3D bioprinted glioma models

被引:20
作者
Yigci, Defne [1 ]
Sarabi, Misagh Rezapour [2 ]
Ustun, Merve [2 ]
Atceken, Nazente [3 ]
Sokullu, Emel [1 ]
Bagci-Onder, Tugba [1 ,3 ]
Tasoglu, Savas [2 ,3 ,4 ,5 ,6 ]
机构
[1] Koc Univ, Sch Med, TR-34450 Istanbul, Turkey
[2] Koc Univ, Grad Sch Sci & Engn, TR-34450 Istanbul, Turkey
[3] Koc Univ, Koc Univ Res Ctr Translat Med, TR-34450 Istanbul, Turkey
[4] Koc Univ, Koc Univ Arcelik Res Ctr Creat Ind KUAR, TR-34450 Istanbul, Turkey
[5] Bogazici Univ, Bogazici Inst Biomed Engn, TR-34684 Istanbul, Turkey
[6] Max Planck Inst Intelligent Syst, Phys Intelligence Dept, D-70569 Stuttgart, Germany
来源
PROGRESS IN BIOMEDICAL ENGINEERING | 2022年 / 4卷 / 04期
关键词
glioma; 3D bioprinting; brain cancer; cancer treatment; in vitro models; ON-A-CHIP; STEM-CELLS; TISSUE; SYSTEM; CANCER; SCAFFOLDS; GLIOBLASTOMA; CONSTRUCTS; INVASION; COMPLEX;
D O I
10.1088/2516-1091/ac7833
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Glioma is one of the most malignant types of cancer and most gliomas remain incurable. One of the hallmarks of glioma is its invasiveness. Furthermore, glioma cells tend to readily detach from the primary tumor and travel through the brain tissue, making complete tumor resection impossible in many cases. To expand the knowledge regarding the invasive behavior of glioma, evaluate drug resistance, and recapitulate the tumor microenvironment, various modeling strategies were proposed in the last decade, including three-dimensional (3D) biomimetic scaffold-free cultures, organ-on-chip microfluidics chips, and 3D bioprinting platforms, which allow for the investigation on patient-specific treatments. The emerging method of 3D bioprinting technology has introduced a time- and cost-efficient approach to create in vitro models that possess the structural and functional characteristics of human organs and tissues by spatially positioning cells and bioink. Here, we review emerging 3D bioprinted models developed for recapitulating the brain environment and glioma tumors, with the purpose of probing glioma cell invasion and gliomagenesis and discuss the potential use of 4D printing and machine learning applications in glioma modelling.
引用
收藏
页数:16
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