Nature CommunicationsCancer BiologyPeer-reviewed journal article
WEE1 inhibitors synergise with mRNA translation defects via activation of the kinase GCN2
Jordan WilsoniD, Jiayi ZhuiD, Vanesa VinciauskaiteiD, Eloise G. LloydiD, Simon C.C. LamiD, Alexandra Hart, Chen Gang GohiD, Fadia Bou-Dagher, Hlib RazumkoviD, Lena KobeliD, Zacharias KontarakisiD, John Fielden, Moritz F. SchlapanskyiD, Joanna I. LoizouiD, Andreas VillungeriD, Jacob E. CorniD, Giulia BiffiiD, Glenn Robert MassoniD, Stefan John MarciniakiD, Aldo S. BaderiD, Stephen P. JacksoniD
Abstract
Inhibitors of the protein kinase WEE1 have emerged as promising agents for cancer therapy. In this study, we uncover synergistic interactions between WEE1 small- molecule inhibitors and defects in mRNA translation, mediated by activation of the integrated stress response (ISR) through the kinase GCN2. Using a pooled CRISPRi screen, we identify GSPT1 and ALKBH8 as factors whose depletion confer hypersensitivity to the WEE1 inhibitor, AZD1775. We demonstrate that this synergy depends on ISR activation, which is induced by the off-target activity of WEE1 inhibitors. Furthermore, PROTAC-based WEE1 inhibitors and molecular glues show reduced or no ISR activation, suggesting potential strategies to minimise off-target toxicity. Our findings reveal that certain WEE1 inhibitors elicit dual toxicity via ISR activation and genotoxic stress, with ISR activation being independent of WEE1 itself or cell-cycle status. This dual mechanism highlights opportunities for combination therapies, such as pairing WEE1 inhibitors with agents targeting the mRNA translation machinery. This study also underscores the need for more precise WEE1 targeting strategies to mitigate off-target effects, with implications for optimising the therapeutic potential of WEE1 inhibitors.
- organism: human
- assay: CRISPR screen
- research focus: cell type annotation
- research focus: drug response / drug discovery
- research focus: perturbation response prediction
- approach: experimental assay
- approach: statistical model
- Citations
- 3
- FWCI
- 0.90
- Field percentile
- top 33%
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