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ATF4 couples MYC-dependent translational activity to bioenergetic demands during tumour progression

Nature Cell Biology volume 21, pages 889–899 (2019)Cite this article

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An Author Correction to this article was published on 17 July 2019

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Abstract

The c-Myc oncogene drives malignant progression and induces robust anabolic and proliferative programmes leading to intrinsic stress. The mechanisms enabling adaptation to MYC-induced stress are not fully understood. Here we reveal an essential role for activating transcription factor 4 (ATF4) in survival following MYC activation. MYC upregulates ATF4 by activating general control nonderepressible 2 (GCN2) kinase through uncharged transfer RNAs. Subsequently, ATF4 co-occupies promoter regions of over 30 MYC-target genes, primarily those regulating amino acid and protein synthesis, including eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1), a negative regulator of translation. 4E-BP1 relieves MYC-induced proteotoxic stress and is essential to balance protein synthesis. 4E-BP1 activity is negatively regulated by mammalian target of rapamycin complex 1 (mTORC1)-dependent phosphorylation and inhibition of mTORC1 signalling rescues ATF4-deficient cells from MYC-induced endoplasmic reticulum stress. Acute deletion of ATF4 significantly delays MYC-driven tumour progression and increases survival in mouse models. Our results establish ATF4 as a cellular rheostat of MYC activity, which ensures that enhanced translation rates are compatible with survival and tumour progression.

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Fig. 1: MYC-induced ATF4 inhibits apoptosis and promotes survival.
Fig. 2: The amino acid sensor GCN2 is activated by uncharged tRNAs and is required for optimal activation of ATF4 on MYC induction.
Fig. 3: ATF4 and MYC bind to common target genes.
Fig. 4: ATF4 suppresses mTORC1-dependent signalling and inhibition of mTORC1 reduces cell death of ATF4-deficient cells following MYC activation.
Fig. 5: Acute ablation of ATF4 significantly delays MYC-driven lymphomagenesis and promotes survival of MYC-driven lymphoma bearing mice.
Fig. 6: EIF4EBP1 positively correlates with ATF4-target gene expression and is associated with poor prognosis.

Data availability

tRNA microarray and ChIP–seq data that support the findings of this study have been deposited in the Gene Expression Omnibus under accession codes GSE116812 and GSE117240, respectively.

The human COAD, BRCA and SARC datasets were derived from the TCGA Data Hub on the University of California Santa Cruz Xena platform (http://xena.ucsc.edu/). The dataset derived from this resource that supports the findings of this study is available in the following links. COAD: https://xenabrowser.net/datapages/?dataset=TCGA.COAD.sampleMap%2FHiSeqV2_PANCAN&host=https%3A%2F%2Ftcga.xenahubs.net&removeHub=https%3A%2F%2Flocal.xena.ucsc.edu%3A7223; BRCA: https://xenabrowser.net/datapages/?dataset=TCGA.BRCA.sampleMap%2FHiSeqV2_PANCAN&host=https%3A%2F%2Ftcga.xenahubs.net&removeHub=https%3A%2F%2Flocal.xena.ucsc.edu%3A7223; SARC: https://xenabrowser.net/datapages/?dataset=TCGA.SARC.sampleMap%2FHiSeqV2_PANCAN&host=https%3A%2F%2Ftcga.xenahubs.net&removeHub=https%3A%2F%2Flocal.xena.ucsc.edu%3A7223. The human DLBCL data were derived from the National Cancer Institute Center for Cancer Genomics website: https://gdc.cancer.gov. The dataset derived from this resource that supports the findings of this study is available at https://gdc.cancer.gov/about-data/publications/DLBCL-2018.

Statistics source data for graphical representations and statistical analyses in Figs. 1–6 and Supplementary Figs. 1–6 are provided in Supplementary Table 3. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

Change history

  • 17 July 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Acknowledgements

We thank D.M. Feldser for critically reading the manuscript. We thank the Koumenis and Maity laboratory members for helpful discussions. This work was supported by National Institutes of Health grants P01CA165997 (D.R., S.Y.F., J.A.D. and C.K.) and 5R01CA198015-04 to R.K.A. F.T. was supported by NIH F31CA183569.

