High-resolution HCA-based phenotypic profiling of tumor spheroids and organoids

Image-based high-content screening (HCS) involving cancer cell lines grown in conventional two-dimensional (2D) cell culture, has provided a cornerstone assay for searching new agents to treat pancreatic ductal adenocarcinoma (PDAC). However, since drug response in tumors in vivo is mediated by a myriad of microenvironmental factors (e.g tumor cytoarchitecture and cellular heterogeneity) the search for advanced cellular systems that can recapitulate more closely the tumor context have become a priority. Tumor spheroids consist in clusters obtained from a single cell population (e.g. 2D cell lines), whereas primary organoids can be established as self-organizing complex three-dimensional (3D) structures from cells of tumor resections from patients. All these tumor in-a-dish models better express chemoresistance mechanisms observed in cancers in vivo, and for this reason, they have been incorporated recently into drug HCS pipelines. The challenge now is to systematically visualize and quantitatively analyze chemoresistance-triggering pathways at the subcellular level, for which it will be necessary to engage image-based phenotypic profiling in those ‘tumor avatars’. We have explored the possibility of devising a HCS platform capable to map the spatial distribution of marker proteins to either cells or organelles within the multicellular structures. Here I present a 3D-HCS platform based on miniaturization of 3D culture in optical-bottom multi-well plates, endowed with a HCA-workflow that is effective at capturing cellular and multicellular morphological features in populations of PDAC spheroids and organoids. Our platform provides a perspective for application of this platform for a dissection of drug penetrance determinants.