Pediatric cancers exhibit complex evolutionary dynamics driven by genetic instability, clonal selection, epigenetic reprogramming, and microenvironmental interactions. Tumor evolution is typically characterized by branching phylogenies, where subclones with unique genetic profiles emerge at different locations and time points. Partly as a result of this diversity, advanced cancers often develop resistance to multiple therapies, complicating treatment strategies. This review explores recurrent themes in clonal evolution across childhood cancers as well as evolution-inspired strategies to counter treatment resistance. A model of dynamic decision making is suggested to accommodate emerging methods for monitoring shifts in a cancer's clonal landscape and the widening repertoire of precision drugs. A larger drug toolbox will allow for more sophisticated evolutionary stratagems to cure or stabilize cancer, using methods such as adaptive therapy, extinction therapy, and reflexive control therapies. However, there are also inherent limits in predicting and controlling cancer evolution- emphasizing the need for early detection, particularly in the setting of predicting relapse, which disproportionately contributes to cancer related mortality in childhood. Understanding the evolutionary trajectories of pediatric cancers can inform more effective, personalized treatment protocols, ultimately enhancing survival rates and quality of life for young patients.
Karlsson et al. (2025) studied this question.