Comprehensive analysis reveals the tumor suppressor role of macrophage signature gene FCER1G in hepatocellular carcinoma
Abstract Hepatocellular carcinoma (HCC) progression is closely linked to the role of macrophages. This study utilized single-cell RNA sequencing and genomic analysis to explore the characteristic genes of macrophages in HCC and their impact on patient prognosis. We obtained single-cell se-quencing d...
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Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-88071-8 |
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| author | Deyu Kong Yiping Zhang Linxin Jiang Nana Long Chengcheng Wang Min Qiu |
| author_facet | Deyu Kong Yiping Zhang Linxin Jiang Nana Long Chengcheng Wang Min Qiu |
| author_sort | Deyu Kong |
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| description | Abstract Hepatocellular carcinoma (HCC) progression is closely linked to the role of macrophages. This study utilized single-cell RNA sequencing and genomic analysis to explore the characteristic genes of macrophages in HCC and their impact on patient prognosis. We obtained single-cell se-quencing data from seven HCC samples in the GEO database. Through principal component analysis and t-SNE dimensionality reduction, we identified 2,000 highly variable genes and per-formed clustering and annotation of 17 cell clusters, revealing 482 macrophage-related feature genes. A LASSO regression model based on these genes was developed to predict the prognosis of HCC patients, with validation in the TCGA-LIHC cohort demonstrating model accuracy (AUC = 0.78, 0.72, 0.71 for 1-, 3-, and 5-year survival rates, respectively). Additionally, patients in the high-risk group exhibited elevated tumor stemness scores, although no significant differences were observed in microsatellite instability (MSI) and tumor mutational burden (TMB) scores. Immune-related analyses revealed that FCER1G expression was downregulated in HCC and was associated with key pathways such as apoptosis and ferroptosis. Reduced FCER1G expression significantly affected HCC cell proliferation and migration. Our prognostic model provides new insights into precision and immunotherapy for HCC and holds significant implications for future clinical applications. |
| format | Article |
| id | doaj-art-5e1c00a7313245a98a505b5ee2b254ef |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-5e1c00a7313245a98a505b5ee2b254ef2025-02-02T12:17:11ZengNature PortfolioScientific Reports2045-23222025-02-0115111410.1038/s41598-025-88071-8Comprehensive analysis reveals the tumor suppressor role of macrophage signature gene FCER1G in hepatocellular carcinomaDeyu Kong0Yiping Zhang1Linxin Jiang2Nana Long3Chengcheng Wang4Min Qiu5Department of Clinical Laboratory, The Second Affiliated Hospital of Chengdu Medical College, National Nuclear Corporation 416 HospitalDepartment of Clinical Laboratory, The Second Affiliated Hospital of Chengdu Medical College, National Nuclear Corporation 416 HospitalDepartment of Clinical Laboratory, The Second Affiliated Hospital of Chengdu Medical College, National Nuclear Corporation 416 HospitalSichuan Integrative Medicine HospitalSichuan Integrative Medicine HospitalSchool of Laboratory Medicine, Chengdu Medical CollegeAbstract Hepatocellular carcinoma (HCC) progression is closely linked to the role of macrophages. This study utilized single-cell RNA sequencing and genomic analysis to explore the characteristic genes of macrophages in HCC and their impact on patient prognosis. We obtained single-cell se-quencing data from seven HCC samples in the GEO database. Through principal component analysis and t-SNE dimensionality reduction, we identified 2,000 highly variable genes and per-formed clustering and annotation of 17 cell clusters, revealing 482 macrophage-related feature genes. A LASSO regression model based on these genes was developed to predict the prognosis of HCC patients, with validation in the TCGA-LIHC cohort demonstrating model accuracy (AUC = 0.78, 0.72, 0.71 for 1-, 3-, and 5-year survival rates, respectively). Additionally, patients in the high-risk group exhibited elevated tumor stemness scores, although no significant differences were observed in microsatellite instability (MSI) and tumor mutational burden (TMB) scores. Immune-related analyses revealed that FCER1G expression was downregulated in HCC and was associated with key pathways such as apoptosis and ferroptosis. Reduced FCER1G expression significantly affected HCC cell proliferation and migration. Our prognostic model provides new insights into precision and immunotherapy for HCC and holds significant implications for future clinical applications.https://doi.org/10.1038/s41598-025-88071-8Hepatocellular carcinomaSingle-cell RNA sequencingMacrophagesRisk scoring modelFCER1G |
| spellingShingle | Deyu Kong Yiping Zhang Linxin Jiang Nana Long Chengcheng Wang Min Qiu Comprehensive analysis reveals the tumor suppressor role of macrophage signature gene FCER1G in hepatocellular carcinoma Scientific Reports Hepatocellular carcinoma Single-cell RNA sequencing Macrophages Risk scoring model FCER1G |
| title | Comprehensive analysis reveals the tumor suppressor role of macrophage signature gene FCER1G in hepatocellular carcinoma |
| title_full | Comprehensive analysis reveals the tumor suppressor role of macrophage signature gene FCER1G in hepatocellular carcinoma |
| title_fullStr | Comprehensive analysis reveals the tumor suppressor role of macrophage signature gene FCER1G in hepatocellular carcinoma |
| title_full_unstemmed | Comprehensive analysis reveals the tumor suppressor role of macrophage signature gene FCER1G in hepatocellular carcinoma |
| title_short | Comprehensive analysis reveals the tumor suppressor role of macrophage signature gene FCER1G in hepatocellular carcinoma |
| title_sort | comprehensive analysis reveals the tumor suppressor role of macrophage signature gene fcer1g in hepatocellular carcinoma |
| topic | Hepatocellular carcinoma Single-cell RNA sequencing Macrophages Risk scoring model FCER1G |
| url | https://doi.org/10.1038/s41598-025-88071-8 |
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