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Homeobox protein Emx2 is a transcription factor that is encoded by the EMX2 gene. In this study, using data from the Cancer Genome Atlas-Thyroid Cancer (TCGA-THCA), we aimed to examine the expression profile of EMX2 and its antisense transcript EMX2OS in papillary thyroid cancer (PTC), their prognostic value and potential regulatory networks. Results showed that in the three variants of PTC, EMX2 was significantly downregulated in classical PTC, while EMX2OS were significantly downregulated in follicular and classical PTC, compared with adjacent normal tissues. Kaplan-Meier survival curves showed that EMX2 and EMX2OS expression was not related to RFS in follicular PTC. In comparison, the high EMX2 or EMX2OS group were associated with better RFS compared with their respective low expression group in classical PTC (p = 0.007 and 0.004 respectively). Correlation analysis showed that EMX2 and EMX2OS were highly co-expressed in PTC tissues (Spearman's r = 0.83). By performing stepwise regression, we found that EMX2OS was better than EMX2 in predicting RFS in classical PTC. Multivariate analysis confirmed that high EMX2OS expression was an independent indicator of favorable RFS in classical PTC (HR: 0.239, 95%CI: 0.100 = 0.569, p = 0.001), after adjustment of pathological stages and residual tumors. By performing in silico analysis, we found that the genes co-expressed with EMX2 or EMX2OS were highly overlapped. KEGG pathway analysis showed that these genes were enriched in the ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling, protein digestion and absorption and proteoglycans in cancer pathways, which are closely related to cancer initiation and progression. Based on the findings, we infer that decreased EMX2OS expression might be a valuable prognostic biomarker of unfavorable RFS in classical PTC.
Pubmed ID: 30576338
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View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
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