Chen Jing, Yu Kun, Zhong Guansheng, Shen Wei
1Department of Urology, Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang Province China.
2Department of Breast and Thyroid Surgery, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, 310014 Zhejiang People's Republic of China.
Cancer Cell Int. 2020 May 7;20:157. doi: 10.1186/s12935-020-01238-3. eCollection 2020.
The mortality rate of clear cell renal cell carcinoma (ccRCC) remains high. The aim of this study was to identify novel prognostic biomarkers by using mA RNA methylation regulators capable of improving the risk-stratification criteria of survival for ccRCC patients.
The gene expression data of 16 mA methylation regulators and its relevant clinical information were extracted from The Cancer Genome Atlas (TCGA) database. The expression pattern of these mA methylation regulators were evaluated. Consensus clustering analysis was conducted to identify clusters of ccRCC patients with different prognosis. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were performed to construct multiple-gene risk signature. A survival analysis was carried out to determine the independent prognostic significance of the signature.
Five mA-related genes (ZC3H13, METTL14, YTHDF2, YTHDF3 and HNRNPA2B1) showed significantly downregulated in tumor tissue, while seven regulators (YTHDC2, FTO, WTAP, METTL3, ALKBH5, RBM15 and KIAA1429) was remarkably upregulated in ccRCC. Consensus clustering analysis identified two clusters of ccRCC with significant differences in overall survival (OS) and tumor stage between them. We also constructed a two-gene signature, METTL3 and METTL14, serving as an independent prognostic indicator for distinguishing ccRCC patients with different prognosis both in training, validation and our own clinical datasets. The receiver operator characteristic (ROC) curve indicated the area under the curve (AUC) in these three datasets were 0.721, 0.684 and 0.828, respectively, demonstrated that the prognostic signature had a good prediction efficiency.
mA methylation regulators exert as potential biomarkers for prognostic stratification of ccRCC patients and may assist clinicians achieving individualized treatment for this patient population.
透明细胞肾细胞癌（ccRCC）的死亡率仍然很高。本研究的目的是通过使用能够改善ccRCC患者生存风险分层标准的m⁶A RNA甲基化调节因子来鉴定新的预后生物标志物。
从癌症基因组图谱（TCGA）数据库中提取16种m⁶A甲基化调节因子的基因表达数据及其相关临床信息。评估这些m⁶A甲基化调节因子的表达模式。进行一致性聚类分析以识别具有不同预后的ccRCC患者群体。进行单变量、最小绝对收缩和选择算子（LASSO）以及多变量Cox回归分析以构建多基因风险特征。进行生存分析以确定该特征的独立预后意义。
5个与m⁶A相关的基因（ZC3H13、METTL14、YTHDF2、YTHDF3和HNRNPA2B1）在肿瘤组织中显著下调，而7个调节因子（YTHDC2、FTO、WTAP、METTL3、ALKBH5、RBM15和KIAA1429）在ccRCC中显著上调。一致性聚类分析确定了两组ccRCC，它们之间的总生存期（OS）和肿瘤分期存在显著差异。我们还构建了一个双基因特征，METTL3和METTL14，作为在训练、验证和我们自己的临床数据集中区分具有不同预后的ccRCC患者的独立预后指标。受试者操作特征（ROC）曲线表明，这三个数据集中的曲线下面积（AUC）分别为0.721、0.684和0.828，表明该预后特征具有良好的预测效率。
m⁶A甲基化调节因子作为ccRCC患者预后分层的潜在生物标志物，可能有助于临床医生对该患者群体实现个体化治疗。
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