Li Jiashuo, Liu Zhenyi, Zhang Gongming, Yin Xue, Yuan Xiaoxue, Xie Wen, Ding Xiaoyan
National Center for Infectious Diseases, Beijing Di'tan Hospital, Capital Medical University, Beijing, China.
Department of Interventional Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Front Oncol. 2025 Mar 18;15:1570647. doi: 10.3389/fonc.2025.1570647. eCollection 2025.
The tumor microenvironment (TME) plays a critical role in the development, progression, and clinical outcomes of hepatocellular carcinoma (HCC). Despite the critical role of natural killer (NK) cells in tumor immunity, there is limited research on their status within the tumor microenvironment of HCC. In this study, single-cell RNA sequencing (scRNA-seq) analysis of HCC datasets was performed to identify potential biomarkers and investigate the involvement of natural killer (NK) cells in the TME.
Single-cell RNA sequencing (scRNA-seq) data were extracted from the GSE149614 dataset and processed for quality control using the "Seurat" package. HCC subtypes from the TCGA dataset were classified through consensus clustering based on differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) was employed to construct co-expression networks. Furthermore, univariate and multivariate Cox regression analyses were conducted to identify variables linked to overall survival. The single-sample gene set enrichment analysis (ssGSEA) was used to analyze immune cells and the screened genes.
A total of 715 DEGs from GSE149614 and 864 DEGs from TCGA were identified, with 25 overlapping DEGs found between the two datasets. A prognostic risk score model based on two genes was then established. Significant differences in immune cell infiltration were observed between high-risk and low-risk groups. Immunohistochemistry showed that HRG expression was decreased in HCC compared to normal tissues, whereas TUBA1B expression was elevated in HCC.
Our study identified a two-gene prognostic signature based on NK cell markers and highlighted their role in the TME, which may offer novel insights in immunotherapy strategies. Additionally, we developed an accurate and reliable prognostic model, combining clinical factors to aid clinicians in decision-making.
肿瘤微环境（TME）在肝细胞癌（HCC）的发生、发展及临床结局中起关键作用。尽管自然杀伤（NK）细胞在肿瘤免疫中发挥着关键作用，但关于其在HCC肿瘤微环境中的状态的研究却很有限。在本研究中，对HCC数据集进行了单细胞RNA测序（scRNA-seq）分析，以识别潜在的生物标志物，并研究自然杀伤（NK）细胞在TME中的作用。
从GSE149614数据集中提取单细胞RNA测序（scRNA-seq）数据，并使用“Seurat”软件包进行质量控制处理。基于差异表达基因（DEG），通过共识聚类对TCGA数据集中的HCC亚型进行分类。采用加权基因共表达网络分析（WGCNA）构建共表达网络。此外，进行单变量和多变量Cox回归分析，以识别与总生存期相关的变量。使用单样本基因集富集分析（ssGSEA）分析免疫细胞和筛选出的基因。
共鉴定出GSE149614中的715个DEG和TCGA中的864个DEG，两个数据集之间发现了25个重叠的DEG。然后建立了基于两个基因的预后风险评分模型。在高风险组和低风险组之间观察到免疫细胞浸润存在显著差异。免疫组织化学显示HCC中HRG表达低于正常组织，而TUBA1B表达在HCC中升高。
我们的研究基于NK细胞标志物鉴定了一个双基因预后特征，并强调了它们在TME中的作用，这可能为免疫治疗策略提供新的见解。此外，我们开发了一个准确可靠的预后模型，结合临床因素以帮助临床医生进行决策。
