ArticleiScience2026
Modeling constrained tumor evolution through hybrid Ornstein-Uhlenbeck and branching dynamics.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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1 author.
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Abstract
Pediatric leukemias evolve under developmental and therapeutic constraints that can limit phenotypic dispersion while allowing stochastic lineage diversification. Here, we evaluate a hybrid Ornstein-Uhlenbeck (OU)-Branching framework that couples mean-reverting continuous-state dynamics with discrete lineage branching, death, and extinction. By treating Brownian motion as the zero-attraction limiting case of OU dynamics, the model tests whether stabilizing attraction improves the description of longitudinal tumor-state trajectories. We benchmarked Brownian diffusion, OU diffusion, a Markov-emission benchmark, a branching-only drift proxy, and an OU-Branching jump-diffusion proxy using likelihood-based case-level model comparison. Applied to longitudinal targeted-sequencing variant-allele-frequency trajectories from pediatric KMT2A-rearranged acute leukemia, OU diffusion, OU-Branching, and Brownian diffusion were preferred in six, six, and four of 16 evaluable patients, respectively. These results support patient-level heterogeneity among constrained mean reversion, branching-like reconfiguration, and near-Brownian drift, positioning OU-Branching as an interpretable scaffold for evolution-aware precision oncology.
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