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GCN2 kinase activation by ATP-competitive kinase inhibitors

Nature Chemical Biology volume 18, pages 207–215 (2022)Cite this article

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Abstract

Small-molecule kinase inhibitors represent a major group of cancer therapeutics, but tumor responses are often incomplete. To identify pathways that modulate kinase inhibitor response, we conducted a genome-wide knockout (KO) screen in glioblastoma cells treated with the pan-ErbB inhibitor neratinib. Loss of general control nonderepressible 2 (GCN2) kinase rendered cells resistant to neratinib, whereas depletion of the GADD34 phosphatase increased neratinib sensitivity. Loss of GCN2 conferred neratinib resistance by preventing binding and activation of GCN2 by neratinib. Several other Food and Drug Administration (FDA)-approved inhibitors, such erlotinib and sunitinib, also bound and activated GCN2. Our results highlight the utility of genome-wide functional screens to uncover novel mechanisms of drug action and document the role of the integrated stress response (ISR) in modulating the response to inhibitors of oncogenic kinases.

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Fig. 1: Loss of the amino acid starvation sensor GCN2 confers resistance to neratinib.
Fig. 2: Sustained ATF4 expression induces cell death.
Fig. 3: Induction of GCN2 by neratinib is uncoupled from EGFR inhibition.
Fig. 4: Neratinib directly activates GCN2.
Fig. 5: Several ATP-competitive kinase inhibitors bind to and activate GCN2.
Fig. 6: Mechanism of GCN2 activation by kinase inhibitors.

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Data availability

The CRISPR screen and RNA-seq data reported in this study have been deposited to the Gene Expression Omnibus with the accession number GSE188958. The LINCS KINOMEscan data is from project ID 20195 (https://lincs.hms.harvard.edu/db/datasets/20195/main). PDB IDs for the crystal structure data used in this study are 3W2Q (ref. 28), 2GS6 (ref. 49) and GCN2 complexed with dovitinib27. Source data are provided with this paper.

Code availability

All scripts for downstream analysis of the CRISPR screen and RNA-seq data are available on GitHub at https://github.com/cot2005/Tang_et_al_2021.

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Acknowledgements

This research was supported by the National Institutes of Health (F31 5F31CA239401-03 (C.P.T.), 1 R35 NS105109 03 (I.K.M.), P30CA008748 (I.K.M., A.M.I., J.D.C.), UL1TR002384 (O.E.), R01CA194547 (O.E.) and R01GM121505 (J.D.C.)), the National Brain Tumor Society Defeat GBM Initiative (I.K.M.), Cycle of Survival (I.K.M.) and LLS SCOR grants 180078-02, 7021-20 (O.E.). We thank J. Blenis, N. Rosen and C. Sawyers for helpful suggestions.

Author information

Authors and Affiliations

  1. Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Colin P. Tang, Owen Clark, Carl Campos, Andrew M. Intlekofer & Ingo K. Mellinghoff

  2. Pharmacology Program, Weill Cornell Medicine, New York, NY, USA

    Colin P. Tang & Ingo K. Mellinghoff

  3. Caryl and Israel Englander Institute for Precision Medicine and Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA

    Colin P. Tang & Olivier Elemento

  4. Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA

    John R. Ferrarone

  5. Puma Biotechnology, Los Angeles, CA, USA

    Alshad S. Lalani

  6. Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    John D. Chodera

  7. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Andrew M. Intlekofer

  8. Physics and Biophysics Program, Weill Cornell Medicine, New York, NY, USA

    Olivier Elemento

  9. Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Ingo K. Mellinghoff

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Contributions

C.P.T. and I.K.M. conceptualized and led the overall project, analyzed results and wrote the manuscript with input from all coauthors. O.E. assisted with experimental design and bioinformatic analysis. J.R.F. assisted with CRISPR KO screens. A.M.I. directed and assisted with metabolic assessments and analysis. J.D.C. directed and assisted with structural analysis. A.S.L. assisted in the design of neratinib in vivo experiments. C.C. performed all of the in vivo experiments. O.C. assisted with the orthotopic in vivo experiment. C.P.T. performed all other experiments, bioinformatic analysis and data visualization.

Corresponding author

Correspondence to Ingo K. Mellinghoff.

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Competing interests

I.K.M. has received research funding from General Electric, Agios and Lilly and has served in advisory roles for Agios, Amgen, Debiopharm, Novartis, Puma Biotechnology, Servier Pharmaceuticals, and Voyager Therapeutics. O.E. is supported by research grants from Janssen, Johnson and Johnson, Volastra, AstraZeneca and Eli Lilly. O.E. is scientific advisor and equity holder in Freenome, Owkin, Volastra Therapeutics and One Three Biotech. A.S.L. is an employee and shareholder of Puma Biotechnology, Inc. J.D.C. has received research funding from the Parker Institute for Cancer Immunotherapy, Relay Therapeutics, Entasis Therapeutics, Silicon Therapeutics, EMD Serono (Merck KGaA), AstraZeneca, Vir Biotechnology, Bayer, XtalPi, Foresite Laboratories, the Molecular Sciences Software Institute, the Starr Cancer Consortium, the Open Force Field Consortium and Cycle for Survival. J.D.C. is a scientific advisor and equity holder in Interline Therapeutics and Redesign Science and a current member of the Scientific Advisory Board of OpenEye Scientific Software. A complete funding history for the Chodera lab can be found at http://choderalab.org/funding. The other authors declare no competing interests.

