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A murine lung cancer co-clinical trial identifies genetic modifiers of therapeutic response

Nature volume 483, pages 613–617 (2012)Cite this article

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Abstract

Targeted therapies have demonstrated efficacy against specific subsets of molecularly defined cancers1,2,3,4. Although most patients with lung cancer are stratified according to a single oncogenic driver, cancers harbouring identical activating genetic mutations show large variations in their responses to the same targeted therapy1,3. The biology underlying this heterogeneity is not well understood, and the impact of co-existing genetic mutations, especially the loss of tumour suppressors5,6,7,8,9, has not been fully explored. Here we use genetically engineered mouse models to conduct a ‘co-clinical’ trial that mirrors an ongoing human clinical trial in patients with KRAS-mutant lung cancers. This trial aims to determine if the MEK inhibitor selumetinib (AZD6244)10 increases the efficacy of docetaxel, a standard of care chemotherapy. Our studies demonstrate that concomitant loss of either p53 (also known as Tp53) or Lkb1 (also known as Stk11), two clinically relevant tumour suppressors6,9,11,12, markedly impaired the response of Kras-mutant cancers to docetaxel monotherapy. We observed that the addition of selumetinib provided substantial benefit for mice with lung cancer caused by Kras and Kras and p53 mutations, but mice with Kras and Lkb1 mutations had primary resistance to this combination therapy. Pharmacodynamic studies, including positron-emission tomography (PET) and computed tomography (CT), identified biological markers in mice and patients that provide a rationale for the differential efficacy of these therapies in the different genotypes. These co-clinical results identify predictive genetic biomarkers that should be validated by interrogating samples from patients enrolled on the concurrent clinical trial. These studies also highlight the rationale for synchronous co-clinical trials, not only to anticipate the results of ongoing human clinical trials, but also to generate clinically relevant hypotheses that can inform the analysis and design of human studies.

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Figure 1: Docetaxel and selumetinib combination therapy is more efficacious than docetaxel monotherapy in Kras and Kras/p53 lung cancers.
Figure 2: FDG-PET predicts treatment response.
Figure 3: Modulation of the MEK–ERK pathway in response to treatment is different across the three genotypes.
Figure 4: Long-term treatment outcome in Kras and Kras/p53 mice.

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Acknowledgements

This work is supported by the National Institutes of Health (CA122794, CA140594, CA137181, CA137008, CA147940, CA137008-01, 1U01CA141576, Lung SPORE P50CA090578), United against Lung Cancer Foundation, American Lung Association and Susan Spooner Research Fund.

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Authors and Affiliations

  1. Department of Medicine, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Zhao Chen, Hiromichi Ebi, Yan Liu, Chunxiao Xu, Pasi A. Jänne, Jeffrey A. Engelman & Kwok-Kin Wong

  2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Zhao Chen, Katherine Cheng, Zandra Walton, Yan Liu, Jing Ouyang, Peng Gao, Michele S. Woo, Chunxiao Xu, Masahiko Yanagita, Abigail Altabef, Catherine Yao, Mohit Butaney, David Jackman, Pasi A. Jänne & Kwok-Kin Wong

  3. Ludwig Center at Dana-Farber/Harvard Cancer Center, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Zhao Chen, Katherine Cheng, Zandra Walton, Yan Liu, Peng Gao, Chunxiao Xu, George D. Demetri & Kwok-Kin Wong

  4. Lurie Family Imaging Center, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Yuchuan Wang, Tanya Tupper, Yanping Sun, Amy Saur & Andrew L. Kung

  5. Department of Imaging, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Yuchuan Wang, Yanping Sun & Mizuki Nishino

  6. Department of Radiology, Brigham and Women’s Hospital, Boston, 02115, Massachusetts, USA

    Yuchuan Wang & Mizuki Nishino

  7. Department of Medical Oncology, Massachusetts General Hospital Cancer Center, Boston, 02114, Massachusetts, USA

    Hiromichi Ebi, Nabeel Bardeesy & Jeffrey A. Engelman

  8. Department of Molecular Pharmacology and Therapeutics, Oncology Institute, Loyola University Chicago Stritch School of Medicine, Maywood, 60153, Illinois, USA

