Image-based profiling identifies compound induced phenotypes in patient-derived organoids

Patient derived organoids (PDOs) closely resemble individual tumor biology. They are thus promising models for drug discovery and precision medicine. Here, we describe high-throughput imaging and automated image analysis of PDOs. We generated PDOs from colorectal cancer patients. Subsequently, we treated them with >500 substances to capture almost 6 million images by confocal microscopy. We developed a software framework to analyze how perturbations alter the organization of multicellular PDOs. Therewith, we observed a rich spectrum of reoccurring phenotypes. Targeting cellular processes, including signaling by MEK, GSK3 or CDKs, led to distinct architectural changes. Also, we detected compound-induced phenotypes only present in subsets of PDOs with specific molecular alterations. Finally, PDO response to anticancer drugs matched the clinical course of corresponding patients. The presented high-throughput imaging workflow and data allow compound profiling with complex multicellular organoid models for drug discovery and personalized medicine. We used microarrays to detail the global programme of gene expression underlying different lines of patient-derived colorectal cancer organoids. We measured total RNA from 16 human patient-derived colorectal cancer organoids.