Evidence map›Paper›PMID 41415904›Full record

ReviewAPL bioengineering2025

Microfluidic lung cancer models: Bridging clinical treatment strategies and tumor microenvironment recapitulation.

Zhiyun Yu, Arsalan A Khan, Wara Naeem, Jeffrey A Borgia, Michael J Liptay, Christopher W Seder, Jian Zhou

Abstract readReview
In one paragraph

Review in APL bioengineering, 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

7 authors.

Zhiyun YuDepartment of Cardiovascular and Thoracic Surgery, Rush University Medical Center, 1725 W Harrison Street, Chicago, Illinois 60612, USA.ORCID https://orcid.org/0000-0001-6568-9978
Arsalan A KhanDepartment of Cardiovascular and Thoracic Surgery, Rush University Medical Center, 1725 W Harrison Street, Chicago, Illinois 60612, USA.
Wara NaeemDepartment of Cardiovascular and Thoracic Surgery, Rush University Medical Center, 1725 W Harrison Street, Chicago, Illinois 60612, USA.ORCID https://orcid.org/0009-0000-6718-1318
Michael J LiptayDepartment of Cardiovascular and Thoracic Surgery, Rush University Medical Center, 1725 W Harrison Street, Chicago, Illinois 60612, USA.ORCID https://orcid.org/0009-0006-1906-5877
Christopher W SederDepartment of Cardiovascular and Thoracic Surgery, Rush University Medical Center, 1725 W Harrison Street, Chicago, Illinois 60612, USA.ORCID https://orcid.org/0000-0002-4070-1245

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer accounting for a majority of cases. Despite advances in targeted therapies and immunotherapy, challenges such as tumor heterogeneity, resistance mechanisms, and limited preclinical models hinder treatment efficacy. Traditional cancer models, including 2D cell cultures and animal models, often fail to accurately replicate the lung's complex architecture, microenvironment, and biomechanical cues, leading to poor predictive performance in drug development. Microfluidic-based organ-on-a-chip technology offers a promising alternative by integrating human-derived cells with precisely controlled perfusion, mechanical cues, and tumor-stroma interactions in physiologically relevant 3D models. These platforms enable the study of lung cancer biology, drug responses, and patient-specific therapeutic outcomes with improved accuracy. In this review, we discuss recent advancements in microfluidic systems for recapitulating normal lung physiology and 3D lung cancer microenvironment, covering various microfluidic platforms with applications in disease modeling and drug testing. Unlike other review articles, we bring first-hand insights from clinicians about the current treatment practice for lung cancer and the clinical utilities of lung cancer-on-a-chip models, which bioengineers have been seeking. We also highlight the translational potential of these systems in personalized oncology and the need for interdisciplinary collaborations, particularly with clinicians, to enhance their clinical impact.

Identifiers

PMID41415904
PMCPMC12711315

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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.