Abstract
Two-dimensional (2D) culture of cancer cells in vitro does not recapitulate the three-dimensional (3D) architecture, heterogeneity and complexity of human tumors. More representative models are required that better reflect key aspects of tumor biology. These are essential studies of cancer biology and immunology as well as for target validation and drug discovery. The Innovative Medicines Initiative (IMI) consortium PREDECT (www.predect.eu) characterized in vitro models of three solid tumor types with the goal to capture elements of tumor complexity and heterogeneity. 2D culture and 3D mono- and stromal co-cultures of increasing complexity, and precision-cut tumor slice models were established. Robust protocols for the generation of these platforms are described. Tissue microarrays were prepared from all the models, permitting immunohistochemical analysis of individual cells, capturing heterogeneity. 3D cultures were also characterized using image analysis. Detailed step-by-step protocols, exemplary datasets from the 2D, 3D, and slice models, and refined analytical methods were established and are presented.
Highlights
Background & SummaryCarcinomas, known as solid tumors, have a complex microenvironment, are cellularly heterogeneous, and have a three-dimensional (3D) architecture[1]
Models were generated from a range of breast, prostate, and lung cancer cell lines as well as from patient-derived xenograft (PDX) and a genetically engineered mouse model (GEMM)
Starting from conventional 2D monocultures, the complexity of the models was increased stepwise to include stromal cells in 2D co-cultures, and in 3D cultures. The latter cultures were generated as free-floating spheroids (‘floaters’), microencapsulated into inert hydrogels and grown in stirred-tank bioreactors (‘alginate-BR’), or embedded in extracellular matrix (ECM), all in the presence or absence of stromal cells[5,6,7,8]
Summary
Carcinomas, known as solid tumors, have a complex microenvironment, are cellularly heterogeneous, and have a three-dimensional (3D) architecture[1]. Despite the wealth of data generated, and strong recommendations to upgrade cell culture models from those growing in two dimensions (2D) (e.g., cellular monolayers on plastic substrates) to 3D models[2], few of these more complex 3D model systems have been used to investigate cancer cell biology in vitro. Neither have they been routinely incorporated into the drug screening cascade alongside standard 2D models despite consistent evidence suggesting that preclinical models largely fail to predict drug efficacy[3]. This guidance should allow other research groups to repeat and extend the data generated by the PREDECT consortium
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