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. 2019 Sep 7;16(10):1338-1348.
doi: 10.7150/ijms.38219. eCollection 2019.

Investigating Novel Genes Potentially Involved in Endometrial Adenocarcinoma using Next-Generation Sequencing and Bioinformatic Approaches

Affiliations

Investigating Novel Genes Potentially Involved in Endometrial Adenocarcinoma using Next-Generation Sequencing and Bioinformatic Approaches

Feng-Hsiang Tang et al. Int J Med Sci. .

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.

Keywords: CSTB; HPGD; bioinformatics; endometrial cancer; miR-127-5p; miR-218-5p; next generation sequencing; papillomavirus.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interest exists.

Figures

Figure 1
Figure 1
Flow chart of the study. Abbreviation: STRING, Search Tool for the Retrieval of Interacting Genes; DAVID, Database for Annotation, Visualization and Integrated Discovery; KEGG, Kyoto Encyclopedia of Genes and Genomes; IPA, Ingenuity® Pathway Analysis.
Figure 2
Figure 2
Overview of the gene expression profiles in endometrial adenocarcinoma. (A) The density plot illustrates smoothed frequency distribution of the fragments per kilobase of transcript per million mapped reads (FPKM) among the cancer part and non-cancer part. (B) The volcano plot of differential gene expression patterns of the cancer part vs. non-cancer part. Significantly dysregulated genes in endometrial adenocarcinoma (cancer part vs. non-cancer part) (those with -log10(q-value) > 1.3 and fold change > 2) were shown in green (downregulated) or orange (upregulated).
Figure 3
Figure 3
Protein-protein interaction network analysis of the dysregulated genes in endometrial adenocarcinoma. The 56 significantly dysregulated genes (47 upregulated and 9 downregulated) were input into the Search Tool for the Retrieval of Interacting Genes (STRING) database for protein-protein interaction (PPI) network analysis. The minimum required interaction score was set to the medium confidence (score = 0.400). Nodes represent proteins and edges represent protein-protein associations. Nodes without edges are not displayed. This analysis obtained a highly interactive PPI network of 56 nodes and 67 edges, with PPI enrichment p value of < 1.0 х 10-16. Most genes in the PPI network were associated with three biological pathways, including defense response (19 genes, shown in blue), response to stimulus (44 genes, shown in green), and immune system process (21 genes, shown in red).
Figure 4
Figure 4
Disease and function analysis of the significantly dysregulated genes in endometrial adenocarcinoma. Using Ingenuity® Pathway Analysis, the associated diseases and functions of the significantly dysregulated genes in endometrial adenocarcinoma were analyzed. Significant diseases and functions (those with a p value < 0.05) are shown in the outer circle, while their categories are shown in the inner circle. The numbers show the counts of involved genes. The area of each disease and function reflects its significant level, based on their -log10(p-value). Downregulated diseases and functions are shown in gray color, while upregulated ones are shown in orange and red colors.
Figure 5
Figure 5
Possible genes associated with the prognosis of endometrial cancer as predicted by the Human Protein Atlas. The prognosis-predicting values of the 56 significantly dysregulated genes in endometrial cancer were assessed using the Human Protein Atlas. The 12 Kaplan-Meier curves (with log-rank p values) show the genes significantly associated with prognosis, including 6 genes associated with poorer prognosis and 3 genes associated with better prognosis.
Figure 5
Figure 5
Possible genes associated with the prognosis of endometrial cancer as predicted by the Human Protein Atlas. The prognosis-predicting values of the 56 significantly dysregulated genes in endometrial cancer were assessed using the Human Protein Atlas. The 12 Kaplan-Meier curves (with log-rank p values) show the genes significantly associated with prognosis, including 6 genes associated with poorer prognosis and 3 genes associated with better prognosis.

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