Evidence map›Paper›PMID 41155044›Full record

ReviewBioengineering (Basel, Switzerland)2025

Label-Free Cancer Detection Methods Based on Biophysical Cell Phenotypes.

Isabel Calejo, Ana Catarina Azevedo, Raquel L Monteiro, Francisco Cruz, Raphaël F Canadas

Abstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 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

5 authors.

Isabel CalejoDepartment of Biomedicine, Faculty of Medicine, University of Porto, 4200-450 Porto, Portugal.ORCID 0000-0002-6015-0655
Ana Catarina AzevedoDepartment of Biomedicine, Faculty of Medicine, University of Porto, 4200-450 Porto, Portugal.
Raquel L MonteiroDepartment of Biomedicine, Faculty of Medicine, University of Porto, 4200-450 Porto, Portugal.ORCID 0009-0001-2488-7553
Francisco CruzRISE-Health, Faculty of Medicine, University of Porto, 4200-450 Porto, Portugal.ORCID 0000-0003-4551-514X
Raphaël F CanadasDepartment of Biomedicine, Faculty of Medicine, University of Porto, 4200-450 Porto, Portugal.

Funding

Fundação para a Ciência e Tecnologia 2022.05237.PTDC"la Caixa" Foundation CI24-10322
6 · The paper itself

Abstract

Progress in clinical diagnosis increasingly relies on innovative technologies and advanced disease biomarker detection methods. While cell labeling remains a well-established technique, label-free approaches offer significant advantages, including reduced workload, minimal sample damage, cost-effectiveness, and simplified chip integration. These approaches focus on the morpho-biophysical properties of cells, eliminating the need for labeling and thus reducing false results while enhancing data reliability and reproducibility. Current label-free methods span conventional and advanced technologies, including phase-contrast microscopy, holographic microscopy, varied cytometries, microfluidics, dynamic light scattering, atomic force microscopy, and electrical impedance spectroscopy. Their integration with artificial intelligence further enhances their utility, enabling rapid, non-invasive cell identification, dynamic cellular interaction monitoring, and electro-mechanical and morphological cue analysis, making them particularly valuable for cancer diagnostics, monitoring, and prognosis. This review compiles recent label-free cancer cell detection developments within clinical and biotechnological laboratory contexts, emphasizing biophysical alterations pertinent to liquid biopsy applications. It highlights interdisciplinary innovations that allow the characterization and potential identification of cancer cells without labeling. Furthermore, a comparative analysis addresses throughput, resolution, and detection capabilities, thereby guiding their effective deployment in biomedical research and clinical oncology settings.

Indexed as

biophysical biomarkerscancer cellscancer diagnosticscell sortinglabel-free methods

Identifiers

PMID41155044
PMCPMC12562235

What OpenQuestion holds

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LicenceCC BY
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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.