Evidence map›Paper›PMID 41097765›Full record

ReviewCancers2025

Tumour-on-Chip Models for the Study of Ovarian Cancer: Current Challenges and Future Prospects.

Sung Yeon Lim, Lamia Sabry Aboelnasr, Mona El-Bahrawy

Abstract readReview
In one paragraph

Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Sung Yeon LimDepartment of Metabolism, Digestion and Reproduction, Imperial College, London W12 0NN, UK.
Lamia Sabry AboelnasrDepartment of Metabolism, Digestion and Reproduction, Imperial College, London W12 0NN, UK.
Mona El-BahrawyDepartment of Metabolism, Digestion and Reproduction, Imperial College, London W12 0NN, UK.ORCID 0000-0002-3414-9618

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer is a highly lethal malignancy, characterised by late-stage diagnosis, marked inter- and intra-tumoural heterogeneity, and frequent development of chemoresistance. Existing preclinical models, including conventional two-dimensional cultures, three-dimensional spheroids, and organoids, only partially recapitulate the structural and functional complexity of the ovarian tumour microenvironment (TME). Tumour-on-chip (CoC) technology has emerged as a promising alternative, enabling the co-culture of tumour and stromal cells within a microengineered platform that incorporates relevant extracellular matrix components, biochemical gradients, and biomechanical cues under precisely controlled microfluidic conditions. This review provides a comprehensive overview of CoC technology relevant to ovarian cancer research, outlining fabrication strategies, device architectures, and TME-integration approaches. We systematically analyse published ovarian cancer-specific CoC models, revealing a surprisingly limited number of studies and a lack of standardisation across design parameters, materials, and outcome measures. Based on these findings, we identify critical technical and biological considerations to inform the rational design of next-generation CoC platforms, with the aim of improving their reproducibility, translational value, and potential for personalised medicine applications.

Indexed as

microfluidicsovarian cancerpersonalized medicinetumour microenvironmenttumour-on-chip

Identifiers

PMID41097765
PMCPMC12523827

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.