Four differentially expressed exosomal miRNAs as prognostic biomarkers and therapy targets in endometrial cancer: Bioinformatic analysis

Abstract

Endometrial cancer (EC) is one of the most common gynecological malignancies worldwide. Accumulated evidence has demonstrated exosomes of cancer cells carry microRNAs (miRNAs) to nonmalignant cells to induce metastasis. Our study aimed to find possible biomarkers of EC. Data for miRNA expression related with exosome from EC patients were downloaded from The Cancer Genome Atlas database, and the miRNA expression profiles associated with exosomes of EC were downloaded from the National Center for Biotechnology Information. We used different algorithms to analyze the differential miRNA expression, infer the relative proportion of immune infiltrating cells, predict chemotherapy sensitivity, and comprehensively score each gene set to evaluate the potential biological function changes of different samples. The gene ontology analysis and Kyoto encyclopedia of genome genomics pathway analysis were performed for specific genes. A total of 13 differential miRNAs were identified, of which 4 were up-regulated. The 4 miRNAs, that is hsa-miR-17-3p, hsa-miR-99b-3p, hsa-miR-193a-5p, and hsa-miR-320d, were the hub exosomal miRNAs that were all closely related to the clinic phenotypes and prognosis of patients. This study preliminarily indicates that the 4 hub exosomal miRNAs (hsa-miR-17-3p, hsa-miR-99b-3p, hsa-miR-193a-5p, and hsa-miR-320d) could be used as prognostic biomarkers or therapy targets in EC. Further studies are required to make sure of their real feasibility and values in the EC clinic and the relative research.

Figure 1.

(A) Volcanic of differential miRNAs [red represented the up-regulated miRNA while green represented the down-regulated miRNA]. (B) Heatmap of differential miRNAs [yellow represented the up-regulated miRNA while green represented the down-regulated miRNA].

Figure 2.

miRNA-mRNA network. [higher expression is red, lower expression is green].

Figure 3.

The function enrichment analysis of target mRNA (Metascape). (A) Barplot of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enriched terms colored by P-values. (B) Network of GO and KEGG enriched terms colored by P-value, where terms containing more target mRNA tend to have a more significant P-value.

Figure 4.

Survival curve produced by data obtained by KM-plot. (A) hsa-miR-17-3p. (B) hsa-miR-99b-3p. (C) hsa-miR-193a-5p. (D) hsa-miR-320d.

Figure 5.

Predicting the prognosis of EC used combined effect analysis paired expression of any 2 genes. (A) hsa-miR-17-3p and hsa-miR-99b-3p. (B) hsa-miR-17-3p and hsa-miR-193a-5p. (C) hsa-miR-17-3p and hsa-miR-320d. (D) hsa-miR-99b-3p and hsa-miR-320d. (E) hsa-miR-99b-3p and hsa-miR-193a-5p. (F) hsa-miR-193a-5p and hsa-miR-320d.

Figure 6.

Nomogram used to predict the 3-year/5-year survival rate of EC patients.

Figure 7.

GSVA analysis displaying pathway differences between high expression and low expression. (A) hsa-miR-17-3p. (B) hsa-miR-99b-3p. (C) hsa-miR-193a-5p. (D) hsa-miR-320d.