3D bioprinting of multilineage human glioblastoma models
Hermida, Miguel Angel
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In the last decade, the importance of three-dimensional cultures has been highlighted as a way to support the correct physiological and pathological behaviour of cell cultures. Many cells behave differently when grown in a 2D environment compared with a 3D matrix and this can result in a different sensitivity to drugs. Especially relevant in cancer is that many forms of interaction and communication between different cell types can either promote or repress cell proliferation and survival. In order to overcome the difficulty of studying cancer cells in a relevant microenvironment, new methods capable of generating 3D multicellular systems need to be implemented. Ideally, these methods have to allow a relatively fast and cheap way of generating different 3D constructs with minimal effects on cells caused by the preparation methods themselves. Spatial organization and automation of these processes would be highly desirable. The approach described in this thesis is based on a 3D printing strategy using the common biocompatible hydrogel, alginate, modified to promote cell attachment. Results show that the printing process can be performed without reduced cell viability; that cells proliferate within the gel and form more complex structures. The results here presented show that glioma stem cells (GSC) can be 3D printed and provide a response to drug treatment that resembles more closely the in vivo situation. Co-culture drug treatments in the 3D printed models showed that the presence of monocytes can increase the sensitivity of the glioma cell line U87MG, while the GSC line G7 showed no difference when co-cultured with microglia. The GSC lines seem to retain pluripotency better in the 3D system than in 2D cultures. Performing co-culture 3D printed studies, a differential kinase activity was observed, showing that macrophage-like cells can increase the activity of ERK, JNK, PKA and p38 only in the printed system. The 3D printing strategy here presented shows potential for biological applications, and the results obtained testing drugs and using biosensors to analyse real-time single-cell signalling changes indicate that the strategy can be a useful tool in cancer research.