Evidence map›Paper›PMID 42113784›Full record

ArticlePloS one2026

Scaffold-free 3D-cell co-culture model system for the study of metastatic cancer in the brain TME.

Pratistha Sarkar, Shreya Ahuja, Iulia M Lazar

Abstract read
In one paragraph

Article in PloS one, 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

5 · Who and what money

Authors and funding

3 authors.

Pratistha SarkarDepartment of Biological Sciences, Blacksburg, Virginia Tech, Blacksburg, Virginia, United States of America.
Shreya AhujaDepartment of Biological Sciences, Blacksburg, Virginia Tech, Blacksburg, Virginia, United States of America.
Iulia M LazarDepartment of Biological Sciences, Blacksburg, Virginia Tech, Blacksburg, Virginia, United States of America.ORCID https://orcid.org/0000-0001-7746-7889

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer involves complex and dynamic interactions among tumor, stromal, immune cells, and the surrounding matrix, however, the protected microenvironment of the brain limits direct access and the execution of mechanistic studies. In this work, we developed a scaffold-free in-vitro brain endothelial-cancer interaction model based on a newly identified affinity between endothelial and cancer cells that enables them to self-assemble into 3D networked constructs supported by high endothelial collagen production and chemokine secretion from both cell types. The model was constructed from human brain endothelial cells (HBEC-5i) and three cancer cell lines derived from breast (MDA-MB-231/triple negative and SK-BR-3/HER2+) and aggressive ovarian (SK-OV-3) cancers. We show that the model mimics the attachment of metastasized cancer cells to the brain networked microvasculature, enabling the study of temporal changes in endothelial morphology and molecular signaling processes that sustain cancer cell migration, survival, proliferation, and angiogenic processes. Moreover, the model exhibits long-term stability, reproducibility, and potential for evaluating anti-cancer agents. Altogether, this simple scaffold-free 3D model offers a low-cost, physiologically relevant tool for studying cancer-endothelial crosstalk and key biological processes that unfold in the tumor microenvironment, to ultimately improve diagnostic capabilities and patient outcomes.

Indexed as

BrainBrain NeoplasmsCell Culture Techniques, Three DimensionalTumor MicroenvironmentBreast NeoplasmsCell Line, TumorCell MovementCell ProliferationCoculture TechniquesEndothelial CellsFemaleHumansMDA-MB-231 CellsModels, BiologicalNeoplasm MetastasisOvarian Neoplasms

Identifiers

PMID42113784
PMCPMC13160345

What OpenQuestion holds

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LicenceCC BY
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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.