Abstract

Abstract Neddylation is a specific pathway within the ubiquitin/proteasome system that is overactive in GBM, and whose upregulation has been associated with glioma progression and worse survival. Pevonedistat (MLN4924) is a first-in-class small-molecule neddylation inhibitor shown to inhibit growth of GBM cells by impacting protein degradation in culture and orthotopic xenografts. However, the determinants of vulnerability are not fully understood. Because the molecular heterogeneity within and across GBM patients obscures therapeutic targets and obfuscates signals of efficacy in clinical trials, we pursue the use of molecular “signatures of vulnerability” to targeted agents in subsets of preclinical models. Selective vulnerability to pevonedistat was shown in a subset of GBM; notably, models with mutations or copy number deletions of PTEN are associated with de novo resistance to pevonedistat. Time-course studies of sensitive and non-sensitive GBM cells using transcriptomics and proteomics/phosphoproteomics uncovered additional determinants of response to pevonedistat. Our results demonstrate that in GBM, resistance to pevonedistat is driven by reduced PTEN-chromatin binding (loss-of-function or lower expression) that is also independent of PTEN’s lipid phosphatase activity (i.e., PI3K/AKT signaling). Across 25 glioma cell lines, we found that PTEN signaling, DNA replication, and chromatin instability pathways are the most significant differentiators between pevonedistat sensitive vs. non-sensitive models. In GBM models with modest to low sensitivity to pevonedistat, TOP2A expression was elevated. Combination treatment with the TOP2A inhibitor, etoposide, proved synergistic with pevonedistat. We report that PTEN status both serves as a novel biomarker for GBM sensitivity to pevonedistat and reveals a synergistic vulnerability to TOP2A inhibitors in combination with pevonedistat. Paired use of GBM PDX models of varying sensitivity with drug development testing allows the advancement of a promising agent as well as a patient-enrollment “signature of vulnerability” likely to increase the likelihood of demonstrating therapeutic efficacy in early stage clinical trials.

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