Endometriosis (EMS) is defined as the presence of endometrial glands and stroma in an abnormal or ectopic location outside the uterine cavity. It occurs in approximately 6–10% of reproductive aged women and is present in 20–50% in women with infertility and 71–87% in women with chronic pelvic pain [
As we all know, decidualization is a physiological process involving the function and morphological changes of endometrial stromal cells and the reconstruction of extracellular matrix [
Nowadays, many microarray studies have shown that miRNAs are differentially expressed in eutopic endometrial tissues with EMS and ectopic endometrial tissues with EMS [
The microarray data of GSE75423 and GSE75422 have been previously used to reveal the mRNA and miRNA expression profiles in decidualized and nondecidualized endometriotic cyst stromal cells (ECSCs) [
(a) The workflow of the study. (b) The volcano of the miRNAs between 4 decidualized ECSCs and 4 untreated ECSCs. (c) The volcano of the mRNAs between 4 decidualized ECSCs and 4 untreated ECSCs. Red represents upregulated miRNAs/mRNAs, and blue represents downregulated miRNAs/mRNAs. The names of the top 10 genes with the lowest
We use the keywords of “endometriosis” and “decidualization” to retrieve data sets about ectopic endometriosis and decidualization in GEO database, which is created and maintained by NCBI. Then, the microarray data of GSE75423 (mRNAs, 4 untreated ECSCs and 4 decidualized ECSCs; Platforms: GPL13497, Agilent-026652 Whole Human Genome Microarray 4x44K v2) and GSE75422 (miRNAs, 4 untreated ECSCs and 4 decidualized ECSCs; Platforms: GPL18402, Agilent-046064 Unrestricted_Human_miRNA_V19.0 Microarray) were collected and downloaded for further analysis.
The miRNA-mRNA pairs were predicted via miRDB (version 7.0;
By comparing the predicted TGs of DEMs with DEGs, only the overlapping genes and their interaction pairs were selected and be used to construct a miRNA-mRNA network.
GO is widely used in annotating genes, gene products, and sequences. KEGG is a comprehensive database for biological interpretation of genome sequences and other high-throughput data. In order to depict the features of the overlapping genes, the GO and KEGG pathway enrichment analysis of overlapping genes were performed by clusterProfiler R package with the criterion:
The online database of STRING (
As shown in Figure
(a) Hierarchical clustering heat map of top 50 DEMs. (b) Hierarchical clustering heat map of 29 DEMs. Red indicates the upregulated expression of DEMs/DEGs. Green indicates the downregulated expression of DEMs/DEGs. (c) The overlapping genes of the DEGs and target genes of DEMs.
Through three online databases, twenty-two miRNAs related to 606 mRNA pairs were obtained (as shown in the supplement (see available
As shown in Figure
miRNA-mRNA network of overlapping genes.
miRNA | mRNA | log FC |
---|---|---|
hsa-miR-155-5p | IRF2BP2 | 1.278440075 |
hsa-miR-155-5p | TRPS1 | 1.005964272 |
hsa-miR-181c-5p | KLF6 | -1.557718922 |
hsa-miR-18a-5p | PDE4D | 3.276145824 |
hsa-miR-30b-5p | CELSR3 | 1.913555396 |
hsa-miR-30b-5p | DDAH1 | -1.029581059 |
hsa-miR-30b-5p | MYBL2 | -2.929273223 |
hsa-miR-30b-5p | PIP4K2A | -1.379812917 |
hsa-miR-378a-3p | IGF1R | 1.382426315 |
hsa-miR-7-5p | ASXL1 | -1.135463993 |
hsa-miR-7-5p | IGSF8 | 1.170019265 |
hsa-miR-7-5p | POLE4 | -1.04694931 |
hsa-miR-766-3p | FUS | -1.404370443 |
hsa-miR-766-3p | PDCL3 | -1.658095629 |
Through analysis, one hundred and sixty-six GO terms were enriched, and the first 10 GO terms with the most obvious enrichment are shown in Figure
(a) GO enrichment analysis of overlapping genes. (b) KEGG pathway enrichment analysis of overlapping genes.
Pathway enrichment analyses of overlapping genes.
