Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Molecular and Experimental Surgery, Clinic for General-, Visceral-, Vascular and Transplant Surgery, Faculty of Medicine and University Hospital Magdeburg, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.
Aging (Albany NY). 2023 Dec 14;15(24):15050-15063. doi: 10.18632/aging.205330.
Predicting the prognosis of hepatocellular carcinoma (HCC) is a major medical challenge and of guiding significance for treatment. This study explored the actual relevance of RNA expression in predicting HCC prognosis. Cox's multiple regression was used to establish a risk score staging classification and to predict the HCC patients' prognosis on the basis of data in the Cancer Genome Atlas (TCGA). We screened seven gene biomarkers related to the prognosis of HCC from the perspective of oxidative stress, including Alpha-Enolase 1(ENO1), N-myc downstream-regulated gene 1 (NDRG1), nucleophosmin (NPM1), metallothionein-3, H2A histone family member X, Thioredoxin reductase 1 (TXNRD1) and interleukin 33 (IL-33). Among them we measured the expression of ENO1, NGDP1, NPM1, TXNRD1 and IL-33 to investigate the reliability of the multi-index prediction. The first four markers' expressions increased successively in the paracellular tissues, the hepatocellular carcinoma samples (from patients with better prognosis) and the hepatocellular carcinoma samples (from patients with poor prognosis), while IL-33 showed the opposite trend. The seven genes increased the sensitivity and specificity of the predictive model, resulting in a significant increase in overall confidence. Compared with the patients with higher-risk scores, the survival rates with lower-risk scores are significantly increased. Risk score is more accurate in predicting the prognosis HCC patients than other clinical factors. In conclusion, we use the Cox regression model to identify seven oxidative stress-related genes, investigate the reliability of the multi-index prediction, and develop a risk staging model for predicting the prognosis of HCC patients and guiding precise treatment strategy.
预测肝细胞癌（HCC）的预后是一个主要的医学挑战，对治疗具有指导意义。本研究探讨了 RNA 表达在预测 HCC 预后中的实际相关性。Cox 的多变量回归用于建立风险评分分期分类，并基于癌症基因组图谱（TCGA）中的数据预测 HCC 患者的预后。我们从氧化应激的角度筛选了与 HCC 预后相关的七个基因生物标志物，包括 Alpha-Enolase 1（ENO1）、N-myc 下游调节基因 1（NDRG1）、核磷蛋白（NPM1）、金属硫蛋白 3、H2A 组蛋白家族成员 X、硫氧还蛋白还原酶 1（TXNRD1）和白细胞介素 33（IL-33）。其中，我们测量了 ENO1、NGDP1、NPM1、TXNRD1 和 IL-33 的表达，以研究多指标预测的可靠性。前四个标志物的表达在细胞旁组织、肝细胞癌样本（来自预后较好的患者）和肝细胞癌样本（来自预后较差的患者）中依次增加，而 IL-33 则表现出相反的趋势。这七个基因提高了预测模型的敏感性和特异性，从而显著提高了整体置信度。与高风险评分的患者相比，低风险评分的患者生存率明显提高。风险评分比其他临床因素更能准确预测 HCC 患者的预后。总之，我们使用 Cox 回归模型识别了七个与氧化应激相关的基因，研究了多指标预测的可靠性，并开发了一个用于预测 HCC 患者预后和指导精准治疗策略的风险分期模型。
