Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Selective inhibitors of mTORC1 activate 4EBP1 and suppress tumor growth

An Author Correction to this article was published on 29 June 2021

This article has been updated

Abstract

The clinical benefits of pan-mTOR active-site inhibitors are limited by toxicity and relief of feedback inhibition of receptor expression. To address these limitations, we designed a series of compounds that selectively inhibit mTORC1 and not mTORC2. These ‘bi-steric inhibitors’ comprise a rapamycin-like core moiety covalently linked to an mTOR active-site inhibitor. Structural modification of these components modulated their affinities for their binding sites on mTOR and the selectivity of the bi-steric compound. mTORC1-selective compounds potently inhibited 4EBP1 phosphorylation and caused regressions of breast cancer xenografts. Inhibition of 4EBP1 phosphorylation was sufficient to block cancer cell growth and was necessary for maximal antitumor activity. At mTORC1-selective doses, these compounds do not alter glucose tolerance, nor do they relieve AKT-dependent feedback inhibition of HER3. Thus, in preclinical models, selective inhibitors of mTORC1 potently inhibit tumor growth while causing less toxicity and receptor reactivation as compared to pan-mTOR inhibitors.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Generation of mTOR bi-steric inhibitors with distinct mTORC1/2 selectivity profiles.
Fig. 2: mTORC1-selective bi-steric inhibitors induce apoptosis and do not induce HER3 expression in vitro.
Fig. 3: Inhibition of 4EBP1 phosphorylation is sufficient to block cell growth in vitro.
Fig. 4: mTORC1-selective bi-steric inhibitors suppress 4EBP1 phosphorylation in tumors and inhibit tumor growth in MCF-7 xenografts.
Fig. 5: mTORC1-selective bi-steric inhibitors do not cause glucose intolerance in vivo.

Data availability

Source data for Extended Data Fig. 7 have been provided as Supplementary Dataset 3. Source data for Extended Data Fig. 7 have been deposited at the Gene Expression Omnibus with the accession number GSE138417. All other data supporting the findings of this study are available from the corresponding authors on reasonable request.

Material availability

Requests for materials should be addressed to N.R. and J.A.M.S. Source data are provided with this paper.

Code availability

Computational code used in this study is available from the corresponding authors on reasonable request.

Change history

References

  1. 1.

    Chalhoub, N. & Baker, S. J. PTEN and the PI3-kinase pathway in cancer. Annu Rev. Pathol. 4, 127–150 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  2. 2.

    Vivanco, I. & Sawyers, C. L. The phosphatidylinositol 3-Kinase AKT pathway in human cancer. Nat. Rev. Cancer 2, 489–501 (2002).

    CAS  PubMed  Article  Google Scholar 

  3. 3.

    Sarbassov, D. D. et al. RICTOR, a novel binding partner of mTOR, defines a rapamycin-insensitive and raptor-independent pathway that regulates the cytoskeleton. Curr. Biol. 14, 1296–1302 (2004).

    CAS  PubMed  Article  Google Scholar 

  4. 4.

    Sengupta, S., Peterson, T. R. & Sabatini, D. M. Regulation of the mTOR complex 1 pathway by nutrients, growth factors, and stress. Mol. Cell 40, 310–322 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. 5.

    Dowling, R. J. et al. mTORC1-mediated cell proliferation, but not cell growth, controlled by the 4E-BPs. Science 328, 1172–1176 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  6. 6.

    Fingar, D. C. et al. mTOR controls cell cycle progression through its cell growth effectors S6K1 and 4E-BP1/eukaryotic translation initiation factor 4E. Mol. Cell. Biol. 24, 200–216 (2004).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  7. 7.

    Sarbassov, D. D., Guertin, D. A., Ali, S. M. & Sabatini, D. M. Phosphorylation and regulation of Akt/PKB by the RICTOR-mTOR complex. Science 307, 1098–1101 (2005).

    CAS  PubMed  Article  Google Scholar 

  8. 8.

    Avdulov, S. et al. Activation of translation complex eIF4F is essential for the genesis and maintenance of the malignant phenotype in human mammary epithelial cells. Cancer Cell 5, 553–563 (2004).

    CAS  PubMed  Article  Google Scholar 

  9. 9.

