Abstract

Treating KRAS-mutant lung adenocarcinoma (LUAD) remains a major challenge in cancer treatment given the difficulties associated with directly inhibiting the KRAS oncoprotein1. One approach to addressing this challenge is to define mutations that frequently co-occur with those in KRAS, which themselves may lead to therapeutic vulnerabilities in tumors. Approximately 20% of KRAS-mutant LUAD tumors carry loss-of-function mutations in the KEAP1 gene encoding Kelch-like ECH-associated protein 1 (refs. 2, 3, 4), a negative regulator of nuclear factor erythroid 2-like 2 (NFE2L2; hereafter NRF2), which is the master transcriptional regulator of the endogenous antioxidant response5,6,7,8,9,10. The high frequency of mutations in KEAP1 suggests an important role for the oxidative stress response in lung tumorigenesis. Using a CRISPR–Cas9-based approach in a mouse model of KRAS-driven LUAD, we examined the effects of Keap1 loss in lung cancer progression. We show that loss of Keap1 hyperactivates NRF2 and promotes KRAS-driven LUAD in mice. Through a combination of CRISPR–Cas9-based genetic screening and metabolomic analyses, we show that Keap1- or Nrf2-mutant cancers are dependent on increased glutaminolysis, and this property can be therapeutically exploited through the pharmacological inhibition of glutaminase. Finally, we provide a rationale for stratification of human patients with lung cancer harboring KRAS/KEAP1- or KRAS/NRF2-mutant lung tumors as likely to respond to glutaminase inhibition.

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Acknowledgements

We thank D. McFadden, R. Possemato, S. Sayin, and T. González-Robles for critical reading of the manuscript; T. Tammela, L. Sullivan, G. DeNicola, and I. Harris for scientific discussions and feedback; S. Levine and T. Mason for massively parallel sequencing expertise; M. Griffin, M. Jennings, and G. Paradis for fluorescence-activated cell sorting (FACS) support; K. Cormier and the Hope Babette Tang (1983) Histology Facility for histology support; I. Baptista, A. Deconinck, J. Teixeira, and K. Yee for administrative support; and the Swanson Biotechnology Center for excellent core facilities. This work was supported in part by the Laura and Isaac Perlmutter Cancer Support Grant, National Institutes of Health (NIH) S10 awards, and Koch Institute Support (core) Grant P30-CA14051 from the National Cancer Institute. T.P. was supported by the American Cancer Society and Hope Funds for Cancer Research. The laboratory of T.P. is supported by the NIH (K22CA201088-01) and the New York University Department of Pathology Bridge Grant. R.R. was supported by the National Science Foundation Graduate Research Fellowship under grant number 1122374. V.I.S. received support from the Swedish Medical Research Council, the AG Fond, and the Wenner-Gren Foundations and is the recipient of EMBO long-term fellowship ALTF 1451-2015 that is co-funded by the European Commission (LTCOFUND2013, GA-2013-609409) with support from Marie Curie Actions. S.E.L. is supported by an NIH training grant (5T32HL007151-38). Human tumor collection by H.I.P. was supported by a National Cancer Institute Early Detection Research Network grant (2U01CA 111295-04). Research in the laboratory of T.J. was supported by Cancer Center Support Grant P30-CA14051 and the Howard Hughes Medical Institute.

Author information

Author notes

    • Rodrigo Romero
    •  & Volkan I Sayin

    These authors contributed equally to this work.

Affiliations

  1. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

    • Rodrigo Romero
    • , Shawn M Davidson
    • , Matthew R Bauer
    • , Donald C Ellis
    • , Arjun Bhutkar
    • , Francisco J Sánchez-Rivera
    • , Lakshmipriya Subbaraj
    • , Matthew G Vander Heiden
    •  & Tyler Jacks
  2. Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

    • Rodrigo Romero
    • , Shawn M Davidson
    • , Donald C Ellis
    • , Francisco J Sánchez-Rivera
    • , Lakshmipriya Subbaraj
    • , Matthew G Vander Heiden
    •  & Tyler Jacks
  3. Department of Pathology, New York University School of Medicine, New York, New York, USA.

