Identification of prognostic biomarkers related to epithelial-mesenchymal transition and anoikis in hepatocellular carcinoma using transcriptomics and single-cell sequencing
BackgroundEpithelial-mesenchymal transition (EMT) and anoikis are critically associated with hepatocellular carcinoma (HCC). However, the precise mechanisms underlying their roles in HCC remain unclear. This study aims to explore the involvement of EMT-related genes (EMTRGs) and anoikis-related gene...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Cell and Developmental Biology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcell.2025.1600546/full |
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| author | Maobing Wang Lu Cheng Lu Cheng Lu Cheng Lu Cheng Kuo Qi Kuo Qi Kuo Qi Kuo Qi Haiping Wang Haiping Wang Haiping Wang Haiping Wang Xun Li Xun Li Xun Li Xun Li |
| author_facet | Maobing Wang Lu Cheng Lu Cheng Lu Cheng Lu Cheng Kuo Qi Kuo Qi Kuo Qi Kuo Qi Haiping Wang Haiping Wang Haiping Wang Haiping Wang Xun Li Xun Li Xun Li Xun Li |
| author_sort | Maobing Wang |
| collection | DOAJ |
| description | BackgroundEpithelial-mesenchymal transition (EMT) and anoikis are critically associated with hepatocellular carcinoma (HCC). However, the precise mechanisms underlying their roles in HCC remain unclear. This study aims to explore the involvement of EMT-related genes (EMTRGs) and anoikis-related genes (ARGs) in HCC.MethodsData from TCGA-HCC, ICGC-LIPI - JP, GSE149614, EMTRGs and ARGs were utilised in this study. It utilised single-cell RNA sequencing for cell sorting. Biomarkers were identified through analyses such as differential expression analysis and weighted gene co-expression network analysis (WGCNA). The risk model and nomogram were constructed based on biomarkers. Subsequently, the potential functions of biomarkers were explored through methods such as enrichment analysis and immune microenvironment analysis. Finally, to confirm the expression of these biomarkers in different prognostic groups, gene expression levels were quantified using real-time quantitative polymerase chain reaction (RT-qPCR).ResultsLAMA4, C7, KPNA2, STMN1, and SF3B4 were identified as biomarkers. The risk score emerged as an independent prognostic factor for patients with HCC. The nomogram showed that these five biomarkers had good predictive ability for the 1-, 3-, and 5-year survival rates of HCC patients. Drug sensitivity analysis revealed significant associations between the IC50 values of 23 drugs and risk scores. In the GSE149614 dataset, most biomarkers were predominantly expressed in stromal cells (endothelial cells and fibroblasts). In TCGA-HCC, all genes, except C7, were upregulated in the HCC samples. RT-qPCR analysis revealed statistically significant upregulation of STMN1 and SF3B4 transcripts in the HCC group, consistent with TCGA-HCC dataset.ConclusionThis study identified five EMTRGs and ARGs (LAMA4, C7, KPNA2, STMN1, and SF3B4) as biomarkers of HCC, offering new insights for further research in HCC pathogenesis. |
| format | Article |
| id | doaj-art-8af73dbb1db741f28449e2e1fd0c0680 |
| institution | OA Journals |
| issn | 2296-634X |
| language | English |
| publishDate | 2025-06-01 |
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| spelling | doaj-art-8af73dbb1db741f28449e2e1fd0c06802025-08-20T02:35:57ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2025-06-011310.3389/fcell.2025.16005461600546Identification of prognostic biomarkers related to epithelial-mesenchymal transition and anoikis in hepatocellular carcinoma using transcriptomics and single-cell sequencingMaobing Wang0Lu Cheng1Lu Cheng2Lu Cheng3Lu Cheng4Kuo Qi5Kuo Qi6Kuo Qi7Kuo Qi8Haiping Wang9Haiping Wang10Haiping Wang11Haiping Wang12Xun Li13Xun Li14Xun Li15Xun Li16The First School of Clinical Medicine, Lanzhou University, Lanzhou, ChinaDepartment of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, ChinaGansu Provincial Key Laboratory of Biotherapy and Regenerative Medicine, Lanzhou, Gansu, ChinaGansu Institute of Hepatobiliary and Pancreatic Surgery, Lanzhou, Gansu, ChinaGansu Province General Surgery Clinical Medical Research Center, Lanzhou, Gansu, ChinaDepartment of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, ChinaGansu Provincial Key Laboratory of Biotherapy and Regenerative Medicine, Lanzhou, Gansu, ChinaGansu Institute of Hepatobiliary and Pancreatic Surgery, Lanzhou, Gansu, ChinaGansu Province General Surgery Clinical Medical Research Center, Lanzhou, Gansu, ChinaDepartment of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, ChinaGansu