The integrated landscape of driver genomic alterations in glioblastoma

Glioblastoma remains one of the most challenging forms of cancer to treat. Here, we develop a computational platform that integrates the analysis of copy number variations and somatic mutations and unravels the landscape of in-frame gene fusions in glioblastoma. We find mutations with loss of heterozygosity of LZTR-1, an adaptor of Cul3-containing E3 ligase complexes. Mutations and deletions disrupt LZTR-1 function, which restrains self-renewal and growth of glioma spheres retaining stem cell features. Loss-of-function mutations of CTNND2 target a neural-specific gene and are associated with transformation of glioma cells along the very aggressive mesenchymal phenotype. We also report recurrent translocations that fuse the coding sequence of EGFR to several partners, with EGFR-SEPT14 as the most frequent functional gene fusion in human glioblastoma. EGFR-SEPT14 fusions activate Stat3 signaling and confer mitogen independency and sensitivity to EGFR inhibition. These results provide important insights into the pathogenesis of glioblastoma and highlight new targets for therapeutic intervention.