Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients.
Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients.
复制标题
结直肠癌患者上皮间质转化的基因组学和预后分析。
DOI：
10.1186/s12885-020-07615-5
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发表时间：
2020-11-23
期刊：
影响因子：
3.8
通讯作者：
Xue M
中科院分区：
文献类型：
--
作者：
Zhang Z;Zheng S;Lin Y;Sun J;Ding N;Chen J;Zhong J;Shi L;Xue M
上皮-间质转化（epithelial-mesenchymal transition， EMT）在胚胎发育、组织形态发生和伤口愈合等多种生理过程中起着关键作用。EMT在肿瘤侵袭、转移和化疗耐药中也起着重要作用。此外，EMT是结直肠癌（CRC）化疗耐药的部分原因。本研究的目的是开发一种基于emt的结直肠癌预后特征。从The Cancer Genome Atlas （TCGA）和Gene Expression Omnibus （GEO）数据库下载RNA-seq和微阵列数据以及临床信息。通过比较正常组织与肿瘤组织的表达，共获得244个emt相关差异表达基因（ERGs）。通过单变量Cox比例风险分析、最小绝对收缩和选择算子（LASSO）和Cox回归分析，确定了11个与emt相关的基因特征与患者的总生存期（OS）至关重要。最后，我们通过整合临床特征和emt相关基因特征，建立了预测结直肠癌患者生存可能性的临床nomogram。结果证实了244个差异表达的ERGs及其富集通路。显著富集分析显示，emt相关信号通路基因与结直肠癌高度相关。Kaplan-Meier分析显示，在TCGA和GEO CRC队列中，11-EMT特征可以显著区分高风险和低风险患者。此外，标定曲线验证了nomogram预测模型与实际观测值之间的良好一致性。我们开发了一种新的emt相关的CRC患者预后预测基因标记，可以提高CRC患者的个体化预后预测。在线版本包含补充材料，可在10.1186/s12885-020-07615-5获得。
The epithelial-mesenchymal transition (EMT) plays a pivotal role in various physiological processes, such as embryonic development, tissue morphogenesis, and wound healing. EMT also plays an important role in cancer invasion, metastasis, and chemoresistance. Additionally, EMT is partially responsible for chemoresistance in colorectal cancer (CRC). The aim of this research is to develop an EMT-based prognostic signature in CRC. RNA-seq and microarray data, together with clinical information, were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. A total of 244 differentially expressed EMT-related genes (ERGs) were obtained by comparing the expression between normal and tumor tissues. An EMT-related signature of 11 genes was identified as crucially related to the overall survival (OS) of patients through univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO), and Cox regression analysis. Finally, we established a clinical nomogram to predict the survival possibility of CRC patients by integrating clinical characteristics and the EMT-related gene signature. Two hundred and forty-four differentially expressed ERGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that EMT-related signaling pathway genes were highly related to CRC. Kaplan-Meier analysis revealed that the 11-EMT signature could significantly distinguish high- and low-risk patients in both TCGA and GEO CRC cohorts. In addition, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. We developed a novel EMT-related gene signature for the prognosis prediction of CRC patients, which could improve the individualized outcome prediction in CRC. The online version contains supplementary material available at 10.1186/s12885-020-07615-5.
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