Provincial Key Laboratory of Biotherapy and Regenerative Medicine, Lanzhou, Gansu, ChinaGansu Institute of Hepatobiliary and Pancreatic Surgery, Lanzhou, Gansu, ChinaGansu Province General Surgery Clinical Medical Research Center, Lanzhou, Gansu, ChinaDepartment of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, ChinaGansu Provincial Key Laboratory of Biotherapy and Regenerative Medicine, Lanzhou, Gansu, ChinaGansu Institute of Hepatobiliary and Pancreatic Surgery, Lanzhou, Gansu, ChinaGansu Province General Surgery Clinical Medical Research Center, Lanzhou, Gansu, ChinaBackgroundEpithelial-mesenchymal transition (EMT) and anoikis are critically associated with hepatocellular carcinoma (HCC). However, the precise mechanisms underlying their roles in HCC remain unclear. This study aims to explore the involvement of EMT-related genes (EMTRGs) and anoikis-related genes (ARGs) in HCC.MethodsData from TCGA-HCC, ICGC-LIPI - JP, GSE149614, EMTRGs and ARGs were utilised in this study. It utilised single-cell RNA sequencing for cell sorting. Biomarkers were identified through analyses such as differential expression analysis and weighted gene co-expression network analysis (WGCNA). The risk model and nomogram were constructed based on biomarkers. Subsequently, the potential functions of biomarkers were explored through methods such as enrichment analysis and immune microenvironment analysis. Finally, to confirm the expression of these biomarkers in different prognostic groups, gene expression levels were quantified using real-time quantitative polymerase chain reaction (RT-qPCR).ResultsLAMA4, C7, KPNA2, STMN1, and SF3B4 were identified as biomarkers. The risk score emerged as an independent prognostic factor for patients with HCC. The nomogram showed that these five biomarkers had good predictive ability for the 1-, 3-, and 5-year survival rates of HCC patients. Drug sensitivity analysis revealed significant associations between the IC50 values of 23 drugs and risk scores. In the GSE149614 dataset, most biomarkers were predominantly expressed in stromal cells (endothelial cells and fibroblasts). In TCGA-HCC, all genes, except C7, were upregulated in the HCC samples. RT-qPCR analysis revealed statistically significant upregulation of STMN1 and SF3B4 transcripts in the HCC group, consistent with TCGA-HCC dataset.ConclusionThis study identified five EMTRGs and ARGs (LAMA4, C7, KPNA2, STMN1, and SF3B4) as biomarkers of HCC, offering new insights for further research in HCC pathogenesis.https://www.frontiersin.org/articles/10.3389/fcell.2025.1600546/fullhepatocellular carcinomaepithelial mesenchymal transitionanoikissingle-cell RNA sequencingbiomarkers |
| spellingShingle | Maobing Wang Lu Cheng Lu Cheng Lu Cheng Lu Cheng Kuo Qi Kuo Qi Kuo Qi Kuo Qi Haiping Wang Haiping Wang Haiping Wang Haiping Wang Xun Li Xun Li Xun Li Xun Li Identification of prognostic biomarkers related to epithelial-mesenchymal transition and anoikis in hepatocellular carcinoma using transcriptomics and single-cell sequencing Frontiers in Cell and Developmental Biology hepatocellular carcinoma epithelial mesenchymal transition anoikis single-cell RNA sequencing biomarkers |
| title | Identification of prognostic biomarkers related to epithelial-mesenchymal transition and anoikis in hepatocellular carcinoma using transcriptomics and single-cell sequencing |
| title_full | Identification of prognostic biomarkers related to epithelial-mesenchymal transition and anoikis in hepatocellular carcinoma using transcriptomics and single-cell sequencing |
| title_fullStr | Identification of prognostic biomarkers related to epithelial-mesenchymal transition and anoikis in hepatocellular carcinoma using transcriptomics and single-cell sequencing |
| title_full_unstemmed | Identification of prognostic biomarkers related to epithelial-mesenchymal transition and anoikis in hepatocellular carcinoma using transcriptomics and single-cell sequencing |
| title_short | Identification of prognostic biomarkers related to epithelial-mesenchymal transition and anoikis in hepatocellular carcinoma using transcriptomics and single-cell sequencing |
| title_sort | identification of prognostic biomarkers related to epithelial mesenchymal transition and anoikis in hepatocellular carcinoma using transcriptomics and single cell sequencing |
| topic | hepatocellular carcinoma epithelial mesenchymal transition anoikis single-cell RNA sequencing biomarkers |
| url | https://www.frontiersin.org/articles/10.3389/fcell.2025.1600546/full |
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