Suppr超能文献

利用具有七个上皮-间质转化相关基因的风险特征来预测肝细胞癌患者的预后。

Risk characteristics with seven epithelial-mesenchymal transition-related genes are used to predict the prognosis of patients with hepatocellular carcinoma.

作者信息

Shi Xianqing, Tu Shuhuan, Zhu Liqun

机构信息

Department of Oncology, Liyang People's Hospital, Liyang, China.

出版信息

J Gastrointest Oncol. 2021 Aug;12(4):1884-1894. doi: 10.21037/jgo-21-394.

Abstract

BACKGROUND

Epithelial-mesenchymal transition (EMT)-related genes (ERGs) have been shown to play an important role in cancer invasion, tumor resistance, and tumor metastasis of hepatocellular carcinoma. This study sought to examine the prognostic value of ERGs and other pre-hepatoma genes.

METHODS

Relevant data from The Cancer Genome Atlas (TCGA) were analyzed and synthesized. Specifically, 1,014 ERGs were downloaded and subject to a gene set enrichment analysis; 318 different EAG expressions were found, and the possible molecular mechanism of EAG was predicted by GO analysis and KEGG analysis. To determine the prediction of ERGS, a Cox regression model was used to establish a risk hypothesis. Based on risk patterns, patients were divided into high- or low-risk groups. Kaplan-Meier and receiver operating characteristic (ROC) curves confirmed the predictive value of the model.

RESULTS

Seven prognostically relevant ERGs (i.e., ECT2, EZH2, MYCN, ROR2, SPP1, SQSTM1, and STC2) were identified. Using Cox's regression analysis method, appropriate cases were selected to establish a new risk prediction model. Under the risk model, the overall survival rate of the low-risk group samples was higher than that of the high-risk group samples (P<0.00001).

CONCLUSIONS

In short, we developed a risk model for liver cancer based on ERGs terminology. This model improve the postpartum treatment of patients with liver cancer.

摘要

背景

上皮-间质转化(EMT)相关基因(ERGs)已被证明在肝细胞癌的癌症侵袭、肿瘤耐药性和肿瘤转移中起重要作用。本研究旨在探讨ERGs和其他肝癌前基因的预后价值。

方法

对来自癌症基因组图谱(TCGA)的相关数据进行分析和综合。具体而言,下载了1014个ERGs并进行基因集富集分析;发现了318种不同的EAG表达,并通过GO分析和KEGG分析预测了EAG可能的分子机制。为了确定ERGS的预测情况,使用Cox回归模型建立风险假设。根据风险模式,将患者分为高风险组或低风险组。Kaplan-Meier曲线和受试者工作特征(ROC)曲线证实了该模型的预测价值。

结果

确定了7个与预后相关的ERGs(即ECT2、EZH2、MYCN、ROR2、SPP1、SQSTM1和STC2)。使用Cox回归分析方法,选择合适的病例建立了一个新的风险预测模型。在该风险模型下,低风险组样本的总生存率高于高风险组样本(P<0.00001)。

结论

简而言之,我们基于ERGs术语开发了一种肝癌风险模型。该模型改善了肝癌患者的产后治疗。

相似文献

本文引用的文献

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验