3D tumor spheroid models for in vitro therapeutic screening: a systematic approach to enhance the biological relevance of data obtained
By M. Zanoni, F. Piccinini, C. Arienti, A. Zamagni, S. Santi, R. Polico, A. Bevilacqua, A. Tesei. Scientific Reports, 2016
1,029 citations recorded by the source corpus.
The potential of a spheroid tumor model composed of cells in different proliferative and metabolic states for the development of new anticancer strategies has been amply demonstrated. However, there is little or no information in the literature on the problems of reproducibility of data originating from experiments using 3D models. Our analyses, carried out using a novel open source software capable of performing an automatic image analysis of 3D tumor colonies, showed that a number of morphology parameters affect the response of large spheroids to treatment. In particular, we found that both spheroid volume and shape may be a source of variability. We also compared some commercially available viability assays specifically designed for 3D models. In conclusion, our data indicate the need for a pre-selection of tumor spheroids of homogeneous volume and shape to reduce data variability to a minimum before use in a cytotoxicity test. In addition, we identified and validated a cytotoxicity test capable of providing meaningful data on the damage induced in large tumor spheroids of up to diameter in 650 μm by different kinds of treatments.
Subfields: Biomedical Engineering, Cell Biology, Oncology
View Paper: https://www.semanticscholar.org/paper/b7bff0a8bac58d56720a39466e3f9d53891055a5
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Citations in the corpus
- 3D tumor spheroids as in vitro models to mimic in vivo human solid tumors resistance to therapeutic drugs (2018, methodology): “optimized to reduce the cost and the lab work, as well as to allow the production of a large number of spheroids, under controlled conditions and compatible with all the cancer cell lines (Zanoni et al., 2016).”
- Systems Biology of Cancer Metastasis (2019, background): “…that can be perturbed with relative ease, while also being able to incorporate some of the complexity of tumor microenvironments such as variations in mechanical properties, matrix chemistry, paracrine signals, and cell-cell interactions(Katt et al., 2016; Singh et al., 2018; Zanoni et al., 2016).”