Preclinical models of glioblastoma: limitations of current models and the promise of new developments

Abstract

Abstract Glioblastoma (GBM) is the most common and aggressive primary brain tumour, yet little progress has been made towards providing better treatment options for patients diagnosed with this devastating condition over the last few decades. The complex nature of the disease, heterogeneity, highly invasive potential of GBM tumours and until recently, reduced investment in research funding compared with other cancer types, are contributing factors to few advancements in disease management. Survival rates remain low with less than 5% of patients surviving 5 years. Another important contributing factor is the use of preclinical models that fail to fully recapitulate GBM pathophysiology, preventing efficient translation from the lab into successful therapies in the clinic. This review critically evaluates current preclinical GBM models, highlighting advantages and disadvantages of using such models, and outlines several emerging techniques in GBM modelling using animal-free approaches. These novel approaches to a highly complex disease such as GBM show evidence of a more truthful recapitulation of GBM pathobiology with high reproducibility. The resulting advancements in this field will offer new biological insights into GBM and its aetiology with potential to contribute towards the development of much needed improved treatments for GBM in future.