ArticleiScience2026
Mathematical modeling of ribosome competition informs testable treatment strategies for drug-tolerant cancer persister cells.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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12 authors.
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Abstract
Systemic therapies for advanced cancers often induce initial responses but rarely achieve durable cures due to acquired resistance. Drug-tolerant persister (DTP) cells survive treatment without additional genetic mutations. We previously showed that melanoma DTP cells globally suppress mRNA translation while selectively maintaining translation of specific mRNAs, but the basis of this selectivity remained unclear. Here, we integrate stochastic modeling with experimental analyses to define the principles governing selective translation in DTP cells. We identify translational reprogramming as a conserved feature of DTP cells across cancer types and treatments. Reduced MYC-dependent ribosome biogenesis limits ribosome availability, creating a translational bottleneck. Modeling reveals that ribosome scarcity drives competition among mRNAs, thereby shaping selective translation. This framework uncovers a ribosome-dependent survival checkpoint in DTP cells and highlights ribosome thresholds as a potential vulnerability for overcoming therapy resistance.
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