Author information

Authors and Affiliations

  1. Department of Radiation Oncology, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Feven Tameire, Ioannis I. Verginadis, Nektaria Maria Leli, Carlo Salas Salinas, Frank Chinga, Alexandra. M. Monroy & Constantinos Koumenis

  2. Institute for Biochemistry and Molecular Biology, University of Hamburg, Hamburg, Germany

    Christine Polte & Zoya Ignatova

  3. School of Medicine and Department of Urology, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA

    Crystal S. Conn & Davide Ruggero

  4. Abramson Cancer Center and Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Rani Ojha & Ravi K. Amaravadi

  5. Penn Bioinformatics Core, Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA

    Weixuan Fu & Paul Wang

  6. Center for Chemical Biology and Translational Medicine, The Wistar Institute, Philadelphia, PA, USA

    Andrew Kossenkov

  7. Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA

    Jiangbin Ye

  8. Department of Biomedical Sciences, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Serge Y. Fuchs

  9. Department of Biochemistry and Molecular Biology and Hollings Cancer Center, Medical University of South Carolina, Charleston, SC, USA

    J. Alan Diehl

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  1. Feven Tameire
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Contributions

F.T. and C.K. conceived the experiments, analysed data and wrote the manuscript. F.T., I.I.V., N.M.L., R.O., C.S., F.C. and A.M.M. performed experiments. C.P. and Z.I. performed tRNA microarray and analysis. C.S.C., J.A.D., S.Y.F. and D.R. provided valuable reagents, important experimental suggestions and helped in manuscript editing. R.K.A. and J.Y. provided important experimental suggestions. A.K. provided bioinformatics support for ChIP–seq data analysis. W.F. and P.W. analysed patient datasets.

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Correspondence to Constantinos Koumenis.

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Integrated supplementary information

Supplementary Figure 1 GCN2 is required for optimal activation of ATF4.

a. Representative immunoblot following MYC activation in DLD-1, MycER cells (top) or MEFs, MycER (bottom). b. qPCR showing mRNA expression in GCN2 +/+ and GCN2 -/- : MycER MEFs (left) and DLD-1 MycER cells (right) normalized to 18s RNA. Three independent experiments, error bars represent mean ± SD, two tailed student t -test. c. Heat map of comparative microarray showing tRNA abundance following MYC activation. Data are relative to the control values. tRNA probes are depicted with their cognate codon and the corresponding amino acid; Meti, initiator tRNAMet, four biological replicates, one way-ANOVA, * p=0.018. d. Principal component analysis (PCA) of the changes in the tRNA abundance following MYC activation. All biological replicates (n=4) from tRNA microarrays (2h, 4h and 8h in panel c) were subjected in the analysis. tRNAs charged with different amino acids are color coded as follows: light gray, hydrophobic; dark gray, hydrophilic; blue, positively charged and red, negatively charged amino acids. e. Heat map of comparative microarrays showing tRNA charging following MYC activation in vehicle or 25μM RNA POLIII inhibitor (ML60218) treated cells. f. tRNA microarray of DLD-1: MycER cells pretreated for two hours with vehicle or ML60218 followed by 4hr of MYC induction showing tRNA abundance. Samples were normalized to vehicle treated cells. n=1. Immunoblot are from three independent experiments showing similar results. Unprocessed scans of blots are shown in Supplementary Fig 7.

Supplementary Figure 2 ATF4/MYC ChIP-seq.

a. Previously reported ATF4 targets occupied by ATF4 at 8hr of MYC induction within 5kb from TSS. b. Functions and pathways significantly enriched among genes bound by ATF4 within 5kb from TSS and upregulated at 8 hours of MYC activation, E=enrichment, FDR=false discovery rate, UP=Uniprot, MF=molecular function, BP=biological process. Two independent biological replicates were used for ChIP-seq showing similar result. P-values were calculated by Ingenuity Pathway Analysis using right-tailed Fisher Exact Test with FDR values indicating correction for multiple testing. c. ChIP-qPCR validation of ATF4 target genes (left) and genes bound by both ATF4 and MYC (right). Technical replicates, n=3.

Supplementary Figure 3 Antioxidants, fatty acids or alpha ketoglutarate do not rescue ATF4 deficient cells.

a. Representative immunoblot of ATF4 deficient MEFs treated with indicated antioxidants, Trolox and N-acetyl-cysteine (NAC) or Dimethyl 2-oxoglutarate (αKG) followed by MYC activation. b. Representative immunoblot of ATF4 deficient MEFs treated with indicated fatty acids followed by MYC activation. c. Representative immunoblot of MEFs treated with (αKG) at earlier time points of MYC activation. Immunoblots are representative of two independent experiments showing similar results. Unprocessed scans of blots are shown in Supplementary Fig 7.

