ReviewBiosensors2025
Recent Advances in SAW Sensors for Detection of Cancer Biomarkers.
Review in Biosensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Nano-biosensors for circulating tumor markers: advancing liquid biopsy toward precision cancer diagnostics.Journal of cancer research and clinical oncology · 2026Review
- Olfactory Science and Technology in Prostate Cancer Diagnosis: From Invertebrate Models to Artificial Intelligence.Life (Basel, Switzerland) · 2026Review
- Biosensor technologies in cancer: tools for early detection and prognostic monitoring.Biomarker research · 2025Review
- CRISPR-based platforms for detecting tumor-associated genetic materials in clinical samples.Bioanalysis · 2025Review
- Different chromatographic techniques and recent advancements for biomedical and pharmaceutical applications.Northern clinics of Istanbul · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Surface acoustic wave (SAW) sensor technology is a promising approach to diagnosing cancer through the detection of cancer biomarkers due to its high sensitivity, potential label-free operation, and fast response times, and, fundamentally, because it is a non-invasive technique in comparison with the current traditional diagnostic techniques for cancer. This review focuses on this application, and for this purpose, the recent literature on cancer biomarkers detected by this advanced technology has been compiled, including that on volatile organic compounds (VOCs) from exhaled breath and larger biomolecules such as proteins, DNA, and microRNAs in body fluids, which demonstrates its great versatility. The conventional techniques for cancer biomarker detection in biofluids, such as ELISA, PCR, SPR, and UV absorbance, exhibit limitations including high costs, slow response times, a reduced sensitivity, the need for specialized instrumentation, and the requirement for highly trained personnel. Different SAW sensor configurations are discussed with attention paid to their specific properties, wave propagation modes, and suitability for different environments. Detailed studies are reviewed, highlighting biomarkers for lung, colorectal, prostate, breast, and ovarian cancer diagnostics, as well as the detection of circulating tumor cells and cancerous cell growth. This review identifies current challenges, including optimizing sensitivity, addressing environmental interferences, and the need for clinical validation. Finally, future research directions are proposed, emphasizing the use of VOC biomarkers and the integration of SAW technology into hybrid systems and microfluidic platforms to enable the creation of scalable, non-invasive diagnostic tools for the detection of cancer in early stages, and, in this way, to minimize the morbidity and mortality associated with this disease.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.