Evidence map›Paper›PMID 41602284›Full record

ReviewFrontiers in chemistry2025

Surface-enhanced Raman spectroscopy for label-free cancer liquid biopsy: from fundamentals to clinical analysis of biofluid.

Ming Chen, Mingjun Zhao, Yue Cai, Qiong Zhang, Zhenzhen Peng, Qiwen Li, Zhibin Wang

Abstract readReview
In one paragraph

Review in Frontiers in chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Beyond the Needle: Is Liquid Biopsy the Future of Veterinary Medicine?International journal of molecular sciences · 2026
    Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. 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

7 authors.

Ming Chen *Department of Nuclear Medicine, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Mingjun Zhao *Department of Nuclear Medicine, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Yue CaiDepartment of Nuclear Medicine, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Qiong ZhangDepartment of Nuclear Medicine, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Zhenzhen PengDepartment of Nuclear Medicine, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Qiwen LiDepartment of Nuclear Medicine, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
Zhibin WangDepartment of Bipharmaceutical Sciences, Faculty of Pharmaceutical Sciences, Shenzhen University of Advanced Technology, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer remains one of the major public health problems due to its high morbidity and mortality globally. Because metastasis is the major cause of cancer death, developing new approaches for early diagnosis is of paramount importance in this context. Surface-enhanced Raman scattering (SERS) has emerged as a cutting-edge analytical technique. SERS features an exceptional sensitivity and specificity, enabling rapid non-destructive detection of trace-level samples. Therefore, SERS technology is widely used across medical disciplines, particularly in cancer diagnosis for early-stage and non-invasive diagnostic evaluation. Using liquid biopsy with rich metabolic information, SERS has facilitated the identification, analysis, and progression monitoring of various cancers. In this review, we systematically summarize recent advances in label-free SERS-based cancer diagnostics. We first outline the fundamental principles of SERS, key substrate fabrication methodologies, and essential spectral analysis techniques. We then highlight the applications of label-free SERS in liquid biopsy using various biofluids, including blood, urine, saliva, and sweat. Finally, we discuss current challenges and future directions in this rapidly evolving field.

Indexed as

cancerclinical biofluidsdeep learninglabel-free detectionliquid biopsySERS

Identifiers

PMID41602284
PMCPMC12832981

What OpenQuestion 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 OpenQuestion graph.