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Oncogenic NRAS signaling differentially regulates survival and proliferation in melanoma

Nature Medicine volume 18, pages 1503–1510 (2012)Cite this article

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A Corrigendum to this article was published on 06 December 2012

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Abstract

The discovery of potent inhibitors of the BRAF proto-oncogene has revolutionized therapy for melanoma harboring mutations in BRAF, yet NRAS-mutant melanoma remains without an effective therapy. Because direct pharmacological inhibition of the RAS proto-oncogene has thus far been unsuccessful, we explored systems biology approaches to identify synergistic drug combination(s) that can mimic RAS inhibition. Here, leveraging an inducible mouse model of NRAS-mutant melanoma, we show that pharmacological inhibition of mitogen-activated protein kinase kinase (MEK) activates apoptosis but not cell-cycle arrest, which is in contrast to complete genetic neuroblastoma RAS homolog (NRAS) extinction, which triggers both of these effects. Network modeling pinpointed cyclin-dependent kinase 4 (CDK4) as a key driver of this differential phenotype. Accordingly, combined pharmacological inhibition of MEK and CDK4 in vivo led to substantial synergy in therapeutic efficacy. We suggest a gradient model of oncogenic NRAS signaling in which the output is gated, resulting in the decoupling of discrete downstream biological phenotypes as a result of incomplete inhibition. Such a gated signaling model offers a new framework to identify nonobvious coextinction target(s) for combined pharmacological inhibition in NRAS-mutant melanomas.

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Figure 1: Characterization of the iNRAS mouse melanoma model and experimental design.
Figure 2: RAS-specific module (RSM) genes are highly enriched for cell-cycle functions.
Figure 3: Cellular proliferation is inhibited by NRASQ61K extinction but not MEK inhibition.
Figure 4: The Cdk4-Rb axis regulates the RAS-specific pathways.
Figure 5: The combination MEK and CDK4/6 inhibition is synergistic in vivo.
Figure 6: NRAS-MAPK activity differentially regulates apoptosis and proliferation.

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  • 20 November 2012

     In the version of this article initially published, the formula to calculate the mutual information matrix, which appears in the last page of the Online Methods, was missing a log multiplier. The error has been corrected in the HTML and PDF versions of the article.

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Acknowledgements

We thank G. Mills, Y. Lu and N. Shih at the MD Anderson Reverse Phase Protein Array core facility; E. Fox at the Dana-Farber Cancer Institute Microarray core facility; S. Zhou for mouse husbandry; R. DePinho and G. Draetta and members of the laboratory, including S. Quayle, M. Chen, A. Blanchette and J. Kamara, for insightful discussions; R. Kwong for manuscript proofreading; D. Camacho for helping develop the TRAP algorithm; and M. Bar-Eli (University of Texas MD Anderson Cancer Center, Houston, Texas) for the SB-2 cell line. L.N.K. is supported by the Postdoctoral Fellowship (117842-PF-09-261-01-TBG) from the American Cancer Society. J.J.C. is supported by the US National Institutes of Health Director's Pioneer Award Program and the Howard Hughes Medical Institute. This work was supported by funding from the US National Institutes of Health to L.C. (U01 CA141508). L.C. is a recipient of the Abby S. and Howard P. Milstein 2009 Innovation Award for Melanoma and Skin Cancer Research and a CPRIT (Cancer Prevention Research Institute of Texas) Scholar in Cancer Research.

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Authors and Affiliations

  1. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA

    Lawrence N Kwong, Huiyun Liu, Shan Jiang, Aliete E Langsdorf, David Jakubosky, Giannicola Genovese, Florian L Muller, Joseph H Jeong, Ryan P Bender, Gerald C Chu & Lynda Chin

  2. Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, Texas, USA

    Lawrence N Kwong, Shan Jiang, Timothy L Helms, Giannicola Genovese, Florian L Muller & Lynda Chin

  3. Department of Biomedical Engineering and Center for BioDynamics, Howard Hughes Medical Institute, Boston University, Boston, Massachusetts, USA

    James C Costello & James J Collins

  4. Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts, USA

    Gerald C Chu

  5. Division of Medical Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA

    Keith T Flaherty

  6. Division of Surgical Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA

    Jennifer A Wargo

  7. Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA

    James J Collins

  8. Institute for Applied Cancer Science, University of Texas MD Anderson Cancer Center, Houston, Texas, USA

    Lynda Chin

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Contributions

L.N.K. performed the majority of experiments described in the manuscript. J.C.C. performed GSEA and TRAP analyses. L.N.K. and J.C.C. jointly generated the remaining statistics. H.L. and T.L.H. helped maintain nude mouse colonies and provided technical assistance in many experiments. S.J. maintained the iNRAS GEM model colony and measured tumor volumes for primary melanomas. A.E.L., D.J. and G.C.C. performed the EVOC work, and the biopsy was supplied by J.A.W. and K.T.F. G.G. and F.L.M. performed some western blotting. J.H.J. generated the iNRAS mouse. R.P.B. assisted in generating the iNRAS time course microarray data. J.J.C. oversaw TRAP and statistical analyses. L.N.K. and L.C. conceived of the study. L.N.K., J.C.C. and L.C. wrote the paper.

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Correspondence to Lynda Chin.

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Kwong, L., Costello, J., Liu, H. et al. Oncogenic NRAS signaling differentially regulates survival and proliferation in melanoma. Nat Med 18, 1503–1510 (2012). https://doi.org/10.1038/nm.2941

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