    Takeshi Shimamura

  9. Department of Statistics & Statistical Laboratory, Center for Survey Statistics & Methodology, Iowa State University, Ames, 50010, Iowa, USA

    Jie Li

  10. Department of Pathology, Brigham and Women’s Hospital, Boston, 02115, Massachusetts, USA

    Shumei Wang, Charles Lee & Lucian R. Chirieac

  11. Department of Pathology and Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, 75390, Texas, USA

    Yuji Nakada, Christopher G. Peña & Diego H. Castrillon

  12. Department of Biostatistics and Computational Biology, Department of Biostatistics, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, 02115, Massachusetts, USA

    Yoko Franchetti

  13. Translational Research Institute, The Scripps Research Institute, Jupiter, 33458, Florida, USA

    Michael D. Cameron

  14. The Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, 27599, North Carolina, USA

    D. Neil Hayes, Matthew D. Wilkerson, Patrick J. Roberts, Carrie B. Lee & Norman E. Sharpless

  15. Division of Hematology/Oncology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Daniel B. Costa

  16. Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Pasi A. Jänne & Kwok-Kin Wong

  17. Department of Medicine and Pathology, Cancer Genetics Program, Beth Israel Deaconess Cancer Center, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Pier Paolo Pandolfi

  18. Department of Systems Biology, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Lewis C. Cantley

  19. Division of Signal Transduction, Beth Israel Deaconess Medical Center, Boston, 02115, Massachusetts, USA

    Lewis C. Cantley

  20. Department of Pediatric Oncology, Dana Farber Cancer Institute and Children’s Hospital, Boston, 02115, Massachusetts, USA

    Andrew L. Kung

Authors
  1. Zhao Chen
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  2. Katherine Cheng
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  3. Zandra Walton
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  20. Yanping Sun
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  21. Yoko Franchetti
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  22. Catherine Yao
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  23. Amy Saur
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  24. Michael D. Cameron
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  31. Mohit Butaney
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  32. Lucian R. Chirieac
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  33. Daniel B. Costa
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  34. David Jackman
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  40. Lewis C. Cantley
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  41. Andrew L. Kung
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  42. Jeffrey A. Engelman
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  43. Kwok-Kin Wong
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Contributions

Z.C., K.C., Z.W., Y.W., H.E., T.S., Y.L., T.T., J.O., J.L., P.G., M.S.W., C.X., M.Y., A.A., S.W., C.L., Y.N., C.G.P., Y.S., Y.F., C.Y., A.S., M.D.C., D.N.H., M.D.W., P.J.R., C.B.L., N.B., N.E.S., D.H.C., G.D.D., P.A.J., L.C.C., C.B.L., M.N. and P.P.P. performed experimental work and data analyses. M.B., L.R.C., D.B.C. and D.J. collected data and provided patient materials. A.L.K., J.A.E. and K.-K.W. conceived and supervised all aspects of the project. All authors contributed to the final manuscript.

Corresponding authors

Correspondence to Andrew L. Kung, Jeffrey A. Engelman or Kwok-Kin Wong.

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Competing interests

N.H. and J.A.E. received research funding from AstraZenca. G.D.D. is a consultant of Champions Biotechnology. K.-K.W., N.E.S., P.A.J., N.B. and D.H.C. have filed a patent on LKB1 as a diagnostic biomarker in cancer. All other authors have no competing financial interest.

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Chen, Z., Cheng, K., Walton, Z. et al. A murine lung cancer co-clinical trial identifies genetic modifiers of therapeutic response. Nature 483, 613–617 (2012). https://doi.org/10.1038/nature10937

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