A Novel Three-LncRNA Signature Predicting Tumor Recurrence in Nonfunctioning Pituitary Adenomas.
A Novel Three-LncRNA Signature Predicting Tumor Recurrence in Nonfunctioning Pituitary Adenomas.
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预测无功能垂体腺瘤肿瘤复发的新型三 LncRNA 特征
DOI：
10.3389/fgene.2021.754503
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发表时间：
2021
影响因子：
3.7
通讯作者：
Li C
中科院分区：
文献类型：
--
作者：
Cheng S;Guo J;Wang D;Fang Q;Liu Y;Xie W;Zhang Y;Li C
无功能性垂体腺瘤（NFPA）手术切除后复发率相对较高。在这里，我们构建了有效的长非编码RNA（lncRNA）的签名来预测NFPA预后。从66个NFPA获得LncRNA表达微阵列测序谱。66例患者随机分为训练组（n = 33）和试验组（n = 33）。使用单变量考克斯回归和机器学习算法来过滤lncRNA。进行时间依赖性受试者工作特征（ROC）分析以改善预测特征。三种lncRNA（L0 C101927765、RP 11 -23N2.4和RP 4 -533D7.4）被包括在对肿瘤复发具有高预测准确性的预后特征中，其在训练/测试组中具有最大的ROC曲线下面积（AUC）值（AUC = 0.87/0.73）。通过Kaplan-Meier生存分析验证特征的预测能力。基于签名的风险评分模型将患者分为两个风险组，各组的无复发生存率差异有统计学意义（log-rank p < 0.001）。此外，ROC分析显示，在训练/测试/整个组中，lncRNA签名预测能力显著优于年龄（AUC = 0.87/0.726/0.798 vs. AUC = 0.683/0.676/0.679）。我们构建并验证了一个预测复发的三lncRNA特征，为NFPA提供了潜在的治疗靶点。
The nonfunctioning pituitary adenoma (NFPA) recurrence rate is relatively high after surgical resection. Here, we constructed effective long noncoding RNA (lncRNA) signatures to predict NFPA prognosis. LncRNAs expression microarray sequencing profiles were obtained from 66 NFPAs. Sixty-six patients were randomly separated into a training (n = 33) and test group (n = 33). Univariable Cox regression and a machine learning algorithm was used to filter lncRNAs. Time-dependent receiver operating characteristic (ROC) analysis was performed to improve the prediction signature. Three lncRNAs (LOC101927765, RP11-23N2.4 and RP4-533D7.4) were included in a prognostic signature with high prediction accuracy for tumor recurrence, which had the largest area under ROC curve (AUC) value in the training/test group (AUC = 0.87/0.73). The predictive ability of the signature was validated by Kaplan-Meier survival analysis. A signature-based risk score model divied patients into two risk group, and the recurrence-free survival rates of the groups were significantly different (log-rank p < 0.001). In addition, the ROC analysis showed that the lncRNA signature predictive ability was significantly better than that of age in the training/testing/entire group (AUC = 0.87/0.726/0.798 vs. AUC = 0.683/0.676/0.679). We constructed and verified a three-lncRNA signature predictive of recurrence, suggesting potential therapeutic targets for NFPA.
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影响因子：
4.1
作者：
Chen, Yong;Wang, Cheng De;Wu, Zhe Bao
通讯作者：
Wu, Zhe Bao
影响因子：
24.5
作者：
Li J;Chen Z;Tian L;Zhou C;He MY;Gao Y;Wang S;Zhou F;Shi S;Feng X;Sun N;Liu Z;Skogerboe G;Dong J;Yao R;Zhao Y;Sun J;Zhang B;Yu Y;Shi X;Luo M;Shao K;Li N;Qiu B;Tan F;Chen R;He J
通讯作者：
He J
影响因子：
2
作者：
Ishwaran H;Lu M
通讯作者：
Lu M
影响因子：
12.4
作者：
Deng, Xuan;Li, Sihan;Guan, Ming
通讯作者：
Guan, Ming
预测乳腺癌生存的四长非编码 RNA 特征。
DOI：
10.1186/s13046-014-0084-7
发表时间：
2014-10-06
期刊：
Journal of experimental & clinical cancer research : CR
影响因子：
--
作者：
Meng J;Li P;Zhang Q;Yang Z;Fu S
通讯作者：
Fu S