Optimal Combined Anticancer Therapy That Can Overcome Cell-Type Specific Drug Resistance Of Breast Cancer

Breast cancer is a complex disease associated with various genomic alterations that influence the dynamical change of signaling network. The inherent heterogeneous characteristics of breast cancer cells often result in variable anti-cancer drug resistance. Despite the recent progress of targeted cancer therapy, the underlying mechanism of such variable drug resistance still remains unclear and needs to be investigated. To tackle this problem with respect to a breast cancer signaling network, we have reconstructed differential breast cancer singling networks by integrating various genomic data of breast tumors and analyzed their state transition dynamics through perturbation simulations that mimick various anti-cancer drug treatments. We then categorized heterogeneous breast cancer cell types into three groups: sensitive, moderate, or resistant to drugs. For each group, we identified a distinct core-signaling mechanism underlying the drug resistance on the basis of attractor landscape analysis. Finally, we have identified an optimal drug combination that can maximize cell death regardless of heterogeneous breast cancer cell types. Our study shows that the attractor landscape analysis of a breast cancer signaling network can unravel the hidden mechanism underlying individual variation in drug responses and provide a new therapeutic strategy that can overcome variable drug resistance. Acknowledgements: This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korea Government, the Ministry of Science, ICT u0026 Future Planning (2014R1A2A1A10052404, 2013M3A9A7046303, and 2010-0017662). Citation Format: Minsoo Choi, Kwang-Hyun Cho. Optimal combined anticancer therapy that can overcome cell-type specific drug resistance of breast cancer. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-27.