Bioinformatics analysis of genes related to endometrial cancer with lymph nodes metastasis
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Abstract:
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, PI3K-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. PI3K-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.
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Project supported by the Scientific Research and Technology Development Program of Guangxi Zhuang Autonomous Region (No.14124004), the Natural Science Foundation Program of Guangxi Zhuang Autonomous Region (No. 2014GXNSFAA118147), and the Clinical Key Specialized Subject Construction Project (Gynecology) of Guangxi Zhuang Autonomous Region (No. 2018-39)