    Roux, P. P. & Topisirovic, I. Signaling pathways involved in the regulation of mRNA translation. Mol. Cell Biol. 38, e00070-18 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  10. 10.

    Feldman, M. E. et al. Active-site inhibitors of mTOR target rapamycin-resistant outputs of mTORC1 and mTORC2. PLoS Biol. 7, e38 (2009).

    PubMed  Article  CAS  Google Scholar 

  11. 11.

    Thoreen, C. C. et al. An ATP-competitive mammalian target of rapamycin inhibitor reveals rapamycin-resistant functions of mTORC1. J. Biol. Chem. 284, 8023–8032 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  12. 12.

    Choi, J., Chen, J., Schreiber, S. L. & Clardy, J. Structure of the FKBP12-rapamycin complex interacting with the binding domain of human FRAP. Science 273, 239–242 (1996).

    CAS  PubMed  Article  Google Scholar 

  13. 13.

    Choo, A. Y., Yoon, S. O., Kim, S. G., Roux, P. P. & Blenis, J. Rapamycin differentially inhibits S6Ks and 4E-BP1 to mediate cell-type-specific repression of mRNA translation. Proc. Natl Acad. Sci. USA 105, 17414–17419 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  14. 14.

    Sarbassov, D. D. et al. Prolonged rapamycin treatment inhibits mTORC2 assembly and Akt/PKB. Mol. Cell 22, 159–168 (2006).

    CAS  PubMed  Article  Google Scholar 

  15. 15.

    Bissler, J. J. et al. Sirolimus for angiomyolipoma in tuberous sclerosis complex or lymphangioleiomyomatosis. N. Engl. J. Med. 358, 140–151 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  16. 16.

    Buti, S., Leonetti, A., Dallatomasina, A. & Bersanelli, M. Everolimus in the management of metastatic renal cell carcinoma: an evidence-based review of its place in therapy. Core Evid. 11, 23–36 (2016).

    PubMed  PubMed Central  Article  Google Scholar 

  17. 17.

    Vinayak, S. & Carlson, R. W. mTOR inhibitors in the treatment of breast cancer. Oncol. 27, 38–44 (2013). 46, 48 passim.

    Google Scholar 

  18. 18.

    Graham, L. et al. A phase II study of the dual mTOR inhibitor MLN0128 in patients with metastatic castration resistant prostate cancer. Invest. N. Drugs 36, 458–467 (2018).

    CAS  Article  Google Scholar 

  19. 19.

    Powles, T. et al. A randomised phase 2 study of AZD2014 versus everolimus in patients with VEGF-refractory metastatic clear cell renal cancer. Eur. Urol. 69, 450–456 (2016).

    CAS  PubMed  Article  Google Scholar 

  20. 20.

    Hagiwara, A. et al. Hepatic mTORC2 activates glycolysis and lipogenesis through Akt, glucokinase, and SREBP1c. Cell Metab. 15, 725–738 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  21. 21.

    Chandarlapaty, S. et al. AKT inhibition relieves feedback suppression of receptor tyrosine kinase expression and activity. Cancer Cell 19, 58–71 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  22. 22.

    Muranen, T. et al. Inhibition of PI3K/mTOR leads to adaptive resistance in matrix-attached cancer cells. Cancer Cell 21, 227–239 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  23. 23.

    Rodrik-Outmezguine, V. S. et al. mTOR kinase inhibition causes feedback-dependent biphasic regulation of AKT signaling. Cancer Disco. 1, 248–259 (2011).

    CAS  Article  Google Scholar 

  24. 24.

    Serra, V. et al. PI3K inhibition results in enhanced HER signaling and acquired ERK dependency in HER2-overexpressing breast cancer. Oncogene 30, 2547–2557 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  25. 25.

    Rodrik-Outmezguine, V. S. et al. Overcoming mTOR resistance mutations with a new-generation mTOR inhibitor. Nature 534, 272–276 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. 26.

    Fan, Q. et al. A kinase inhibitor targeted to mTORC1 drives regression in glioblastoma. Cancer Cell 31, 424–435 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  27. 27.

    Mohr, K. et al. Rational design of dualsteric GPCR ligands: quests and promise. Br. J. Pharmacol. 159, 997–1008 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  28. 28.

