Evidence map›Paper›PMID 42280221›Full record

ReviewMolecules (Basel, Switzerland)2026

Recent Advances on Sensor Technologies for the Monitoring of Tumor Markers.

Yubang Dong, Qi Zhao, Yining Feng, Weikang Yang, Bo Wang, Yuqing Wang, Mingyuan Gao, Jie Zhang, Tianzhu Guan

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yubang DongCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110016, China.
Qi ZhaoCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110016, China.ORCID 0000-0002-7981-9478
Yining FengSchool of Food Science and Engineering, Yangzhou University, Yangzhou 225127, China.ORCID 0009-0003-4482-6680
Weikang YangSchool of Food Science and Engineering, Yangzhou University, Yangzhou 225127, China.
Bo WangSchool of Food Science and Engineering, Yangzhou University, Yangzhou 225127, China.ORCID 0009-0005-6104-4327
Yuqing WangSchool of Food Science and Engineering, Yangzhou University, Yangzhou 225127, China.
Mingyuan GaoSchool of Food Science and Engineering, Yangzhou University, Yangzhou 225127, China.
Jie ZhangCollege of Food Science and Engineering, Jilin University, Changchun 130062, China.ORCID 0000-0002-6944-2021
Tianzhu GuanSchool of Food Science and Engineering, Yangzhou University, Yangzhou 225127, China.ORCID 0000-0001-6395-7019

Funding

Department of Finance of Jiangsu Province BK20200954
6 · The paper itself

Abstract

Sensor technologies have been increasingly recognized as a cornerstone for advancing tumor diagnostics amid the global health challenge posed by cancer. Traditional diagnostic methods are often constrained by inherent tumor heterogeneity, while liquid biopsy has emerged as a transformative minimally invasive alternative, with biosensors playing a pivotal role in its clinical translation. This review summarizes the progress of tumor diagnostic biosensors, focusing on electrochemical and fluorescent sensors. Electrochemical sensors excel in quantitative precision, miniaturization, and point-of-care (POCT) applicability, enabling ultra-sensitive detection of biomarkers such as circulating tumor cells, circulating tumor DNA, and exosomes through nanomaterial modification and signal amplification strategies. Fluorescent sensors, meanwhile, offer superior multiplexing capability and in situ imaging performance, which are further enhanced by novel nanomaterials. Additionally, it covers other promising sensor types including Surface-Enhanced Raman Scattering, microfluidic, photoelectrochemical, field-effect transistor, and clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins-based sensors. Current research efforts are concentrated on multiplexed detection, point-of-care integration, and translation toward higher-order clinical functions such as cancer subtype discrimination, risk stratification, and prognosis. Future directions will focus on multimodal integration, intelligent data analysis, and prospective clinical validation against hard endpoints to facilitate the implementation of precision oncology.

Indexed as

Biomarkers, TumorBiosensing TechniquesNeoplasmsElectrochemical TechniquesHumansNeoplastic Cells, CirculatingPoint-of-Care SystemsBiomarkers, Tumordetection and monitoringfuture prospectssensor technologiestumor markers

Identifiers

PMID42280221
PMCPMC13258736

What OpenQuestion holds

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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.