While it is increasingly recognized that three-dimensional (3D) cell culture models recapitulate drug responses of human cancers with more fidelity than monolayer cultures, a lack of quantitative analysis methods limit their implementation for reliable and routine assessment of emerging therapies. Here, we introduce an approach based on computational analysis of fluorescence image data to provide high-content readouts of dose-dependent cytotoxicity, growth inhibition, treatment-induced architectural changes and size-dependent response in 3D tumour models. We demonstrate this approach in adherent 3D ovarian and pancreatic multiwell extracellular matrix tumour overlays subjected to a panel of clinically relevant cytotoxic modalities and appropriately designed controls for reliable quantification of fluorescence signal. This streamlined methodology reads out the high density of information embedded in 3D culture systems, while maintaining a level of speed and efficiency traditionally achieved with global colorimetric reporters in order to facilitate broader implementation of 3D tumour models in therapeutic screening.
Dartmouth Digital Commons Citation
Celli, Jonathan P.; Rizvi, Imran; Blanden, Adam R.; Massodi, Iqbal; Massodi, Iqbal; Glidden, Michael D.; Pogue, Brian; and Hasan, Tayyaba, "An Imaging-Based Platform for High-Content, Quantitative Evaluation of Therapeutic Response in 3d Tumour Models" (2014). Open Dartmouth: Published works by Dartmouth faculty. 2531.