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

Journal Article (Journal Article)

Targeted therapies have demonstrated efficacy against specific subsets of molecularly defined cancers. 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 therapy. The biology underlying this heterogeneity is not well understood, and the impact of co-existing genetic mutations, especially the loss of tumour suppressors, 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) 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 suppressors, 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.

Full Text

Duke Authors

Cited Authors

  • Chen, Z; Cheng, K; Walton, Z; Wang, Y; Ebi, H; Shimamura, T; Liu, Y; Tupper, T; Ouyang, J; Li, J; Gao, P; Woo, MS; Xu, C; Yanagita, M; Altabef, A; Wang, S; Lee, C; Nakada, Y; Peña, CG; Sun, Y; Franchetti, Y; Yao, C; Saur, A; Cameron, MD; Nishino, M; Hayes, DN; Wilkerson, MD; Roberts, PJ; Lee, CB; Bardeesy, N; Butaney, M; Chirieac, LR; Costa, DB; Jackman, D; Sharpless, NE; Castrillon, DH; Demetri, GD; Jänne, PA; Pandolfi, PP; Cantley, LC; Kung, AL; Engelman, JA; Wong, K-K

Published Date

  • March 18, 2012

Published In

Volume / Issue

  • 483 / 7391

Start / End Page

  • 613 - 617

PubMed ID

  • 22425996

Pubmed Central ID

  • PMC3385933

Electronic International Standard Serial Number (EISSN)

  • 1476-4687

Digital Object Identifier (DOI)

  • 10.1038/nature10937


  • eng

Conference Location

  • England