    Valant, C., Robert Lane, J., Sexton, P. M. & Christopoulos, A. The best of both worlds? Bitopic orthosteric/allosteric ligands of g protein-coupled receptors. Annu. Rev. Pharmacol. Toxicol. 52, 153–178 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  29. 29.

    Yu, K. et al. Biochemical, cellular, and in vivo activity of novel ATP-competitive and selective inhibitors of the mammalian target of rapamycin. Cancer Res. 69, 6232–6240 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  30. 30.

    Chen, X. et al. Cryo-EM structure of human mTOR complex 2. Cell Res. 28, 518–528 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. 31.

    O’Reilly, K. E. et al. mTOR inhibition induces upstream receptor tyrosine kinase signaling and activates Akt. Cancer Res. 66, 1500–1508 (2006).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  32. 32.

    Shi, Y., Yan, H., Frost, P., Gera, J. & Lichtenstein, A. Mammalian target of rapamycin inhibitors activate the AKT kinase in multiple myeloma cells by up-regulating the insulin-like growth factor receptor/insulin receptor substrate-1/phosphatidylinositol 3-kinase cascade. Mol. Cancer Ther. 4, 1533–1540 (2005).

    CAS  PubMed  Article  Google Scholar 

  33. 33.

    Sun, S. Y. et al. Activation of Akt and eIF4E survival pathways by rapamycin-mediated mammalian target of rapamycin inhibition. Cancer Res. 65, 7052–7058 (2005).

    CAS  PubMed  Article  Google Scholar 

  34. 34.

    Bayle, J. H. et al. Rapamycin analogs with differential binding specificity permit orthogonal control of protein activity. Chem. Biol. 13, 99–107 (2006).

    CAS  PubMed  Article  Google Scholar 

  35. 35.

    Luengo, J. I. et al. Structure-activity studies of rapamycin analogs: evidence that the C-7 methoxy group is part of the effector domain and positioned at the FKBP12-FRAP interface. Chem. Biol. 2, 471–481 (1995).

    CAS  PubMed  Article  Google Scholar 

  36. 36.

    Reichling, L. J. et al. Pharmacological characterization of purified recombinant mTOR FRB-kinase domain using fluorescence-based assays. J. Biomol. Screen 13, 238–244 (2008).

    CAS  PubMed  Article  Google Scholar 

  37. 37.

    Patricelli, M. P. et al. Functional interrogation of the kinome using nucleotide acyl phosphates. Biochemistry 46, 350–358 (2007).

    CAS  PubMed  Article  Google Scholar 

  38. 38.

    She, Q. B. et al. 4E-BP1 is a key effector of the oncogenic activation of the AKT and ERK signaling pathways that integrates their function in tumors. Cancer Cell 18, 39–51 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  39. 39.

    Hsieh, A. C. et al. Genetic dissection of the oncogenic mTOR pathway reveals druggable addiction to translational control via 4EBP-eIF4E. Cancer Cell 17, 249–261 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  40. 40.

    Rong, L. et al. Control of eIF4E cellular localization by eIF4E-binding proteins, 4E-BPs. RNA 14, 1318–1327 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. 41.

    Petroulakis, E. et al. p53-dependent translational control of senescence and transformation via 4E-BPs. Cancer Cell 16, 439–446 (2009).

    CAS  PubMed  Article  Google Scholar 

  42. 42.

    Bhat, M. et al. Targeting the translation machinery in cancer. Nat. Rev. Drug Disco. 14, 261–278 (2015).

    CAS  Article  Google Scholar 

  43. 43.

    Masvidal, L., Hulea, L., Furic, L., Topisirovic, I. & Larsson, O. mTOR-sensitive translation: cleared fog reveals more trees. RNA Biol. 14, 1299–1305 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  44. 44.

    Gandin, V. et al. nanoCAGE reveals 5′ UTR features that define specific modes of translation of functionally related MTOR-sensitive mRNAs. Genome Res 26, 636–648 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  45. 45.

    Larsson, O. et al. Distinct perturbation of the translatome by the antidiabetic drug metformin. Proc. Natl Acad. Sci. USA 109, 8977–8982 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  46. 46.

