Department of Hepatobiliary, Pancreatic and Splenic Surgery, People's Hospital of Luzhou City, Luzhou, China.
Department of Hepatobiliary Surgery, Tongnan District People's Hospital, Chongqing, China.
J Immunol Res. 2022 Jul 12;2022:6535009. doi: 10.1155/2022/6535009. eCollection 2022.
Hepatocellular carcinoma (HCC) with high heterogeneity is one of the most frequent malignant tumors. However, there were no studies to create a clinical stage-related gene signature for HCC patients. Differentially expressed genes (DEGs) associated with clinical stage of HCC were analyzed based on TCGA datasets. Functional enrichment analysis was carried out by the use of stage-related DEGs. Then, the least absolute shrinkage and selection operator (LASSO) regression and univariate Cox regression were performed to reduce the overfit and the number of genes for further analysis. Next, survival and ROC assays were carried out to demonstrate the model using TCGA. Functional analysis and immune microenvironment analysis related to stage-related DEGs were performed. Reverse transcriptase polymerase chain reaction (RT-PCR) and Cell Counting Kit-8 (CCK-8) assays were applied to examine the expression and function of PNCK in HCC. In this research, there were 21 DEGs between HCC specimens with stage (I-II) and HCC specimens with stage (III-IV), including 20 increased genes and 1 decreased genes. A novel seven-gene signature (including PITX2, PNCK, GLIS1, SCNN1G, MMP1, ZNF488, and SHISA9) was created for the prediction of outcomes of HCC patients. The ROC curves confirmed the prognostic value of the new model. Cox assays demonstrated that the seven-gene signature can independently forecast overall survival. The immune analysis revealed that patients with low risk score exhibited more immune activities. Moreover, we confirmed that PNCK expressions were distinctly increased in HCC, and its silence suppressed the proliferation of HCC cells. Overall, our research offered a robust and reliable gene signature which displayed an important value in the prediction of overall survival of HCC patients and might deliver more effective personalized therapies.
肝细胞癌（HCC）具有高度异质性，是最常见的恶性肿瘤之一。然而，目前尚无研究为 HCC 患者创建与临床分期相关的基因特征。本研究基于 TCGA 数据集分析与 HCC 临床分期相关的差异表达基因（DEGs）。使用与分期相关的 DEGs 进行功能富集分析。然后，进行最小绝对收缩和选择算子（LASSO）回归和单变量 Cox 回归，以减少过拟合和进一步分析的基因数量。接下来，使用 TCGA 进行生存和 ROC 分析来验证模型。进行与分期相关的 DEGs 相关的功能分析和免疫微环境分析。应用逆转录聚合酶链反应（RT-PCR）和细胞计数试剂盒-8（CCK-8）检测 HCC 中 PNCK 的表达和功能。在这项研究中，有 21 个 DEGs 存在于分期（I-II）和分期（III-IV）的 HCC 标本之间，包括 20 个上调基因和 1 个下调基因。创建了一个新的七基因特征（包括 PITX2、PNCK、GLIS1、SCNN1G、MMP1、ZNF488 和 SHISA9），用于预测 HCC 患者的结局。ROC 曲线证实了新模型的预后价值。Cox 分析表明，该七基因特征可独立预测总生存期。免疫分析显示，低风险评分的患者表现出更多的免疫活性。此外，我们证实 PNCK 在 HCC 中表达明显增加，其沉默抑制了 HCC 细胞的增殖。总的来说，我们的研究提供了一个强大而可靠的基因特征，在预测 HCC 患者的总生存期方面具有重要价值，并可能提供更有效的个体化治疗。
