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.

  • Article
  • Published:

An allosteric inhibitor against the therapy-resistant mutant forms of EGFR in non-small cell lung cancer

Nature Cancer volume 3, pages 402–417 (2022)Cite this article

Subjects

Abstract

Epidermal growth factor receptor (EGFR) therapy using small-molecule tyrosine kinase inhibitors (TKIs) is initially efficacious in patients with EGFR-mutant lung cancer, although drug resistance eventually develops. Allosteric EGFR inhibitors, which bind to a different EGFR site than existing ATP-competitive EGFR TKIs, have been developed as a strategy to overcome therapy-resistant EGFR mutations. Here we identify and characterize JBJ-09-063, a mutant-selective allosteric EGFR inhibitor that is effective across EGFR TKI-sensitive and resistant models, including those with EGFR T790M and C797S mutations. We further uncover that EGFR homo- or heterodimerization with other ERBB family members, as well as the EGFR L747S mutation, confers resistance to JBJ-09-063, but not to ATP-competitive EGFR TKIs. Overall, our studies highlight the potential clinical utility of JBJ-09-063 as a single agent or in combination with EGFR TKIs to define more effective strategies to treat EGFR-mutant lung cancer.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Characterization of JBJ-09-063 in enzymatic assays, in vitro Ba/F3 cellular studies and in vivo xenograft models.
Fig. 2: JBJ-09-063 efficacy in human cancer cells is enhanced when combined with gefitinib.
Fig. 3: Forced dimerization of EGFR with other ERBB family members impart resistance to JBJ-09-063.
Fig. 4: Ligand-induced dimerization can render cells resistant to JBJ-09-063.
Fig. 5: JBJ-09-063 is effective in TKI-naive EGFR L858R mutant models.
Fig. 6: JBJ-09-063 is effective in a broad range of osimertinib-resistant EGFR mutant contexts.
Fig. 7: JBJ-09-063 is effective in H1975 cells exogenously expressing the osimertinib-resistant mutations.
Fig. 8: L747S mutation is an on-target resistance mechanism to JBJ-09-063, but not to osimertinib.

Similar content being viewed by others

Data availability

All data in this study are presented in the article and Supplementary Information. The structure in Fig. 1a has been deposited in the PDB with the accession code 7JXQ. The structure depicted in Fig. 6b was accessed via PDB accession code 4ZAU. The CRISPR sequencing data in Extended Data Fig. 1g were deposited into the NCBI Biosample database (PRJNA798765) and are publicly available. All materials are available upon request and through a material transfer agreement. Source data are provided with this paper.

References

  1. Bray, F. et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 68, 394–424 (2018).

    Article  PubMed  Google Scholar 

  2. Siegel, R. L., Miller, K. D. & Jemal, A. Cancer statistics, 2020. CA Cancer J. Clin. 70, 7–30 (2020).

    Article  PubMed  Google Scholar 

  3. Maemondo, M. et al. Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. N. Engl. J. Med. 362, 2380–2388 (2010).

    Article  CAS  PubMed  Google Scholar 

  4. Mitsudomi, T. et al. Gefitinib versus cisplatin plus docetaxel in patients with non-small-cell lung cancer harbouring mutations of the epidermal growth factor receptor (WJTOG3405): an open label, randomised phase 3 trial. Lancet Oncol. 11, 121–128 (2010).

    Article  CAS  PubMed  Google Scholar 

  5. Zhou, C. et al. Erlotinib versus chemotherapy as first-line treatment for patients with advanced EGFR mutation-positive non-small-cell lung cancer (OPTIMAL, CTONG-0802): a multicentre, open-label, randomised, phase 3 study. Lancet Oncol. 12, 735–742 (2011).

    Article  CAS  PubMed  Google Scholar 

  6. Rosell, R. et al. Erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol. 13, 239–246 (2012).

    Article  CAS  PubMed  Google Scholar 

  7. Park, K. et al. Afatinib versus gefitinib as first-line treatment of patients with EGFR mutation-positive non-small-cell lung cancer (LUX-Lung 7): a phase 2B, open-label, randomised controlled trial. Lancet Oncol. 17, 577–589 (2016).

    Article  CAS  PubMed  Google Scholar 

  8. Sequist, L. V. et al. Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations. J. Clin. Oncol. 31, 3327–3334 (2013).

