Evidence map›Paper›PMID 41683755›Full record

ReviewInternational journal of molecular sciences2026

Mechano-Organ-on-Chip for Cancer Research.

Luyang Wang, James Chung Wai Cheung, Xia Zhao, Bee Luan Khoo, Siu Hong Dexter Wong

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Organoid technology in cancer research.Molecular biomedicine · 2026
    Review
  3. 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

5 authors.

Luyang WangSchool of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, China.
James Chung Wai CheungDepartment of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China.ORCID 0000-0001-7446-0569
Xia ZhaoSchool of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, China.ORCID 0000-0001-9167-0840
Bee Luan KhooDepartment of Biomedical Engineering, College of Biomedicine, City University of Hong Kong, Kowloon, Hong Kong SAR, China.ORCID 0000-0003-1100-9994
Siu Hong Dexter WongSchool of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, China.ORCID 0000-0001-7920-4599

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mechano-Organ-on-Chip (Mechano-OoC) platforms are emerging as powerful microphysiological systems that place mechanical cues at the center of tumor modeling, providing a scalable and human-relevant approach to recapitulate the biophysical complexity of the tumor microenvironment. Mechanical factors such as matrix stiffness, viscoelasticity, solid stress, interstitial flow, confinement, and shear critically regulate cancer progression, metastasis, immune interactions, and treatment response, yet remain poorly captured by conventional in vitro models and are often studied separately in tumor-on-chip and mechanobiology research. In this review, we summarize recent advances in mechano-OoC technologies for cancer research, highlighting strategies that integrate engineered mechanical cues with microfluidics, tunable extracellular matrices, vascular and stromal interfaces, and dynamic loading to model tumor invasion, vascular transport, immune trafficking, and drug delivery. We also discuss emerging approaches for real-time, multimodal readouts, including sensor-integrated platforms and artificial intelligence-assisted data analysis, and outline key challenges that limit translation, such as device complexity, limited throughput, insufficient standardization, and inadequate validation against in vivo and clinical data. By organizing progress across platform engineering, sensing and readout, data standardization, and AI-driven analytics, this review provides a unified framework for advancing mechanobiology-aware tumor models and guiding the development of predictive preclinical platforms for precision cancer therapy.

Indexed as

Lab-On-A-Chip DevicesNeoplasmsAnimalsExtracellular MatrixHumansMechanotransduction, CellularMicrofluidicsMicrophysiological SystemsTumor MicroenvironmentMechano-Organ-on-Chipmechanotransductionmicrophysiological systemstumor microenvironment mechanics

Identifiers

PMID41683755
PMCPMC12898056

What OpenQuestion holds

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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 OpenQuestion graph.