Abstract 180: Automation and high content imaging of 3D triple negative breast cancer patient-derived tumoroids assay for compound screening

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Abstract Introduction: Currently there are no clinically approved small molecule targeted therapies for triple negative breast cancer, underlining the critical need to discover new therapeutic targets. Patient-derived cell-based 3D cancer models are highly valuable tools for cancer research and drug development. Primary tumor-derived models can recapitulate tumor heterogeneity and morphology, as well as complex genetic and molecular composition accelerating drug development and drug testing. However, the complexity of performing 3D assays remains a hurdle for adopting these methods for compound screening. In the present study we describe automation of imaging and cell culture methods that enables scaling up complex 3D cell-based assays and compound screening. Methods: We developed an integrated workcell that includes a confocal imaging system, an automated CO2 incubator, an automated liquid handler, and a Collaborative Robot combining different instruments. Workcell allows automation of compound testing, culture monitoring, and evaluation of phenotypic effects of drugs with high content imaging. Tumoroids were formed from primary cells isolated from a patient-derived tumor explant, TU-BcX-4IC, that represents metaplastic breast cancer with a triple-negative breast cancer subtype. Cells were expanded in 2D format, then tumoroids were formed by plating 2,000 cells per well in U-shape low attachment 384 plates. Tumoroids (200 μm in diameter) were formed 48 hr after plating and were treated with 165 compounds of approved cancer drugs from the NCI library at multiple concentrations (10 nM to 100 μM). Compound dilutions, additions, media additions, and staining were performed using liquid handler. During incubation with compounds, tumoroids were monitored daily using transmitted light imaging. For end point assay tumoroids were stained with viability dyes and imaged using automated confocal imaging system. Advanced image analysis included 3D reconstitution and complex phenotypic evaluation of tumoroids. Results: We characterized multiple quantitative descriptors that can be used for studying tumor phenotypes and compound effects including characterization of size and integrity, cell morphology and viability, as well as determining presence and expression levels for various cell markers. Concentration-dependent effects of numerous compounds were observed across multiple read-outs that indicate cytotoxic effects, with 8 compounds demonstrating effects at 10 nM (e.g, romidepsin, trametinib, bortezomib, carfilzomib, and panobinostat). These compounds include HDAC inhibitors and proteosome inhibitors. Conclusions: We demonstrated methods for increased throughput and automation in 3D cancer assays and compound screening, and also analysis approaches and descriptors that provide information about cell phenotypes and compound effects. Citation Format: Oksana Sirenko, Angeline Lim, Courtney K. Brock, Katya Nikolov, Cathy Olsen, Evan F. Cromwell, Margarite D. Matossian, Matthew E. Burow. Automation and high content imaging of 3D triple negative breast cancer patient-derived tumoroids assay for compound screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 180.

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