MicroRNA signature predicts survival in papillary thyroid carcinoma
MicroRNA signature predicts survival in papillary thyroid carcinoma
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MicroRNA 特征预测甲状腺乳头状癌的生存率
DOI：
10.1002/jcb.28966
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发表时间：
2019-10-01
影响因子：
4
通讯作者：
Lv Yunxia
中科院分区：
文献类型：
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作者：
Xiong Chengfeng;Cai Gengming;Lv Yunxia
甲状腺乳头状癌（PTC）占甲状腺恶性肿瘤的大多数。最近，几项微小RNA（miRNA）表达谱研究利用生物信息学表明miRNA特征可作为各种恶性肿瘤的潜在预后生物标志物。然而，尚未建立PTC的预后miRNA生物标志物。本研究的目的是通过分析从癌症基因组图谱数据库下载的高通量miRNA数据及其相关临床特征，鉴定对PTC患者总生存期（OS）具有预后价值的miRNA。从我们的数据集中，在肿瘤和非肿瘤样本之间鉴定了150种差异表达的miRNA;在这些miRNA中，118种上调，32种下调。在150个差异表达的miRNA中，鉴定出4个miRNA标签，其可靠地预测PTC患者的OS。这种miRNA特征能够将患者分为高风险组和低风险组，OS有显著差异（P < .01）。在测试集中验证了该特征的预后价值（P <0.01）。根据多变量分析，四种miRNA特征是独立的预后预测因子，并且在预测5年疾病生存方面表现出良好的性能，其曲线下面积（AUC）评分为0.886。因此，这种特征可以作为一种新的生物标志物，用于预测PTC患者的生存。
Papillary thyroid cancer (PTC) accounts for the majority of malignant thyroid tumors. Recently, several microRNA (miRNA) expression profiling studies have used bioinformatics to suggest miRNA signatures as potential prognostic biomarkers in various malignancies. However, a prognostic miRNA biomarker has not yet been established for PTC. The aim of the present study was to identify miRNAs with prognostic value for the overall survival (OS) of patients with PTC by analyzing high‐throughput miRNA data and their associated clinical characteristics downloaded from The Cancer Genome Atlas database. From our dataset, 150 differentially expressed miRNAs were identified between tumor and nontumor samples; of these miRNAs, 118 were upregulated and 32 were downregulated. Among the 150 differentially expressed miRNAs, a four miRNA signature was identified that reliably predicts OS in patients with PTC. This miRNA signature was able to classify patients into a high‐risk group and a low‐risk group with a significant difference in OS (P < .01). The prognostic value of the signature was validated in a testing set ( P < .01). The four miRNA signature was an independent prognostic predictor according to the multivariate analysis and demonstrated good performance in predicting 5‐year disease survival with an area under the receiver operating characteristic curve area under the curve (AUC) score of 0.886. Thus, this signature may serve as a novel biomarker for predicting the survival of patients with PTC.