Evidence map›Paper›PMID 39439549›Full record

ArticleFrontiers in bioengineering and biotechnology2024

Assessing the metastatic potential of circulating tumor cells using an organ-on-chip model.

Karin F Schmid, Soheila Zeinali, Susanne K Moser, Christelle Dubey, Sabine Schneider, Haibin Deng, Simon Haefliger, Thomas M Marti, Olivier T Guenat

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. 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

9 authors.

Karin F Schmid *Organs-on-chip Technologies Laboratory, ARTORG Center, University of Bern, Bern, Switzerland.
Soheila Zeinali *Organs-on-chip Technologies Laboratory, ARTORG Center, University of Bern, Bern, Switzerland.
Susanne K MoserOrgans-on-chip Technologies Laboratory, ARTORG Center, University of Bern, Bern, Switzerland.
Christelle DubeyDepartment of General Thoracic Surgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Sabine SchneiderOrgans-on-chip Technologies Laboratory, ARTORG Center, University of Bern, Bern, Switzerland.
Haibin DengDepartment of General Thoracic Surgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Simon HaefligerDepartment of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Thomas M MartiDepartment of General Thoracic Surgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Olivier T GuenatOrgans-on-chip Technologies Laboratory, ARTORG Center, University of Bern, Bern, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metastatic lung cancer remains a leading cause of death worldwide, with its intricate metastatic cascade posing significant challenges to researchers and clinicians. Despite substantial progress in understanding this cascade, many aspects remain elusive. Microfluidic-based vasculature-on-chip models have emerged as powerful tools in cancer research, enabling the simulation of specific stages of tumor progression. In this study, we investigate the extravasation behaviors of A549 lung cancer cell subpopulations, revealing distinct differences based on their phenotypes. Our results show that holoclones, which exhibit an epithelial phenotype, do not undergo extravasation. In contrast, paraclones, characterized by a mesenchymal phenotype, demonstrate a notable capacity for extravasation. Furthermore, we observed that paraclones migrate significantly faster than holoclones within the microfluidic model. Importantly, we found that the depletion of vascular endothelial growth factor (VEGF) effectively inhibits the extravasation of paraclones. These findings highlight the utility of microfluidic-based models in replicating key aspects of the metastatic cascade. The insights gained from this study underscore the potential of these models to advance precision medicine by facilitating the assessment of patient-specific cancer cell dynamics and drug responses. This approach could lead to improved strategies for predicting metastatic risk and tailoring personalized cancer therapies, potentially involving the sampling of cancer cells from patients during tumor resection or biopsies.

Indexed as

A549 subclonesEMTepithelial phenotypeextravasationmesenchymal phenotypemetastasismicrovasculature-on-chipVEGF

Identifiers

PMID39439549
PMCPMC11493642

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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.