title: Modeling of signaling crosstalk-mediated drug resistance and its implications on drug combination.
abstract: The efficacy of pharmacological perturbation to the signaling transduction network depends on the network topology. However, whether and how signaling dynamics mediated by crosstalk contributes to the drug resistance are not fully understood and remain to be systematically explored. In this study, motivated by a realistic signaling network linked by crosstalk between EGF/EGFR/Ras/MEK/ERK pathway and HGF/HGFR/PI3K/AKT pathway, we develop kinetic models for several small networks with typical crosstalk modules to investigate the role of the architecture of crosstalk in inducing drug resistance. Our results demonstrate that crosstalk inhibition diminishes the response of signaling output to the external stimuli. Moreover, we show that signaling crosstalk affects the relative sensitivity of drugs, and some types of crosstalk modules that could yield resistance to the targeted drugs were identified. Furthermore, we quantitatively evaluate the relative efficacy and synergism of drug combinations. For the modules that are resistant to the targeted drug, we identify drug targets that can not only increase the relative drug efficacy but also act synergistically. In addition, we analyze the role of the strength of crosstalk in switching a module between drug-sensitive and drug-resistant. Our study provides mechanistic insights into the signaling crosstalk-mediated mechanisms of drug resistance and provides implications for the design of synergistic drug combinations to reduce drug resistance.
authors: Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China.|School of Mathematical and Computational Science, Sun Yat-Sen University, Guangzhou, 510000, China.|School of Life Science, Sun Yat-Sen University, Guangzhou, 510275, China.
authors: Xiaoqiang
authors: X
authors: Sun
authors: School of Mathematical Sciences, Beijing Normal University, Beijing, 100875, China.
authors: Jiguang
authors: J
authors: Bao
authors: School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, 221116, China.
authors: Zhuhong
authors: Z
authors: You
authors: School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu, 221116, China.
authors: Xing
authors: X
authors: Chen
authors: School of Life Science, Sun Yat-Sen University, Guangzhou, 510275, China.|Collaborative Innovation Center of Cancer Medicine, Sun Yat-Sen University, Guangzhou, 510060, China.
authors: Jun
authors: J
authors: Cui
mesh_terms: D017209:Apoptosis / Q000187:drug effects; D045744:Cell Line, Tumor; D019295:Computational Biology; D004338:Drug Combinations; D019008:Drug Resistance, Neoplasm; D004357:Drug Synergism; D048049:Extracellular Signal-Regulated MAP Kinases / Q000378:metabolism; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D019869:Phosphatidylinositol 3-Kinases / Q000378:metabolism; D010766:Phosphorylation; D047428:Protein Kinase Inhibitors / Q000494:pharmacology; D051057:Proto-Oncogene Proteins c-akt / Q000378:metabolism; D015398:Signal Transduction; D012984:Software
chemical_list: D004338:Drug Combinations; D047428:Protein Kinase Inhibitors; D019869:Phosphatidylinositol 3-Kinases; D051057:Proto-Oncogene Proteins c-akt; D048049:Extracellular Signal-Regulated MAP Kinases
keywords: drug combination; drug resistance; signaling crosstalk; synergism