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Updated: Aug 14, 2025
Multiparametric Tumor Organoid Drug Screening Using Widefield Live-Cell Imaging for Bulk and Single-Organoid Analysis
Published on: December 23, 2022
Multiparametric Tumor Organoid Drug Screening Using Widefield Live-Cell Imaging for Bulk and Single-Organoid Analysis
Maxim Le Compte1, Edgar Cardenas De La Hoz2, Sofía Peeters1
1Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp.
Abstract:
Patient-derived tumor organoids (PDTOs) hold great promise for preclinical and translational research and predicting the patient therapy response from ex vivo drug screenings. However, current adenosine triphosphate (ATP)-based drug screening assays do not capture the complexity of a drug response (cytostatic or cytotoxic) and intratumor heterogeneity that has been shown to be retained in PDTOs due to a bulk readout. Live-cell imaging is a powerful tool to overcome this issue and visualize drug responses more in-depth. However, image analysis software is often not adapted to the three-dimensionality of PDTOs, requires fluorescent viability dyes, or is not compatible with a 384-well microplate format. This paper describes a semi-automated methodology to seed, treat, and image PDTOs in a high-throughput, 384-well format using conventional, widefield, live-cell imaging systems. In addition, we developed viability marker-free image analysis software to quantify growth rate-based drug response metrics that improve reproducibility and correct growth rate variations between different PDTO lines. Using the normalized drug response metric, which scores drug response based on the growth rate normalized to a positive and negative control condition, and a fluorescent cell death dye, cytotoxic and cytostatic drug responses can be easily distinguished, profoundly improving the classification of responders and non-responders. In addition, drug-response heterogeneity can by quantified from single-organoid drug response analysis to identify potential, resistant clones. Ultimately, this method aims to improve the prediction of clinical therapy response by capturing a multiparametric drug response signature, which includes kinetic growth arrest and cell death quantification.
Insights
This study introduces a new method for analyzing patient-derived tumor organoids (PDTOs) using live-cell imaging. The approach enhances drug screening by distinguishing between cytostatic and cytotoxic responses and quantifying heterogeneity for better therapy prediction.
Area of Science:
- * Oncology
- * Preclinical drug development
- * Translational research
Background:
- * Patient-derived tumor organoids (PDTOs) show promise for predicting therapy response but current assays lack depth.
- * Existing adenosine triphosphate (ATP)-based assays fail to capture cytostatic/cytotoxic drug effects and tumor heterogeneity.
- * Current live-cell imaging analysis software is often incompatible with 3D organoids, high-throughput formats, or requires fluorescent dyes.
Purpose of the Study:
- * To develop a high-throughput, semi-automated methodology for culturing and imaging PDTOs in a 384-well format.
- * To create novel image analysis software for marker-free quantification of PDTO drug responses.
- * To improve the distinction between cytostatic and cytotoxic drug effects and quantify drug response heterogeneity.
Main Methods:
- * A semi-automated method for seeding, treating, and imaging PDTOs in a 384-well microplate format using widefield live-cell imaging.
- * Development of viability marker-free image analysis software to quantify growth rate-based drug response metrics.
- * Utilization of a normalized drug response metric and a fluorescent cell death dye to differentiate drug effects and analyze heterogeneity.
Main Results:
- * The developed methodology enables high-throughput, marker-free analysis of PDTOs.
- * Novel software accurately quantifies growth rate-based drug response metrics, improving reproducibility.
- * The normalized drug response metric effectively distinguishes cytostatic from cytotoxic effects, enhancing responder classification.
- * Single-organoid analysis allows for quantification of drug response heterogeneity and identification of resistant clones.
Conclusions:
- * This method provides a robust platform for advanced PDTO drug screening in a high-throughput format.
- * The marker-free analysis and multiparametric drug response signature improve the prediction of clinical therapy response.
- * The approach captures kinetic growth arrest and cell death, offering deeper insights into drug efficacy and resistance mechanisms.
