Towards deciphering glioblastoma intra-tumoral heterogeneity: The importance of integrating multidimensional models

Glioblastoma (GBM) is the most common and severe form of brain cancer among adults. Its aggressiveness is largely attributed to its complex and heterogeneous biology that despite maximal surgery and multimodal chemoradiation treatment, inevitably recurs. Traditional large-scale profiling approaches have contributed substantially to the understanding of patient-to-patient inter-tumoral differences in GBM. However, it is now clear that biological differences within an individual (intra-tumoral heterogeneity) are also a prominent factor in treatment resistance and recurrence of GBM and will likely require integration of data from multiple recently developed omics platforms to fully unravel. Here we dissect the growing geospatial model of GBM, which layers intra-tumoral heterogeneity on a GBM stem cell (GSC) precursor, single cell, and spatial level. We discuss potential unique and inter-dependant aspects of the model including potential discordances between observed genotypes and phenotypes in GBM.

Automated summary

Glioblastoma (GBM) is the most common and severe form of brain cancer among adults, and its aggressiveness is due to its complex and heterogeneous biology. Traditional large-scale profiling approaches have contributed to the understanding of inter-tumoral differences in GBM, but it is now clear that intra-tumoral heterogeneity is also important in treatment resistance and recurrence. The growing geospatial model of GBM layers intra-tumoral heterogeneity on different levels and discusses potential discordances between genotypes and phenotypes in GBM.