    Article  CAS  PubMed  Google Scholar 

  9. Wu, Y. L. et al. Dacomitinib versus gefitinib as first-line treatment for patients with EGFR-mutation-positive non-small-cell lung cancer (ARCHER 1050): a randomised, open-label, phase 3 trial. Lancet Oncol. 18, 1454–1466 (2017).

    Article  CAS  PubMed  Google Scholar 

  10. Wu, Y. L. et al. Afatinib versus cisplatin plus gemcitabine for first-line treatment of Asian patients with advanced non-small-cell lung cancer harbouring EGFR mutations (LUX-Lung 6): an open-label, randomised phase 3 trial. Lancet Oncol. 15, 213–222 (2014).

    Article  CAS  PubMed  Google Scholar 

  11. Soria, J. C. et al. Osimertinib in untreated EGFR-mutated advanced non-small-cell lung cancer. N. Engl. J. Med. 378, 113–125 (2018).

    Article  CAS  PubMed  Google Scholar 

  12. Janne, P. A. et al. AZD9291 in EGFR inhibitor-resistant non-small-cell lung cancer. N. Engl. J. Med. 372, 1689–1699 (2015).

    Article  PubMed  Google Scholar 

  13. Mok, T. S. et al. Osimertinib or platinum-pemetrexed in EGFR T790M-positive lung cancer. N. Engl. J. Med. 376, 629–640 (2017).

    Article  CAS  PubMed  Google Scholar 

  14. Cho, B. C. et al. Osimertinib versus standard of care EGFR TKI as first-line treatment in patients with EGFRm advanced NSCLC: FLAURA Asian subset. J. Thorac. Oncol. 14, 99–106 (2019).

    Article  CAS  PubMed  Google Scholar 

  15. Ramalingam, S. S. et al. Osimertinib as first-line treatment of EGFR mutation-positive advanced non-small-cell lung cancer. J. Clin. Oncol. 36, 841–849 (2018).

    Article  CAS  PubMed  Google Scholar 

  16. Soria, J. C. & Ramalingam, S. S. Osimertinib in EGFR mutation-positive advanced NSCLC. N. Engl. J. Med. 378, 1262–1263 (2018).

    Article  PubMed  Google Scholar 

  17. Mok, T. S. et al. Improvement in overall survival in a randomized study that compared dacomitinib with gefitinib in patients with advanced non-small-cell lung cancer and EGFR-activating mutations. J. Clin. Oncol. 36, 2244–2250 (2018).

    Article  CAS  PubMed  Google Scholar 

  18. Ahn, M. J. et al. Osimertinib in patients with T790M mutation-positive, advanced non-small cell lung cancer: long-term follow-up from a pooled analysis of 2 phase 2 studies. Cancer 125, 892–901 (2019).

    Article  CAS  PubMed  Google Scholar 

  19. Auliac, J. B. et al. Real-life efficacy of osimertinib in pretreated patients with advanced non-small cell lung cancer harboring EGFR T790M mutation. Lung Cancer 127, 96–102 (2019).

    Article  PubMed  Google Scholar 

  20. Igawa, S. et al. Impact of EGFR genotype on the efficacy of osimertinib in EGFR tyrosine kinase inhibitor-resistant patients with non-small cell lung cancer: a prospective observational study. Cancer Manag. Res. 11, 4883–4892 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Thress, K. S. et al. Acquired EGFR C797S mutation mediates resistance to AZD9291 in non-small cell lung cancer harboring EGFR T790M. Nat. Med. 21, 560–562 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Rangachari, D. et al. EGFR-mutated lung cancers resistant to osimertinib through EGFR C797S respond to first-generation reversible EGFR inhibitors but eventually acquire EGFR T790M/C797S in preclinical models and clinical samples. J. Thorac. Oncol. 14, 1995–2002 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Jia, Y. et al. Overcoming EGFR(T790M) and EGFR(C797S) resistance with mutant-selective allosteric inhibitors. Nature 534, 129–132 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. To, C. et al. Single and dual targeting of mutant EGFR with an allosteric inhibitor. Cancer Discov. 9, 926–943 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. De Clercq, D. J. H. et al. Discovery and optimization of dibenzodiazepinones as allosteric mutant-selective EGFR inhibitors. ACS Med. Chem. Lett. 10, 1549–1553 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Engelman, J. A. et al. Allelic dilution obscures detection of a biologically significant resistance mutation in EGFR-amplified lung cancer. J. Clin. Invest. 116, 2695–2706 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Gallant, J.-N. et al. EGFR kinase domain duplication (EGFR-KDD) is a novel oncogenic driver in lung cancer that is clinically responsive to afatinib. Cancer Discov. 5, 1155–1163 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Gallant, J. N. et al. EGFR kinase domain duplication (EGFR-KDD) is a novel oncogenic driver in lung cancer that is clinically responsive to afatinib. Cancer Discov. 5, 1155–1163 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Alam, M. S. Proximity ligation assay (PLA). Curr. Protoc. Immunol. 123, e58 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Leonetti, A. et al. Resistance mechanisms to osimertinib in EGFR-mutated non-small cell lung cancer. Br. J. Cancer 121, 725–737 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Lin, L. et al. Acquired rare recurrent EGFR mutations as mechanisms of resistance to Osimertinib in lung cancer and in silico structural modelling. Am. J. Cancer Res. 10, 4005–4015 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Hu, H. et al. Three subtypes of lung cancer fibroblasts define distinct therapeutic paradigms.Cancer Cell 39, 1531–1547 (2021).

