Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma
Abstract Hepatocellular carcinoma (HCC) is a predominant cause of cancer-related mortality globally, noted for its propensity towards late-stage diagnosis and scarcity of effective treatment modalities. The process of metabolic reprogramming, with a specific emphasis on lipid metabolism, is instrume...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-025-85506-0 |
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| author | Hua Dai Xin Tao Yuansen Shu Fanrong Liu Xiaoping Cheng Xiushen Li Bairui Shu Hongcheng Luo XuXiang Chen Zhaorui Cheng |
| author_facet | Hua Dai Xin Tao Yuansen Shu Fanrong Liu Xiaoping Cheng Xiushen Li Bairui Shu Hongcheng Luo XuXiang Chen Zhaorui Cheng |
| author_sort | Hua Dai |
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| description | Abstract Hepatocellular carcinoma (HCC) is a predominant cause of cancer-related mortality globally, noted for its propensity towards late-stage diagnosis and scarcity of effective treatment modalities. The process of metabolic reprogramming, with a specific emphasis on lipid metabolism, is instrumental in the progression of HCC. Nevertheless, the precise mechanisms through which lipid metabolism impacts HCC and its viability as a therapeutic target have yet to be fully elucidated. In the current investigation, single-cell RNA sequencing in conjunction with weighted gene co-expression network analysis (WGCNA) was utilized to delineate lipid metabolism-related genes correlated with the prognostic outcomes of hepatocellular carcinoma (HCC). Data procurement encompassed transcriptomic and clinical datasets from HCC patients, sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories. Subsequent to this, consensus clustering analysis was implemented to stratify patients into distinct subgroups, contingent upon the expression patterns of lipid metabolism genes. Further analytical procedures involved functional enrichment analysis, evaluation of immune infiltration, and examination of the mutation landscape.PTGES3 was identified as a pivotal gene associated with lipid metabolism. Subsequent to its identification, cellular communication analysis was employed to assess the immunological attributes of PTGES3 within the tumor microenvironment. The functional role of PTGES3 was further corroborated through molecular docking simulations and in vitro experimental assays. We identified 27 genes associated with lipid metabolism, 18 of which exhibited significant correlation with overall survival in HCC patients. PTGES3 emerged as a central gene, demonstrating a robust association with immune cell infiltration and unfavorable prognosis. Cellular communication analysis revealed that PTGES3 exhibits the highest communication intensity with T cells, modulating the tumor microenvironment by potentiating the FN1/CD44 + MDK/NCL signaling pathway. Elevated expression of PTGES3 was linked to immunosuppressive cascades, diminished responsiveness to immunotherapy, and inferior overall survival outcomes. Molecular docking analysis indicated that etoposide, methotrexate, and doxorubicin could effectively bind to PTGES3. In vitro experiments confirmed that PTGES3 knockdown significantly impaired the proliferation, invasion, and migration of HCC cells. This study highlights the pivotal role of lipid metabolism in HCC progression and identifies PTGES3 as a potential prognostic biomarker and therapeutic target. These findings offer new insights into the development of targeted therapies for HCC, particularly in patients with high PTGES3 expression. |
| format | Article |
| id | doaj-art-6c280cd6a3b44f898333902910089390 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-6c280cd6a3b44f8983339029100893902025-01-19T12:23:25ZengNature PortfolioScientific Reports2045-23222025-01-0115112310.1038/s41598-025-85506-0Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinomaHua Dai0Xin Tao1Yuansen Shu2Fanrong Liu3Xiaoping Cheng4Xiushen Li5Bairui Shu6Hongcheng Luo7XuXiang Chen8Zhaorui Cheng9The First Affiliated Hospital, Jiangxi Medical College, Nanchang UniversityThe Second Affiliated Hospital, Jiangxi Medical College, Nanchang UniversityDepartment of Emergency, the Eighth Affiliated Hospital of Sun Yat-sen UniversityThe Second Affiliated Hospital, Jiangxi Medical College, Nanchang UniversityThe First Affiliated