This study aims to investigate metabolic reprogramming heterogeneity in hepatocellular carcinoma (HCC) cells and identify novel therapeutic targets for HCC treatment. Single-cell RNA sequencing data from public databases were used to analyze the TME of HCC and reveal the characteristics of different cell subsets, including mononuclear phagocytes, epithelial cells, endothelial cells, NK/T cells, B cells, and unknown cells. The analysis revealed that these cell subsets play their own unique roles in tumor progression and immune escape. Analysis of copy number variations (CNVs) was performed on tumor-derived epithelial cells, with the epithelial cells in Cluster 3 subgroup showing the highest CNV levels. Gene Ontology (GO) enrichment analysis revealed that these cell subsets were involved in a variety of biological processes such as immune response, cell communication, and metabolic pathways, which were consistent with their functional roles. Pseudotemporal analysis further delineated the malignant trajectory of HCC cells, with Cluster 3 exhibiting enhanced phosphatidylinositol metabolism, suggesting a critical role for metabolic reprogramming in tumor invasion and proliferation. Furthermore, a diagnostic model incorporating metabolic reprogramming-associated gene signatures was established, which effectively distinguished HCC from normal tissues. Among these signatures, splicing factor 3a subunit 3 (SF3A3) was identified as both diagnostic and independent prognostic biomarker. Mechanistically, SF3A3 knockdown in HCC cell lines significantly suppressed proliferation, migration, PI3K/AKT signaling, and EMT marker expression, thereby demonstrating its role in driving HCC aggressiveness. In conclusion, these findings elucidate novel molecular characteristics of HCC based on metabolic reprogramming, while establishing SF3A3 as a promising multi-faceted target for HCC diagnosis, prognostic assessment, and therapeutic intervention.
Exploring the level of metabolic reprogramming and the role of prognostic factor SF3A3 in hepatocellular carcinoma through integrated single-cell landscape analysis.
通过整合单细胞景观分析,探索代谢重编程水平以及预后因子SF3A3在肝细胞癌中的作用
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作者:Wei Wanshuo, Gan Yuan, Zhang Xindan, Chen Yumo, Huang Zengfeng, Wang Shuhan, Xie Xiaomei, Li Yongle, Qin Pengtao, Jiang Lihe
| 期刊: | PLoS One | 影响因子: | 2.600 |
| 时间: | 2025 | 起止号: | 2025 May 27; 20(5):e0323559 |
| doi: | 10.1371/journal.pone.0323559 | 研究方向: | 代谢、细胞生物学 |
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