Mathematical modelling of ribosome competition informs testable treatment strategies for drug-tolerant cancer persister cells

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.

Recommended citation: Tang, Xinpu^#, Yuqing Wang^#, Yi Pu^#, Kaixiu Li, Zheyu Ding, Mengyao Wang, Luis Almeida, Michael Cerezo, Yarong Cao, Caroline Robert, Diane Peurichard^*, and Shensi Shen^*. 2026. "Mathematical modeling of ribosome competition informs testable treatment strategies for drug-tolerant cancer persister cells." iScience 29 (4):115493. doi: https://doi.org/10.1016/j.isci.2026.115493.
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