Department of Pathology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin, Tianjin, 300060, China.
BMC Immunol. 2024 Sep 9;25(1):59. doi: 10.1186/s12865-024-00649-5.
To ascertain the connection between cuproptosis-related genes (CRGs) and the prognosis of hepatocellular carcinoma (HCC) via single-cell RNA sequencing (scRNA-seq) and RNA sequencing (RNA-seq) data, relevant data were downloaded from the GEO and TCGA databases. The differentially expressed CRGs (DE-CRGs) were filtered by the overlaps in differentially expressed genes (DEGs) between HCC patients and normal controls (NCs) in the scRNA-seq database, DE-CRGs between high- and low-CRG-activity cells, and DEGs between HCC patients and NCs in the TCGA database.
Thirty-three DE-CRGs in HCC were identified. A prognostic model (PM) was created employing six survival-related genes (SRGs) (NDRG2, CYB5A, SOX4, MYC, TM4SF1, and IFI27) via univariate Cox regression analysis and LASSO. The predictive ability of the model was validated via a nomogram and receiver operating characteristic curves. Research has employed tumor immune dysfunction and exclusion as a means to examine the influence of PM on immunological heterogeneity. Macrophage M0 levels were significantly different between the high-risk group (HRG) and the low-risk group (LRG), and a greater macrophage level was linked to a more unfavorable prognosis. The drug sensitivity data indicated a substantial difference in the half-maximal drug-suppressive concentrations of idarubicin and rapamycin between the HRG and the LRG. The model was verified by employing public datasets and our cohort at both the protein and mRNA levels.
A PM using 6 SRGs (NDRG2, CYB5A, SOX4, MYC, TM4SF1, and IFI27) was developed via bioinformatics research. This model might provide a fresh perspective for assessing and managing HCC.
通过单细胞 RNA 测序（scRNA-seq）和 RNA 测序（RNA-seq）数据，从 GEO 和 TCGA 数据库中下载相关数据，确定与铜死亡相关基因（CRGs）与肝细胞癌（HCC）预后之间的联系。在 scRNA-seq 数据库中，通过 HCC 患者与正常对照（NC）之间差异表达基因（DEGs）的重叠、高和低 CRG 活性细胞之间的差异表达 CRGs（DE-CRGs）以及 TCGA 数据库中 HCC 患者与 NC 之间的 DEGs 筛选差异表达 CRGs（DE-CRGs）。
鉴定出 33 个 HCC 中的 DE-CRGs。通过单因素 Cox 回归分析和 LASSO 分析，采用 6 个生存相关基因（NDRG2、CYB5A、SOX4、MYC、TM4SF1 和 IFI27）构建了预后模型（PM）。通过列线图和受试者工作特征曲线验证了模型的预测能力。研究采用肿瘤免疫功能障碍和排除作为评估 PM 对免疫异质性影响的手段。高风险组（HRG）和低风险组（LRG）之间巨噬细胞 M0 水平存在显著差异，巨噬细胞水平较高与预后较差相关。药物敏感性数据表明，idarubicin 和 rapamycin 的半最大药物抑制浓度在 HRG 和 LRG 之间存在显著差异。该模型在蛋白和 mRNA 水平上通过公共数据集和我们的队列进行了验证。
通过生物信息学研究构建了一个使用 6 个 SRGs（NDRG2、CYB5A、SOX4、MYC、TM4SF1 和 IFI27）的 PM。该模型可能为评估和管理 HCC 提供新的视角。
