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Prediction of drug combinations that effectively target cancer cells is a critical challenge for cancer therapy, in particular for triple-negative breast cancer (TNBC), a highly aggressive breast cancer subtype with no effective targeted treatment. As signalling pathway networks critically control cancer cell behaviour, analysis of signalling network activity and crosstalk can help predict potent drug combinations and rational stratification of patients, thus bringing therapeutic and prognostic values. We have previously showed that the non-receptor tyrosine kinase PYK2 is a downstream effector of EGFR and c-Met and demonstrated their crosstalk signalling in basal-like TNBC. Here we applied a systems modelling approach and developed a mechanistic model of the integrated EGFR-PYK2-c-Met signalling network to identify and prioritize potent drug combinations for TNBC. Model predictions validated by experimental data revealed that among six potential combinations of drug pairs targeting the central nodes of the network, including EGFR, c-Met, PYK2 and STAT3, co-targeting of EGFR and PYK2 and to a lesser extent of EGFR and c-Met yielded strongest synergistic effect. Importantly, the synergy in co-targeting EGFR and PYK2 was linked to switch-like cell proliferation-associated responses. Moreover, simulations of patient-specific models using public gene expression data of TNBC patients led to predictive stratification of patients into subgroups displaying distinct susceptibility to specific drug combinations. These results suggest that mechanistic systems modelling is a powerful approach for the rational design, prediction and prioritization of potent combination therapies for individual patients, thus providing a concrete step towards personalized treatment for TNBC and other tumour types., Competing Interests: The authors have declared that no competing interests exist.

Triple-negative breast cancer (TNBC) is a highly aggressive, heterogeneous disease with poor prognosis and no effective targeted therapies. EGFR is highly expressed in basal-like TNBC and is considered as a potential therapeutic target. However, EGFR targeting exerts only marginal clinical benefits, possibly due to activation of compensatory signaling pathways, which are frequently associated with HER3 upregulation. Here we show that concomitant targeting of EGFR and the nonreceptor tyrosine kinases PYK2/FAK synergistically inhibits the proliferation of basal-like TNBC cells in vitro and attenuates tumor growth in a mouse xenograft model. Dual targeting of EGFR and PYK2/FAK inhibited complementary key growth and survival pathways mediated by AKT, S6K, STAT3, and ERK1/2 activation. PYK2 inhibition also abrogated HER3 upregulation in response to EGFR antagonists, thereby circumventing HER3-associated drug resistance. Mechanistically, PYK2 inhibition facilitated the proteasomal degradation of HER3 while inducing upregulation of NDRG1 (N-myc downstream regulated 1 gene). NDRG1 enhanced the interaction of HER3 with the ubiquitin ligase NEDD4, while PYK2, which interacts with NEDD4 and HER3, interfered with NEDD4-HER3 binding, suggesting that the PYK2-NDRG1-NEDD4 circuit has a critical role in receptor degradation, drug response, and resistance mechanism. Our studies offer a preclinical proof of concept for a strategy of cotargeting the EGFR and PYK2/FAK kinases to improve TNBC therapy. Cancer Res; 77(1); 86-99. ©2016 AACR., (©2016 American Association for Cancer Research.)