Abstract
Objective:The formation of three-dimensional spheroid tumor model using the scaffold-based platforms has been demonstrated over many years now. 3D tumor models are generated mainly in non-scalable culture systems, using synthetic and biological scaffolds. Many of these models fail to reflect the complex tumor microenvironment and do not allow long-term monitoring of tumor progression. This has resulted in inconsistent data in drug testing assays during preclinical and clinical studies. Methods:To overcome these limitations, we have developed 3D tissueoids model by using novel AXTEX-4D platform. Results:Cancer 3D tissueoids demonstrated the basic features of 3D cell culture with rapid attachment, proliferation, and longevity with contiguous cytoskeleton and hypoxic core. This study also demonstrated greater drug resistance in 3D-MCF-7 tissueoids in comparison to 2D monolayer cell culture. Conclusion:In conclusion, 3D-tissueoids are more responsive than 2D-cultured cells in simulating important tumor characteristics, anti-apoptotic features, and their resulting drug resistance.
Highlights
Globocan 2018 estimated incidence of 18.1 million new cancer cases and 9.6 million cancer deaths
To determine how a 3-D arrangement of cells influences cytoskeletal organization, we investigated the arrangement of actin in PC3 and MCF-7 cells in comparison with 2D cells. 3D cultures of prostate cancer cells (PC-3) and breast cancer cells (MCF-7) were used to determine whether the AXTEX-4DTM platform was suitable for two cell types forming loose or compact tissueoids respectively
We aimed to describe the characteristics of a 3D tissueoids model that was developed using AXTEX-4DTM platform (Baru et al, 2021a)
Summary
Globocan 2018 estimated incidence of 18.1 million new cancer cases and 9.6 million cancer deaths. The development of effective anticancer drugs significantly requires and depends on reliable in vitro high-tech screening systems (Kitaeva et al, 2020). The absence of reliable and effective in vitro screening models that could mimic key aspects of the tumor microenvironment, such as drug resistance and phenotypic changes to cells, impedes the reliable translation of in vitro findings into in vivo clinical models. The poor correlation between preclinical in vitro and in vivo data with clinical trials has an adverse impact on drug development costs, with the trial cost vary from $3 million to $347 million (Moore et al, 2018) (Martin et al, 2017). The action is required to develop effective and reliable in vitro models that reflect the in vivo tumor microenvironment and in vivo efficacy more accurately
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