Rapid 3D Bioprinting of Glioblastoma Model Mimicking Native Biophysical Heterogeneity

Min Tang(University of California San Diego), Shashi Kant Tiwari(University of California San Diego), Kriti Agrawal(University of California San Diego), Matthew L. Tan(University of California San Diego), Jason Dang(University of California San Diego), Trevor Tam(University of California San Diego), Jing Tian(University of California San Diego), Xueyi Wan(University of California San Diego), Jacob Schimelman(University of California San Diego), Shangting You(University of California San Diego), Qinghui Xia(University of California San Diego), Tariq M. Rana(University of California San Diego), Shaochen Chen(University of California San Diego)
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January 27, 2021
Cited by 115Open Access
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Abstract

Glioblastoma multiforme (GBM) is the most lethal primary brain tumor characterized by high cellular and molecular heterogeneity, hypervascularization, and innate drug resistance. Cellular components and extracellular matrix (ECM) are the two primary sources of heterogeneity in GBM. Here, biomimetic tri-regional GBM models with tumor regions, acellular ECM regions, and an endothelial region with regional stiffnesses patterned corresponding to the GBM stroma, pathological or normal brain parenchyma, and brain capillaries, are developed. Patient-derived GBM cells, human endothelial cells, and hyaluronic acid derivatives are used to generate a species-matched and biochemically relevant microenvironment. This in vitro study demonstrates that biophysical cues are involved in various tumor cell behaviors and angiogenic potentials and promote different molecular subtypes of GBM. The stiff models are enriched in the mesenchymal subtype, exhibit diffuse invasion of tumor cells, and induce protruding angiogenesis and higher drug resistance to temozolomide. Meanwhile, the soft models demonstrate enrichment in the classical subtype and support expansive cell growth. The three-dimensional bioprinting technology utilized in this study enables rapid, flexible, and reproducible patient-specific GBM modeling with biophysical heterogeneity that can be employed by future studies as a tunable system to interrogate GBM disease mechanisms and screen drug compounds.


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