Zhang Yongping, Sui Ping, Zhong Cheng, Liu Jiansheng
Department of Hepatobiliary and Pancreatic Surgery, The First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan 030001, Shanxi Province, China.
Department of Oncology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, 264000, Shandong, China.
J Cancer. 2024 Feb 25;15(8):2260-2275. doi: 10.7150/jca.92558. eCollection 2024.
: Hepatocellular carcinoma often results in late-stage diagnosis, leading to decreased treatment success. To improve prognosis, this study integrates cuproptosis with immune risk scoring models for HCC patients. We identified differentially expressed genes connected to cuproptosis and immune responses using Pearson correlation. A risk signature was then constructed via LASSO regression, and its robustness was validated in the International Cancer Genome Consortium dataset. Additionally, qPCR confirmed findings in tumor and normal tissues. : Eight genes emerged as key prognostic markers from the 110 differentially expressed genes linked to cuproptosis and immunity. A risk-scoring model was developed using gene expression, effectively categorizing patients into low- or high-risk groups. Validated in the ICGC dataset, high-risk patients had significantly reduced survival times. Multivariate Cox regression affirmed the risk signature's independent predictive capability. A clinical nomogram based on the risk signature was generated. Notably, low-risk patients might benefit more from immune checkpoint inhibitors. qPCR and western blotting results substantiated our bioinformatics findings. : The genetic risk signature linked to cuproptosis and immunity holds potential as a vital prognostic biomarker for Hepatocellular carcinoma, providing avenues for tailored therapeutic strategies.
肝细胞癌常导致晚期诊断，从而降低治疗成功率。为改善预后，本研究将铜死亡与肝癌患者的免疫风险评分模型相结合。我们使用Pearson相关性分析确定了与铜死亡和免疫反应相关的差异表达基因。然后通过LASSO回归构建风险特征，并在国际癌症基因组联盟数据集中验证其稳健性。此外，qPCR在肿瘤组织和正常组织中证实了研究结果。：在与铜死亡和免疫相关的110个差异表达基因中，有8个基因成为关键的预后标志物。利用基因表达建立了风险评分模型，有效地将患者分为低风险组或高风险组。在ICGC数据集中得到验证，高风险患者的生存时间显著缩短。多变量Cox回归证实了风险特征的独立预测能力。生成了基于风险特征的临床列线图。值得注意的是，低风险患者可能从免疫检查点抑制剂中获益更多。qPCR和蛋白质印迹结果证实了我们的生物信息学研究结果。：与铜死亡和免疫相关的遗传风险特征有望成为肝细胞癌重要的预后生物标志物，为量身定制治疗策略提供途径。
