Evidence map›Paper›PMID 40076201›Full record

ReviewMolecules (Basel, Switzerland)2025

Multifaceted Approaches in Epithelial Cell Adhesion Molecule-Mediated Circulating Tumor Cell Isolation.

Dora Szerenyi, Gabor Jarvas, Andras Guttman

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Circulating Tumor Cells for the Monitoring of Lung Cancer Therapies.International journal of molecular sciences · 2025
    Review
  5. Article
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.

Dora SzerenyiResearch Institute of Biomolecular and Chemical Engineering, Faculty of Engineering, University of Pannonia, 8200 Veszprem, Hungary.ORCID 0000-0002-4615-1926
Gabor JarvasResearch Institute of Biomolecular and Chemical Engineering, Faculty of Engineering, University of Pannonia, 8200 Veszprem, Hungary.ORCID 0000-0002-9289-6304
Andras GuttmanResearch Institute of Biomolecular and Chemical Engineering, Faculty of Engineering, University of Pannonia, 8200 Veszprem, Hungary.

Funding

National Research, Development, and Innovation Office, Hungary #2021-1.1.4-GYORSÍTÓSÁV-2022-00038
6 · The paper itself

Abstract

Circulating tumor cells (CTCs) are pivotal in cancer metastasis and serve as valuable biomarkers for diagnosis, prognosis, and treatment monitoring. Traditional CTC capture methods predominantly utilize the epithelial cell adhesion molecule (EpCAM) as a marker for isolation. However, the heterogeneity of these circulating cells and the epithelial-to-mesenchymal transition process (wherein epithelial cells acquire mesenchymal characteristics) limit the efficacy of EpCAM-based capture techniques. In this paper, we critically review the role of the EpCAM in CTC capture, explore the impact of epithelial-to-mesenchymal transition on EpCAM expression, and discuss alternative biomarkers and strategies to enhance CTC isolation. By evaluating the limitations of EpCAM-mediated capture and the challenges posed by epithelial-to-mesenchymal transition, we aim to provide insights into the development of more comprehensive liquid biopsy approaches for cancer management.

Indexed as

Cell SeparationEpithelial Cell Adhesion MoleculeNeoplasmsNeoplastic Cells, CirculatingAnimalsBiomarkers, TumorEpithelial-Mesenchymal TransitionHumansLiquid BiopsyBiomarkers, TumorEPCAM protein, humanEpithelial Cell Adhesion MoleculeCTCEMTimmuno-affinitylabel-free isolationliquid biopsysurface markers

Identifiers

PMID40076201
PMCPMC11901967

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.