Supplementary Figure 4 ATF4 and MYC cooperatively regulate EIF4EBP1.

a. qPCR showing expression of mRNAs in wild type and ATF4 -/-, MycER MEFs normalized to 18s RNA. b. qPCR showing expression of mRNAs in control and ATF4 knockdown DLD-1, MycER cells normalized to 18s RNA. a,b Three independent experiments, error bars represent mean ± SD, two tailed student t-test. c. Representative immunoblot of ATF4 -/-, MycER MEFs pretreated with indicated drugs for 2 hours prior to MYC activation. Rapamycin (Rapa) 200nM. Representative immunoblot from three independent experiments showing similar results. d. Clonogenic survival of ATF4 -/-, MycER MEFs after activation of MYC in the absence or presence of Rapamycin (200nM). Graph from there independent experiments, error bars represent mean ± SD, two tailed student t-test. e.35S incorporation in ATF4 -/-, MycER MEFs following MYC activation. Representative autoradiograph is shown. Graph data from three independent experiments, normalized to β-actin. Error bars represent mean ± SD, two tailed student t-test. f. ATF4-/-, MycER MEFs were pretreated with 5mM 4-Phenylbutyric acid (4PBA) for 2hrs followed by MYC activation. Representative western blot from two independent experiments is shown. g. Annexin V staining of cells transfected with the shown siRNAs, n=2, error bars represent mean ± SEM. Unprocessed scans of blots are shown in Supplementary Fig 7.

Supplementary Figure 5 Loss of GCN2 does not affect MYC driven lymphomagenesis but loss of GCN2 combined with inhibition of PERK promotes survival of MYC driven lymphoma bearing mice.

a. Representative images of genotyping PCR products of mice. PCR was performed more than three times independently. b. Kaplan-Meier analysis for overall survival of Eµ-Myc/+; Gcn2+/+ (n=28), Eµ-Myc/+; Gcn2+/- (n=27) and Eµ-Myc/+; Gcn2-/- mice(n=30). Kaplan-Meier curves were analyzed by two-tailed log-rank test. c. Representative western blot assessing ISR signaling in B cells isolated from tumor bearing mice or WT litter mates. Immunoblot is a representative of 3 independent experiments showing similar results. d. Schematic showing the treatment regimen performed in allograft model of lymphomagenesis. 2 million lymphoma cells were injected via tail vein into mice and LY-4 treatment was started three days after tumor injection. e. Body weight of mice injected with lymphoma cells during LY-4 treatment, (n=8 per each group). f. Pancreas weight of the mice in panel e. n=7 mice per group. Error bars represent mean ± SD, two tailed student t-test. g. Kaplan-Meier analysis for overall survival of mice treated with either vehicle or LY-4 (n=8 per each group). Kaplan-Meier curves were analyzed by two-tailed log-rank test. h. Representative immunoblot of ISR signaling examined in tumors isolated from the indicated groups in panel d at the end of the experiment. i. Quantification of immunoblots for p-eIF2α, including panel c. n = 3 for GCN2 +/+: Veh, n = 6 for GCN2 +/+: LY-4, n = 7 for GCN2 -/-: Veh and GCN2 -/-: LY-4. Error bars represent mean ± SD, two tailed student t-test. Unprocessed scans of blots are shown in Supplementary Fig 8. Unprocessed scans of blots are shown in Supplementary Fig 8.

Supplementary Figure 6 Acute deletion of ATF4 significantly delays MYC driven lymphomagenesis.

a. Schematic showing insertion of LoxP sites in mouse Atf4 locus. Exon 2 and 3, which code for ATF4 protein are deleted after Cre recombinase mediated excision. b. Genotyping PCR products of mice used in in vivo experiments. 1=Eμ-Myc/+, Rosa26CreERT2/+, ATF4+/+ 2= Eμ-Myc/+, Rosa26CreERT2/+, ATF4fl/fl, 3= WT. c. Kaplan-Meier analysis for lymphoma-free survival of mice bearing Eµ-Myc; ATF4+/+ lymphoma treated with either vehicle (veh) or tamoxifen (tam) for 5 days, n=10. Kaplan-Meier curves were analyzed by two-tailed log-rank test. d. mRNA expression of ATF4 from Fig 4d, showing a significant reduction of ATF4 mRNA in B cells treated with tamoxifen, n=3, mice per group. Error bars represent mean ± SD, two tailed student t-test. e. mRNA expression of ATF4 at the endpoint mice treated with vehicle or tamoxifen whose survival is shown in Fig 4b, c. n=3, mice per group. Error bars represent mean ± SD, two tailed student t-test.

Supplementary Figure 7

Unprocessed scans of western blots.

Supplementary information

Supplementary Information

Supplementary Figuress 1–7 and Supplementary Table titles and legends.

Reporting Summary

Supplementary Table 1

List of primers used.

Supplementary Table 2

List of antibodies used.

Supplementary Table 3

Statistics source data.

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Tameire, F., Verginadis, I.I., Leli, N.M. et al. ATF4 couples MYC-dependent translational activity to bioenergetic demands during tumour progression. Nat Cell Biol 21, 889–899 (2019). https://doi.org/10.1038/s41556-019-0347-9

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