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. 2018 Oct;16(4):5375-5382.
doi: 10.3892/ol.2018.9243. Epub 2018 Jul 31.

Identifying miRNA-mRNA regulation network of major depressive disorder in ovarian cancer patients

Chengjiang Wu  1   2 , Yangjing Zhao  2 , Yuefang Liu  2   3 , Xinxin Yang  2 , Meina Yan  2 , Yujiao Min  2 , Zihui Pan  2 , Shali Qiu  2 , Sheng Xia  2 , Jun Yu  4 , Peifang Yang  4 , Bing Wan  1 , Qixiang Shao  2
Affiliations

Identifying miRNA-mRNA regulation network of major depressive disorder in ovarian cancer patients

Chengjiang Wu et al. Oncol Lett. 2018 Oct.

Abstract

Major depression disorder (MDD) has become increasingly common in patients with ovarian cancer, which complicates the treatment course. The microRNA (miRNA)-mRNA regulation network may help elucidate the potential mechanism of MDD in ovarian cancer. The differentially expressed microRNAs (DEmiRs) and mRNAs (DEmRNAs) were therefore identified from the GSE61741, GSE58105 and GSE9116 ovarian cancer datasets using GEO2R. The target genes of the DEmiRs were then obtained using the TargetScan, microRNAorg, microT-CDS, miRDB and miRTarBase prediction tools. The DAVID program was used to identify the KEGG pathways of target genes, and the core genes of major depressive disorder (MDD) were identified using the Kaplan-Meier Plotter for ovarian cancer. A total of 5 DEmiRs (miR-23b-3p, miR-33b-3p, miR-1265, miR-933 and miR-629-5p) were obtained from GSE61741 and GSE58105. The target genes of these DEmiRs were enriched in pathways that were considered high risk for developing MDD in ovarian cancer. A total of 11 risk genes were selected from these pathways as the core genes in the miRNA-mRNA network of MDD in ovarian cancer, and eventually identified the following 12 miRNA-mRNAs pairs: miR-629-5p-FGF1, miR-629-5p-AKT3, miR-629-5p-MAGI2, miR-933-BDNF, miR-933-MEF2A, miR-23b-3p-TJP1, miR-23b-3p-JMJD1, miR-23b-3p-APAF1, miR-23b-3p-CAB39, miR-1265-CDKN1B, miR-33b-3p-CDKN1B, and miR-33b-3p-F2R. These results may provide novel insights into the mechanisms of developing MDD in ovarian cancer patients.

Keywords: KEGG pathway; gene ontology; major depressive disorder; miRNA-mRNA regulation network; ovarian cancer.

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Figures

Figure 1.
Figure 1.
Intersection of miRNA target genes predicted by five kinds of software. (A) miR-23b-3p, (B) miR-33b-3p, (C) miR-629-5p, (D) miR-933 and (E) miR-1265.
Figure 2.
Figure 2.
Top 15 biological process of the risk genes.
Figure 3.
Figure 3.
Top 20 pathway enrichment of the risk genes.
Figure 4.
Figure 4.
miRNA-risk genes-pathways regulation network. The blue circle represents target genes belonging not to the DEGs of GSE9116; The green circle represents downregulated target genes existing in DEGs of GSE9116; The red circle represents upregulated target genes existing in DEGs of GSE9116; The green triangle represents downregulated risk genes; The red triangle represents upregulated risk genes; The red hexagonal represents upregulated DEmiRs; The green hexagonal represents downregulated DEmiRs. The green square represents risk signaling pathway; The red square represents non-risk signaling pathway.
Figure 5.
Figure 5.
Kaplan-Meier curves of overall survival for 11 core genes. (A) AKT3, (B) CAB39, (C) CDKN1B, (D) F2R, (E) FGF1, (F) JMJD1C, (G) MAGI2, (H) MEF2A, (I) TJP1, (J) APAF1 and (K) BDNF.
Figure 6.
Figure 6.
miRNA-core gene-risk signaling pathway regulation network. The red hexagonal represents upregulated DEmiRs; The green hexagonal represents downregulated DEmiRs; The green triangle represents downregulated core genes; The red triangle represents upregulated core genes; The bule square represents risk signaling pathway. DEmiRs, differentially expressed microRNAs.
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