    Article  CAS  PubMed  Google Scholar 

  33. Ma, S. et al. Epiregulin confers EGFR-TKI resistance via EGFR/ErbB2 heterodimer in non-small cell lung cancer. Oncogene 40, 2596–2609 (2021).

    Article  CAS  PubMed  Google Scholar 

  34. Mancini, M. et al. An oligoclonal antibody durably overcomes resistance of lung cancer to third-generation EGFR inhibitors. EMBO Mol. Med. 10, 294–308 (2018).

    Article  CAS  PubMed  Google Scholar 

  35. Cho, J. et al. Cetuximab response of lung cancer-derived EGF receptor mutants is associated with asymmetric dimerization. Cancer Res. 73, 6770–6779 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wylie, A. A. et al. The allosteric inhibitor ABL001 enables dual targeting of BCR-ABL1. Nature 543, 733–737 (2017).

    Article  CAS  PubMed  Google Scholar 

  37. Hughes, T. P. et al. Asciminib in chronic myeloid leukemia after ABL kinase inhibitor failure. N. Engl. J. Med. 381, 2315–2326 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Eide, C. A. et al. Combining the allosteric inhibitor asciminib with ponatinib suppresses emergence of and restores efficacy against highly resistant BCR-ABL1 mutants. Cancer Cell 36, 431–443 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Yun, C. H. et al. The T790M mutation in EGFR kinase causes drug resistance by increasing the affinity for ATP. Proc. Natl Acad. Sci. USA 105, 2070–2075 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Winter, G. et al. DIALS: implementation and evaluation of a new integration package. Acta Crystallogr. D 74, 85–97 (2018).

    Article  CAS  Google Scholar 

  41. Morin, A. et al. Collaboration gets the most out of software. Elife 2, e01456 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Winter, G. xia2: an expert system for macromolecular crystallography data reduction. J. Appl. Crystallogr. 43, 186–190 (2010).

    Article  CAS  Google Scholar 

  43. Adams, P. D. et al. PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr. D 66, 213–221 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D 66, 486–501 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Zhou, W. et al. Novel mutant-selective EGFR kinase inhibitors against EGFR T790M. Nature 462, 1070–1074 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Kosaka, T. et al. Response heterogeneity of EGFR and HER2 exon 20 insertions to covalent EGFR and HER2 inhibitors. Cancer Res. 77, 2712–2721 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Jang, J. et al. Mutant-selective allosteric EGFR degraders are effective against a broad range of drug-resistant mutations. Angew. Chem. Int. Ed. 59, 14481–14489 (2020).

    Article  CAS  Google Scholar 

  48. Bahcall, M. et al. Amplification of wild-type KRAS imparts resistance to crizotinib in MET exon 14 mutant non-small cell lung cancer. Clin. Cancer Res. 24, 5963–5976 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Tracy, S. et al. Gefitinib induces apoptosis in the EGFRL858R non-small-cell lung cancer cell line H3255. Cancer Res. 64, 7241–7244 (2004).

