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Background:Tumor microenvironment plays an essential role in the growth of malignancy.Understanding how tumor cells co-evolve with tumor-associated immune cells and stromal cells is important for tumor treatment.Methods:In this paper,we propose a logistic population dynamics model for quantifying the intercellular signaling network in non-small-cell lung cancer (NSCLC).The model describes the evolutionary dynamics of cells and signaling proteins and was used to predict effective receptor targets through combination strategy analysis.Then,we optimized a multi-target strategy analysis algorithm that was verified by applying it to virtual patients with heterogeneous conditions.Furthermore,to deal with acquired resistance which was commonly observed in patients with NSCLC,we proposed a novel targeting strategy-tracking targeted therapy,to optimize the treatment by improving the therapeutic strategy periodically.Results:The synergistic effect when inhibiting multiple signaling pathways may help significantly retard carcinogenic processes associated with disease progression,compared with suppression of a single signaling pathway.While traditional treatment (surgery,radiotherapy and chemotherapy) tends to attack tumor cells directly,the multi-target therapy we suggested here is aimed to inhibit the development of tumor by emasculating the relative competitive advantages of tumor cells and promoting that of normal cells.Conclusion:The combination of traditional and targeted therapy,as an interesting experiment,was significantly more effective in treatment of virtual patients due to a clear complementary relationship between the two therapeutic schemes.