Adaptive therapy: a tumor therapy strategy based on Darwinian evolution theory
Lei Zhang, Jianli Ma, Lei Liu, Guozheng Li, Hui Li, Yi Hao, Xin Zhang, Xin Ma, Yihai Chen, Jiale Wu, Xinheng Wang, Shuai Yang, Shouping Xu
Abstract
Cancer progression is a dynamic process of continuous evolution, in which genetic diversity and heterogeneity are generated by clonal and subclonal amplification based on random mutations. Traditional cancer treatment strategies have a great challenge, which often leads to treatment failure due to drug resistance. Integrating evolutionary dynamics into treatment regimens may be an effective way to overcome the problem of drug resistance. In particular, a potential treatment is adaptive therapy, which strategy advocates containment strategies that adjust the treatment cycles according to tumor evolution to control the growth of treatment-resistant cells. In this review, we first summarize the shortcomings of traditional tumor treatment methods in evolution and then introduce the theoretical basis and research status of adaptive therapy. By analyzing the limitations of adaptive therapy and exploring possible solutions, we can broaden people's understanding of adaptive therapy and provide new insights and strategies for tumor treatment. • Traditional treatment strategies ignore the role of tumor evolution. • Adaptive therapy integrates evolutionary principles into tumor management. • Mathematical models combined with clinical data can predict the internal evolutionary dynamics of tumors. • Adaptive therapy can prolong tumor progression time of patients with disseminated tumor compared with traditional therapy.