Developing multi-target therapeutics to fine-tune the evolutionary dynamics of the cancer ecosystem

Multi-target therapies, either in combination or in sequential order, have been advocated to combat intrinsic and acquired resistance to anti-cancer drugs However, the effectiveness of multi-target anti-cancer therapy in the clinic is limited. The selection of cancer cells obeys Darwin's law of evolution. Under the pressure of drug perturbation, the cancer cell can adapt versatile molecular and cellular mechanisms for survival, and often evolves into more aggressive or metastasis phenotypes At the molecular level, acquired mutations resulting from drug treatment may modify drug metabolism (e.g., increasing efflux, decreasing uptake, and enhancing detoxification etc.) and alter drug-target interactions. At the cellular level, multiple pathways support the survival of cancer cells. The inhibition of one pathway may result in the activation of an alternative pathway. Although novel approaches to optimizing combination therapies have been proposed to defer these drug resistance mechanisms Polygenic drug-resistance mechanisms are present in sub-clones prior to the initiation of therapy If the therapy cannot target all sub-clones that drive the cancer progress in a fast-killing mode, it would prompt the rapid growth of sub-clones that are not sensitive to the treatment Unfortunately, the number of driver mutations in advanced tumors is substantial It could be an impossible mission to target all driver mutations. The existence of cancer stem cells adds another dimension of complexity. The conventional single or combinational anti-cancer drug is incapable of killing cancer stem cells. When a cancer cell is killed by chemotherapy, it could send signals to stimulate the proliferation of the cancer stem cell, leading to the repopulation of the drug-resistance tumor Thus, new strategies are needed to combat anti-cancer drug resistance with the goal to improve the effectiveness of anti-cancer therapy.