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Macrophage marker gene-driven prognostic models for esophageal cancer: integrating multi-omics analysis and therapeutic strategies

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机构: [1]Guangzhou Med Univ, Affiliated Qingyuan Hosp, Qingyuan Peoples Hosp, Dept Oncol, Qingyuan, Peoples R China [2]Sichuan Univ, West China Hosp, Dept Urol, Chengdu, Peoples R China [3]Sichuan Univ, West China Hosp, Inst Urol, Chengdu, Peoples R China [4]Sichuan Univ, West China Hosp, Natl Clin Res Ctr Geriatr, Chengdu, Peoples R China [5]Kunming Med Univ, Affiliated Hosp 1, Dept Urol, Kunming, Peoples R China [6]Guangdong Med Univ, Dongguan, Peoples R China [7]Guangzhou Med Univ, Affiliated Qingyuan Hosp, Qingyuan Peoples Hosp, Dept Orthoped, Qingyuan, Peoples R China
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关键词: Esophageal cancer Macrophages Prognostic model Single-cell RNA sequencing

摘要:
By integrating single-cell and bulk RNA-sequencing data for esophageal cancer (ESCA), we developed and validated a seven-macrophage-gene prognostic signature (FCN1, SCARB2, ATF5, PHLDA2, GLIPR1, CHORDC1, and BCKDK). This signature effectively stratified patients into high- and low-risk groups with significantly different overall survival, achieving area under the curve (AUC) values greater than 0.7 for 1-, 2-, and 3-year survival prediction. A high-risk status correlated with an immunosuppressive tumor microenvironment, characterized by lower infiltration of B cells and CD8 + T cells, and was associated with reduced sensitivity to multiple chemotherapeutic agents, including Cisplatin and 5-Fluorouracil. Conversely, a low-risk status was linked to greater immune cell infiltration and higher predicted chemosensitivity. At the single-cell level, pseudotime analysis revealed that macrophage maturation significantly correlated with a decreasing risk score, suggesting that mature macrophages may contribute to a favorable prognosis. Furthermore, cell communication analysis identified high-risk macrophages as dominant drivers of a pro-tumorigenic microenvironment via signaling pathways, such as SPP1 and complement. In conclusion, this seven-gene signature is a robust prognostic biomarker that offers a new strategy for personalized risk assessment and treatment selection in ESCA.

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出版当年[2025]版:
大类 | 4 区 生物学
小类 | 4 区 生物工程与应用微生物
最新[2025]版:
大类 | 4 区 生物学
小类 | 4 区 生物工程与应用微生物
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出版当年[2024]版:
Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
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Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

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第一作者机构: [1]Guangzhou Med Univ, Affiliated Qingyuan Hosp, Qingyuan Peoples Hosp, Dept Oncol, Qingyuan, Peoples R China
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