Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.

IF 3.5 3区 医学 Q2 ONCOLOGY
Frontiers in Oncology Pub Date : 2025-03-18 eCollection Date: 2025-01-01 DOI:10.3389/fonc.2025.1570647
Jiashuo Li, Zhenyi Liu, Gongming Zhang, Xue Yin, Xiaoxue Yuan, Wen Xie, Xiaoyan Ding
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Abstract

Background: 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.

Methods: 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.

Result: 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.

Conclusion: 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.

通过整合整体和单细胞RNA-seq数据揭示NK细胞对HCC预后的异质性。
背景:肿瘤微环境(tumor microenvironment, TME)在肝细胞癌(HCC)的发生、进展和临床结局中起着至关重要的作用。尽管自然杀伤细胞(NK)在肿瘤免疫中起着至关重要的作用,但其在HCC肿瘤微环境中的地位研究有限。在这项研究中,对HCC数据集进行了单细胞RNA测序(scRNA-seq)分析,以鉴定潜在的生物标志物,并研究自然杀伤(NK)细胞在TME中的作用。方法:从GSE149614数据集中提取单细胞RNA测序(scRNA-seq)数据,使用“Seurat”包进行质量控制处理。TCGA数据集中的HCC亚型通过基于差异表达基因(DEGs)的共识聚类进行分类。采用加权基因共表达网络分析法(WGCNA)构建共表达网络。此外,还进行了单因素和多因素Cox回归分析,以确定与总生存率相关的变量。采用单样本基因集富集分析(ssGSEA)对免疫细胞和筛选的基因进行分析。结果:从GSE149614和TCGA中分别鉴定出715个和864个基因,其中25个基因重叠。然后建立基于两个基因的预后风险评分模型。免疫细胞浸润在高危组和低危组之间存在显著差异。免疫组化结果显示,与正常组织相比,HCC中HRG表达降低,而TUBA1B表达升高。结论:我们的研究确定了基于NK细胞标记的双基因预后标记,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,结合临床因素来帮助临床医生做出决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Oncology
Frontiers in Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
6.20
自引率
10.60%
发文量
6641
审稿时长
14 weeks
期刊介绍: Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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