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铁死亡相关 lncRNA 特征和免疫相关基因特征的开发和验证,用于预测皮肤黑色素瘤患者的预后。

Development and validation of ferroptosis-related lncRNA signature and immune-related gene signature for predicting the prognosis of cutaneous melanoma patients.

机构信息

Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.

School of Computer Science, Hunan First Normal University, Changsha, 410205, China.

出版信息

Apoptosis. 2023 Jun;28(5-6):840-859. doi: 10.1007/s10495-023-01831-7. Epub 2023 Mar 24.

Abstract

Ferroptosis, a form of cell death caused by iron-dependent peroxidation of lipids, plays an important role in cancer. Recent studies have shown that long noncoding RNAs (lncRNAs) are involved in the regulation of ferroptosis in tumor cells and are also closely related to tumor immunity. Immune cell infiltration in the tumor microenvironment affects the prognosis and clinical outcome of immunotherapy in melanoma patients, and immune cell classification may be able to accurately predict the prognosis of melanoma patients. However, the prognostic value of ferroptosis-related lncRNAs (FRLs) in melanoma has not been thoroughly explored, and it is difficult to define the immune characteristics of melanoma. We used The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) database, and the FerrDb database to identify FRLs. FRLs with prognostic value were evaluated in an experimental cohort utilizing univariate, LASSO (least absolute shrinkage and selection operator) and multivariate Cox regression, followed by in vitro assays evaluating the expression levels and the biological functions of three candidate FRLs. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to assess the validity of the risk model, and the drug sensitivity of FRLs was examined by drug sensitivity analysis. The differentially expressed genes between the high- and low-risk groups in the risk model were enriched in the immune pathway, and we further found immune gene signatures (IRGs) that could predict the prognosis of melanoma patients through a series of methods including single-sample Gene Set Enrichment Analysis (ssGSEA). Finally, two GEO cohorts were used to validate the predictive accuracy and reliability of these two signature models. Our findings suggest that FRLs and IRGs have the potential to predict the prognosis of patients with cutaneous melanoma.

摘要

铁死亡是一种由脂质铁依赖性过氧化引起的细胞死亡形式,在癌症中起重要作用。最近的研究表明,长非编码 RNA(lncRNA)参与肿瘤细胞中铁死亡的调节,并且与肿瘤免疫密切相关。肿瘤微环境中的免疫细胞浸润影响黑色素瘤患者免疫治疗的预后和临床结局,而免疫细胞分类可能能够准确预测黑色素瘤患者的预后。然而,铁死亡相关 lncRNA(FRL)在黑色素瘤中的预后价值尚未得到深入探讨,也难以定义黑色素瘤的免疫特征。我们使用了癌症基因组图谱(TCGA)、基因组织表达(GTEx)数据库和 FerrDb 数据库来识别 FRL。在实验队列中,使用单变量、LASSO(最小绝对收缩和选择算子)和多变量 Cox 回归评估具有预后价值的 FRL,然后进行体外试验评估三种候选 FRL 的表达水平和生物学功能。Kaplan-Meier(K-M)和接收者操作特征(ROC)曲线分析用于评估风险模型的有效性,并通过药物敏感性分析检查 FRL 的药物敏感性。风险模型中高低风险组之间的差异表达基因在免疫途径中富集,我们通过包括单样本基因集富集分析(ssGSEA)在内的一系列方法进一步发现了可以预测黑色素瘤患者预后的免疫基因特征(IRG)。最后,使用两个 GEO 队列验证了这两个签名模型的预测准确性和可靠性。我们的研究结果表明,FRL 和 IRG 有潜力预测皮肤黑色素瘤患者的预后。

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