Popis: |
The tumor microenvironment contributes significantly to tumor initiation, progression, and resistance to chemotherapy. Much of our understanding of the tumor and its microenvironment is developed using various methods of cell culture. Throughout the last two decades, research has increasingly shown that 3D cell culture systems can remarkably recapitulate the complexity of tumor architecture and physiology compared to traditional 2D models. Unlike the flat culture system, these novel models enabled more cell-cell and cell-extracellular matrix interactions. By mimicking in vivo microenvironment, 3D culture systems promise to become accurate tools ready to be used in diagnosis, drug screening, and personalized medicine. In this review, we discussed the importance of 3D culture in simulating the tumor microenvironment and focused on the effects of cancer cell-microenvironment interactions on cancer behavior, resistance, proliferation, and metastasis. Finally, we assessed the role of 3D cell culture systems in the contexts of drug screening. 2D culture system is used to study cancer cell growth, progression, behavior, and drug response. It provides contact between cells and supports paracrine crosstalk between host cells and cancer cells. However, this system fails to simulate the architecture and the physiological aspects of in vivo tumor microenvironment due to the absence of cell-cell/ cell-ECM interactions as well as unlimited access to O2 and nutrients, and the absence of tumor heterogeneity. Recently advanced research has led researchers to generate 3D culture system that can better recapitulate the in vivo environment by providing hypoxic medium, facilitating cell-cell and cell-ECM, interactions, and recapitulating heterogeneity of the tumor. Several approaches are used to maintain and expand cancer cells in 3D culture systems such as tumor spheroids (cell aggregate that mimics the in vivo growth of tumor cells), scaffold-based approaches, bioreactors, microfluidic derives, and organoids. 3D systems are currently used for disease modeling and pre-clinical drug testing. |