Hospital, Jiangxi Medical College, Nanchang UniversityDepartment of Traditional Chinese Medicine, Jiangxi Provincial Maternal and Child Health HospitalZhongshan Medical College, Sun Yat sen UniversityDepartment of Urology, The Eighth Affiliated Hospital of Sun Yat-sen UniversityDepartment of Emergency, the Eighth Affiliated Hospital of Sun Yat-sen UniversityDepartment of Emergency, the Eighth Affiliated Hospital of Sun Yat-sen UniversityAbstract Hepatocellular carcinoma (HCC) is a predominant cause of cancer-related mortality globally, noted for its propensity towards late-stage diagnosis and scarcity of effective treatment modalities. The process of metabolic reprogramming, with a specific emphasis on lipid metabolism, is instrumental in the progression of HCC. Nevertheless, the precise mechanisms through which lipid metabolism impacts HCC and its viability as a therapeutic target have yet to be fully elucidated. In the current investigation, single-cell RNA sequencing in conjunction with weighted gene co-expression network analysis (WGCNA) was utilized to delineate lipid metabolism-related genes correlated with the prognostic outcomes of hepatocellular carcinoma (HCC). Data procurement encompassed transcriptomic and clinical datasets from HCC patients, sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories. Subsequent to this, consensus clustering analysis was implemented to stratify patients into distinct subgroups, contingent upon the expression patterns of lipid metabolism genes. Further analytical procedures involved functional enrichment analysis, evaluation of immune infiltration, and examination of the mutation landscape.PTGES3 was identified as a pivotal gene associated with lipid metabolism. Subsequent to its identification, cellular communication analysis was employed to assess the immunological attributes of PTGES3 within the tumor microenvironment. The functional role of PTGES3 was further corroborated through molecular docking simulations and in vitro experimental assays. We identified 27 genes associated with lipid metabolism, 18 of which exhibited significant correlation with overall survival in HCC patients. PTGES3 emerged as a central gene, demonstrating a robust association with immune cell infiltration and unfavorable prognosis. Cellular communication analysis revealed that PTGES3 exhibits the highest communication intensity with T cells, modulating the tumor microenvironment by potentiating the FN1/CD44 + MDK/NCL signaling pathway. Elevated expression of PTGES3 was linked to immunosuppressive cascades, diminished responsiveness to immunotherapy, and inferior overall survival outcomes. Molecular docking analysis indicated that etoposide, methotrexate, and doxorubicin could effectively bind to PTGES3. In vitro experiments confirmed that PTGES3 knockdown significantly impaired the proliferation, invasion, and migration of HCC cells. This study highlights the pivotal role of lipid metabolism in HCC progression and identifies PTGES3 as a potential prognostic biomarker and therapeutic target. These findings offer new insights into the development of targeted therapies for HCC, particularly in patients with high PTGES3 expression.https://doi.org/10.1038/s41598-025-85506-0Hepatocellular carcinomaLipid metabolismPTGES3Single-cell RNA sequencingImmunotherapyMolecular docking |
| spellingShingle | Hua Dai Xin Tao Yuansen Shu Fanrong Liu Xiaoping Cheng Xiushen Li Bairui Shu Hongcheng Luo XuXiang Chen Zhaorui Cheng Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma Scientific Reports Hepatocellular carcinoma Lipid metabolism PTGES3 Single-cell RNA sequencing Immunotherapy Molecular docking |
| title | Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma |
| title_full | Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma |
| title_fullStr | Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma |
| title_full_unstemmed | Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma |
| title_short | Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma |
| title_sort | integrating single cell rna seq and bulk rna seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma |
| topic | Hepatocellular carcinoma Lipid metabolism PTGES3 Single-cell RNA sequencing Immunotherapy Molecular docking |
| url | https://doi.org/10.1038/s41598-025-85506-0 |
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