Evidence map›Paper›PMID 42006289›Full record

ArticleiScience2026

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

Xinpu Tang, Yuqing Wang, Yi Pu, Kaixiu Li, Zheyu Ding, Mengyao Wang, Luis Almeida, Michael Cerezo, Yarong Cao, Caroline Robert and 2 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Xinpu TangInstitute of Thoracic Oncology and National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610000, China.
Yuqing WangInstitute of Thoracic Oncology and National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610000, China.
Yi PuInstitute of Thoracic Oncology and National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610000, China.
Kaixiu LiInstitute of Thoracic Oncology and National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610000, China.
Zheyu DingInstitute of Thoracic Oncology and National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610000, China.
Mengyao WangInstitute of Thoracic Oncology and National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610000, China.
Luis AlmeidaSorbonne Université, CNRS, Université Paris Cité, LPSM, Paris 75006, France.
Michael CerezoINSERM, U1065, Equipe 12, Centre Méditerranéen de Médecine Moléculaire (C3M), Nice, France.
Yarong CaoInstitute of Thoracic Oncology and National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610000, China.
Caroline RobertINSERM U981, Gustave Roussy Cancer Campus, Villejuif, France.
Diane PeurichardSorbonne Université, Inria, CNRS, Université Paris Cité, Laboratoire Jacques-Louis Lions UMR7598, Equipe MUSCLEES, Paris 75006, France.
Shensi ShenInstitute of Thoracic Oncology and National Clinical Research Center for Geriatrics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

cancermathematical biosciencestherapy

Identifiers

PMID42006289
PMCPMC13091540

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.