MODL-26. EVOLUTION OF MULTI-FACETED GLIOBLASTOMA MICROENVIRONMENTS IN 3D

Abstract

Abstract Glioblastomas (GBM) account for poor prognosis and dismal survival rates in patients due to their highly aggressive infiltrative nature to rapidly migrate within the brain. Experimental treatments for GBMs using animal models often elicit severe side effects and there are major doubts regarding the usefulness of such in vivo models when undergoing animal to human clinical translation. Here, we describe the development of a series of 3D bioengineered GBM models towards the generation of a more physiologically representative system in which candidate drugs can be tested. Glioma cell lines U87 and U251 derived from human GBM were used along with associated knockdowns of previously described anti-migratory and pro-migratory genes or anti-migratory inhibitors to examine their roles in the actin polymerization pathway in cancer cell migration. GBM models were fabricated by implantation of spheroids within hydrogel microenvironments that were fashioned to exhibit migratory collagen tracts within a non-cell adhesive outer shell. The distribution of collagen was organised to have low, intermediate, and high-density regions within the construct, replicating the complexity of native GBM. 3D models were then cultured under control conditions (media only) or treated with anti-migratory drugs (CCG-1423, rhosin or combination). Using light-sheet and confocal microscopy, migration velocity, cell phenotype and migratory behaviours were analysed in live and fixed tumour mimics. In models where migration is promoted, actin was vastly upregulated and cells assumed a migratory mesenchymal phenotype, whereas under anti-migratory drug treatment, cells were amoeboid in shape with a dramatic reduction in actin expression and consequently limited migration velocity. Here, we have demonstrated that it is possible to develop biologically-relevant GBM models that capture the anisotropic nature of the tumour microenvironment using multi-layer biopolymer engineering. The ultimate goal of this research is to develop technology that can help provide personalised treatments for GBM and subsequently improve patient outcomes.