Evidence map›Paper›PMID 42629612›Full record

ArticleJournal of gastroenterology and hepatology2026

Integrated Transcriptomic Analysis and Machine Learning Identify THY1 as a Key Regulator of Cancer-Associated Fibroblast Infiltration, Promoting Malignant Progression and Immune Escape in Gastric Cancer.

Sihui Hou, Mengzhu Sang, Yan Wang, Haosheng Que, Yi Liu, Manman Zhang

Abstract read
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Article in Journal of gastroenterology and hepatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Sihui HouDepartment of Gastroenterology, Xuzhou Central Hospital, Southeast University, Xuzhou, Jiangsu Province, China.
Mengzhu SangDepartment of Gastroenterology, Xuzhou Central Hospital, Southeast University, Xuzhou, Jiangsu Province, China.
Yan WangDepartment of Gastroenterology, Xuzhou Central Hospital, Southeast University, Xuzhou, Jiangsu Province, China.
Haosheng QueDepartment of Gastroenterology, Xuzhou Central Hospital, Southeast University, Xuzhou, Jiangsu Province, China.
Yi LiuDepartment of Gastroenterology, Xuzhou Central Hospital, Southeast University, Xuzhou, Jiangsu Province, China.ORCID https://orcid.org/0009-0009-4812-6968
Manman ZhangDepartment of Gastroenterology, Xuzhou Central Hospital, Southeast University, Xuzhou, Jiangsu Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHeterogeneity in cancer-associated fibroblast (CAF) infiltration within the tumor microenvironment is closely associated with gastric cancer progression and immune evasion; however, precise CAF-related diagnostic markers and actionable therapeutic targets remain scarce.

methodsWeighted gene coexpression network analysis (WGCNA) was employed to screen CAF-related coexpression modules. Gastric cancer samples were stratified into molecular subtypes via nonnegative matrix factorization (NMF). Core genes were screened using LASSO regression, SVM-RFE, and RF. Functional assays (Western blot, CCK-8, colony formation, Transwell, tube formation, ELISA, and flow cytometry) were conducted to assess THY1's role in CAF activation and effects on tumor/immune cells.

resultsWGCNA identified modules correlated with CAF abundance, yielding 417 hub genes. NMF classified gastric cancer into two molecular subtypes with distinct differences in immune microenvironment, drug sensitivity, and pathway activity. Four core genes (THY1, VASH1, CHSY3, and CDH11) were consistently identified. The nomogram model demonstrated strong diagnostic performance for discriminating gastric cancer from normal tissue (AUC = 0.907 in the discovery cohort and > 0.85 in the validation cohort), with calibration and decision curve analysis (DCA) supporting clinical utility. THY1 knockdown in CAFs downregulated activation markers. Conditioned medium of THY1-deficient CAFs reduced cell proliferation and invasion, inhibited HUVEC tube formation, enhanced CD8

conclusionCAF-derived THY1 promoted malignant phenotypes and immune evasion by modulating CAF function and paracrine cross talk with tumor cells, endothelial cells, and CD8

Indexed as

Cancer-Associated FibroblastsGene Expression ProfilingMachine LearningStomach NeoplasmsThy-1 AntigensTranscriptomeTumor EscapeDisease ProgressionHumansTumor MicroenvironmentThy-1 Antigenscancer‐associated fibroblastsgastric cancerimmune evasionmachine learningsingle‐cell RNA sequencingthy‐1 cell surface antigentumor microenvironment

Identifiers

PMID42629612
PMCPMC13534242

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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.