Bioprinting of in vitro tumor models for personalized cancer treatment: a review. (7th July 2020) - Mao, Shuangshuang; Pang, Yuan; Liu, Tiankun; Shao, Yongchun; He, Jianyu; Yang, Huayu; Mao, Yilei; Sun, Wei
Abstract: Studying biological characteristics of tumors and evaluating the treatment effects require appropriate in vitro tumor models. However, the occurrence, progression, and migration of tumors involve spatiotemporal changes, cell–microenvironment and cell–cell interactions, and signal transmission in cells, which makes the construction of in vitro tumor models extremely challenging. In the past few years, advances in biomaterials and tissue engineering methods, especially development of the bioprinting technology, have paved the way for innovative platform technologies for in vitro cancer research. Bioprinting can accurately control the distribution of cells, active molecules, and biomaterials. Furthermore, this technology recapitulates the key characteristics of the tumor microenvironment and constructs in vitro tumor models with bionic structures and physiological systems. These models can be used as robust platforms to study tumor initiation, interaction with the microenvironment, angiogenesis, motility and invasion, as well as intra- and extravasation. Bioprinted tumor models can also be used for high-throughput drug screening and validation and provide the possibility for personalized cancer treatment research. This review describes the basic characteristics of the tumor and its microenvironment and focuses on the importance and relevance of bioprinting technology in the construction of tumor models. Research progress in the bioprinting of monocellular, multicellular, and personalized tumor models is discussed, and comprehensive application of bioprinting in preclinical drug screening and innovative therapy is reviewed. Finally, we offer our perspective on the shortcomings of the existing models and explore new technologies to outline the direction of future development and application prospects of next-generation tumor models.