Department of Pharmacy, Traditional Chinese and Western Medicine Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Medicine (Baltimore). 2023 Dec 15;102(50):e36611. doi: 10.1097/MD.0000000000036611.
The objective of this study is to explore the relationship between cuproptosis-related long noncoding RNAs (lncRNAs) in hepatocellular carcinoma (HCC). RNA-seq data, including lncRNAs and related clinical information of HCC patients, were downloaded from The Cancer Genome Atlas database. A signature composed 3 cuproptosis-related lncRNAs was constructed by LASSO analysis, and HCC patients were classified into high- and low-risk groups. Patients in the high-risk group had a poorer prognosis compared with the low-risk group. Univariate Cox and multivariate Cox regression analyses confirmed that the signature model was an independent risk factor compared to other clinical biomarkers. Furthermore, gene set enrichment analysis indicated that metabolism-related pathways were enriched in low-risk group, including drug metabolism, and fatty acid metabolism. Further research demonstrated that there were markedly differences in drug response between the high- and low-risk group. Immune related analysis showed that the most type of immune cells and immunological function in the high-risk group were different with the risk-group. Finally, TP53 mutation rate and the tumor mutational burden in the high-risk group were higher compared with the low-risk group. In conclusion, we constructed a prognostic signature based on the expression of cuproptosis-related lncRNAs to predict HCC patients' prognosis, drug response and immune microenvironment, and further research will be conducted to uncover the mechanisms.
本研究旨在探讨肝细胞癌（HCC）中与铜死亡相关的长链非编码 RNA（lncRNA）之间的关系。从癌症基因组图谱数据库中下载了包括 HCC 患者 lncRNA 及相关临床信息的 RNA-seq 数据。通过 LASSO 分析构建了由 3 个铜死亡相关 lncRNA 组成的特征，将 HCC 患者分为高风险组和低风险组。与低风险组相比，高风险组患者的预后更差。单因素 Cox 和多因素 Cox 回归分析证实，与其他临床生物标志物相比，该特征模型是一个独立的危险因素。此外，基因集富集分析表明，低风险组中富集了与代谢相关的途径，包括药物代谢和脂肪酸代谢。进一步的研究表明，高风险组和低风险组之间在药物反应方面存在明显差异。免疫相关分析显示，高风险组中大多数类型的免疫细胞和免疫功能与风险组不同。最后，与低风险组相比，高风险组中 TP53 突变率和肿瘤突变负担更高。总之，我们构建了一个基于铜死亡相关 lncRNA 表达的预后特征，以预测 HCC 患者的预后、药物反应和免疫微环境，进一步的研究将揭示其机制。
