背景：铜脆细胞死亡是一种新定义的细胞死亡形式，它是否与肝细胞癌有关仍不明确。方法：我们从加州大学圣塔克鲁兹分校（UCSC）和癌症基因组图谱（TCGA）获取了患者的RNA表达数据和随访信息。我们分析了与铜脆细胞死亡相关的基因（CRGs）的mRNA水平，并进行了单变量Cox分析。肝细胞癌（LIHC）被选择进行进一步的研究。我们使用实时定量PCR（RT-qPCR）、Western印迹（WB）、免疫组化（IHC）和Transwell实验来确定LIHC中CRGs的表达模式和功能。接下来，我们确定了与CRGs相关的长链非编码RNA（CRLs）以及HCC和正常病例中差异表达的CRLs。我们使用单变量Cox分析、最小绝对收缩选择算子（LASSO）分析和Cox回归分析构建了预后模型。我们使用单变量和多元Cox分析来评估风险模型是否可以作为总体生存期的独立危险因素。在不同的风险组中进行免疫相关分析、肿瘤突变负荷（TMB）和基因集富集分析（GSEA）。最后，我们评估了预测模型在药物敏感性方面的性能。结果：CRGs的表达水平在肿瘤和正常组织之间存在显著差异。Dihydrolipoamide S-Acetyltransferase (DLAT)的高表达与HCC细胞的转移相关，并预示着HCC患者的预后不佳。我们的预后模型包括四个铜脆细胞死亡相关的长链非编码RNA（AC011476.3，AC026412.3，NRAV，MKLN1-AS）。预后模型在预测生存率方面表现良好。Cox回归分析的结果表明，风险评分可以作为生存时间的独立预后因素。生存分析显示，低风险患者的生存期比高风险患者更长。免疫分析的结果显示，风险评分与B细胞和CD4+T细胞Th2呈正相关，而与内皮细胞和造血细胞呈负相关。此外，免疫检查点基因在高风险组中的表达倍数比低风险组高。高风险组的遗传突变率比低风险组高，但生存时间较短。GSEA揭示了高风险组富集的信号通路大多与免疫相关，而低风险组则与代谢相关的通路富集。药物敏感性分析表明，我们的模型有能力预测临床治疗的疗效。结论：铜脆细胞死亡相关的长链非编码RNA预后公式是预测HCC患者预后和药物敏感性的一种新型预测因子。版权所有©2023陈、孙、冯、陈、季、谢、黄、陈、张、聂、范、吴和夏。

Background: Cuproptosis is a newly defined form of cell death, whether cuproptosis involved in hepatocellular carcinoma (HCC) remains elusive. Method: We obtained patients' RNA expression data and follow-up information from University of California Santa Cruz (UCSC) and The Cancer Genome Atlas (TCGA). We analyzed the mRNA level of Cuproptosis-related genes (CRGs) and performed univariate Cox analysis. Liver hepatocellular carcinoma (LIHC) was chosen for further investigation. Real-Time quantitative PCR (RT-qPCR), Western blotting (WB), Immunohistochemical (IHC), and Transwell assays were used to determine expression patterns and functions of CRGs in LIHC. Next, we identified CRGs-related lncRNAs (CRLs) and differentially expressed CRLs between HCC and normal cases. Univariate Cox analysis, least absolute shrinkage selection operator (LASSO) analysis and Cox regression analysis were used to construct the prognostic model. Univariate and multivariate Cox analysis was used to assess whether the risk model can act as an independent risk factor of overall survival duration. Different risk groups performed immune correlation analysis, tumor mutation burden (TMB), and Gene Set Enrichment Analysis (GSEA) analysis were performed in different risk groups. Finally, we assessed the performance of the predictive model in drug sensitivity. Results: CRGs expression levels have significant differences between tumor and normal tissues. High expression of Dihydrolipoamide S-Acetyltransferase (DLAT) correlated to metastasis of HCC cells and indicated poor prognosis for HCC patients. Our prognostic model consisted of four cuproptosis-related lncRNA (AC011476.3, AC026412.3, NRAV, MKLN1-AS). The prognostic model performed well in predicting survival rates. The results from Cox regression analysis suggested that risk score can serve as an independent prognostic element for survival durations. Survival analysis revealed that low risk patients have extended survival periods compared with those with high risk. The results of the immune analysis indicated that risk score has a positive correlation with B cell and CD4+ T cell Th2, while has a negative relationship with endothelial cell and hematopoietic cells. Besides, immune checkpoint genes have higher expression folds in the high-risk set than in the low-risk set. The high-risk group had higher rates of genetic mutation than the low-risk set while having a shorter survival time. GSEA revealed the signaling pathways enriched in the high-risk group were mostly immune-related, while metabolic-related pathways were enriched in the low-risk group. Drugs sensitivity analysis indicated that our model has the ability to predict the efficacy of clinical treatment. Conclusion: The Cuproptosis-related lncRNAs prognostic formula is a novel predictor of HCC patients' prognosis and drug sensitivity.Copyright © 2023 Chen, Sun, Feng, Chen, Ji, Xie, Huang, Chen, Zhang, Nie, Fan, Wu and Xia.