Evidence map›Paper›PMID 41456229›Full record

ArticleDiscover oncology2025

Single cell analysis reveals cancer associated fibroblast subtypes as prognostic markers and therapeutic targets in gastric cancer.

Dazhou Li, Guihui Tong, Wenqing Huang

Abstract read
In one paragraph

Article in Discover oncology, 2025. 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Dazhou LiDepartment of Pathology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510163, China.
Guihui TongDepartment of Pathology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510163, China.
Wenqing HuangDepartment of Pathology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China. dazhoulee@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesCancer-associated fibroblasts (CAFs) play a pivotal role in Gastric cancer (GC) progression and immune modulation. This study aimed to identify CAF subtypes using single-cell analysis and evaluate their prognostic and therapeutic relevance in GC.

methodsCAF gene sets were derived from 13 single-cell datasets and quantified via ssGSEA in bulk transcriptomic cohorts (TCGA and GEO). Consensus clustering defined CAF-based subtypes. Immune infiltration was evaluated using CIBERSORT, xCell, MCPcounter, and ESTIMATE. Immunotherapy response was predicted using TIDE and ImmuCellAI. Chemotherapeutic sensitivity was assessed via PRISM, CTRP, and GDSC databases. Hub genes were identified by WGCNA, and a prognostic model was constructed and validated in external cohorts and at the single-cell level.

resultsTwo CAF subtypes, FA_H and FA_L, were identified. FA_H was associated with poor prognosis, higher M2 macrophage infiltration, and immunosuppressive pathways, while FA_L correlated with improved survival and stronger predicted response to immune checkpoint inhibitors. Dasatinib was predicted as a potential therapeutic agent specifically for FA_H subtype. A five-gene prognostic model (COL1A2, NDN, SPARC, VCAN, TCEAL7) showed consistent predictive performance across datasets. Functional validation confirmed upregulation of TCEAL7 in CAFs and its role in promoting GC cell invasion.

conclusionSingle-cell-based CAF subtyping defines clinically relevant heterogeneity in GC. The FA_H subtype may serve as both a prognostic biomarker and therapeutic target, particularly for dasatinib-based or immunomodulatory strategies.

Indexed as

Cancer-associated fibroblastsGastric cancerPrognostic modelSingle-cell RNA sequencingTumor microenvironment

Identifiers

PMID41456229
PMCPMC12858713

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