    Article  CAS  PubMed  Google Scholar 

  50. Ercan, D. et al. EGFR mutations and resistance to irreversible pyrimidine-based EGFR inhibitors. Clin. Cancer Res. 21, 3913–3923 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank K. Elenius (University of Turku, Finland) for generously providing the pBABE constructs, the MGH CCI DNA Core for their next-generation sequencing services, E. Cohen from the Molecular Biology Core Facilities at the DFCI for processing the DFCI52-C797S and GR-C797S cell line validation FASTA data in Integrative Genomics Viewer and all staff at the DFCI Animal Resources Facility for their mouse husbandry services. This study was supported by National Cancer Institute grants R35CA220497 (P.A.J.), RO1 CA201049 (M.J.E., N.S.G. and P.A.J) and PO1CA154303 (M.J.E., N.S.G. and P.A.J); American Cancer Society grant CRP-17-111-01-CDD (P.A.J.); the Balassiano Family Fund for Lung Cancer Research (P.A.J.); the Gohl Family Lung Cancer Research Fund (P.A.J.); and Takeda. T.S.B. is supported by a Ruth L. Kirschstein National Research Service Award (1F32CA247198-01). Y.K. is supported in part by Japan Society for the Promotion of Science Overseas Research Fellowships and Research Fellowship from Uehara Memorial Foundation. This work used NE-CAT beamlines (P30 GM124165) and an Eiger detector (S10OD021527) at the Advanced Photon Source (DE-AC02-06CH11357).

Author information

Author notes

  1. Jaebong Jang

    Present address: College of Pharmacy, Korea University, Sejong, Korea

  2. David E. Heppner

    Present address: Department of Chemistry, University at Buffalo, Buffalo, NY, USA

  3. Yoshihisa Kobayashi

    Present address: Division of Molecular Pathology, National Cancer Center Research Institute, Tokyo, Japan

  4. Kari J. Kurppa

    Present address: Institute of Biomedicine, MediCity Research Laboratories, University of Turku, Turku, Finland

  5. Nathanael S. Gray

    Present address: Department of Medicinal Chemistry and Department of Chemistry and Systems Biology, Stanford University, Stanford, CA, USA

  6. These authors contributed equally: Ciric To, Tyler S. Beyett, Jaebong Jang.

Authors and Affiliations

  1. Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, MA, USA

    Ciric To, William W. Feng, Magda Bahcall, Heidi M. Haikala, Bo H. Shin, Yoshihisa Kobayashi, Kari J. Kurppa, Atsuko Ogino, Mierzhati Mushajiang, Chunxiao Xu, Yanxi Zhang & Pasi A. Jänne

  2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA

    Ciric To, William W. Feng, Magda Bahcall, Heidi M. Haikala, Bo H. Shin, Yoshihisa Kobayashi, Kari J. Kurppa, Atsuko Ogino, Mierzhati Mushajiang, Chunxiao Xu, Yanxi Zhang & Pasi A. Jänne

  3. Department of Medicine, Harvard Medical School, Boston, MA, USA

    Ciric To, William W. Feng, Magda Bahcall, Heidi M. Haikala, Bo H. Shin, Yoshihisa Kobayashi, Kari J. Kurppa, Atsuko Ogino, Mierzhati Mushajiang, Chunxiao Xu, Yanxi Zhang & Pasi A. Jänne

  4. Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA

    Tyler S. Beyett, Jaebong Jang, David E. Heppner, Jaimin K. Rana, Thomas W. Gero, David A. Scott, Michael J. Eck & Nathanael S. Gray

  5. Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA

    Tyler S. Beyett, Jaebong Jang, David E. Heppner, Jaimin K. Rana, Thomas W. Gero, David A. Scott, Michael J. Eck & Nathanael S. Gray

  6. Experimental Therapeutics Core and Belfer Center for Applied Cancer Science, Dana-Farber Cancer Institute, Boston, MA, USA

    Brittaney A. Leeper, Kara M. Soroko, Michael J. Poitras & Prafulla C. Gokhale

  7. Institute of Biomedicine, MediCity Research Laboratories, University of Turku, Turku, Finland

    Kamal Wahid

  8. Department of Molecular Therapeutics, The Scripps Research Institute, Jupiter, FL, USA

    Michael D. Cameron

Authors
  1. Ciric To
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tyler S. Beyett
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jaebong Jang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. William W. Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Magda Bahcall
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Heidi M. Haikala
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Bo H. Shin
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. David E. Heppner
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jaimin K. Rana
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Brittaney A. Leeper
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Kara M. Soroko
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Michael J. Poitras
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Prafulla C. Gokhale
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Yoshihisa Kobayashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Kamal Wahid
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Kari J. Kurppa
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Thomas W. Gero
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Michael D. Cameron
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Atsuko Ogino
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Mierzhati Mushajiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Chunxiao Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Yanxi Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. David A. Scott
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Michael J. Eck
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Nathanael S. Gray
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Pasi A. Jänne
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

