Evidence map›Paper›PMID 39881946›Full record

ArticleCancer management and research2025

Diagnostic Value of Glycosylated Extracellular Vesicle microRNAs in Gastric Cancer.

Shunda Wang, Cuidie Ma, Zhihua Ren, Yufei Zhang, Kun Hao, Chengxiu Liu, Lida Xu, Shun He, Jianwei Zhang

Abstract read
In one paragraph

Article in Cancer management and research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Novel Liquid Biopsy in Gastrointestinal Cancers.Journal of gastroenterology and hepatology · 2026
    Review
  4. 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

9 authors.

Shunda Wang *Department of Pancreatic and Gastric Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People's Republic of China.ORCID 0000-0002-3506-7948
Cuidie Ma *College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China.
Zhihua Ren *Department of General Surgery, Qilu Hospital Fo Shandong University, Jinan, 250012, People's Republic of China.
Yufei ZhangCollege of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China.
Kun HaoBeijing Hotgen Biotech Co., Ltd, Beijing, 102600, People's Republic of China.
Chengxiu LiuBeijing Hotgen Biotech Co., Ltd, Beijing, 102600, People's Republic of China.
Lida XuBeijing Hotgen Biotech Co., Ltd, Beijing, 102600, People's Republic of China.
Shun HeDepartment of Endoscopy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People's Republic of China.
Jianwei ZhangDepartment of Pancreatic and Gastric Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Early diagnosis is crucial for improving the prognosis of patients with gastric cancer (GC). However, the currently used biomarkers for diagnosing GC have limited sensitivity and specificity. This study aimed to develop a novel diagnostic model based on miRNAs from glycosylated extracellular vesicles and evaluate its effectiveness in diagnosing gastric cancer. Methods: GlyExo-capture technology was used to isolate glycosylated extracellular vesicles from serum samples. The signatures were screened in a discovery cohort of GC patients (n=55) and non-disease controls (n=46) using an integrated process, including high-throughput sequencing technology, screening using a complete bioinformatics algorithm, validation using RT-qPCR, and evaluation by constructing a diagnostic model. The diagnostic model was evaluated in an independent validation cohort (n=139). Results: We developed a diagnostic model for GC based on five miRNA pairs. This diagnostic model demonstrated high sensitivity, specificity, and stable performance in distinguishing GC patients from non-cancer controls with AUC of 0.930 in the independent validation cohort, particularly in differentiating early-stage GC from benign patients. The markers also showed excellent performance in indicating perineural invasion status and lymph node metastasis in the testing cohort. Discussion: The model demonstrated high sensitivity and specificity in diagnosing patients with GC, especially in differentiating early-stage GC from benign patients. The five miRNA pairs could also aid in making treatment decisions. Thus, miRNAs derived from glycosylated exosomes are promising biomarkers for cancer diagnosis.

Indexed as

biomarkerdiagnosisextracellular vesiclesgastric cancermicroRNAs

Identifiers

PMID39881946
PMCPMC11776422

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.