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Peer review information Nature Chemical Biology thanks the anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 CRISPR screen resistance candidates are significant and consistent.

a, Schematic of genome-wide CRISPR screens using the TKOv3 library. b, Representative graph of a CRISPR screen showing the second highest sgRNA (per gene) frequencies of SKMG3 cell line treated with 2 µM neratinib versus vehicle for 14 days. c, Effect of GCN2-KO on neratinib treatment measured by SKMG3 cell growth and assessed by trypan blue exclusion after 6 days. Immunoblot confirming GCN2-KO on right side. Data are presented as mean values ± SD of n = 3 biologically independent samples. d, Spearman correlation matrix of all CRISPR screen experiments showing spearman coefficients. e, false discovery rates of ISR pathway genes from drugZ analyzed CRISPR screens. f, Immunoblot of ATF4 induction by 4 hour 675 nM neratinib in parental and ATF4-KO SF268 cells. c,e,f, Western blots were performed with a minimum of n = 2 biological replicates with similar results obtained each time.

Source data

Extended Data Fig. 2 Induction of the ISR by neratinib is GCN2 dependent.

a, Immunoblot of SKMG3 parental and GCN2-KO and SF268 parental and GCN2-KO cells treated with 675 nM neratinib for 4 hours. b, ISR induction time course in TS895 cells EGFP or GCN2-KO cells treated with 675 nM neratinib for indicated times. Western blots were performed with a minimum of n = 2 biological replicates with similar results obtained each time.

Source data

Extended Data Fig. 3 Constitutive activation of eIF2α induces cell death.

a, Immunoblot of SF268 cells were transduced with doxycycline (dox) inducible wild-type (WT) or constitutively active (S51D) eIF2α and treated with 5 µg/mL dox for indicated times (upper band, tagged recombinant eIF2α). Western blots were performed with a minimum of n = 2 biological replicates with similar results obtained each time. b, effect of dox induced WT or S51D eIF2α on cell growth. Data are presented as mean values ± SD of n = 3 biologically independent samples.

Source data

Extended Data Fig. 4 Induction of the amino acid starvation response by neratinib requires GCN2.

a, Volcano plots and gene set enrichment analysis results showing differential expression of genes in SF268 cells treated with 675 nM neratinib or vehicle for 6 hours and b, 72 hours with gene labels corresponding to the enriched krige amino acid gene set. c, gene set enrichment analysis results showing differential expression of genes in SF268 cells treated with 675 nM neratinib or vehicle for 6 hours and d, 72 hours. e, gene set enrichment plot for the amino acid deprivation gene set for intracranial TS895 tumors treated with neratinib 40 mpk for 3 hours. f, Plot comparing the enrichment of ER stress and amino acid deprivation pathways between SF268 parental and GCN2-KO cell lines treated with 675 nM neratinib for 6 hours. g, Comparison of ISR signaling in the presence of neratinib (1 µM)[lanes 1 and 2 also shown in Fig. 2e], glutamine (Gln) starvation, and ER stress by tunicamycin (5 µg/mL) for 4 hours. Western blots were performed with a minimum of n = 2 biological replicates with similar results obtained each time.

Source data

Extended Data Fig. 5 GCN2 is sufficient for neratinib induced eIF2α phosphorylation.

a, Schematic of recombinant GCN2 electroporation rescue. b, immunoblot of eIF2α phosphorylation for SKMG3 cells electroporated with recombinant GCN2 then treated with 675 nM neratinib for 4 hours. Western blots were performed with a minimum of n = 2 biological replicates with similar results obtained each time. c, image quantification of eIF2α phosphorylation, normalized to vinculin.

Source data

Extended Data Fig. 6 GCN2 loss confers resistance to GCN2 activating KIT inhibitor.

a, Immunoblot of ISR signaling in GIST-T1 (Left) and SF268 parental/GCN2-KO (Right) treated with the KIT inhibitor sunitinib for 4 hours. Western blots were performed with a minimum of n = 2 biological replicates with similar results obtained each time. b, Bar graph comparing the effect of sunitinib on SF268 parental and GCN2-KO cell growth after 6 days. Data are presented as mean values ± SD of n = 3 biologically independent samples. Significance was determined with a two sided student t-test.

Source data

Extended Data Fig. 7 GCN2 activation by dovitinib synergizes with osimertinib.

a, Immunoblot of SF268 cells treated with either neratinib (Ner), osimertinib (Osi), or canertinib (Can) for 4 hours. Western blots were performed with a minimum of n = 2 biological replicates with similar results obtained each time. b, Scatterplot of a CRISPR screen showing the second highest sgRNA (per gene) frequencies of SF268 cell line treated with 3 µM osimertinib versus vehicle for 21 days. ISR pathway members and PTEN are labeled. c, Synergy between GCN2 activation by dovitinib (0 - 1.5 µM) and EGFR inhibition by Osimertinib (0 - 2 µM) in SF268 parental (left) and GCN2-KO (right) cells. Synergy assessed with Bliss synergy scores.

Source data

Supplementary information

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Tang, C.P., Clark, O., Ferrarone, J.R. et al. GCN2 kinase activation by ATP-competitive kinase inhibitors. Nat Chem Biol 18, 207–215 (2022). https://doi.org/10.1038/s41589-021-00947-8

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