C.T. and P.A.J. conceived and designed the studies, interpreted the findings and wrote the manuscript. C.T., T.S.B., W.W.F., H.M.H., B.H.S., J.K.R., D.E.H. and M.M. performed experiments and prepared figures. B.A.L., K.M.S., M.J.P. and P.C.G. conducted and coordinated the in vivo studies. J.J., T.W.G. and D.A.S. synthesized the JBJ-09-063 compound. Y.K. generated the H3255GR-C797S and DFCI52-C797S cell lines. M.B., W.W.F., K.W. and K.J.K. generated the constructs for transfection experiments. M.C. performed the pharmacokinetic studies of JBJ-09-063. A.O., C.X. and Y.Z. established the DFCI52 cell line and DFCI52 patient-derived xenograft. M.J.E. and N.S.G. provided crucial feedback on all experimental design and data interpretation. C.T. and P.A.J. supervised the studies and coordinated the efforts of all authors. All authors reviewed the manuscript.

Corresponding authors

Correspondence to David A. Scott, Michael J. Eck, Nathanael S. Gray or Pasi A. Jänne.

Ethics declarations

Competing interests

P.A.J. has received consulting fees from AstraZeneca, Boehringer Ingelheim, Pfizer, Roche/Genentech, Takeda Oncology, ACEA Biosciences, Eli Lilly and Company, Araxes Pharma, Ignyta, Mirati Therapeutics, Novartis, LOXO Oncology, Daiichi Sankyo, Sanofi Oncology, Voronoi, SFJ Pharmaceuticals, Biocartis, Novartis Oncology, Nuvalent, Esai, Bayer, Transcenta, Silicon Therapeutics, Allorion Therapeutics, Accutar Biotech and AbbVie; receives post-marketing royalties from DFCI-owned intellectual property on EGFR mutations licensed to Lab Corp; receives or has received sponsored research funding from AstraZeneca, Astellas, Daichi-Sankyo, PUMA, Boehringer Ingelheim, Eli Lilly and Company, Revolution Medicines and Takeda and has stock ownership in Gatekeeper Pharmaceuticals. N.S.G. is a founder, science advisory board member and equity holder in Gatekeeper, Syros, Petra, C4, Allorion, Jengu, B2S, Inception, EoCys, Larkspur (board member) and Soltego (board member). The Gray lab receives or has received research funding from Novartis, Takeda, Astellas, Taiho, Jansen, Kinogen, Arbella, Deerfield and Sanofi. M.J.E. has served as a paid consultant to Novartis Institutes for Biomedical Research and H3 Biomedicine. M.J.E. receives sponsored research support from Novartis, Sanofi and Takeda. D.E.H. is a consultant for Logos Capital and the Jefferies Group. The series of compounds to which JBJ-04-125-02 and JBJ-09-063 belong is described in US patent 10,836,722 B2. All other authors declare no competing interests.

Peer review

Peer review information

Nature Cancer thanks Rafael Rosell, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

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

Extended data

Extended Data Fig. 1 Structure, potency, pharmacodynamic studies of JBJ-09-063 and the development and validation of H3255GR-C797S and DFIC52-C797S model in vitro.

a, Positive Fo-Fc electron density at 3 sigma for JBJ-09-063. b, Cell viability assay and c, Western Blot analyses of EGFRL858R/C797S Ba/F3 cells treated with increasing concentrations of JBJ-09-063, osimertinib and gefitinib. Data shown in panel b is a representative figure from N=3 independent experiments with 3 technical replicates in each experiment. d, Pharmacodynamic study of JBJ-09-063 in lung tumor tissues of H1975 xenograft mice dosed with 50 mg/kg of the compound. Samples were collected at 0 or 2, 8, 16 and 24h after dosing and samples were processed for Western Blotting analyses. e, Treatment history of patient who was given the first-generation TKI erlotinib (pink bar). Pleural effusion was subsequently drawn (orange arrow with PDX) to establish patient-derived xenograft (PDX) model. DFCI52 cell line was derived from PDX tumors (mouse #135 derived from the effusion). f, Workflow of EGFRL858R/T790M/C797S cell line generation: H3255GR and DFCI52 cells, which already harbor the EGFRL858R/T790M mutation, were transfected by nucleofection with a sgRNA designed to incorporate the C797S mutation in cis with EGFRT790M. 100 nM osimertinib was used for selection for 1 week and samples were sent for next-generation sequencing to determine the presence and frequency of C797S mutation. g, Visualization of the presence and frequency of T790M and C797S allele variants in cis in H3255GR-C797S and DFCI52-C797S cells using Integrated Genome Viewer (IGV). h, Cell viability assays and i, Western Blot analyses of H3255GR vs. H3255GR-C797S and DFCI52 vs. DFCI52-C797S cells treated with increasing concentrations of osimertinib. Data shown in panel h is a representative figure from N=3 independent experiments with 3 technical replicates in each experiment. All cell viability assays shown in this figure were graphed as a percentage of activity relative to DMSO control (mean ± SD) over indicated concentrations.