    Basu, B. et al. First-in-human pharmacokinetic and pharmacodynamic study of the dual m-TORC 1/2 inhibitor AZD2014. Clin. Cancer Res. 21, 3412–3419 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  47. 47.

    Steinfeld, T., Mammen, M., Smith, J. A., Wilson, R. D. & Jasper, J. R. A novel multivalent ligand that bridges the allosteric and orthosteric binding sites of the M2 muscarinic receptor. Mol. Pharmacol. 72, 291–302 (2007).

    CAS  PubMed  Article  Google Scholar 

  48. 48.

    Thoreen, C. C. et al. A unifying model for mTORC1-mediated regulation of mRNA translation. Nature 485, 109–113 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. 49.

    Gandin, V. et al. Polysome fractionation and analysis of mammalian translatomes on a genome-wide scale. J. Vis. Exp. 2014, 51455 (2014).

    Google Scholar 

  50. 50.

    Oertlin, C. et al. Generally applicable transcriptome-wide analysis of translation using anota2seq. Nucleic Acids Res. 47, e70 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  51. 51.

    Picelli, S. et al. Full-length RNA-seq from single cells using Smart-seq2. Nat. Protoc. 9, 171–181 (2014).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  52. 52.

    Ewels, P. A. et al. The nf-core framework for community-curated bioinformatics pipelines. Nat. Biotechnol. 38, 276–278 (2020).

    CAS  PubMed  Article  Google Scholar 

  53. 53.

    Ritchie, M. E. et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  54. 54.

    Robinson, M. D. & Oshlack, A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 11, R25 (2010).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  55. 55.

    Cenik, C. et al. Integrative analysis of RNA, translation, and protein levels reveals distinct regulatory variation across humans. Genome Res. 25, 1610–1621 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  56. 56.

    Lorent, J. et al. Translational offsetting as a mode of estrogen receptor alpha-dependent regulation of gene expression. EMBO J. 38, https://doi.org/10.15252/embj.2018101323 (2019).

Download references

Acknowledgements

We thank S. Kelsey and M.A. Goldsmith for scientific guidance and critical review of the manuscript, and A.I. Bassan for invaluable discussions leading to this work. We gratefully acknowledge the contributions of M.J. Gliedt, J. Pitzen, C. Semko, G. Wang and W. Won for the syntheses of the bi-steric mTORC1 inhibitors. N.R. is supported by an NCI Outstanding investigator grant, R35 CA210085 and a Breast Cancer Research Foundation Grant, BCRF17-139. I.T. is supported by Senior Scholar Award from Le Fonds de recherche du Québec–Santé (FRQS) and acknowledges support from Cancer Research Society grant no. 102585. L.H. is supported by Junior 1 Scholar Award from Le Fonds de recherche du Québec–Santé (FRQS). O.L. is a Wallenberg Academy Fellow. We also thank the researchers at WuXi Apptec who supported our in vivo pharmacology efforts. This study was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA008748.

Author information

Affiliations

Authors

Contributions

B.J.L., J.A.B., N.T., S.L.W., T.H., A.M., L.H., G.K., S.M., I.T. and D.W. designed, conducted and interpreted in vitro cellular experiments that include cell proliferation, apoptosis, phosphorylation and cap-binding affinity assays, and gene overexpression, knockout and knockdown. H.L. and O.L. designed, conducted and interpreted the polysome profiling study. B.J.L. and N.T. designed, oversaw and interpreted the KiNativ studies. D.W. designed, oversaw and interpreted the TR–FRET competitive binding and ternary complex assays. B.J.L., J.A.B., E.G.L., J.W.E., D.L., Zhengping W., Zhican W., Y.Z., D.W. and M.S. contributed experimental design, conduct and interpretation of in vivo efficacy, PK/PD and GTT experiments. G.L.B., A.P.T., G.K., J.B.A. and A.L.G. contributed the design and synthesis of RMC-4287, RMC-4627, RMC-4529 and RMC-4745. J.A.M.S., N.R., I.T. and O.L. supervised and contributed to the design and interpretation of all experiments from their respective collaborating groups. B.J.L., J.A.B., D.W., J.A.M.S. and N.R. wrote the manuscript with input from all coauthors.

