Alteration of differentiation in glioblastoma: from spatial transcriptomics approaches to the identification of a suppressor event

Glioblastoma is one of the most devastating forms of primary brain tumor, with a survival of 14.6 months from the diagnosis. Despite the aggressive treatments used in the clinic, consisting of surgical resection followed by radiotherapy and concurrent chemotherapy using temozolomide, the absence of novel treatments and the development of resistance to standard-of-care therapies continue to position glioblastoma as the most challenging brain tumor in adults. The main factor contributing to the incurability of glioblastoma is the extensive heterogeneity. This heterogeneity, which is evident both at intratumoral and inter-patient levels, represents a substantial obstacle to the achievement of effective treatments. In this context, the use of single-cell resolution appears one of the most powerful means for understanding the intricacies and unravelling the heterogeneity of glioblastoma. Although single-cell RNA sequencing studies have provided and still provide valuable insights, they lack the essential spatial context that is critical for unravelling the heterogeneity of glioblastoma. This limitation impedes the understanding of interactions among distinct subpopulations and their intricate relationships with the neuronal microenvironment. To gain insights into the heterogeneity of glioblastoma, we used the spatially resolved RNA sequencing technology to analyse glioblastoma samples deriving from 3 different patients. For each patient, we focused on four distinct tumor regions, i. e. the proliferating tumor area, the necrotic core, the infiltrating area, and a distal healthy area. Cancer cells identified in the infiltrating regions exhibited a unique pattern of cell subpopulations, with the oligodendrocytes as the most represented in this area. In addition, we managed to generate patient-derived glioblastoma organoids from nearly all areas, with the tumor regions displaying the highest growth rates. These patient-derived organoids, which represent fundamental models useful to faithfully replicate the disease in vitro, may be employed in future analyses. Finally, we also derived glioblastoma stem cell cultures from the different tumor regions, with the proliferating tumor area showing the highest rate of success. In the second part, we aimed to gain a deeper understanding of the molecular mechanisms that underlie the development of glioblastoma, which is crucial for developing effective treatments, and characterise ELAVL2 role, highlighting its potential role as a potential tumor suppressor in glioblastoma. Collectively, our findings suggest that ELAVL2 promotes the exit of glioblastoma stem cells from quiescence, boosting their self-renewal capacity while also facilitating neuronal differentiation. The in vivo validation of our results using an orthotopic human glioblastoma stem cell xenograft model and a D. melanogaster genetic model strongly supports our findings and points to deletion of ELAVL2 as a factor that increases aggressiveness in glioblastoma stem cells and in vivo.