Identification of a six-gene signature with prognostic value for patients with endometrial carcinoma.
Identification of a six-gene signature with prognostic value for patients with endometrial carcinoma.
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作者：
Wang Y;Ren F;Chen P;Liu S;Song Z;Ma X
子宫体子宫内膜癌(UCEC)在世界范围内的女性中经常被诊断为子宫内膜癌。然而，由于异质性，预后结果是不同的。因此，本研究的目的是确定一个可以预测UCEC患者预后的基因标志。UCEC基因表达谱首先从癌症基因组图谱(TCGA)数据库下载。经过数据处理和正向筛选，筛选出11个390个关键基因。将UCEC样本随机分为训练集和测试集。总共有996个有预后价值的基因随后在训练集中进行了单变量COX生存分析，P值为0.01。接下来，利用稳健的基于似然的生存模型，我们开发了一个在UCEC中具有预后功能的六基因标记(CTSW、PCSK4、LRRC8D、TNFRSF18、IHH和CDKN2A)。基于这六个基因特征，通过多变量Cox比例风险回归建立了预后风险评分系统。根据Kaplan-Meier曲线，高风险组患者的总体生存(OS)结果显著低于低风险组(对数等级检验P值0.0001)。该签名在测试数据集中和整个TCGA数据集中得到了进一步验证。综上所述，我们进行了一项综合性研究，以开发六个基因标志来预测UCEC患者的预后。我们的发现可能为预后提供新的生物标志物，并对了解UCEC的治疗靶点具有重要意义。
Uterine corpus endometrial carcinoma (UCEC) is frequently diagnosed among women worldwide. However, there are different prognostic outcomes because of heterogeneity. Thus, the aim of the current study was to identify a gene signature that can predict the prognosis of patients with UCEC. UCEC gene expression profiles were first downloaded from the The Cancer Genome Atlas (TCGA) database. After data processing and forward screening, 11 390 key genes were selected. The UCEC samples were randomly divided into training and testing sets. In total, 996 genes with prognostic value were then examined by univariate Cox survival analysis with a P‐value <0.01 in the training set. Next, using robust likelihood‐based survival modeling, we developed a six‐gene signature (CTSW, PCSK4, LRRC8D, TNFRSF18, IHH, and CDKN2A) with a prognostic function in UCEC. A prognostic risk score system was developed by multivariate Cox proportional hazard regression based on this six‐gene signature. According to the Kaplan‐Meier curve, patients in the high‐risk group had significantly poorer overall survival (OS) outcomes than those in the low‐risk group (log‐rank test P‐value <0.0001). This signature was further validated in the testing dataset and the entire TCGA dataset. In conclusion, we conducted an integrated study to develop a six‐gene signature for the prognostic prediction of patients with UCEC. Our findings may provide novel biomarkers for prognosis and have significant implications in the understanding of therapeutic targets for UCEC.
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影响因子：
64.8
作者：
通讯作者：
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DOI：
10.1073/pnas.96.7.3993
发表时间：
1999-03-30
影响因子：
11.1
作者：
Inoue, K;Roussel, MF;Sherr, CJ
通讯作者：
Sherr, CJ
影响因子：
3.9
作者：
Jiang X;Tang H;Chen T
通讯作者：
Chen T
影响因子：
3.7
作者：
Liu, Yang;Phong Quang;Ghobrial, Irene M.
通讯作者：
Ghobrial, Irene M.
影响因子：
--
作者：
Chen H;Sun X;Ge W;Qian Y;Bai R;Zheng S
通讯作者：
Zheng S