present in ovarian carcinoma. Disrupting the function of c-Myc and its downstream target genes is a promising strategy for cancer therapy. Our objective was to evaluate the potential effects of small-molecule c-Myc inhibitor, 10058-F4, on ovarian carcinoma cells and the underlying mechanisms by which 10058-F4 exerts its actions. Using MTT assay, colony formation, flow cytometry and Annexin V FITC assays, we found that 10058-F4 significantly inhibited cell proliferation of both SKOV3 and Hey ovarian cancer cells in a dose dependent manner through induction of apoptosis and cell cycle G1 arrest. Treatment with 10058-F4 reduced cellular ATP production and ROS levels in SKOV3 and Hey cells. Consistently, primary cultures of ovarian cancer treated with 10058-F4 showed induction of caspase-3 activity and inhibition of cell proliferation in 15 of 18 cases. The response to 10058-F4 was independent the level of c-Myc protein over-expression in primary cultures of ovarian carcinoma. These novel findings suggest that the growth of ovarian cancer cells is dependent upon c-MYC activity and that targeting c-Myc-Max heterodimerization could be a potential therapeutic strategy for ovarian cancer.