Evidence map›Paper›PMID 41469748›Full record

ReviewBiomarker research2025

Biosensor technologies in cancer: tools for early detection and prognostic monitoring.

Mei Kei Fam, Nurul Izza Ismail, Afzal Izzaz Zahari, Nor Azlin Ghazali, Norfarazieda Hassan

Abstract readReview
In one paragraph

Review in Biomarker research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Mei Kei FamDepartment of Biomedical Science, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, Kepala Batas, Penang, 13200, Malaysia.
Nurul Izza IsmailSchool of Biological Sciences, Universiti Sains Malaysia, Gelugor, Penang, 11800, Malaysia.
Afzal Izzaz ZahariSchool of Management, Universiti Sains Malaysia, Gelugor, Penang, 11800, Malaysia.
Nor Azlin GhazaliSchool of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal, Penang, 14300, Malaysia.
Norfarazieda HassanDepartment of Biomedical Science, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, Kepala Batas, Penang, 13200, Malaysia. fara.hassan@usm.my.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer remains a leading cause of mortality worldwide, necessitating advances in diagnostic technologies to improve early detection and patient outcomes. Traditional methods such as imaging and biopsy are effective and widely used clinically but are often limited by invasiveness, high cost, and lack of sensitivity for early-stage cancer. In response, biosensors have emerged as promising tools capable of detecting cancer-associated biomarkers including circulating tumor DNA, microRNAs, exosomes, and tumor-associated proteins. These devices are noninvasive, rapid, highly sensitive, and offer real-time monitoring capabilities. This review bridges engineering principles with clinical readiness, covering basic principles, material advances, and evidence supporting clinical use across electrochemical, optical, piezoelectric, and field-effect transistor (FET)-based biosensors. We highlight recent breakthroughs in nanomaterials, amplification strategies, device miniaturization, and wearable biosensor platforms. Despite their advances, current biosensors face challenges in terms of sensitivity, nonspecific binding and signal drift, standardization, manufacturing scalability, production costs, regulatory validation and real-world reproducibility, which restrict their widespread clinical application. This review also discusses the integration between biosensors, artificial intelligence, and liquid biopsy workflows that could pave the way for point-of-care testing and personalized cancer management.

Indexed as

BiosensorsCancerElectrochemicalFETOpticalPiezoelectric

Identifiers

PMID41469748
PMCPMC12784512

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.