Corresponding authors

Correspondence to Jacqueline A. M. Smith or Neal Rosen.

Ethics declarations

Competing interests

N.R. reports grants from Revolutionary Medicines and Boehringer Ingelheim; grants and consulting fees from AstraZeneca and Pfizer Array; consulting fees (scientific advisory board) from Ribon Therapeutics, Tarveda Therapeutics, and Chugai Pharmaceuticals; scientific advisory board fees and equity in Beigene and Zai Laboratories; and equity in Kura Oncology and Fortress. I.T. and O.L. have consulted at and are recipients of research grants from Revolution Medicines. B.J.L., G.L.B., A.P.T., N.T., S.L.W., T.H., A.M., E.G.L., J.W.E., G.K., D.L., Zhengping W., Zhican W., Y.Z., D.W., J.B.A., M.S., A.L.G. and J.A.M.S. are current or former employees of Revolution Medicines, Inc. The other authors declare no competing interests.

Additional information

Peer review information Nature Chemical Biology thanks Nathaneal Gray, Masahiro Morita and the other, 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 Bi-steric inhibitors are selective for mTORC1 in multiple cell lines.

a, Immunoblot analysis of whole cell lysates from MDA-MB-468 (ER-, PR-, HER2-/PTEN null, EGFR amplified), MCF-7 (ER + /PIK3CA E545K), ZR-75-1 (ER + /PTEN PL108R), and HCC1954 (HER2 + /PIK3CA H1047R) breast cancer cell lines incubated with indicated compounds for 4 hours. Data are representative of at least n = 2 independent experiments. b, Immunoblot analysis of whole cell lysates from A375 (melanoma, BRAF V600E), MCF-7, and PC3 (prostate cancer, TP53 deletion) cells incubated with indicated compounds for 4 and 24 hours. Data are representative of at least n = 2 independent experiments.

Source data

Extended Data Fig. 2 Selectivity of bi-steric inhibitors for mTORC1 is independent of feedback activation of AKT.

Immunoblot analysis of whole cell lysates from MCF-7 cells transfected with HA-Myr-AKT or vector control for 24 hours followed by exposure to indicated compounds for 4 hours. Data are representative of at least n = 2 independent experiments.

Source data

Extended Data Fig. 3 Cellular activity of mTOR bi-steric inhibitors is dependent on formation of an FKBP12-mTOR inhibitor-FRB ternary complex.

a, Concentration-dependent formation of a ternary complex with emGFP-FKBP12, GST-mTOR (residues 1360-2549), and inhibitor detected by TR-FRET signal from LanthaScreen TB-anti-GST antibody. 100% ternary complex formation is defined by signal with 1 µM rapamycin. Data are the mean of technical duplicates from n = 1 experiment. b, Immunoblot analysis for FKBP12 protein in parental and FKBP12 knockout NCI-H358 cells (analysis performed in n = 1 experiment to verify FKBP12 knockout). c, Concentration responses of p4EBP1 T37/T46 determined from whole cell lysates of parental (filled circles) and FKBP12 knockout (open circles) NCI-H358 cells treated with increasing concentrations of indicated compounds for four hours. Data are the mean of n = 2 experiments each done in technical duplicates, with error bars representing SD. d, Concentration responses of cellular proliferation determined for parental (filled circles) and FKBP12 knockout (open circles) NCI-H358 cells treated with increasing concentrations of indicated compounds for 72 hours. Data are the mean of n = 2 experiments each done in technical duplicates, with error bars representing SD. e, Concentration responses of p4EBP1 T37/T46 determined from whole cell lysates of MDA-MB-468 cells treated with increasing concentrations of indicated compounds in the presence, or absence, of FK506 (10 μM) for four hours. Data are the mean of n = 3 experiments each done in technical duplicates, with error bars representing SD. f, Immunoblot analysis of whole cell lysates from parental MCF-7 cells and MCF-7 cells harboring mTOR F2108L treated with increasing concentrations of indicated compounds for four hours. Data are representative of at least n = 2 independent experiments.

