Evidence map›Paper›PMID 39868185›Full record

ArticlebioRxiv : the preprint server for biology2025

Tissue-dependent mechanosensing by cells derived from human tumors.

Kshitiz Parihar, Jonathan Nukpezah, Daniel V Iwamoto, Katrina Cruz, Fitzroy J Byfield, LiKang Chin, Maria E Murray, Melissa G Mendez, Anne S van Oosten, Anne Herrmann and 6 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

5 · Who and what money

Authors and funding

16 authors.

Kshitiz Parihar
Jonathan Nukpezah
Daniel V Iwamoto
Katrina Cruz
Fitzroy J Byfield
LiKang Chin
Maria E Murray
Melissa G Mendez
Anne S van Oosten
Anne Herrmann
Elisabeth E Charrier
Peter A Galie
Megan Donlick
Tongkeun Lee
Paul A Janmey
Ravi RadhakrishnanORCID 0000-0003-0686-2851

Funding

Tissue mechanics reprograms the tissue to malignancy and metastasisR35CA242447 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI VALERIE MARIE WEAVER · 2020 to 2026
$6.6M
Pathological consequences of altered tissue mechanics in fibrosisR01EB017753 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI JANMEY, PAUL A, SHENOY, VIVEK · 2014 to 2025
$6.3M
A physical sciences approach to investigate the role of exosomes in metastatic progressionU01CA250044 · NCI · UNIVERSITY OF PENNSYLVANIA · PI GUO, WEI, RADHAKRISHNAN, RAVI · 2021 to 2025
$3.9M
NCI NIH HHS R35 CA242447NCI NIH HHS U01 CA250044NIBIB NIH HHS R01 EB017753
6 · The paper itself

Abstract

Alterations of the extracellular matrix (ECM), including both mechanical (such as stiffening of the ECM) and chemical (such as variation of adhesion proteins and deposition of hyaluronic acid (HA)) changes, in malignant tissues have been shown to mediate tumor progression. To survey how cells from different tissue types respond to various changes in ECM mechanics and composition, we measured physical characteristics (adherent area, shape, cell stiffness, and cell speed) of 25 cancer and 5 non-tumorigenic cell lines on 7 different substrate conditions. Our results indicate substantial heterogeneity in how cell mechanics changes within and across tissue types in response to mechanosensitive and chemosensitive changes in ECM. The analysis also underscores the role of HA in ECM with some cell lines showing changes in cell mechanics in response to presence of HA in soft substrate that are similar to those observed on stiff substrate. This pan-cancer investigation also highlights the importance of tissue-type and cell line specificity for inferences made based on comparison between physical properties of cancer and normal cells. Lastly, using unsupervised machine learning, we identify phenotypic classes that characterize the physical plasticity, i.e. the distribution of physical feature values attainable, of a particular cell type in response to different ECM-based conditions.

Identifiers

PMID39868185
PMCPMC11761415

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.