Kong Deyu, Zhang Yiping, Jiang Linxin, Long Nana, Wang Chengcheng, Qiu Min
Department of Clinical Laboratory, The Second Affiliated Hospital of Chengdu Medical College, National Nuclear Corporation 416 Hospital, Chengdu, Sichuan, China.
Sichuan Integrative Medicine Hospital, 610041, Chengdu, Sichuan, China.
Sci Rep. 2025 Feb 1;15(1):3995. doi: 10.1038/s41598-025-88071-8.
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.
肝细胞癌(HCC)的进展与巨噬细胞的作用密切相关。本研究利用单细胞RNA测序和基因组分析来探索HCC中巨噬细胞的特征基因及其对患者预后的影响。我们从GEO数据库中的七个HCC样本获得了单细胞测序数据。通过主成分分析和t-SNE降维,我们鉴定出2000个高变基因,并对17个细胞簇进行了聚类和注释,揭示了482个巨噬细胞相关的特征基因。基于这些基因构建了一个LASSO回归模型来预测HCC患者的预后,在TCGA-LIHC队列中的验证表明模型具有准确性(1年、3年和5年生存率的AUC分别为0.78、0.72和0.71)。此外,高风险组患者的肿瘤干性评分升高,尽管在微卫星不稳定性(MSI)和肿瘤突变负担(TMB)评分方面未观察到显著差异。免疫相关分析显示,FCER1G在HCC中表达下调,且与凋亡和铁死亡等关键通路相关。FCER1G表达降低显著影响HCC细胞的增殖和迁移能力。我们的预后模型为HCC的精准治疗和免疫治疗提供了新的见解,对未来的临床应用具有重要意义。