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Sci. Signal., 13 August 2013
Vol. 6, Issue 288, p. ra68
Computational Modeling of ERBB2-Amplified Breast Cancer Identifies Combined ErbB2/3 Blockade as Superior to the Combination of MEK and AKT Inhibitors
Daniel C. Kirouac1*,
Jin Y. Du1,
Charlotte F. McDonagh1,
Ulrik B. Nielsen1, and
Matthew D. Onsum1,2
1 Merrimack Pharmaceuticals Inc., 1 Kendall Square, Suite B7201, Cambridge, MA 02139, USA. 2 Silver Creek Pharmaceuticals, 409 Illinois Street, San Francisco, CA 94158, USA.
These authors contributed equally to this work.
Crosstalk and compensatory circuits within cancer signaling networks limit the activity of most targeted therapies. For example, altered signaling in the networks activated by the ErbB family of receptors, particularly in ERBB2-amplified cancers, contributes to drug resistance. We developed a multiscale systems model of signaling networks in ERBB2-amplified breast cancer to quantitatively investigate relationships between biomarkers (markers of network activity) and combination drug efficacy. This model linked ErbB receptor family signaling to breast tumor growth through two kinase cascades: the PI3K/AKT survival pathway and the Ras/MEK/ERK growth and proliferation pathway. The model predicted molecular mechanisms of resistance to individual therapeutics. In particular, ERBB2-amplified breast cancer cells stimulated with the ErbB3 ligand heregulin were resistant to growth arrest induced by inhibitors of AKT and MEK or coapplication of two inhibitors of the receptor ErbB2 [Herceptin (trastuzumab) and Tykerb (lapatinib)]. We used model simulations to predict the response of ErbB2-positive breast cancer xenografts to combination therapies and verified these predictions in mice. Treatment with trastuzumab, lapatinib, and the ErbB3 inhibitor MM-111 was more effective in inhibiting tumor growth than the combination of AKT and MEK inhibitors and even induced tumor regression, indicating that targeting both ErbB3 and ErbB2 may be an improved therapeutic approach for ErbB2-positive breast cancer patients.
Citation: D. C. Kirouac, J. Y. Du, J. Lahdenranta, R. Overland, D. Yarar, V. Paragas, E. Pace, C. F. McDonagh, U. B. Nielsen, M. D. Onsum, Computational Modeling of ERBB2-Amplified Breast Cancer Identifies Combined ErbB2/3 Blockade as Superior to the Combination of MEK and AKT Inhibitors. Sci. Signal.6, ra68 (2013).
Birgit Schoeberl, Emily A. Pace, Jonathan B. Fitzgerald, Brian D. Harms, Lihui Xu, Lin Nie, Bryan Linggi, Ashish Kalra, Violette Paragas, Raghida Bukhalid, Viara Grantcharova, Neeraj Kohli, Kip A. West, Magdalena Leszczyniecka, Michael J. Feldhaus, Arthur J. Kudla, and Ulrik B. Nielsen (30 June 2009) Sci. Signal.2 (77), ra31.
[DOI: 10.1126/scisignal.2000352] |Editor's Summary »|Abstract »|Full Text »|PDF »|Supplementary Materials »
Elizabeth M. Adler and Nancy R. Gough (10 April 2007) Sci. STKE2007 (381), eg2.
[DOI: 10.1126/stke.3812007eg2] |Abstract »|Full Text »|PDF »