解读一种预测透明细胞肾癌预后的新型坏死相关miRNA特征

Jiaying Bao, J. Li, Han Lin, Wen-jin Zhang, B. Guo, Jun-jie Li, Liang-min Fu, Yang-peng Sun
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引用次数: 8

摘要

透明细胞肾细胞癌(ccRCC)是肾细胞癌中最常见的组织学和破坏性亚型。坏死性上睑下垂是一种程序性细胞死亡,可引起明显的炎症反应。mirna在通过坏死下垂的癌症进展中发挥重要作用。然而,与坏死相关的mirna的预后价值仍然不明确。本研究提取了39个与坏死相关的miRNAs (NRMs),并利用癌症基因组图谱(TCGA)的数据鉴定了正常和肿瘤样本之间17个差异表达的NRMs。应用单因素Cox比例风险回归分析和LASSO Cox回归模型,在训练队列中鉴定出6个与坏死相关的miRNA特征,并通过qRT-PCR验证其表达水平。根据这些mirna的表达水平,将所有患者分为高危组和低危组。高危组患者总生存率较差(P < 0.0001)。随时间变化的ROC曲线证实了我们的签名的良好性能。结果在测试队列和整个TCGA队列中得到验证。单因素和多因素Cox回归模型显示,风险评分是一个独立的预后因素。此外,构建了一个具有良好性能的预测nomogram,以增强构建的签名在临床环境中的实施。然后,我们使用miRBD、miRTarBase和TargetScan来预测六种坏死相关mirna的靶基因。基因本体和京都基因与基因组百科分析表明,392个潜在靶基因在细胞增殖相关的生物学过程中富集。利用6个mirna和59个差异表达靶基因构建miRNA-mRNA相互作用网络,选择11个枢纽基因进行生存和肿瘤浸润分析。药物敏感性分析揭示了可能有助于癌症治疗的潜在药物。因此,坏死相关基因在肿瘤生物学中发挥着重要作用。我们首次开发了一个与坏死相关的miRNA信号来预测ccRCC的预后。
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Deciphering a Novel Necroptosis-Related miRNA Signature for Predicting the Prognosis of Clear Cell Renal Carcinoma
Clear cell renal cell carcinoma (ccRCC) is the most common histological and devastating subtype of renal cell carcinoma. Necroptosis is a form of programmed cell death that causes prominent inflammatory responses. miRNAs play a significant role in cancer progression through necroptosis. However, the prognostic value of necroptosis-related miRNAs remains ambiguous. In this study, 39 necroptosis-related miRNAs (NRMs) were extracted and 17 differentially expressed NRMs between normal and tumor samples were identified using data form The Cancer Genome Atlas (TCGA). After applying univariate Cox proportional hazard regression analysis and LASSO Cox regression model, six necroptosis-related miRNA signatures were identified in the training cohort and their expression levels were verified by qRT-PCR. Using the expression levels of these miRNAs, all patients were divided into the high- and low-risk groups. Patients in the high-risk group showed poor overall survival (P < 0.0001). Time-dependent ROC curves confirmed the good performance of our signature. The results were verified in the testing cohort and the entire TCGA cohort. Univariate and multivariate Cox regression models demonstrated that the risk score was an independent prognostic factor. Additionally, a predictive nomogram with good performance was constructed to enhance the implementation of the constructed signature in a clinical setting. We then employed miRBD, miRTarBase, and TargetScan to predict the target genes of six necroptosis-related miRNAs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that 392 potential target genes were enriched in cell proliferation-related biological processes. Six miRNAs and 59 differentially expressed target genes were used to construct an miRNA–mRNA interaction network, and 11 hub genes were selected for survival and tumor infiltration analysis. Drug sensitivity analysis revealed potential drugs that may contribute to cancer management. Hence, necroptosis-related genes play an important role in cancer biology. We developed, for the first time, a necroptosis-related miRNA signature to predict ccRCC prognosis.
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