Evidence map›Paper›PMID 41724590›Full record

ReviewThe FEBS journal2026

Beyond the chaos: How architecture structures tumour biology.

Lea Dörner, Catrin Lutz, Stefan Prekovic, Hendrik A Messal

Abstract readReview
In one paragraph

Review in The FEBS journal, 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

4 authors.

Lea DörnerDivision of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.ORCID 0009-0006-8975-1012
Catrin LutzDivision of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.ORCID 0009-0002-5152-6785
Stefan PrekovicCenter for Molecular Medicine, UMC Utrecht, The Netherlands.
Hendrik A MessalDivision of Tumor Biology and Immunology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.ORCID 0000-0003-2259-0286

Funding

Nederlandse Organisatie voor Wetenschappelijk Onderzoek 09150161910151
6 · The paper itself

Abstract

Cancer is increasingly recognised as a complex and heterogeneous disease, shaped not only by genetic mutations but also by the physical and biochemical context in which tumours develop. The spatial position of a cell, including its physical, cellular and molecular surroundings, shapes its fate, phenotypic plasticity and potential to transform and drive tumour progression and evolution. Tissue architecture provides a powerful framework for understanding the complex dynamics of cancer. It integrates the structural organisation of the tumour and its surrounding tissue, the distribution of physical forces, biochemical niches, cellular neighbourhoods, and the broader tissue and organ context in which the tumour develops. Together, these elements form a dynamic and evolving landscape that is continuously remodelled through the multiscale communication of cellular, biochemical and mechanical components. Understanding the principles that govern these interactions reveals that cancer is not merely a chaotic aggregation of cells, but a patterned system shaped by coordinated spatial relationships. Here, we discuss the recent literature to examine how physical, biochemical and cellular relationships orchestrate tumour initiation, progression and treatment resistance, and how their collaboration acts not as a passive scaffold, but as the architect of tumour behaviour.

Indexed as

NeoplasmsTumor MicroenvironmentAnimalsHumansbiochemistrybiophysicscellular neighbourhoodsmicroenvironmentTissue architecturetumour biology

Identifiers

PMID41724590
PMCPMC13147316

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.