Why 3D in vitro cancer models are the future of cancer research?

Tumors are three-dimensional (3D) entities characterized by complex structural architecture which is necessary for adequate intercellular, intracellular and cell-to-matrix interactions among the aberrant cells in cancer. In the field of cancer research, 2D cell cultures are traditionally used for decades in the majority of experiments. The reasons for this are the vast benefits these models provide, including simplicity and cost effectiveness. However, it is now known that these models are exposed to much higher stiffness, they lose physiological extracellular matrix (ECM) on artificial plastic surfaces as well as differentiation, polarization and cell-cell communication. This leads to the loss of crucial cellular signaling pathways and changes in cell responses to stimuli when compared to in vivo conditions. Moreover, they cannot adequately mimic the complexity and dynamic interactions of the tumor microenvironment (TME) which is of great importance in anticancer drug treatments. 3D models seem more biomimetic compared to 2D cell monolayers because they offer the opportunity to model the cancer mass together with its environment which seems the key factor in promoting and directing cancer invasion. 3D cell culture with its additional dimensionality makes the difference in cellular responses because it influences the spatial and physical aspects of the cells in 3D culture. This affects the signal transduction and makes the behavior of 3D-cultured cells more physiologically relevant and reflective of in vivo cellular responses. This review focuses on major differences between 2D and 3D cell cultures, highlighting the importance of considering bioengineering humanized 3D cancer models as the future in cancer research. Additionally, it presents diverse 3D models currently used in cancer research, outlining their benefits and limitations. Precisely, this review highlights the differences between the 3D models with the focus on tumor stroma interactions, cell population and extracellular matrix composition providing methods and examples for each model from the studies done so far.