Dai Weiyu, Xiao Yizhi, Tang Weimei, Li Jiaying, Hong Linjie, Zhang Jieming, Pei Miaomiao, Lin Jianjiao, Liu Side, Wu Xiaosheng, Xiang Li, Wang Jide
Guangdong Provincial Key Laboratory of Gastroenterology, Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Department of Gastroenterology, Longgang District People's Hospital, Shenzhen, China.
Front Genet. 2021 Jun 24;12:661306. doi: 10.3389/fgene.2021.661306. eCollection 2021.
It has been widely reported that epithelial-mesenchymal transition (EMT) is associated with malignant progression in gastric cancer (GC). Integration of the molecules related to EMT for predicting overall survival (OS) is meaningful for understanding the role of EMT in GC. Here, we aimed to establish an EMT-related gene signature in GC.
Transcriptional profiles and clinical data of GC were downloaded from The Cancer Genome Atlas (TCGA). We constructed EMT-related gene signature for predicting OS by using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Time-dependent receiver operating characteristic (ROC), Kaplan-Meier analysis were performed to assess its predictive value. A nomogram combining the prognostic signature with clinical characteristics for OS prediction was established. And its predictive power was estimated by concordance index (C-index), time-dependent ROC curve, calibration curve and decision curve analysis (DCA). GSE62254 dataset from Gene Expression Omnibus (GEO) was used for external validation. Quantitative real-time PCR (qRT-PCR) was used to detected the mRNA expression of the five EMT-related genes in human normal gastric mucosal and GC cell lines. To further understand the potential mechanisms of the signature, Gene Set Enrichment Analysis (GSEA), pathway enrichment analysis, predictions of transcription factors (TFs)/miRNAs were performed.
A novel EMT-related gene signature (including ITGAV, DAB2, SERPINE1, MATN3, PLOD2) was constructed for OS prediction of GC. With external validation, ROC curves indicated the signature's good performance. Patients stratified into high- and low-risk groups based on the signature yielded significantly different prognosis. Univariate and multivariate Cox regression suggested that the signature was an independent prognostic variable. Nomogram for prognostication including the signature presented better predictive accuracy and clinical usefulness than the similar model without risk score to some extent with external validation. The qRT-PCR assays suggested that high expression of the five EMT-related genes could be found in human GC cell lines compared with normal gastric mucosal cell line. GSEA and pathway enrichment analysis revealed that focal adhesion and ECM-receptor interaction might be the two important pathways to the signature.
Our EMT-related gene signature may have practical application as an independent prognostic factor in GC.
上皮-间质转化（EMT）与胃癌（GC）的恶性进展相关，这一观点已被广泛报道。整合与EMT相关的分子以预测总生存期（OS），对于理解EMT在GC中的作用具有重要意义。在此，我们旨在构建GC中与EMT相关的基因特征。
从癌症基因组图谱（TCGA）下载GC的转录谱和临床数据。我们通过单变量Cox回归和最小绝对收缩与选择算子（LASSO）回归分析构建用于预测OS的EMT相关基因特征。进行时间依赖性受试者工作特征（ROC）分析、Kaplan-Meier分析以评估其预测价值。建立了一个将预后特征与临床特征相结合用于OS预测的列线图。并通过一致性指数（C-index）、时间依赖性ROC曲线、校准曲线和决策曲线分析（DCA）评估其预测能力。使用来自基因表达综合数据库（GEO）的GSE62254数据集进行外部验证。采用定量实时PCR（qRT-PCR）检测人正常胃黏膜和GC细胞系中五个与EMT相关基因的mRNA表达。为进一步了解该特征的潜在机制，进行了基因集富集分析（GSEA）、通路富集分析、转录因子（TFs）/微小RNA（miRNAs）预测。
构建了一种用于GC患者OS预测的新型EMT相关基因特征（包括整合素αV（ITGAV）、Disabled-2（DAB2）、丝氨酸蛋白酶抑制剂E1（SERPINE1）、基质金属蛋白酶3（MATN3）、赖氨酰氧化酶样2（PLOD2））。经外部验证，ROC曲线表明该特征具有良好的性能。根据该特征将患者分为高风险和低风险组，其预后有显著差异。单变量和多变量Cox回归表明该特征是一个独立的预后变量。在外部验证中，包含该特征的预后列线图在一定程度上比无风险评分的类似模型具有更好的预测准确性和临床实用性。qRT-PCR检测表明，与正常胃黏膜细胞系相比，人GC细胞系中五个与EMT相关基因的表达较高。GSEA和通路富集分析表明，粘着斑和细胞外基质受体相互作用可能是该特征的两个重要通路。
我们构建的与EMT相关的基因特征可能作为GC中一个独立的预后因素具有实际应用价值。
