Supplementary Material for: Cuproptosis-Related lncRNA Risk Model for Hepatocellular Carcinoma Prognosis and Immunotherapy Response

Background: Cuproptosis is a type of cell death caused by copper imbalance associated with the growth and proliferation of cancer cells. Long noncoding RNAs (lncRNAs) play a crucial role in hepatocellular carcinoma (HCC) development. Here, we aimed to investigate the role of cuproptosis-related lncRNAs in the clinical prognostic prediction and immunotherapy for HCC. Methods: A correlation network between lncRNAs and cuproptosis-related genes in HCC was constructed by conducting co-expression and Cox regression analyses. LASSO-Cox analysis was used to obtain lncRNAs that constitute the cuproptosis-associated lncRNA signature, which was then used to predict patient prognosis and immunotherapy response. To verify the clinical applicability of the risk model, a nomogram was constructed and an anti-neoplastic drug sensitivity analysis was performed. Results: Four cuproptosis-related lncRNAs (AL590705.3, SPRY4-AS1, AC135050.5, and AL031985.3) were identified and used to develop a prognostic signature for HCC. Based on the four lncRNAs, a risk prediction model was established. For overall survival (OS) in HCC patients, the area under the ROC curve (AUC) for the risk score was 0.715, outperforming traditional clinical factors such as age (AUC=0.531), gender (AUC=0.509), and stage (AUC=0.671). High-risk patients had worse overall survival, progression-free survival, and higher mortality. Independent ROC analysis, nomogram‐based modeling, and concordance index analysis indicated that the risk model has high predictive accuracy for HCC. Conclusions: This model demonstrates potential in predicting prognosis, and offers novel insights to the treatment and management of HCC. Our study suggests that lncRNAs may serve as a novel biomarker and potential therapeutic target for HCC.

研究背景：铜死亡（Cuproptosis）是一种由铜离子失衡诱发的细胞死亡类型，与癌细胞的生长增殖密切相关。长链非编码RNA（Long noncoding RNAs，lncRNAs）在肝细胞癌（Hepatocellular carcinoma，HCC）的发生发展中发挥关键作用。本研究旨在探讨铜死亡相关lncRNAs在肝细胞癌临床预后预测及免疫治疗中的应用价值。
研究方法：通过共表达分析与Cox回归分析，构建肝细胞癌中lncRNAs与铜死亡相关基因的共表达调控网络。采用LASSO-Cox分析筛选出可构建铜死亡相关lncRNA预后特征的分子，进而利用该特征预测患者预后与免疫治疗响应情况。为验证该风险模型的临床适用性，本研究构建了列线图（nomogram）并开展抗肿瘤药物敏感性分析。
研究结果：本研究共筛选出4种铜死亡相关lncRNAs（AL590705.3、SPRY4-AS1、AC135050.5及AL031985.3），并以此构建肝细胞癌预后特征模型。基于这4种lncRNAs建立的风险预测模型中，肝细胞癌患者的总生存期（Overall survival，OS）风险评分的受试者工作特征曲线下面积（Area under the ROC curve，AUC）达0.715，优于年龄（AUC=0.531）、性别（AUC=0.509）及临床分期（AUC=0.671）等传统临床指标。高危组患者的总生存期、无进展生存期更短，死亡率更高。独立ROC分析、基于列线图的建模及一致性指数（concordance index）分析均证实，该风险模型对肝细胞癌具有较高的预测准确度。
研究结论：该风险模型在肝细胞癌预后预测中展现出潜在应用价值，为肝癌的治疗与管理提供了全新的研究思路。本研究提示，lncRNAs可作为肝细胞癌新型生物标志物及潜在治疗靶点。