Source data

Extended Data Fig. 4 mTORC1 bi-steric inhibitors cause reduced induction of HER3 in vitro and in vivo.

a, Immunoblot analysis of whole cell lysates from T47D cells treated with indicated compounds for 16 hours. Data are representative of at least n = 2 independent experiments. b, Immunoblot analysis of lysates from T47D xenografts over a period of 24 hours following in vivo administration of a single dose of the indicated compounds. Data are representative of at least n = 2 independent experiments.

Source data

Extended Data Fig. 5 Inhibition of 4EBP1 phosphorylation is important for maximal activity of mTOR bi-steric inhibitors.

a, Immunoblot analysis of whole cell lysates from MDA-MB-468 and MCF-7 sgGFP and sg4EBP1 cells incubated with increasing concentrations of RapaLink-1 for 4 hours. Data are representative of at least n = 2 independent experiments. b, In vitro cap-binding affinity assay and immunoblot analysis of whole cell lysates from MDA-MB-468 sgGFP and sg4EBP1 cells. Data are representative of at least n = 2 independent experiments. c, Cell viability of MDA-MB-468 sgGFP and sg4EBP1 cells incubated with increasing concentrations of RapaLink-1 for up to 5 days. Data are a mean of technical duplicates, and representative of at least n = 2 independent experiments. d, In vitro cap-binding affinity assay and immunoblot analysis of MCF-7 shScr and sh4EBP1 KD cells serum-starved (0% FBS) for 18 hours, then serum-stimulated (10% FBS) and incubated for two hours with compounds at EC80 concentrations: BiS-13x (3 nM), BiS-35x (35 nM), and MLN0128 (40 nM). Serum-starved cells served as a control. Data are representative of two independent experiments with similar results. e, Cell viability of MCF-7 shScr and sh4EBP1 cells (knockdown by scrambled shRNA and shRNA against 4EBP1, respectively) exposed to the indicated compounds for 72 hours. Viability was measured as viable cell counts normalized to DMSO-treated cells, with center bars representing the mean of n = 2 or 3 technical replicates and error bars representing SD of n = 3 technical replicates. Data are a representative experiment of at least n = 2 independent experiments. f, Cell viability of 4EBP1/2 WT and 4EBP1/2 DKO MEFs exposed to indicated compounds for 72 hours. Viability was measured as viable cell counts normalized to DMSO-treated cells, with center bars representing mean of n = 2 or 3 experiments and error bars representing SD of n = 3 experiments.

Source data

Extended Data Fig. 6 Inhibition of global protein synthesis by mTOR bi-steric inhibitors is partially dependent on 4EBP1.

a, Immunoblot analysis of whole cell lysates from MCF-7 cells incubated with indicated inhibitors for 4 hours and pulsed with 1 µM puromycin (Puro) for the last 30 minutes. Data are representative of at least n = 2 independent experiments. b, Immunoblot analysis of whole cell lysates from MCF-7 control (siScr) and 4EBP1-depleted (si4EBP1) cells incubated with increasing concentrations of RapaLink-1 for 4 hours and pulsed with 1 µM puromycin for the last 30 minutes. Data are representative of at least n = 2 independent experiments.

Source data

Extended Data Fig. 7 Translational reprogramming by bi-steric and active-site inhibitors of mTOR is modulated by inhibition of mTORC1.

a, Scatter plots of polysome-associated RNA vs. cytosolic RNA log2 fold changes for the four comparisons: DMSO (complete media) vs. starvation [top left], MLN0128 vs. DMSO [top right], BiS-13x vs. MLN0128 [bottom left] and BiS-35x vs. MLN0128 [bottom right]. For each comparison, genes are colored according to their mode for regulation of gene expression derived from analysis using anota2seq50 and the number of such regulated transcripts is indicated: ‘translation’ denotes transcripts whose change in polysome-association (up or down) could not be explained by a corresponding change in total mRNA level (that is changes in translational efficiency leading to altered protein level); ‘buffering’ denotes transcripts whose change in the total mRNA pool (up or down) was offset at the level of translation such that the association with polysomes remained largely unaltered (that is a change in total mRNA level opposed by a change in translational efficiency, which is expected to lead to unaltered protein levels despite changes in mRNA levels [as recently described]55,56; ‘abundance’ denotes transcript which show a similar change in the total mRNA pool and association with polysomes (that is a change in transcription or mRNA stability leading to altered protein level). b, Samples from the polysome-profiling experiment (normalized data) were projected on the 2 first components of a centered principal component analysis (the proportion of the variance explained by each component is indicated). Data points are colored according to their RNA source (total mRNA or polysome-associated mRNA), shapes denote treatments (DMSO, MLN0128, BiS-13, BiS-35x, or starvation) and the numbers indicate biological replicates (1-4). The library preparation was performed twice on biological replicate 1 providing 2 technical replicates labeled 1 A and 1B. Replicate 1 A was excluded from the downstream analysis.

