Evidence map›Paper›PMID 41367615›Full record

ArticleFrontiers in genetics2025

Revealing the key modules and potential prognostic markers of gastric cancer transformation based on weighted gene co-expression networks.

Heng Li, Wen Li, Zhen Yang, Haiyu Liu, Xiaoping Zhang, Yufeng Zhao, Hao Gu

Abstract read
In one paragraph

Article in Frontiers in genetics, 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.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Heng Li *Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Wen Li *School of Pharmacy, Lanzhou University, Lanzhou, China.
Zhen YangTianjin University of Traditional Chinese Medicine, Tianjin, China.
Haiyu LiuData Center of Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Xiaoping ZhangData Center of Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Yufeng ZhaoData Center of Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Hao GuData Center of Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aims to identify key modules and targets during the transition from gastric precancerous lesions to gastric cancer by performing weighted gene co-expression network analysis (WGCNA) on gene microarray datasets from the Gene Expression Omnibus (GEO) database containing gastritis, gastric cancer and precancerous lesions, providing insights for early intervention in gastric cancer. Methods: Transcriptomic data from precancerous lesions (including low-grade and high-grade intraepithelial neoplasia) and early gastric cancer were analyzed using differential gene analysis, WGCNA, and survival analysis. Critical modules and genes associated with disease progression were identified. The prognostic value and expression changes of these genes were evaluated, and their expression patterns across disease states were validated in external datasets to confirm key genes involved in the inflammation-cancer transformation into gastric cancer. Results: WGCNA identified four key modules: pink, purple, red, and magenta. The first three modules were most strongly associated with low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia, and early gastric cancer, respectively, while magenta was linked to all three stages. Functional analysis reveals: Pink module: Enriched in inflammation-related pathways. Purple module: Involved in chemical carcinogenesis and beta-alanine metabolism. Red module: Associated with immune response and inflammation, participating in NF-kappa B and Toll-like receptor signaling pathways. Magenta module: Linked to complement activation and immune response, enriched in cytokine-cytokine receptor interaction and chemokine signaling pathways. Core genes are filtered based on gene significance (GS > 0.2) and module membership (MM > 0.8). Among 20 shared core genes across disease stages, 13 genes (e.g., Conclusion: WGCNA reveals modules associated with gastric precancerous lesions and cancer progression.

Indexed as

gastric cancerkey genekey moduleprecancerous lesions of the stomachWGCNA

Identifiers

PMID41367615
PMCPMC12685459

What Socratic holds

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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 Socratic graph.