Source data

Extended Data Fig. 2 JBJ-09-063 efficacy is reduced in vitro unless combined with gefitinib in H3255GR and DFCI52 cells or with osimertinib in H3255GR-C797S and DFCI52-C797S cells.

a, Cell viability and b, Western blot analyses of H3255GR cells treated with indicated concentrations of osimertinib, JBJ-09-063 and JBJ-04-125-02. c, Cell viability, d, apoptosis and e, Western Blot analyses of DFCI52 cells treated with indicated concentrations of gefitinib, JBJ-09-063 or the combination of both agents. Cell viability of H3255GR-C797S cells in panel f, and DFIC52-C797S cells in panel g treated with indicated concentrations of JBJ-09-063 and osimertinib as a single agent or in combination of both compounds. h, Western Blot analyses of H3255GR-C797S and DFIC52-C797S cells treated with indicated concentrations of JBJ-09-063 and osimertinib as a single agent or in combination of both compounds. All cell viability assays shown in this figure were graphed as a percentage of activity relative to DMSO control (mean ± SD) over indicated concentrations. Data shown in panels a, c, f, g are representative figures from N=3 independent experiments with 3 technical replicates in each experiment. The apoptosis experiments were graphed as normalized caspase-3/7 activity (in average arbitrary units ± SEM)) over time. Data shown in panel f is a representative figure from N=3 independent experiments with 12 technical replicates in each experiment.

Source data

Supplementary information

Reporting Summary

Supplementary Tables

Supplementary Table 1. Data collection and refinement statistics (molecular replacement) of JBJ-09-063. Supplementary Table 2. IC50 of JBJ-04-125-02 and JBJ-09-063 in enzymatic assays, Ba/F3 cells, H1975 cells, and human cancer cells. Supplementary Table 3. Pharmacokinetic profile of JBJ-09-063. Supplementary Table 4. Sequences and primers for plasmids and cell lines generation.

Source data

Source Data Fig. 1

Unprocessed western blots with molecular markers.

Source Data Fig. 1

Quantitation of statistical data.

Source Data Fig. 2

Unprocessed western blots with molecular markers.

Source Data Fig. 2

Quantitation for statistical data.

Source Data Fig. 3

Unprocessed western blots with molecular markers.

Source Data Fig. 3

Quantitation of statistical data.

Source Data Fig. 4

Unprocessed western blots with molecular markers.

Source Data Fig. 4

Quantitation for statistical data

Source Data Fig. 5

Unprocessed western blots with molecular markers.

Source Data Fig. 5

Quantitation of statistical data.

Source Data Fig. 6

Unprocessed western blots with molecular markers.

Source Data Fig. 6

Quantitation of statistical data.

Source Data Fig. 7

Unprocessed western blots with molecular markers.

Source Data Fig. 7

Quantitation for statistical data.

Source Data Fig. 8

Unprocessed western blots with molecular markers.

Source Data Fig. 8

Quantitation for statistical data.

Source Data Extended Data Fig. 1

Unprocessed western blots with molecular markers.

Source Data Extended Data Fig. 1

Quantitation of statistical data

Source Data Extended Data Fig. 2

Unprocessed western blots with molecular markers..

Source Data Extended Data Fig. 2

Quantitation of statistical data.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

To, C., Beyett, T.S., Jang, J. et al. An allosteric inhibitor against the therapy-resistant mutant forms of EGFR in non-small cell lung cancer. Nat Cancer 3, 402–417 (2022). https://doi.org/10.1038/s43018-022-00351-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43018-022-00351-8

This article is cited by

Search

Advanced 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