N6-Methylandenosine-Related lncRNAs Are Potential Biomarkers for Predicting the Overall Survival of Lower-Grade Glioma Patients
N6-Methylandenosine-Related lncRNAs Are Potential Biomarkers for Predicting the Overall Survival of Lower-Grade Glioma Patients
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N6-甲基腺苷相关 lncRNA 是预测低级别胶质瘤患者总体生存率的潜在生物标志物
DOI：
10.3389/fcell.2020.00642
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发表时间：
2020-07-23
影响因子：
5.5
通讯作者：
Zhu, Xingen
中科院分区：
文献类型：
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作者：
Tu, Zewei;Wu, Lei;Zhu, Xingen
在癌症基因组图谱 (TCGA) 和中国胶质瘤基因组图谱 (CGGA) 数据集中的 646 个低级别胶质瘤 (LGG) 样本中研究了 N6-甲基腺苷相关长非编码 RNA (m6A 相关 lncRNA) 的预后价值。我们采用 Pearson 相关分析来探索 m6A 相关的 lncRNA，然后进行单变量 Cox 回归分析来筛选它们在 LGG 患者中的预后作用。 24 个预后 m6A 相关 lncRNA 被鉴定为预后 lncRNA，并将它们输入最小绝对收缩和选择算子 (LASSO) Cox 回归中，以在 TCGA 数据集中建立 m6A 相关 lncRNA 预后特征（m6A-LPS，包括 9 个 m6A 相关预后 lncRNA）。计算患者相应的风险评分，并根据每个数据集中风险评分的中值将LGG患者分为低风险亚组和高风险亚组。 m6A-LPS 在 CGGA 数据集中得到验证，并在分层分析中显示出强大的预后能力。主成分分析显示，低风险和高风险亚组具有不同的 m6A 状态。富集分析表明，与恶性肿瘤相关的生物过程、途径和标志在高风险亚组中更为常见。此外，我们构建了一个列线图（基于 m6A-LPS、年龄和世界卫生组织分级），该列线图能够很强地预测两个数据集中 LGG 患者的总生存期 (OS)。我们还基于 24 种 m6A 相关 lncRNA 中的 7 种建立了竞争性内源 RNA (ceRNA) 网络。此外，我们还使用实时定量聚合酶链反应测定法检测了 22 个临床样本中的 5 个 m6A 相关 lncRNA 表达水平。
The prognostic value of N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) was investigated in 646 lower-grade glioma (LGG) samples from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) datasets. We implemented Pearson correlation analysis to explore the m6A-related lncRNAs, and then univariate Cox regression analysis was performed to screen their prognostic roles in LGG patients. Twenty-four prognostic m6A-related lncRNAs were identified as prognostic lncRNAs and they were inputted in a least absolute shrinkage and selection operator (LASSO) Cox regression to establish a m6A-related lncRNA prognostic signature (m6A-LPS, including 9 m6A-related prognostic lncRNAs) in the TCGA dataset. Corresponding risk scores of patients were calculated and divided LGG patients into low- and high-risk subgroups by the median value of risk scores in each dataset. The m6A-LPS was validated in the CGGA dataset and it showed a robust prognostic ability in the stratification analysis. Principal component analysis showed that the low- and high-risk subgroups had distinct m6A status. Enrichment analysis indicated that malignancy-associated biological processes, pathways and hallmarks were more common in the high-risk subgroup. Moreover, we constructed a nomogram (based on m6A-LPS, age and World Health Organization grade) that had a strong ability to forecast the overall survival (OS) of the LGG patients in both datasets. We also establish a competing endogenous RNA (ceRNA) network based on seven of the twenty-four m6A-related lncRNAs. Besides, we also detected five m6A-related lncRNA expression levels in 22 clinical samples using quantitative real-time polymerase chain reaction assay.