Comprehensive analysis of cuproptosis-related lncRNAs for prognostic significance and immune microenvironment characterization in hepatocellular carcinoma

全面分析杯状凋亡相关 lncRNA 对肝细胞癌预后意义及免疫微环境特征的影响

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作者:Duguang Li, Shengxi Jin, Peng Chen, Yiyin Zhang, Yirun Li, Cheng Zhong, Xiaoxiao Fan, Hui Lin

Abstract

Cuproptosis was characterized as a novel type of programmed cell death. Recently, however, the role of cuproptosis-related long noncoding RNAs (CRLs) in tumors has not yet been studied. Identifying a predictive CRL signature in hepatocellular carcinoma (HCC) and investigating its putative molecular function were the goals of this work. Initially, Pearson's test was used to assess the relationship between lncRNAs and cuproptosis-associated genes obtained from HCC data of The Cancer Genome Atlas (TCGA). By implementing differential expression and univariate Cox analysis, 61 prognostic CRLs were subsequent to the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. A prognostic risk score model was then constructed to evaluate its ability to predict patients' survival when combined with clinicopathological parameters in HCC. The five-lncRNA prognostic signature categorized the HCC patients into high- and low-risk groups. The low-risk group exhibited more sensitivity to elesclomol than the high-risk one. Surprisingly, distinct mitochondrial metabolism pathways connected to cuproptosis and pivotal immune-related pathways were observed between the two groups via gene set enrichment analysis (GSEA). Meanwhile, there were substantial differences between the high-risk group and the low-risk group in terms of tumor-infiltrating immune cells (TIICs). Furthermore, a positive relationship was shown between the risk score and the expression of immune checkpoints. Additionally, differential expression of the five lncRNAs was confirmed in our own HCC samples and cell lines via RT-qPCR. Finally, in vitro assays confirmed that WARS2-AS1 and MKLN1-AS knockdown could sensitize HCC cells to elesclomol-induced cuproptosis. Overall, our predictive signature may predict the prognosis of HCC patients in an independent manner, give a better understanding of how CRLs work in HCC, and offer therapeutic reference for patients with HCC.

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