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J Cell Commun Signal. 2018 Dec;12(4):723-730. doi: 10.1007/s12079-018-0469-z. Epub 2018 Jun 16.

Modelling glioma invasion using 3D bioprinting and scaffold-free 3D culture.

Author information

1
Department of Cellular and Physiological Sciences, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
2
Cyfuse Biomedical K.K, University of Tokyo Entrepreneur Plaza, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
3
Department of Cellular and Physiological Sciences, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada. christian.naus@ubc.ca.

Abstract

Glioma is a highly aggressive form of brain cancer, with some subtypes having 5-year survival rates of less than 5%. Tumour cell invasion into the surrounding parenchyma seems to be the primary driver of these poor outcomes, as most gliomas recur within 2 cm of the original surgically-resected tumour. Many current approaches to the development of anticancer therapy attempt to target genetic weaknesses in a particular cancer, but may not take into account the microenvironment experienced by a tumour and the patient-specific genetic differences in susceptibility to treatment. Here we demonstrate the use of complementary approaches, 3D bioprinting and scaffold-free 3D tissue culture, to examine the invasion of glioma cells into neural-like tissue with 3D confocal microscopy. We found that, while both approaches were successful, the use of 3D tissue culture for organoid development offers the advantage of broad accessibility. As a proof-of-concept of our approach, we developed a system in which we could model the invasion of human glioma cells into mouse neural progenitor cell-derived spheroids. We show that we can follow invasion of human tumour cells using cell-tracking dyes and 3D laser scanning confocal microscopy, both in real time and in fixed samples. We validated these results using conventional cryosectioning. Our scaffold-free 3D approach has broad applicability, as we were easily able to examine invasion using different neural progenitor cell lines, thus mimicking differences that might be observed in patient brain tissue. These results, once applied to iPSC-derived cerebral organoids that incorporate the somatic genetic variability of patients, offer the promise of truly personalized treatments for brain cancer.

KEYWORDS:

3D bioprinting; Cerebral organoid; Confocal microscopy; Connexin43; Gap junctions; Glioma

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