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Sharing a new data visualization from our ongoing work on clonal dynamics in therapy-resistant malignancies.

#CancerStemCells #ClonalEvolution #TumorHeterogeneity #TherapyResistance #MinimalResidualDisease #CancerModeling #TumorPlasticity #SingleCellGenomics
Sharing a new data visualization from our ongoing work on clonal dynamics in therapy-resistant malignancies. Figure title: "Subclonal expansion and cancer stem cell enrichment across therapy phases" Subtitle: "Simulated clonal trajectories: therapy-resistant subclones expand as CSC fraction rises through relapse" The visualization employs a clonal fan slopegraph, in which branching subclone trajectories are tracked across four discrete treatment phases (diagnosis, induction response, minimal residual disease, and relapse). Each terminal branch corresponds to a genetically distinct subclone, with vertical position encoding its relative population frequency and branch width scaled to absolute clone size. Superimposed CSC-fraction ribbons quantify the proportion of cells within each subclone bearing a cancer stem cell (CSC) phenotype, operationally defined here by a composite stemness signature. I want to emphasize that the underlying data are simulated. The trajectories are generated from a stochastic branching model parameterized to reproduce a well-documented, literature-grounded trend rather than to represent a specific empirical cohort. The intent is illustrative and hypothesis-clarifying. The central pattern is instructive. Under cytotoxic pressure, dominant treatment-sensitive subclones contract sharply during induction, producing an apparent response, while minor subclones harboring resistance-conferring lesions persist through the MRD bottleneck. Critically, these persistent subclones exhibit disproportionately elevated CSC fractions, consistent with the notion that quiescent, stemness-associated states underwrite drug tolerance and subsequent regrowth. During relapse, the resistant subclones undergo expansion, and the population-level CSC fraction rises accordingly, reflecting both selection and plasticity-driven state transitions.
August 27, 2026 at 5:00 PM