Computational extension models clonal diversification and relapse in pediatric leukemia, suggesting stabilizing selection influences outcomes.
Pediatric cancers evolve under developmental constraints that limit mutational diversity yet preserve adaptive potential. A computational extension of the Hybrid Ornstein-Uhlenbeck (OU)-Branching framework was developed to model clonal diversification and phenotypic stabilization in pediatric leukemia. The OU component captures mean-reverting dynamics representing developmental homeostasis, while the branching component introduces stochastic lineage bifurcation and extinction. Using de-identified clinical metadata from Ahlgren et al. (Nature Communications, 2025; 16:8964), the model simulates patient-specific evolutionary trajectories across relapse categories and disease subtypes (B-ALL, T-ALL, MPAL, AML). Simulations reproduce observed clinical trends-rapid relapse and limited diversification in early or refractory KMT2A-r ALL, and slower, therapy-resistant relapses in AML. Group- and patient-level analyses demonstrate how the balance between stabilizing selection (theta) and diversification rate (lambda) determines clonal persistence and phenotypic drift. This computational implementation provides a quantitative framework for linking developmental constraint, clonal diversity, and therapeutic response in pediatric malignancies and establishes a tractable platform for model-driven hypothesis testing and translational oncology.
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Seunghwan Kim (2025) studied this question.
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