Cellular evolution upon Glioblastoma recurrence at single-cell resolution

Glioblastoma is the most aggressive and prevalent type of primary brain cancer and has a poor prognosis with median survival of 1 year. The disease is managed best with a multimodal approach combining surgical resection and postoperative chemo-radiotherapy, however, even with the best treatment the majority of patients relapse and once the disease recurs it’s practically resistant to treatment.

Substantial efforts made in recent years to characterize the molecular mechanisms governing GBM tumor evolution, including characterization of four GBM genomic subtypes by TCGA as well as dissection of the heterogeneous intra-tumor ecosystem at the unprecedented resolution provided by single-cell sequencing technologies, laid the ground to understanding the biological mechanisms underlying and driving this terrible disease. However, a comprehensive understanding of the mechanisms responsible for recurrence and resistance to treatment are still lacking.

Our work tackles this problem at single-cell resolution and to the best of our knowledge is first of its kind. Using frozen tumor sample pairs obtained from adult and pediatric GBM patients at two time points - initial diagnosis and first recurrence - we perform single nuclei RNAseq and computationally dissect the intra-tumor composition and uncover the differences between the matched transcriptomes. This unveils the cellular evolution upon recurrence that is driven by tremendous genetic and epigenetic changes, as well as by changes in the composition of the TME, that these tumors undergo between the different time-points and enables characterizing better the mechanisms that govern resistance to treatment which will ultimately result in improved therapeutic outcomes for patients.