A Nomogram Based on a Three-Gene Signature Derived from AATF Coexpressed Genes Predicts Overall Survival of Hepatocellular Carcinoma Patients
A Nomogram Based on a Three-Gene Signature Derived from AATF Coexpressed Genes Predicts Overall Survival of Hepatocellular Carcinoma Patients
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DOI：
10.1155/2020/7310768
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发表时间：
2020-04-23
影响因子：
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通讯作者：
Li, Wenli
中科院分区：
文献类型：
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作者：
Liu, Jun;Lu, Jianjun;Li, Wenli
背景肝细胞癌（HCC）是一种常见的恶性肿瘤，死亡率极高。因此，迫切需要筛选HCC的关键生物标志物，以预测预后并开发更多的个体化治疗。近年来，AATF被认为是HCC发生的一个重要因素。方法.我们的目的是建立一个基因标签来预测肝癌患者的总生存率。首先，我们在基因表达综合数据库（GEO）、癌症基因组图谱（TCGA）和国际癌症基因组联合会（ICGC）数据库中检查了AATF的表达水平。通过泊松相关系数在TCGA数据集中鉴定与AATF共表达的基因，并用于建立用于生存预测的基因特征。然后在ICGC数据集中验证该基因签名的预后意义，并用于构建用于临床实践的组合预后模型。结果从三个公共数据库中下载2521例HCC患者的基因表达数据和临床信息。AATF在肝癌组织中的表达高于癌旁正常肝组织。通过Poisson相关系数鉴定与AATF共表达的644个基因，并通过单变量和多变量最小绝对收缩和选择算子考克斯回归分析用于建立三基因签名（KIF20 A、UCK 2和SLC 41 A3）。然后使用这三个基因签名来构建用于临床实践的组合列线图。结论这种基于三基因标签的整合诺模图可以很好地预测HCC患者的总生存期。三基因标签可能是HCC的潜在治疗靶点。
Background. Hepatocellular carcinoma (HCC) is a common cancer with an extremely high mortality rate. Therefore, there is an urgent need in screening key biomarkers of HCC to predict the prognosis and develop more individual treatments. Recently, AATF is reported to be an important factor contributing to HCC. Methods. We aimed to establish a gene signature to predict overall survival of HCC patients. Firstly, we examined the expression level of AATF in the Gene Expression Omnibus (GEO), the Cancer Genome Atlas (TCGA), and the International Union of Cancer Genome (ICGC) databases. Genes coexpressed with AATF were identified in the TCGA dataset by the Poisson correlation coefficient and used to establish a gene signature for survival prediction. The prognostic significance of this gene signature was then validated in the ICGC dataset and used to build a combined prognostic model for clinical practice. Results. Gene expression data and clinical information of 2521 HCC patients were downloaded from three public databases. AATF expression in HCC tissue was higher than that in matched normal liver tissues. 644 genes coexpressed with AATF were identified by the Poisson correlation coefficient and used to establish a three-gene signature (KIF20A, UCK2, and SLC41A3) by the univariate and multivariate least absolute shrinkage and selection operator Cox regression analyses. This three-gene signature was then used to build a combined nomogram for clinical practice. Conclusion. This integrated nomogram based on the three-gene signature can predict overall survival for HCC patients well. The three-gene signature may be a potential therapeutic target in HCC.