Wu Yinbing, Peng Huanjun, Chen Guangkang, Tu Yinuo, Yu Xinpei
Department of Hepatobiliary Surgery, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China.
Department of Oncology, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China.
PeerJ. 2025 May 20;13:e19337. doi: 10.7717/peerj.19337. eCollection 2025.
BACKGROUND: Hepatocellular carcinoma (HCC) is a highly aggressive malignancy. As a specific immune cell subpopulation, FGFBP2 NK cells play a crucial part in immune surveillance of HCC progression. This study set out to identify prognostic signature related to FGFBP2 NK cell in HCC. METHODS: Bulk and scRNA-seq data were derived from the public databases. The single cell atlas of HCC and heterogeneity of natural killer (NK) cells were delineated by "Seurat" package. Pseudo-time trajectory of FGFBP2 NK cell was constructed by "Monocle2" package. Cell-cell interactions were analyzed by "CellChat" package. Prognostic signature was screened to develop a RiskScore model, and the prediction robustness was verified. Immune cell infiltration and immunotherapy response were assessed between different risk groups. Drug sensitivity was predicted by "oncoPredict" package. The expressions of the prognosis gene signature were detected by test utilizing HCC cells. The effects of key genes on the proliferative, migratory and invasive capacity of HCC cells were assessed by EdU assay, wound healing and Transwell assay. RESULTS: The proportion of NK cell in HCC samples was markedly decreased than that in healthy samples. NK cell was further divided into three cell subpopulations, and FGFBP2 NK cell was associated with the prognosis of HCC patients. Pseudo-time trajectory analysis of FGFBP2 NK cell revealed two differential expression gene clusters. FGFBP2 NK cell exhibited extensive intercellular communication in HCC. Further, eight prognostic signatures were identified, including six "risk" genes (, , , , , ) and two "protective" genes (, ). RiskScore model was established with good prognostic prediction performance. In comparison to low-risk group, high-risk group had poorer prognosis, lower immune cell infiltration, and higher TIDE score. Moreover, 16 drugs showed significant correlation with RiskScore. Additionally, the expressions of was downregulated while , , , , , and were up-regulated in HCC cells. and silencing could suppress the proliferation, migration and invasion abilities of HCC cells. CONCLUSION: This study identified eight prognostic gene signatures related to FGFBP2 NK cell in HCC, which may serve as potential therapeutic targets for HCC.
背景：肝细胞癌（HCC）是一种侵袭性很强的恶性肿瘤。作为一种特定的免疫细胞亚群，FGFBP2自然杀伤（NK）细胞在HCC进展的免疫监视中起关键作用。本研究旨在鉴定与HCC中FGFBP2 NK细胞相关的预后特征。 方法：批量和单细胞RNA测序（scRNA-seq）数据来自公共数据库。使用“Seurat”软件包描绘HCC的单细胞图谱和自然杀伤（NK）细胞的异质性。使用“Monocle2”软件包构建FGFBP2 NK细胞的拟时间轨迹。通过“CellChat”软件包分析细胞间相互作用。筛选预后特征以建立风险评分模型，并验证预测的稳健性。评估不同风险组之间的免疫细胞浸润和免疫治疗反应。使用“oncoPredict”软件包预测药物敏感性。利用HCC细胞通过实验检测预后基因特征的表达。通过EdU实验、伤口愈合实验和Transwell实验评估关键基因对HCC细胞增殖、迁移和侵袭能力的影响。 结果：HCC样本中NK细胞的比例明显低于健康样本。NK细胞进一步分为三个细胞亚群，且FGFBP2 NK细胞与HCC患者的预后相关。FGFBP2 NK细胞的拟时间轨迹分析揭示了两个差异表达基因簇。FGFBP2 NK细胞在HCC中表现出广泛的细胞间通讯。此外，鉴定出八个预后特征，包括六个“风险”基因（、、、、、）和两个“保护”基因（、）。建立的风险评分模型具有良好的预后预测性能。与低风险组相比，高风险组预后较差，免疫细胞浸润较低，且肿瘤免疫功能障碍和排斥（TIDE）评分较高。此外，16种药物与风险评分显著相关。另外，在HCC细胞中表达下调，而、、、、和表达上调。和基因沉默可抑制HCC细胞的增殖、迁移和侵袭能力。 结论：本研究鉴定出与HCC中FGFBP2 NK细胞相关的八个预后基因特征，它们可能成为HCC的潜在治疗靶点。
Cancer Res Commun. 2024-7-1
J Gastroenterol Hepatol. 2024-9
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