Evidence map›Paper›PMID 40087537›Full record

ArticleNature materials2025

Force transmission is a master regulator of mechanical cell competition.

Andreas Schoenit, Siavash Monfared, Lucas Anger, Carine Rosse, Varun Venkatesh, Lakshmi Balasubramaniam, Elisabetta Marangoni, Philippe Chavrier, René-Marc Mège, Amin Doostmohammadi and 1 more

Abstract read
In one paragraph

Article in Nature materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Cell competition driven by secreted ligands: Modeling liver metastasis of colorectal cancer.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Muscle fibre denervation in ageing.Clinical science (London, England : 1979) · 2026
    Review
  4. Article
  5. Article
  6. Tissue turnover and rejuvenation through mechanics.Frontiers in cell and developmental biology · 2026
    Review
  7. Article
  8. Review
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

11 authors.

Andreas Schoenit *Université Paris Cité, CNRS, Institut Jacques Monod, Paris, France.ORCID 0000-0003-3714-5636
Siavash Monfared *Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.
Lucas Anger *Université Paris Cité, CNRS, Institut Jacques Monod, Paris, France.ORCID 0009-0004-9878-1630
Carine RosseUniversité Paris Cité, CNRS, Institut Jacques Monod, Paris, France.ORCID 0000-0002-8373-8048
Varun VenkateshNiels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0001-8833-9890
Lakshmi BalasubramaniamUniversité Paris Cité, CNRS, Institut Jacques Monod, Paris, France.ORCID 0000-0001-6881-8261
Elisabetta MarangoniTranslational Research Department, Institut Curie, PSL Research University, Paris, France.ORCID 0000-0002-3337-6448
Philippe ChavrierInstitut Curie, Paris Université Sciences et Lettres, CNRS, Paris, France.ORCID 0000-0002-7351-733X
René-Marc MègeUniversité Paris Cité, CNRS, Institut Jacques Monod, Paris, France. rene-marc.mege@ijm.fr.ORCID 0000-0001-8128-5543
Amin DoostmohammadiNiels Bohr Institute, University of Copenhagen, Copenhagen, Denmark. doostmohammadi@nbi.ku.dk.ORCID 0000-0002-1116-4268
Benoit LadouxUniversité Paris Cité, CNRS, Institut Jacques Monod, Paris, France. benoit.ladoux@fau.de.ORCID 0000-0003-2086-1556

Funding

Agence Nationale de la Recherche (French National Research Agency) ANR-10-INBS-04Agence Nationale de la Recherche (French National Research Agency) ANR-11-LABX-0071Agence Nationale de la Recherche (French National Research Agency) ANR-19-CE13-0016Agence Nationale de la Recherche (French National Research Agency) NR-17-CE13-0012EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) Adv-101019835EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) PhysCoMeT, 101041418Institut National Du Cancer (French National Cancer Institute) PLBIO18-236Ligue Contre le Cancer Equipe Labélisée 2019Novo Nordisk Fonden (Novo Nordisk Foundation) NNF18SA0035142Novo Nordisk Fonden (Novo Nordisk Foundation) NNF21OC006868Villum Fonden (Villum Foundation) 29476
6 · The paper itself

Abstract

Cell competition is a tissue surveillance mechanism for eliminating unwanted cells, being indispensable in development, infection and tumourigenesis. Although studies have established the role of biochemical mechanisms in this process, due to challenges in measuring forces in these systems, how mechanical forces determine the competition outcome remains unclear. Here we report a form of cell competition that is regulated by differences in force transmission capabilities, selecting for cell types with stronger intercellular adhesion. Direct force measurements in ex vivo tissues and different cell lines reveal that there is an increased mechanical activity at the interface between two competing cell types, which can lead to large stress fluctuations resulting in upward forces and cell elimination. We show how a winning cell type endowed with a stronger intercellular adhesion exhibits higher resistance to elimination and benefiting from efficient force transmission to the neighbouring cells. This cell elimination mechanism could have broad implications for keeping the strong force transmission ability for maintaining tissue boundaries and cell invasion pathology.

Indexed as

Cell CompetitionAnimalsBiomechanical PhenomenaCell AdhesionHumansMiceStress, Mechanical

Identifiers

PMID40087537
PMCPMC12133594

What OpenQuestion holds

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Registered trials

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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.