Department of Hematology, Qilu Hospital of Shandong University, Jinan, 250012, Shandong, China.
Department of Lymphoma and Plasmacytoma Disease, Senior Department of Hematology, The Fifth Medical Center of PLA General Hospital, Beijing, China.
Sci Rep. 2024 Jun 5;14(1):12926. doi: 10.1038/s41598-024-63433-w.
Cuproptosis is a newly defined form of programmed cell death that relies on mitochondria respiration. Long noncoding RNAs (lncRNAs) play crucial roles in tumorigenesis and metastasis. However, whether cuproptosis-related lncRNAs are involved in the pathogenesis of diffuse large B cell lymphoma (DLBCL) remains unclear. This study aimed to identify the prognostic signatures of cuproptosis-related lncRNAs in DLBCL and investigate their potential molecular functions. RNA-Seq data and clinical information for DLBCL were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Cuproptosis-related lncRNAs were screened out through Pearson correlation analysis. Utilizing univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis, we identified seven cuproptosis-related lncRNAs and developed a risk prediction model to evaluate its prognostic value across multiple groups. GO and KEGG functional analyses, single-sample GSEA (ssGSEA), and the ESTIMATE algorithm were used to analyze the mechanisms and immune status between the different risk groups. Additionally, drug sensitivity analysis identified drugs with potential efficacy in DLBCL. Finally, the protein-protein interaction (PPI) network were constructed based on the weighted gene co-expression network analysis (WGCNA). We identified a set of seven cuproptosis-related lncRNAs including LINC00294, RNF139-AS1, LINC00654, WWC2-AS2, LINC00661, LINC01165 and LINC01398, based on which we constructed a risk model for DLBCL. The high-risk group was associated with shorter survival time than the low-risk group, and the signature-based risk score demonstrated superior prognostic ability for DLBCL patients compared to traditional clinical features. By analyzing the immune landscapes between two groups, we found that immunosuppressive cell types were significantly increased in high-risk DLBCL group. Moreover, functional enrichment analysis highlighted the association of differentially expressed genes with metabolic, inflammatory and immune-related pathways in DLBCL patients. We also found that the high-risk group showed more sensitivity to vinorelbine and pyrimethamine. A cuproptosis-related lncRNA signature was established to predict the prognosis and provide insights into potential therapeutic strategies for DLBCL patients.
铜死亡是一种依赖于线粒体呼吸的新定义的细胞死亡形式。长链非编码 RNA(lncRNA)在肿瘤发生和转移中发挥着关键作用。然而,铜死亡相关 lncRNA 是否参与弥漫性大 B 细胞淋巴瘤(DLBCL)的发病机制尚不清楚。本研究旨在鉴定 DLBCL 中与铜死亡相关的 lncRNA 的预后特征,并研究其潜在的分子功能。从癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)中收集了用于 DLBCL 的 RNA-Seq 数据和临床信息。通过 Pearson 相关分析筛选出铜死亡相关 lncRNA。利用单因素 Cox、最小绝对值收缩和选择算子(Lasso)和多因素 Cox 回归分析,我们鉴定出 7 个铜死亡相关 lncRNA,并开发了一个风险预测模型,以评估其在多个组中的预后价值。GO 和 KEGG 功能分析、单样本 GSEA(ssGSEA)和 ESTIMATE 算法用于分析不同风险组之间的机制和免疫状态。此外,药物敏感性分析确定了对 DLBCL 有潜在疗效的药物。最后,基于加权基因共表达网络分析(WGCNA)构建蛋白质-蛋白质相互作用(PPI)网络。我们鉴定了一组 7 个铜死亡相关 lncRNA,包括 LINC00294、RNF139-AS1、LINC00654、WWC2-AS2、LINC00661、LINC01165 和 LINC01398,基于这些 lncRNA 构建了 DLBCL 的风险模型。与低风险组相比,高风险组的生存时间更短,基于signature 的风险评分在预测 DLBCL 患者预后方面优于传统临床特征。通过分析两组之间的免疫景观,我们发现高危 DLBCL 组中免疫抑制性细胞类型显著增加。此外,功能富集分析突出了差异表达基因与代谢、炎症和免疫相关途径的关联。我们还发现,高危组对长春瑞滨和乙胺嘧啶更敏感。建立了一个铜死亡相关 lncRNA 特征来预测预后,并为 DLBCL 患者提供潜在的治疗策略。
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