    • Volkan I Sayin
    • , Simranjit X Singh
    • , Sarah E LeBoeuf
    • , Triantafyllia R Karakousi
    • , Britney Martinez
    • , Andre L Moreira
    •  & Thales Papagiannakopoulos
  4. Tufts University, Boston, Massachusetts, USA.

    • Roderick T Bronson
  5. Harvard Medical School, Boston, Massachusetts, USA.

    • Roderick T Bronson
  6. Department of Immunology and Infectious Diseases, Montana State University, Bozeman, Montana, USA.

    • Justin R Prigge
    •  & Edward E Schmidt
  7. National Institutes of Health Chemical Genomics Center, Division of Preclinical Innovation, National Center for Advancing Translational Sciences, US National Institutes of Health, Bethesda, Maryland, USA.

    • Craig J Thomas
  8. Department of Cardiothoracic Surgery, New York University Langone Medical Center, New York, New York, USA.

    • Chandra Goparaju
    •  & Harvey I Pass
  9. Champions Oncology, Hackensack, New Jersey, USA.

    • Angela Davies
  10. Genome Technology Center, New York University School of Medicine, New York, New York, USA.

    • Igor Dolgalev
    •  & Adriana Heguy
  11. Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Viola Allaj
    • , John T Poirier
    •  & Charles M Rudin
  12. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Viola Allaj
    • , John T Poirier
    •  & Charles M Rudin
  13. Howard Hughes Medical Institute, Chevy Chase, Maryland, USA.

    • Tyler Jacks
  14. Perlmutter Cancer Center, New York University School of Medicine, New York, New York, USA.

    • Thales Papagiannakopoulos

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Contributions

R.R., V.I.S., F.J.S.-R., T.J., and T.P. designed the study; R.R., V.I.S., M.R.B., S.M.D., S.X.S., S.E.L., T.R.K., D.C.E., L.S., and B.M. performed experiments; A.B. and I.D. conducted bioinformatic analyses; S.M.D. and M.G.V.H. provided feedback and interpretation of metabolism data; E.E.S. and J.R.P. provided custom NRF2 antibody; C.J.T. provided advice and feedback on CB-839 administration; R.T.B. performed histopathological analysis of GEMMs; A.D., V.A., J.T.P., and C.M.R. generated and characterized PDX models; I.D., A.H., A.L.M., C.G., and H.I.P. were involved in human tumor collection, sequencing, and characterization; R.R., V.I.S., T.J., and T.P. wrote the manuscript with comments from all authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Tyler Jacks or Thales Papagiannakopoulos.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–12.

  2. 2.

    Life Sciences Reporting Summary

Excel files

  1. 1.

    Supplementary Table 1

    Targeted exome capture of 88 LUAD tumors from the NYU Center for Biospecimen Research and Development

  2. 2.

    Supplementary Table 2

    GEMM derived Keap1-mutant gene expression signature (z-score table) and top enriched gene sets from MSigDB curated and Oncosig collections. Genes with increasingly positive scores are over-expressed in Keap1-mutant samples whereas those with negative scores exhibit relatively lower expression in Keap1- mutant samples (magnitude denotes strength of a gene's expression correlation with the signature)

  3. 3.

    Supplementary Table 3

    Nrf2 core target gene set derived from the union of three published datasets and Nrf2-induced targets from individual datasets

  4. 4.

    Supplementary Table 4

    Human lung adenocarcinoma (TCGA) derived KEAP1- mutant gene expression signature (z-score table) and top enriched genes sets from MSigDB curated collections. Genes with increasingly positive scores are over-expressed in KEAP1-mutant samples whereas those with negative scores exhibit relatively lower expression in KEAP1-mutant samples (magnitude denotes strength of a gene's expression correlation with the signature)

  5. 5.

    Supplementary Table 5

    Univariate and Multivariate Cox regression analyses for overall survival in the TCGA lung adenocarcinoma patient cohort

  6. 6.

    Supplementary Table 6

    CRISPR/Cas9 Nrf2 transcriptional target screen containing sgRNA sequences, gene descriptions, and sgRNA scores

  7. 7.

    Supplementary Table 7

    Clinical and genetic features of PDX models

  8. 8.

    Supplementary Table 8

    Primer Sequences

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DOI

https://doi.org/10.1038/nm.4407

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