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鉴定具有淋巴转移的胃癌的预后 28 基因表达特征。

Identification of a prognostic 28-gene expression signature for gastric cancer with lymphatic metastasis.

机构信息

Department of Gastroenterology, Tianjin Medical University General Hospital, Tianjin 300052, China.

Department of Gastroenterology, Affiliated Hospital of North China University of Science and Technology, Tangshan, Hebei 063000, China.

出版信息

Biosci Rep. 2019 May 2;39(5). doi: 10.1042/BSR20182179. Print 2019 May 31.

Abstract

Gastric cancer (GC) patients have high mortality due to late-stage diagnosis, which is closely associated with lymph node metastasis. Exploring the molecular mechanisms of lymphatic metastasis may inform the research into early diagnostics of GC. In the present study, we obtained RNA-Seq data from The Cancer Genome Altas and used Limma package to identify differentially expressed genes (DEGs) between lymphatic metastases and non-lymphatic metastases in GC tissues. Then, we used an elastic net-regularized COX proportional hazard model for gene selection from the DEGs and constructed a regression model composed of 28-gene signatures. Furthermore, we assessed the prognostic performance of the 28-gene signature by analyzing the receive operating characteristic curves. In addition, we selected the gene PELI2 amongst 28 genes and assessed the roles of this gene in GC cells. The good prognostic performance of the 28-gene signature was confirmed in the testing set, which was also validated by GSE66229 dataset. In addition, the biological experiments showed that PELI2 could promote the growth and metastasis of GC cells by regulating vascular endothelial growth factor C. Our study indicates that the identified 28-gene signature could be considered as a sensitive predictive tool for lymphatic metastasis in GC.

摘要

胃癌(GC)患者由于晚期诊断导致死亡率高,这与淋巴结转移密切相关。探索淋巴转移的分子机制可能有助于研究 GC 的早期诊断。在本研究中,我们从癌症基因组图谱(TCGA)获得了 RNA-Seq 数据,并使用 Limma 软件包在 GC 组织中识别出淋巴转移和非淋巴转移之间的差异表达基因(DEGs)。然后,我们使用弹性网络正则化 COX 比例风险模型从 DEGs 中进行基因选择,并构建了由 28 个基因特征组成的回归模型。此外,我们通过分析接收者操作特征曲线来评估 28 个基因特征的预后性能。此外,我们从 28 个基因中选择了基因 PELI2,并评估了该基因在 GC 细胞中的作用。在测试集中,该 28 个基因特征的预后性能得到了确认,在 GSE66229 数据集也得到了验证。此外,生物学实验表明,PELI2 可以通过调节血管内皮生长因子 C 来促进 GC 细胞的生长和转移。我们的研究表明,所鉴定的 28 个基因特征可被视为 GC 中淋巴转移的敏感预测工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc65/6499450/2213ef96fdef/bsr-39-bsr20182179-g1.jpg

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