Evidence map›Paper›PMID 41225026›Full record

ArticleScientific reports2025

Cancer-associated fibroblast subtype and risk signature as predictors of prognosis and treatment effectiveness in gastric cancer.

Ruyue Chen, Zengwu Yao, Lixin Jiang, Jinchen Hu

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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.

Ruyue ChenDepartment of Gastrointestinal Surgery, Yantai Yuhuangding Hospital, Qingdao University, No. 20 Yuhuangding East Road, Zhifu District, Yantai, 264001, China.
Zengwu YaoDepartment of Gastrointestinal Surgery, Yantai Yuhuangding Hospital, Qingdao University, No. 20 Yuhuangding East Road, Zhifu District, Yantai, 264001, China.
Lixin JiangDepartment of Gastrointestinal Surgery, Yantai Yuhuangding Hospital, Qingdao University, No. 20 Yuhuangding East Road, Zhifu District, Yantai, 264001, China. jianglixin_1969@163.com.
Jinchen HuDepartment of Gastrointestinal Surgery, Yantai Yuhuangding Hospital, Qingdao University, No. 20 Yuhuangding East Road, Zhifu District, Yantai, 264001, China. hujinchen2000@163.com.

Funding

Shandong Province Medical and Health Technology Project 202304010040
6 · The paper itself

Abstract

Despite the persistent high incidence and mortality rates of gastric cancer, limited progress has been made in improving prognosis.cancer-associated fibroblasts (CAFs) hold promise as novel biomarkers, yet their specific roles and mechanisms in gastric cancer remain enigmatic. We utilized the TCGA-STAD dataset for model training and the GSE84433 dataset for validation to explore potential associations between cancer-associated fibroblasts (CAFs) and clinical outcomes in gastric cancer. Through consensus clustering, differential expression analysis, enrichment analysis, and immune infiltration assessment, Kaplan-Meier (KM) survival analysis, and TIMER database exploration, we examined the prognostic significance and underlying biological mechanisms of CAF-related genes in gastric cancer. A CAF risk model (CAF-RM) was developed to assess the correlation between risk scores and survival, drug sensitivity, and immune infiltration. The model was further validated through immunohistochemical (IHC) and immunofluorescence (IF) staining. Utilizing data from 42 CAF-related genes, consensus clustering identified two distinct patient subgroups, C1 and C2, with significant differences in survival, immune scores, and immune cell infiltration. A Cox-Lasso regression-derived CAF-RM accurately discriminated high-risk from low-risk gastric cancer patients, consistent with validation cohort results, IHC and IF staining. These findings suggest that CAFs play a role in the tumor immune microenvironment of gastric cancer and highlight the efficacy of CAF-RM in prognosis prediction. CAF subtypes associate with immune tumor microenvironment alterations in gastric cancer. The validated CAF risk model predicts patient survival, immune infiltration, and drug sensitivity, enhancing understanding of CAFs and guiding gastric cancer therapy.

Indexed as

Cancer-Associated FibroblastsStomach NeoplasmsBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMalePrognosisRisk FactorsTreatment OutcomeTumor MicroenvironmentBiomarkers, TumorCAFsGastric cancerImmunotherapyPrognosisSubtype

Identifiers

PMID41225026
PMCPMC12612168

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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.