Glioblastoma, from disease understanding towards optimal cell-based invitro models

Abstract

BackgroundGlioblastoma (GBM) patients are notoriously difficult to treat and ultimately all succumb to disease. This unfortunate scenario motivates research into better characterizing and understanding this disease, and into developing novel research tools by which potential novel therapeutics and treatment options initially can be evaluated pre-clinically. Here, we provide a concise overview of glioblastoma epidemiology, disease classification, the challenges faced in the treatment of glioblastoma and current novel treatment strategies. From this, we lead into a description and assessment of advanced cell-based models that aim to narrow the gap between pre-clinical and clinical studies. Such invitro models are required to deliver reliable and meaningful data for the development and pre-validation of novel therapeutics and treatments.ConclusionsThe toolbox for GBM cell-based models has expanded substantially, with the possibility of 3D printing tumour tissues and thereby replicating invivo tissue architectures now looming on the horizon. A comparison of experimental cell-based model systems and techniques highlights advantages and drawbacks of the various tools available, based on which cell-based models and experimental approaches best suited to address a diversity of research questions in the glioblastoma research field can be selected.