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Purpose: The multi-kinase inhibitor (mKi) regorafenib has demonstrated efficacy in chemorefractory patients with metastatic colorectal cancer (mCRC). However, lack of predictive biomarkers and concerns over significant toxicities hamper the use of regorafenib in clinical practice., Experimental Design: Serial liquid biopsies were obtained at baseline and monthly until disease progression in chemorefractory patients with mCRC treated with regorafenib in a phase II clinical trial (PROSPECT-R n = 40; NCT03010722) and in a multicentric validation cohort (n = 241). Tissue biopsies collected at baseline, after 2 months and at progression in the PROSPECT-R trial were used to establish patient-derived organoids (PDO) and for molecular analyses. MicroRNA profiling was performed on baseline bloods using the NanoString nCounter platform and results were validated by digital-droplet PCR and/or ISH in paired liquid and tissue biopsies. PDOs co-cultures and PDO-xenotransplants were generated for functional analyses., Results: Large-scale microRNA expression analysis in longitudinal matched liquid and tissue biopsies from the PROSPECT-R trial identified MIR652-3p as a biomarker of clinical benefit to regorafenib. These findings were confirmed in an independent validation cohort and in a "control" group of 100 patients treated with lonsurf. Using ex vivo co-culture assays paired with single-cell RNA-sequencing of PDO established pre- and post-treatment, we modeled regorafenib response observed in vivo and in patients, and showed that MIR652-3p controls resistance to regorafenib by impairing regorafenib-induced lethal autophagy and by orchestrating the switch from neo-angiogenesis to vessel co-option., Conclusions: Our results identify MIR652-3p as a potential biomarker and as a driver of cell and non-cell-autonomous mechanisms of resistance to regorafenib., (©2024 American Association for Cancer Research.)

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.

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. © 2017 International Society for Advancement of Cytometry., (© 2017 International Society for Advancement of Cytometry.)

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.

To ensure cell-based assays are performed properly, both cell concentration and viability have to be determined so that the data can be normalized to generate meaningful and comparable results. Cell-based assays performed in immuno-oncology, toxicology, or bioprocessing research often require measuring of multiple samples and conditions, thus the current automated cell counter that uses single disposable counting slides is not practical for high-throughput screening assays. In the recent years, a plate-based image cytometry system has been developed for high-throughput biomolecular screening assays. In this work, we demonstrate a high-throughput AO/PI-based cell concentration and viability method using the Celigo image cytometer. First, we validate the method by comparing directly to Cellometer automated cell counter. Next, cell concentration dynamic range, viability dynamic range, and consistency are determined. The high-throughput AO/PI method described here allows for 96-well to 384-well plate samples to be analyzed in less than 7 min, which greatly reduces the time required for the single sample-based automated cell counter. In addition, this method can improve the efficiency for high-throughput screening assays, where multiple cell counts and viability measurements are needed prior to performing assays such as flow cytometry, ELISA, or simply plating cells for cell culture., Competing Interests: The authors, LLC, TS, KK, DK, SK, OD, SC, NL, and JQ declare competing financial interests. The work performed in this manuscript is for reporting on product performance of Nexcelom Bioscience, LLC. The performed experiments were to demonstrate novel high-throughput screening method for cell concentration and viability using AO/PI on Celigo image cytometer.