Abstract

Abstract Background Glioblastoma is the most prevalent and severe type of malignant brain tumor in adults. Although the genetic make-up initiating glioblastoma is increasingly better understood, a better understanding in the mechanisms that drive its evolution, heterogeneity and therapy resistance may reveal new directions for therapy development. To get better insights into glioblastoma evolution, we analyzed and deconvoluted transcriptomes of primary and recurrent glioblastoma resections. Material and Methods Matching primary and secondary resections from n=185 uniformly treated glioblastoma patients were collected as part of EORTC Study 1542 and RNA-sequenced. Data was extended with pairs from n=51 patients from the GLASS study. The datasets were subjected to differential and deconvolution analysis using in-house algorithms. Results When projecting the tumor samples into a reduced Glioblastoma Intrinsic Transcriptional Subtype space, visualization of transitions indicated that the CL subtype switches most often. As we found no more transitions from MES to other subtypes than to be expected by chance, we concluded that MES is an end-state. On average, tumor purity percentages decreased from ~67% to ~50%, mostly due to an increase in macrophages/microglia. Differential expression analysis was performed with correction for the fraction of non-malignant cells. While expression of glioblastoma associated oncogenes did not change significantly over time, marker genes for macrophages/microglia, neurons and oligodendrocytes were up-regulated whereas endothelial cell markers were down-regulated. A cluster of ~30 extracellular matrix associated (ECM) genes increased significantly over time. Single cell RNA-seq, IF-staining and RNA-ish indicated the signature is most strongly expressed near intra-tumoral vessels. Since endothelial marker genes were down-regulated over time, this suggests a form of prognostic vessel progression with a representative transcriptome signature. Conclusion Using a large cohort and validation set of uniformly treated patients, we demonstrate how the glioblastoma transcriptome changes over time with in particular changes the composition of the tumor and its environment. The tumor purity decrease over times suggests a more invasive phenotype or recruitment of non-malignant cells or a combination of both. A post-progression increase in expression of ECM-associated genes expressed near blood vessels was associated with poor survival. Concluding, while no consistent path for transcriptional evolution of tumor cells was observed other than transitions to the MES subtype, glioblastoma becomes more aggressive in time by (re-)organizing its environment.

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