Authors

A Lim¹; P Macha¹; Z Tong¹; O Buddhikot¹; O Sirenko¹; E Fraser²; H Amijee²; 
¹ Molecular Devices (UK) Ltd, UK;  ² Cellesce Limited, UK

Discussion

Patient derived organoids (PDOs) represent a promising tool to reduce pipeline attrition in drug discovery. They fully represent the 3D architecture, cell-cell interactions and tissue microenvironment of the original tissue, including the cancer stem cell niches. Studies show that patients and their derived organoids respond similarly to drugs. PDOs are therefore an advanced and biologically relevant, in vitro model for the prediction of therapeutic efficacy and toxicity. 

A semi-automated bioprocess has been developed by Cellesce, for the controlled production of standardised PDOs at scale, for use in high throughput screens. The resulting PDOs are of a uniform size, high viability and provided in an assay-ready format. In this study, these PDOs were used to identify and develop assays and readouts that represent the complex biology of these models and the changes associated with large-scale compound treatments.

Colorectal cancer PDOs were seeded in multi-well plates manually, or with an automated cell bioprinter and dispenser. They were treated with selected anti-cancer drugs. The PDOs were monitored over time using transmitted light imaging. For the analysis of size, texture and additional morphological and phenotypic readouts, a deep learning-based image segmentation model was developed to facilitate automation of this process. A viability assay was carried out using live/dead cell dyes and the PDOs were imaged in 3D on a high content confocal imager. 

Of the known anti-cancer drugs tested, PDOs treated with romidepsin and trametinib showed the most significant reduction in size, with a greater number of dead cells compared to the other compounds and controls. Overall, our results show the potential for the utility of PDOs in both precision medicine and high-throughput drug discovery, through automation and high-content imaging.