Semi-Automated Computational Assessment of Cancer Organoid Viability Using Rapid Live-Cell Microscopy

Abstract

The creation of patient-derived cancer organoids represents a key advance in preclinical modeling and has recently been applied to a variety of human solid tumor types. However, conventional methods used to assess in vivo tumor tissue treatment response are poorly suited for the evaluation of cancer organoids because they are time-intensive and involve tissue destruction. To address this issue, we established a suite of 3-dimensional patient-derived glioma organoids, treated them with chemoradiotherapy, stained organoids with non-toxic cell dyes, and imaged them using a rapid laser scanning confocal microscopy method termed “Apex Imaging.” We then developed and tested a fragmentation algorithm to quantify heterogeneity in the topography of the organoids as a potential surrogate marker of viability. This algorithm, SSDquant, provides a 3-dimensional visual representation of the organoid surface and a numerical measurement of the sum-squared distance (SSD) from the derived mass center of the organoid. We tested whether SSD scores correlate with traditional immunohistochemistry-derived cell viability markers (cellularity and cleaved caspase 3 expression) and observed statistically significant associations between them using linear regression analysis. Our work describes a quantitative, non-invasive approach for the serial measurement of patient-derived cancer organoid viability, thus opening new avenues for the application of these models to studies of cancer biology and therapy.

Matched three-dimensional organoids and two-dimensional cell lines of melanoma brain metastases mirror response to targeted molecular therapy

“…Using the doses determined from the cell line, we then administered the effective doses of each treatment to the MBM SXOs for 48 hours. We evaluated their response using an established method for live cell fluorescence imaging microscopy [20]. There was an appreciable increase in the propidium iodide (PI) signal with monotherapy treatment and a significant decrease in the organoid viability with dual-targeted molecular therapy ( Fig.…”

“…Organoid viability was quantified using the Nikon NIS-Elements software to generate the percent viability of live cells (Hoechst positive) relative to dead cells (Hoechst plus propidium iodide). Prior correlation of cellularity and viability between live cell imaging and traditional histopathology establishes the utility of this assay in assessing treatment response [20].…”