Glioblastoma vulnerability to neddylation inhibition is dependent on PTEN status, and dysregulation of the cell cycle and DNA replication.

Background: Neddylation (NAE) inhibition, affecting posttranslational protein function and turnover, is a promising therapeutic approach to cancer. We report the cytotoxic vulnerability to NAE inhibitors in a subset of glioblastoma (GBM) preclinical models and identify genetic alterations and biological processes underlying differential response. Methods: GBM DNA sequencing and transcriptomic data were queried for genes associated with response to NAE inhibition; candidates were validated by molecular techniques. Multi-omics and functional assays revealed processes implicated in NAE inhibition response. Results: Transcriptomics and shotgun proteomics depict PTEN signaling, DNA replication, and DNA repair pathways as significant differentiators between sensitive and resistant models. Vulnerability to MLN4924, a NAE inhibitor, is associated with elevated S-phase populations, DNA re-replication, and DNA damage. In a panel of GBM models, loss of WT PTEN is associated with resistance to different NAE inhibitors. A NAE inhibition response gene set could segregate the GBM cell lines that are most resistant to MLN4924. Conclusions: Loss of WT PTEN is associated with non-sensitivity to 3 different compounds that inhibit NAE in GBM. A NAE inhibition response gene set largely consisting of DNA replication genes could segregate GBM cell lines most resistant to NAEi and may be the basis for future development of NAE inhibition signatures of vulnerability and clinical trial enrollment within a precision medicine paradigm.

PTEN loss drives resistance to the neddylation inhibitor MLN4924 in glioblastoma and can be overcome with TOP2A inhibitors.

BACKGROUND: Neddylation inhibition, affecting posttranslational protein function and turnover, is a promising therapeutic approach to cancer. We report vulnerability to MLN4924 or pevonedistat (a neddylation inhibitor) in a subset of glioblastoma (GBM) preclinical models and identify biomarkers, mechanisms, and signatures of differential response. METHODS: GBM sequencing data were queried for genes associated with MLN4924 response status; candidates were validated by molecular techniques. Time-course transcriptomics and proteomics revealed processes implicated in MLN4924 response. RESULTS: Vulnerability to MLN4924 is associated with elevated S-phase populations, re-replication, and DNA damage. Transcriptomics and shotgun proteomics depict PTEN signaling, DNA replication, and chromatin instability pathways as significant differentiators between sensitive and resistant models. Loss of PTEN and its nuclear functions is associated with resistance to MLN4924. Time-course proteomics identified elevated TOP2A in resistant models through treatment. TOP2A inhibitors combined with MLN4924 prove synergistic. CONCLUSIONS: We show that PTEN status serves as both a novel biomarker for MLN4924 response in GBM and reveals a vulnerability to TOP2A inhibitors in combination with MLN4924.