Wang Xiaowu, Qu Liangchen, Wen Zhikai, Wu Zhixuan, Xue Yuxiang, Yang Xuejia, Yuan Ziwei, Guo Yangyang, Lin Xingcheng
The Third Affiliated Hospital of Wenzhou Medical University, Zhejiang Province, Rui'an, 325200, China.
Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, 318000, Zhejiang Province, China.
Immunol Res. 2025 Feb 13;73(1):51. doi: 10.1007/s12026-025-09603-y.
In hepatocellular carcinoma (HCC) individuals, the influence of numerous variables on the HCC prognosis has gained widespread recognition. Nevertheless, there remains a need for further elucidation regarding the underlying mechanism of PANoptosis-related genes (PRGs) on HCC. A consensus clustering approach, based on the TCGA-LIHC data, was used to identify specific subtypes linked to PANoptosis in this study. Next, a signature consisting of predictive differentially expressed genes for these subtypes was established using a least absolute shrinkage and selection operator (LASSO) regression analysis. Additionally, the reliability of the signature was confirmed through verification investigations using the data from the ICGC database and TCGA-LIHC. In the end, we developed a nomogram to enhance the clinical effectiveness of our prediction tool. PRG signature in this study has been highly related to the prognosis of individuals diagnosed with HCC, which was established with six genes. Also, this signature and clinicopathological features were put together to create a nomogram. Interestingly, the forecasting efficiency of this combination approach is better than other prediction models in the reported literature. In addition, an examination of the immunological surroundings indicates that the group with low risk exhibited elevated ESTIMATE score, ImmuneScores, and StromalScores. More, significant differences in infiltrating immune cells and the expression levels of immune-related genes were found between the two groups. In HCC patients, the PRG signature exhibits potential as a biomarker, offering a significant point of reference for tailoring individual therapy.
在肝细胞癌（HCC）患者中，众多变量对HCC预后的影响已得到广泛认可。然而，关于PAN凋亡相关基因（PRG）对HCC的潜在作用机制仍需进一步阐明。本研究基于TCGA-LIHC数据，采用一致性聚类方法来识别与PAN凋亡相关的特定亚型。接下来，使用最小绝对收缩和选择算子（LASSO）回归分析建立了这些亚型的预测性差异表达基因组成的特征。此外，通过使用ICGC数据库和TCGA-LIHC的数据进行验证研究，证实了该特征的可靠性。最后，我们开发了一种列线图以提高我们预测工具的临床有效性。本研究中的PRG特征与被诊断为HCC的患者的预后高度相关，它由六个基因建立。此外，该特征与临床病理特征相结合创建了一个列线图。有趣的是，这种联合方法的预测效率优于文献中报道的其他预测模型。此外，对免疫微环境的检查表明，低风险组的ESTIMATE评分、免疫评分和基质评分升高。而且，两组之间在浸润免疫细胞和免疫相关基因的表达水平上存在显著差异。在HCC患者中，PRG特征作为一种生物标志物具有潜力，为个性化治疗提供了重要参考依据。
