子宫内膜癌淋巴结转移相关基因的生物信息学分析

Bioinformatics analysis of genes related to endometrial cancer with lymph nodes metastasis

目的:基于芯片数据分析和生物信息学方法挖掘与子宫内膜癌淋巴结转移相关的潜在差异表达基因。方法:在GEO数据库中筛选子宫内膜癌淋巴结转移相关的mRNA表达谱芯片数据,分析mRNA表达谱,筛选差异表达基因;通过生物学过程注释、生物信号通路富集、文本挖掘及蛋白/基因相互作用等综合生物信息学方法再次分析,挖掘与子宫内膜癌淋巴结转移相关的信号通路和基因。结果:在GEO数据库获得GSE2109、GSE39099芯片数据,将共同差异表达基因及信号通路富集,获得8条与子宫内膜癌淋巴结转移显著相关的信号通路(type I interferon、interferon-gamma-mediated、PI3K-Akt、Rap1、TGF-beta、cGMP-PKG、Wnt、Ras)及调控这些信号通路的14个差异表达基因,其中11个基因与宫内膜癌淋巴结转移相关并且形成蛋白相互作用网络。PI3K-Akt信号通路可能是子宫内膜癌淋巴结转移的重要信号通路,基因VEGFC、IRS1可能是子宫内膜癌淋巴结转移相关的重要候选基因。结论:通过对芯片数据生物信息学分析,筛选出与子宫内膜癌淋巴结转移相关的8条信号通路及11个差异表达基因。

Objective: To investigate the potential genes associated with lymph nodes metastasis in endometrial cancer(EC) through microarray data analysis and bioinformatics methods. Methods: We screened mRNA expression profiling chip data related to lymph node metastasis of EC from the GEO database and analyzed mRNA expression profile to screen the differentially expressed genes;with the integrated bioinformatics approach, such as biological process annotation, biological signaling pathway enrichment, text mining and protein/gene interactions, we further explored the signaling pathways and genes associated with lymph node metastasis in endometrial cancer. Results: GSE2109 and GSE39099 accessions were obtained in the GEO database, and 8 signaling pathways related to lymph node metastasis in EC(type I interferon, interferon-gamma-mediated, PI3 K-Akt, Rap1, TGF-beta, cGMP-PKG, Wnt and Ras) and 14 differentially expressed genes that regulate these pathways were found though the signaling pathways enrichment of common differentially expressed genes. Among them, 11 genes were associated with lymph node metastasis of EC and formed a protein-protein interaction network. PI3 K-Akt signaling pathway may be an important signaling pathway for lymph node metastasis in EC. VEGFC and IRS1 may be the important candidate genes related to the regulation of lymph node metastasis in EC. Conclusion: Eight signaling pathways and 11 differentially expressed genes were identified to be associated with lymph node metastasis in EC by bioinformatics analysis.