Evidence map›Paper›PMID 42326762›Full record

ArticleInternational journal of genomics2026

Exosome-Related Gene Signature Predicts Prognosis and Immunotherapy in Gastric Cancer.

Qunru Jiao, Rui Zhang, Yingyun Guo, Xiulan Peng, Longshu Zhou

Abstract read
In one paragraph

Article in International journal of genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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.

Qunru JiaoDepartment of Rehabilitation, The Second Affiliated Hospital of Jianghan University, Wuhan, Hubei, China.
Rui ZhangDepartment of Pharmacy, The Second People's Hospital of Fuyang City, Fuyang, Anhui, China.
Yingyun GuoDepartment of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China, rmhospital.com.
Xiulan PengDepartment of Oncology, The Second Affiliated Hospital of Jianghan University, Wuhan, Hubei, China.ORCID https://orcid.org/0000-0001-8336-4253
Longshu ZhouDepartment of Cardiothoracic Surgery, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, Hubei, China, hbmu.edu.cn.ORCID https://orcid.org/0009-0000-3068-1001

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exosomes play a crucial role in tumor progression. However, reliable exosome-related biomarkers for predicting prognosis in gastric cancer (GC) remain scarce. This study is aimed at developing an exosome-related gene risk signature (ERGRS) to predict the survival outcomes and immunotherapy sensitivity in GC patients. RNA sequencing data from exoRbase and TCGA datasets were analyzed to identify differentially expressed exosome-related genes associated with survival in GC. A multivariate Cox regression model was used to construct the ERGRS and a prognostic nomogram. The ERGRS's predictive performance was assessed using the Kaplan-Meier and receiver operating characteristic (ROC) curve analyses in both training and validation datasets. Furthermore, the relationship between the ERGRS risk score and clinical features, copy number variation, and immunotherapy sensitivity was explored through data mining. Western blotting was performed to validate protein expression levels of key exosome-related genes in GC tissues. Four exosome-related genes-TRAF2, ASCL2, NOX4, and MMRN1-were identified as independent prognostic factors. GC Patients with low-risk scores showed significantly better survival outcomes. Univariate and multivariate Cox regression analyses confirmed the ERGRS as an independent predictor of survival in GC. A prognostic nomogram incorporating risk score, age, and tumor stage was developed to effectively predict patient survival. Immune checkpoint analysis suggested that patients with low-risk scores may respond better to immunotherapy. The ERGRS represents a promising tool for prognostic prediction and guides the clinical care of GC patients.

Indexed as

exosomesgastric cancerimmune infiltrationnomogramprognostic signature

Identifiers

PMID42326762
PMCPMC13280462

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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.