Evidence map›Paper›PMID 40514731›Full record

ReviewEuropean journal of medical research2025

Advances in the application of extracellular vesicles in precise diagnosis of pancreatic cancer.

Haiyang Yu, Congling Xin, Yu Zhou, Xiaoyi Ding

Abstract readReview
In one paragraph

Review in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

4 authors.

Haiyang Yu *Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Congling Xin *Department of Gynecology, Fudan University Shanghai Cancer Center Minhang District, Shanghai, 200240, China.
Yu ZhouDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China. zy12534@rjh.com.cn.
Xiaoyi DingDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China. dxy10456@rjh.com.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer is a highly malignant tumor with poor prognosis, emphasizing the need for accurate early diagnosis. EVs, as mediators of intercellular communication, carry DNA, RNA, and proteins that show differential but not tumor-specific expression patterns in pancreatic cancer. Studies have shown that combining RNA markers in EVs (such as miRNA, circRNA, and lncRNA) with serum CA 19-9 testing can significantly enhance diagnostic accuracy for pancreatic cancer. EV-associated proteins have exhibited favorable diagnostic performance in early-stage pancreatic cancer in preliminary studies, though their clinical applicability remains to be further validated. Furthermore, mutations in KRAS, TP53, and SMAD4 genes within EVs offer a promising avenue for non-invasive liquid biopsy. However, challenges such as standardization, low sensitivity, and specificity still hinder the clinical application of EVs. Future research should focus on strategies including multi-omics integration, AI-assisted analysis, multi-marker combined detection, and large-scale clinical validation to further improve the diagnostic capability for pancreatic cancer. Overcoming these obstacles may position EVs as a vital tool in the diagnosis of pancreatic cancer.

Indexed as

Biomarkers, TumorExtracellular VesiclesPancreatic NeoplasmsHumansLiquid BiopsyBiomarkers, TumorDiagnosisExtracellular vesiclesPancreatic cancer

Identifiers

PMID40514731
PMCPMC12164127

What Socratic 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 Socratic graph.