Investigating novel genes potentially involved in endometrial adenocarcinoma using next-generation sequencing and bioinformatic approaches

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Abstract

Endometrial cancer is one of the most common cancers in women worldwide, affecting more than 300,000 women annually. Dysregulated gene expression, especially those mediated by microRNAs, play important role in the development and progression of cancer. This study aimed to investigate differentially expressed genes in endometrial adenocarcinoma using next generation sequencing (NGS) and bioinformatics. The gene expression profiles and microRNA profiles of endometrial adenocarcinoma (cancer part) and normal endometrial tissue (non-cancer part) were assessed with NGS. We identified 56 significantly dysregulated genes, including 47 upregulated and 9 downregulated genes, in endometrial adenocarcinoma. Most of these genes were associated with defense response, response to stimulus, and immune system process, and further pathway analysis showed that human papillomavirus infection was the most significant pathway in endometrial adenocarcinoma. In addition, these genes were also associated with decreased cell death and survival as well as increased cellular movement. The analyses using Human Protein Atlas, identified 6 genes (PEG10, CLDN1, ASS1, WNT7A, GLDC, and RSAD2) significantly associated with poorer prognosis and 3 genes (SFN, PIGR, and CDKN1A) significantly associated with better prognosis. Combining with the data of microRNA profiles using microRNA target predicting tools, two significantly dysregulated microRNA-mediated gene expression changes in endometrial adenocarcinoma were identified: downregulated hsa-miR-127-5p with upregulated CSTB and upregulated hsa-miR-218-5p with downregulated HPGD. These findings may contribute important new insights into possible novel diagnostic or therapeutic strategies for endometrial adenocarcinoma.

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Tang, F. H., Chang, W. A., Tsai, E. M., Tsai, M. J., & Kuo, P. L. (2019). Investigating novel genes potentially involved in endometrial adenocarcinoma using next-generation sequencing and bioinformatic approaches. International Journal of Medical Sciences, 16(10), 1338–1348. https://doi.org/10.7150/ijms.38219

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