Overview

The transition from traditional flat cell cultures to 3D organoid models marks a significant advancement in understanding biological systems. However, the high-throughput screening of organoids is challenging due to their complex morphology and varied responses.

Introduction

We introduced a novel protocol employing live-cell imaging to monitor the dynamic drug response in organoids. To enhance the accuracy and efficiency of our analysis, we developed Orbits, a fully automated image and data analysis pipeline and platform.

Methods

We applied label-free organoid detection from brightfield images and integrated a novel drug response metric, the Normalized Organoid Growth Rate (NOGR), to accurately capture the complexity of tumor organoid drug responses. The protocol was applied to 11 distinct drug combination strategies, focusing particularly on Auranofin, a candidate for drug repurposing. Screening was conducted on 10 patient-derived organoid lines from healthy lung, lung cancer, and pancreatic cancer.

Results

Our findings reveal a notable correlation between low CA12 mRNA expression and increased sensitivity to Auranofin. Additionally, the study identified several drug candidates that, in combination with Auranofin, demonstrate a synergistic enhancement of efficacy, selectively targeting tumor cells. This comprehensive analysis was made possible by processing nearly 37.000 images through Orbits, our sophisticated automated pipeline.

Conclusion

Our study represents a significant leap in organoid-based drug discovery. The proposed high-throughput screening protocol and Orbits analysis pipeline provide a robust method for drug screening, facilitating the rapid identification of effective therapeutic strategies. The pipeline is available at the UAntwerp DrugVision.AI service platform and the software through Orbits Oncology spin-off.