Editors' ChoiceBioengineering

3D bioprinting chips away at glioblastomal resistance

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Science Translational Medicine  10 Apr 2019:
Vol. 11, Issue 487, eaax1724
DOI: 10.1126/scitranslmed.aax1724

Abstract

3D-printed tumor-on-a-chip devices closely resembling tumor microenvironment help customize patient treatment regimens for glioblastoma.

Glioblastoma is the most common and aggressive form of brain tumor. Cells extracted from glioblastomal biopsies or tumor resections that are grown in the lab have been poor predictors of in vivo tumor response to current treatment regimens. Yi et al. sought to recapitulate elements of the in vivo tumor environment around extracted cells in vitro to create a more physiologically relevant test bed for clinical therapeutic selection.

The authors developed simple yet elegant tumor-on-a-chip devices through direct deposition three-dimensional (3D) printing techniques to recreate critical aspects of the glioblastomal microenvironment. Specifically, they printed patient-derived cancer cells onto chips within an animal brain tissue–derived extracellular matrix carrier and surrounded them with vascular endothelial cells, simulating the cancer-stromal interaction. A combination of a glass coverslip seal, and an additional layer of gas permeable 3D-printed silicone was used to create physiologically representative oxygen gradients within these samples. These tumors-on-chips predicted patient tumor response to or resistance against combinations of therapies. The timeline for creating these chips and the cost of using them as screening tools for prospective treatment modes appear to offer distinct advantages over much-lauded patient-derived xenograft models.

Despite the promising results from these seven patient-derived tumors-on-chips, further study is warranted to see if this enhanced simulation of the tumor microenvironment captures all key biochemical and biophysical cues. It will be important to understand whether cells seeded from a specific portion of the tumor are representative of the entire tumor’s response and if the response to treatment observed using the chips truly mirrors what happens to cells in the in vivo tumor at a genetic and transcriptomic level. Is the absence of an immune response component an important limitation of this model? If these questions can be addressed, this bioprinted experimental setup could also potentially be used as a platform for screening new therapeutics singly or in combination, with applications in other cancer types as well.

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