Evidence map›Paper›PMID 40777056›Full record

ArticleiScience2025

Mesenchymal-epithelial transition reduces proliferation but increases immune evasion in tumor spheroids.

Gina Dimari, Yueyuan Hu, Annika Frenzel, Anke Fuchs, Alexander A Wurm, Elisabeth Fischer-Friedrich

Abstract read
In one paragraph

Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

Gina DimariCluster of Excellence Physics of Life, Technische Universität Dresden, 01307 Dresden, Saxony, Germany.
Yueyuan HuCenter for Regenerative Therapies Dresden, Technische Universität Dresden, 01307 Dresden, Saxony, Germany.
Annika FrenzelCluster of Excellence Physics of Life, Technische Universität Dresden, 01307 Dresden, Saxony, Germany.
Anke FuchsCenter for Regenerative Therapies Dresden, Technische Universität Dresden, 01307 Dresden, Saxony, Germany.
Alexander A WurmMildred Scheel Early Career Center, National Center for Tumor Diseases (NCT/UCC) Dresden, Medical Faculty and University Hospital Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Saxony, Germany.
Elisabeth Fischer-FriedrichCluster of Excellence Physics of Life, Technische Universität Dresden, 01307 Dresden, Saxony, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mesenchymal-epithelial transition (MET) whether full or partial, has been implicated in secondary tumor growth during metastasis. Here, we explore whether MET enhances tumor outgrowth by boosting proliferation, using MET-inducible mesenchymal cancer cell lines. Surprisingly, we found that crowding inhibition of proliferation persists both before and after MET, however, escaping crowding conferred a proliferative advantage to mesenchymal cells. In three-dimensional culture, MET caused a reduction in proliferation, accompanied by changes in proliferative signaling of focal adhesions and actomyosin. Furthermore, co-culture experiments with peripheral blood mononuclear cells revealed that MET-induced spheroids demonstrate an increased evasion to immune cell attack. This effect is likely mediated by both a confined morphology and alterations in the expression of key immunomodulatory molecules. Together, these findings suggest that MET may contribute to secondary tumor outgrowth, not by boosting proliferation, but by enhancing survival in immune-challenging environments.

Indexed as

Biological processCancerMicroenvironment

Identifiers

PMID40777056
PMCPMC12329601

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.