ID | Description | Gene ID | |
---|---|---|---|
hsa05202 | Transcriptional misregulation in cancer | 0.007683802 | IGF1R/FUS |
hsa03410 | Base excision repair | 0.024668593 | POLE4 |
hsa03030 | DNA replication | 0.026885814 | POLE4 |
hsa03420 | Nucleotide excision repair | 0.034979724 | POLE4 |
hsa04913 | Ovarian steroidogenesis | 0.036445299 | IGF1R |
hsa04730 | Long-term depression | 0.04447285 | IGF1R |
hsa04213 | Longevity regulating pathway-multiple species | 0.045926399 | IGF1R |
As shown in Figure
A miRNA-mRNA network. Circle represents mRNA and triangle represents miRNA. The lines represent the connection within them. It is worth noting that there are only two genes (IGF1R and KLF6) in the PPI network. Red represents upregulated miRNAs/mRNAs, and blue represents downregulated miRNAs/mRNAs.
EMS is a common gynecological disease in women, which can lead to symptoms such as pelvic pain and female infertility. At the same time, the endometrial tissue undergoes periodic decidualization during the women’s menstrual cycle. It is worth noting that the decidualization of ectopic endometrial tissue in patients with EMS is easily confused with malignant ovarian tumors, and its specific molecular biological mechanism is still unclear. Therefore, an in-depth study of the key genes and mechanisms of ectopic endometrial decidualization is of great significance for the diagnosis and treatment of EMS.
Recently, much attention has been focused on miRNAs, which can regulate gene expression at the post-transcriptional level, thereby further affecting cell proliferation, migration and invasion, signal transduction, autophagy, and apoptosis [
In this study, we employed an integrative methodology to construct a miRNA-mRNA network and analyzed undiscovered pathways possibly regulated by those miRNAs. In our view, this innovative strategy of analysis may help to shed light on the genetic background of the disease, suggesting further molecular investigations in novel pathogenic mechanisms. Firstly, we selected 29 DEMs and 523 DEGs as our subsequent research object. Then, we constructed a miRNA-mRNA network and found 14 overlapping genes in miRNA-mRNA network may participate in the process of decidualization of ECSCs through metabolism (e.g., retinoic acid receptor binding, phosphatidylinositol-mediated signaling, inositol lipid-mediated signaling, ovarian steroidogenesis, and arginine catabolic process) and immunity (such as B cell differentiation). Many immunological factors are known to contribute significantly to the pathogenesis and pathophysiology of EMS, and both chronic local inflammation and autoantibodies in EMS share numerous similarities with autoimmune diseases (AD). Previous studies have shown that soluble chemoattractant proteins expressed in ectopic tissues of patients with EMS can recruit innate immune cells (such as neutrophils, natural killer cells, and macrophages) to accumulate in ectopic endometrial tissues [
In terms of metabolism, many studies have reported that decidualization of eutopic endometrium is related to metabolism, such as PKM2 and BPA [
In the miRNA-mRNA network, miRNA-30d-5p, miRNA-30b-5p, miRNA-181c-5p, and miRNA-766-3p were highly expressed in decidual ECSCs, while
Among the 14 overlapping genes, we found 6 downregulated mRNAs and 8 upregulated mRNAs in decidualized ECSCs. Some of them have been reported to play important roles in the development of tumor proliferation, apoptosis, and metastasis, such as
Nowadays, many studies have investigated the role of miRNAs in EMS [
In conclusion, through microarray of miRNA-mRNA expression profiles, we discovered the miRNAs, potentially regulated genes, and possible pathways associated with decidualization of ECSCs. The molecular roles that these dysregulated miRNAs play in EMS were not completely elucidated. Our study, however, had some obvious limitations. The further functional experiments are needed to back and validate the function of these miRNAs in the decidualization of ECSCs.
The expression data associated with this article is available on GEO databases (
The funder had no role in the study design, data collection, and analysis, except for bioinformatics training, writing the manuscript, and decision to publish.
The authors declare that they have no competing interests.
JZL and BZ performed the comparative analysis using bioinformatics tools. CY participated in the data analysis and discussion. JZL and BZ interpreted the results and wrote the manuscript. QHC organized and supervised the project. All authors read and approved the final manuscript. Junzui Li and Bin Zhao contributed equally to this work.
This work was financially supported by the National Key R&D Program of China (SQ2017YFSF080005) and the National Science Foundation of China (No. 81871145).
The first table named “miRNA-mRNA pairs” is a supplement to the manuscript. The second table named “GO enrichment analysis” and the third table named “KEGG enrichment analysis” are used.