Xiao Jingjing, Liu Zhenhua, Wang Jinlong, Zhang Shuaimin, Zhang Yi
Department of Hepatobiliary Surgery, Guizhou Provincial People's Hospital, Guiyang, China.
School of Clinical Medicine, Guizhou Medical University, Guiyang, China.
Front Oncol. 2022 Aug 30;12:941211. doi: 10.3389/fonc.2022.941211. eCollection 2022.
Cuprotosis is a newly discovered form of non-apoptotic regulated cell death and is characterized by copper-dependent and associated with mitochondrial respiration. However, the prognostic significance and function of cuprotosis-related genes (CRGs) in hepatocellular carcinoma (HCC) are unknown. This study aims to develop cuprotosis-mediated patterns-related gene (CMPRG) prediction models for the prognosis of patients with HCC, exploring the functional underlying the CRGs on the influence of tumor microenvironment (TME) features.
This study obtained transcriptome profiling and the corresponding clinical information from the TCGA and GEO databases. Besides, the Cox regression model with LASSO was implemented to build a multi-gene signature, which was then validated in an internal validation set and two external validation sets through Kaplan-Meier, DCA, and ROC analyses.
According to the LASSO analysis, we screened out a cuprotosis-mediated pattern 5-gene combination (including PBK; MMP1; GNAZ; GPC1 and AKR1D1). A nomogram was constructed for the presentation of the final model. The ROC curve assessed the model's predictive ability, which resulted in an area under the curve (AUC) values ranging from 0.604 to 0.787 underwent internal and two external validation sets. Meanwhile, the risk score divided the patients into two groups of high and low risk, and the survival rate of high-risk patients was significantly lower than that of low-risk patients (P<0.01). The risk score could be an independent prognostic factor in the multifactorial Cox regression analysis (P<0.01). Functional analysis revealed that immune status, mutational loads, and drug sensitivity differed between the two risk groups.
In summary, we identified three cuprotosis-mediated patterns in HCC. And CMPRGs are a promising candidate biomarker for HCC early detection, owing to their strong performance in predicting HCC prognosis and therapy. Quantifying cuprotosis-mediated patterns in individual samples may help improve the understanding of multiomic characteristics and guide the development of targeted therapy for HCC.
铜中毒是一种新发现的非凋亡性调节性细胞死亡形式,其特征是铜依赖性并与线粒体呼吸相关。然而,铜中毒相关基因(CRGs)在肝细胞癌(HCC)中的预后意义和功能尚不清楚。本研究旨在建立用于HCC患者预后的铜中毒介导模式相关基因(CMPRG)预测模型,探索CRGs对肿瘤微环境(TME)特征影响的潜在功能。
本研究从TCGA和GEO数据库中获取转录组图谱及相应的临床信息。此外,采用带有LASSO的Cox回归模型构建多基因特征,然后通过Kaplan-Meier、DCA和ROC分析在内部验证集和两个外部验证集中进行验证。
根据LASSO分析,我们筛选出一个由5个基因组成的铜中毒介导模式组合(包括PBK;MMP1;GNAZ;GPC1和AKR1D1)。构建了列线图以展示最终模型。ROC曲线评估了模型的预测能力,在内部和两个外部验证集中,曲线下面积(AUC)值范围为0.604至0.787。同时,风险评分将患者分为高风险和低风险两组,高风险患者的生存率显著低于低风险患者(P<0.01)。在多因素Cox回归分析中,风险评分可能是一个独立的预后因素(P<0.01)。功能分析显示,两个风险组之间的免疫状态、突变负荷和药物敏感性存在差异。
总之,我们在HCC中鉴定出三种铜中毒介导模式。由于CMPRGs在预测HCC预后和治疗方面表现出色,它们是HCC早期检测的一个有前景的候选生物标志物。量化个体样本中的铜中毒介导模式可能有助于提高对多组学特征的理解,并指导HCC靶向治疗的发展。