Extended Data Fig. 8 mTORC1-selective bi-steric inhibitors suppress S6 phosphorylation in tumors and inhibit tumor growth in MCF-7 xenografts.

a, Levels of pS6 S240/S244 as percent of control determined for lysates from MCF-7 tumors at end of study over a period of 72 hours following the final dose of a repeat dosing schedule. Data are the mean signal of each group (n = 3) and error bars represent SD. b, Mean tumor volume of MCF-7 xenografts following daily oral administration (po qd) of MLN0128, and once weekly intraperitoneal (ip qw) administration of bi-steric inhibitors (n = 12 animals per group), with error bars representing SEM. c, Percent tumor volume change of individual MCF-7 xenografts with daily oral administration (po qd) of MLN0128, and once weekly intraperitoneal (ip qw) administration of bi-steric inhibitors. Gray zone represents 10% margin of error for tumor growth and shrinkage. Similar results for each agent were observed in at least n = 2 independent experiments.

Source data

Extended Data Fig. 9 mTORC1-selective bi-steric inhibitors suppress 4EBP1 phosphorylation in tumors and inhibit tumor growth in HCC1954 xenografts.

a, Level of p4EBP1 T37/T46 as percent of control determined for lysates from HCC1954 tumors at end of study over a period of 72 hours following the final dose of a repeat dosing schedule (left), and unbound plasma concentration of inhibitors over time (right). Data are the mean signal of each group (n = 3) and error bars represent SD. b, Level of p4EBP1 T37/T46 as percent of control determined for lysates from HCC1954 tumors after a single dose of inhibitors (left), and unbound plasma concentration of inhibitors over time (right). Data are the mean signal of each group (n = 3) and error bars represent SD. c, Waterfall plot of individual end of study tumor responses, with tumor volume expressed as a percentage of initial tumor volume at time of study. Each animal is represented as a separate bar. d, Mean tumor volume of HCC1954 xenografts following once weekly intraperitoneal (ip qw) administration of bi-steric inhibitors (n = 12 animals per group), with error bars representing SEM. e, Percent tumor volume change of individual HCC1954 xenografts with once weekly intraperitoneal (ip qw) administration of bi-steric inhibitors. Gray zone represents 10% margin of error for tumor growth and shrinkage. f, Mean percent body weight change of HCC1954 xenografts (n = 12 animals per group), with error bars representing SEM. Similar results for each agent were observed in at least n = 2 independent experiments.

Source data

Supplementary information

Supplementary Information

Supplementary Tables 1–3 and Note 1 (contains Supplementary Tables 4–11).

Reporting Summary

Supplementary Dataset 1

Lee_Supp_Dataset_1

Supplementary Dataset 2

Lee_Supp_Dataset_2

Supplementary Dataset 3

Lee_Supp_Dataset_3

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 2

Unprocessed immunoblots.

Source Data Fig. 3

Unprocessed immunoblots.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 4

Unprocessed immunoblots.

Source Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 1

Unprocessed immunoblots.

Source Data Extended Data Fig. 2

Unprocessed immunoblots.

Source Data Extended Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 3

Unprocessed immunoblots.

Source Data Extended Data Fig. 4

Unprocessed immunoblots.

Source Data Extended Data Fig. 5

Unprocessed immunoblots.

Source Data Extended Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 6

Unprocessed immunoblots.

Source Data Extended Data Fig. 8

Statistical source data.

Source Data Extended Data Fig. 9

Statistical source data.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lee, B.J., Boyer, J.A., Burnett, G.L. et al. Selective inhibitors of mTORC1 activate 4EBP1 and suppress tumor growth. Nat Chem Biol 17, 1065–1074 (2021). https://doi.org/10.1038/s41589-021-00813-7

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing