Identification and potential value of candidate microRNAs in granulosa cells of polycystic ovary syndrome

Aberrant miR-3135b and miR-1273g-3p expression in the peripheral blood samples of BRCA1/2 (±) ovarian cancer patients

Ovarian cancer (OC) ranks as the eighth most prevalent malignancy among women globally. The short non-coding RNA molecules, microRNAs (miRNAs) target multiple mRNAs and regulate the gene expression. Here in this study, we aimed to validate miR-3135b and miR-1273g-3p as novel biomarkers for prognostic and diagnostic factor OC. After RNA isolation, we analyzed the miR-3135b and miR-1273g-3p expression in peripheral blood samples derived from 150 OC patients. Subsequently, we compared their expression levels with 100 healthy controls. The differences of miR-3135b and miR-1273g-3p expression were detected using the Quantitative Real Time-PCR (qRT-PCR) technique following miRNA-specific cDNA synthesis pursing miRNA separation. The miR-3135b and miR-1273g-3p were higher in OC patients who tested positive for BRCA1/2 compared to BRCA-negative patients, and healthy cases. The level of miR-3135b demonstrated a roughly 4.82-fold increase in OC patients in comparison to the healthy cases, while miR-1273g-3p expression exhibited a roughly 6.77-fold increase. The receiver operating characteristic (ROC) analysis has demonstrated the potential of miR-3135b and miR-1273g-3p as markers for distinguishing between OC patients and healthy controls. The higher expressions of miR-3135b and miR-1273g-3p could be associated with OC development. Moreover, miR-3135b may have a diagnostic potential and miR-1273g-3p may have both diagnostic and prognostic potential in OC cell differentiation. The string analysis has revealed an association between miR-1273g-3p and the MDM2 gene, suggesting a potential link to tumor formation through the proteasomal degradation of the TP53 tumor suppressor gene. Additionally, the analysis indicates an association of miR-1273g-3p with CHEK1, a gene involved in checkpoint-mediated cell cycle arrest. String analysis also indicates that miR-3135b is associated with the MAPK1 gene, causing activation of the oncogenesis cascade. In conclusion, miR-1273g-3p, and miR-3135b exhibit significant potential as diagnostic markers. However, further research is needed to comprehensively investigate these miRNAs diagnostic and predictive characteristics in a larger cohort.

Construction of a competing endogenous RNA network to identify drug targets against polycystic ovary syndrome

STUDY QUESTION

Would the construction of a competing endogenous RNA (ceRNA) network help identify new drug targets for the development of potential therapies for polycystic ovary syndrome (PCOS)?

SUMMARY ANSWER

Both Food and Drug Administartion (FDA)-approved and candidate drugs could be identified by combining bioinformatics approaches with clinical sample analysis based on our established ceRNA network.

WHAT IS KNOWN ALREADY

Thus far, no effective drugs are available for treating PCOS. ceRNAs play crucial roles in multiple diseases, and some of them are in current use as prognostic biomarkers as well as for chemo-response and drug prediction.

STUDY DESIGN, SIZE, DURATION

For the bioinformatics part, five microarrays of human granulosa cells were considered eligible after applying strict screening criteria and were used to construct the ceRNA network for target identification. For population-based validation, samples from 24 women with and without PCOS were collected from January 2021 to July 2021.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The public data included 27 unaffected women and 25 women with PCOS, according to the Rotterdam criteria proposed in 2003. The limma and RobustRankAggreg R packages were used to identify differentially expressed messenger RNAs and noncoding RNAs. Gene Ontology, Reactome and Kyoto Encyclopedia of Genes and Gemomes (KEGG) enrichment analyses were performed. A ceRNA network was constructed by integrating the differentially expressed genes and target genes. The population-based validation included human luteinized granulosa cell samples from 12 unaffected women and 12 women with PCOS. Quantitative real-time polymerase chain reaction was conducted to detect the levels of mRNAs and microRNAs (miRNAs). Connectivity map and computational model algorithms were implemented to predict therapeutic drugs from the ceRNA network. Additionally, we compared the predicted drugs with known clinical medications in DrugBank.

MAIN RESULTS AND THE ROLE OF CHANCE

A set of 10 mRNAs, 11 miRNAs and 53 long non-coding RNAs (lncRNAs) were differentially expressed. Functional enrichment analysis revealed the highest relevance to immune system-related biological processes and signalling pathways, such as cytokine secretion and leucocyte chemotaxis. A ceRNA consisting of two lncRNAs, two miRNAs and five mRNAs was constructed. Through network construction via bioinformatic analysis, we identified some already approved drugs (such as metformin) that could target some molecules in the network as potential drug candidates for PCOS.

LARGE SCALE DATA

Public sequencing data were obtained from GSE34526, GSE84376, GSE102293, GSE106724 and GSE114419, which have been deposited in the Gene Expression Omnibus database.

LIMITATIONS, REASONS FOR CAUTION

Experiments, such as immunoprecipitation, luciferase reporter assays and animal model studies, are needed to validate the potential targets in the ceRNA network before the identified drug candidates can be tested using cellular and animal model systems.

WIDER IMPLICATIONS OF THE FINDINGS

Our findings provide new bioinformatic insight into the possible pathogenesis of PCOS from ceRNA network analysis, which has not been previously studied in the human reproductive field. Our study also reveals some potential drug candidates for the future development of possible therapies against PCOS.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by grants from the National Key Research and Development Program of China (2021YFC2700400) and the National Natural Science Foundation of China (82001498). The authors have no conflicts of interest to disclose.

The Translational Role of miRNA in Polycystic Ovary Syndrome: From Bench to Bedside—A Systematic Literature Review

MicroRNAs (miRNAs) are small, non-coding RNAs that are essential for the regulation of post-transcriptional gene expression during tissue development and differentiation. They are involved in the regulation of manifold metabolic and hormonal processes and, within the female reproductive tract, in oocyte maturation and folliculogenesis. Altered miRNA levels have been observed in oncological and inflammatory diseases, diabetes or polycystic ovary syndrome (PCOS). Therefore, miRNAs are proving to be promising potential biomarkers. In women with PCOS, circulating miRNAs can be obtained from whole blood, serum, plasma, urine, and follicular fluid. Our systematic review summarizes data from 2010–2021 on miRNA expression in granulosa and theca cells; the relationship between miRNAs, hormonal changes, glucose and lipid metabolism in women with PCOS; and the potential role of altered miRNAs in fertility (oocyte quality) in PCOS. Furthermore, we discuss miRNAs as a potential therapeutic target in PCOS and as a diagnostic marker for PCOS.

The lncRNA-miRNA-mRNA ceRNA network in mural granulosa cells of patients with polycystic ovary syndrome: an analysis of Gene Expression Omnibus data

Background

Polycystic ovary syndrome (PCOS) is one of the most common endocrine abnormalities in women of reproductive age. In this study, we set out to construct a molecular long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) network according to the competitive endogenous RNA (ceRNA) theory and obtain insights into the related biological characteristics and pathways.

Methods

We downloaded two gene expression profile datasets of mural granulosa cells (MGCs) of women with PCOS and healthy women without PCOS (GSE84376 and GSE106724) from Gene Expression Omnibus (GEO) DataSets. Using GEO2R, we identified the mRNAs and non-coding RNAs with differential expression. The DIANA-microT-CDS algorithm was applied to predict the genes targeted by the differentially expressed miRNAs. The lncRNA-miRNA interactions were predicted using DIANA-LncBase v2. Then, we constructed the lncRNA-miRNA-mRNA network. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was employed to identify the functions and enriched pathways of the genes. Subsequently, STRING was used to construct the protein-protein interaction (PPI) network. cytoHubba in Cytoscape was used to rank the hub genes, and finally, PPI modules were screened with Cytoscape MCODE.

Results

There were 462 mRNAs, 2,464 lncRNAs, and 55 miRNAs which showed differential expression between the MGCs of patients with PCOS and those of healthy controls. Based on the PPI analysis, differentially expressed genes (DEGs) were significantly enriched in retinol metabolism, drug metabolism—cytochrome P450, malaria, the Hippo signaling pathway, and glycine, serine, and threonine metabolism. The ceRNA network contained 71 lncRNA nodes, 14 miRNA nodes, and 69 mRNA nodes, as well as 167 edges. We identified some novel genes and non-coding RNAs that might be involved in PCOS, including CD163, MRC1, VSIG4, CCL2, CCR2, SPP1, hsa-miR-3135b, hsa-miR-4649-3p, hsa-miR-1231, hsa-miR-3609, and hsa-miR-4433b-3p.

Conclusions

This study identified a novel lncRNA-miRNA-mRNA network based on the ceRNA mechanism in PCOS. Some novel genes and non-coding RNAs that may be involved in the occurrence and development of PCOS were excavated, including CD163, MRC1, VSIG4, CCL2, CCR2, SPP1, hsa-miR-3135b, hsa-miR-4649-3p, hsa-miR-1231, hsa-miR-3609, and hsa-miR-4433b-3p. However, our findings need to be validated by in vivo and in vitro experiments.

Bioinformatics Analysis of ceRNA Network Related to Polycystic Ovarian Syndrome

Introduction

Polycystic ovary syndrome (PCOS) is caused by the hormonal environment in utero, abnormal metabolism, and genetics, and it is common in women of childbearing age. A large number of studies have reported that lncRNA is important to the biological process of cancer and can be used as a potential prognostic biomarker. Thus, we studied lncRNAs' roles in PCOS in this article.

Methods

We obtained mRNAs', miRNAs', and lncRNAs' expression profiles in PCOS specimens and normal specimens from the National Biotechnology Information Gene Expression Comprehensive Center database. The EdgeR software package is used to distinguish the differentially expressed lncRNAs, miRNAs, and mRNAs. Functional enrichment analysis was carried out by the clusterProfiler R Package, and the lncRNA-miRNA-mRNA interaction ceRNA network was built in Cytoscape plug-in BiNGO and Database for Annotation, Visualization, and Integration Discovery (DAVID), respectively.

Results

We distinguished differentially expressed RNAs, including 1087 lncRNAs, 14 miRNAs, and 566 mRNAs in PCOS. Among them, 410 lncRNAs, 11 miRNAs, and 185 mRNAs were contained in the ceRNA regulatory network. The outcomes from Gene Ontology (GO) analysis showed that the differentially expressed mRNAs (DEMs) were mainly enriched in response to the maternal process involved in female pregnancy, morphogenesis of embryonic epithelium, and the intracellular steroid hormone receptor signaling pathway. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis data showed that DEMs were primarily enriched in pathways related to the TGF-β signaling pathway, Type I diabetes mellitus, and glycolysis/gluconeogenesis. In addition, we chose NONHSAT123397, ENST00000564619, and NONHSAT077997 as key lncRNAs due to their high bearing on PCOS.

Conclusion

ceRNA networks play an important role in PCOS. The research indicated that specific lncRNAs were related to PCOS development. NONHSAT123397, ENST00000564619, and NONHSAT077997 could be regarded as potential diagnostic mechanisms and biomarkers for PCOS. This discovery might provide more effective and more novel insights into the mechanisms of PCOS worthy of further exploration.

Identification of critical miRNAs and mRNAs associated with polycystic ovary syndrome

AIM

Polycystic ovary syndrome (PCOS) is a complicated endocrine and metabolic abnormality diseases common in women of child-bearing age. This study aims to screen out critical miRNAs and mRNAs associated with PCOS, which may be conducive to offer novel insights and treatment for the diseases.

METHODS

Three mRNA datasets and one miRNA dataset derived from granulosa cells of patients with PCOS and normal controls were downloaded to obtain the differentially expressed mRNAs (DEmRNAs) and miRNAs (DEmiRNAs). Then, DEmiRNA-target DEmRNAs analysis and functional annotation of DEmiRNA-target DEmRNAs were performed. Quantitative real time polymerase chain reaction (qRT-PCR) validation of the expression of the selected DEmRNAs and DEmiRNAs were performed.

RESULTS

A total of 1643 DEmRNAs, 88 DEmiRNAs, 2406 DEmiRNA (down)-DEmRNA (up), and 2179 DEmiRNA (up)-DEmRNA (down) pairs were obtained. The functional annotation of DEmiRNA-target DEmRNAs revealed that C-type lectin receptor signaling pathway, Steroid biosynthesis and Galactose metabolism were significantly enriched KEGG pathways.

CONCLUSION

These findings may provide make contribution to understanding PCOS pathogenesis, diagnosis, or treatment.

Non-coding RNAs in polycystic ovary syndrome: a systematic review and meta-analysis

BACKGROUND

Genetic, environmental and epigenetical factors may play important roles in the pathogenesis of polycystic ovary syndrome (PCOS), however the etiology of PCOS remains unclear. Studies indicated that non-coding RNAs (ncRNAs) were involved in the occurrence and development of PCOS. Thus, we aim to perform a systematic review and meta-analysis to investigate the presence and dysregulated expression of ncRNAs in human PCOS.

METHODS

We searched in PubMed, Medline, Web of Science and Embase until July 2019 and summarized all eligible publications focusing on microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs) and small interfering RNAs (siRNAs) in PCOS.

RESULTS

Sixty-seven articles were included in our systematic review and 9 articles were included in meta-analysis. There is little overlap between studies when comparing miRNA profiles. Sensitivity analysis showed that the expression of miR-93 was upregulated in PCOS patients (WMD 0.75, P < 0.00001), without heterogeneity among remaining studies (I2 = 0%).

CONCLUSION

A large number of ncRNAs with altered levels were observed in plasma, serum, follicular fluid, granulosa cells or other issues from PCOS patients. Aberrant ncRNAs expression in PCOS may lead to aberrant steroidogenesis, adipocyte dysfunction, altered ovarian cell proliferation and/or apoptosis and have the potential to be used as diagnostic biomarkers.

Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis

BACKGROUND

This study was aimed at mining crucial long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) for the development of polycystic ovary syndrome (PCOS) based on the coexpression and the competitive endogenous RNA (ceRNA) theories and investigating the underlying therapeutic drugs that may function by reversing the expression of lncRNAs, miRNAs, and mRNAs.

METHODS

RNA (GSE106724, GSE114419, GSE137684, and GSE138518) or miRNA (GSE84376 and GSE138572) expression profile datasets of PCOS patients were downloaded from the Gene Expression Omnibus database. The weighted gene coexpression network analysis (WGCNA) using four RNA datasets was conducted to construct the lncRNA-mRNA coexpression networks, while the common differentially expressed miRNAs in two miRNA datasets and module RNAs were used to establish the ceRNA network. A protein-protein interaction (PPI) network was created to explore the potential interactions between genes. Gene Ontology and KEGG pathway enrichment analyses were performed to explore the functions of genes in networks. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) analyses were performed to identify potential therapeutic agents for PCOS.

RESULTS

Three modules (black, magenta, and yellow) were identified to be PCOS-related after WGCNA analysis, in which KLF3-AS1-PLCG2, MAPKAPK5-AS1-MAP3K14, and WWC2-AS2-TXNIP were important coexpression relationship pairs. WWC2-AS2-hsa-miR-382-PLCG2 was a crucial ceRNA loop in the ceRNA network. The PPI network showed that MAP3K14 and TXNIP could interact with hub genes PLK1 (degree = 21) and TLR1 (degree = 18), respectively. These genes were enriched into mitosis (PLK1), immune response (PLCG2 and TLR1), and cell cycle (TXNIP and PLK1) biological processes. Ten small molecule drugs (especially quercetin) were considered to be therapeutical for PCOS.

CONCLUSION

Our study may provide a novel insight into the mechanisms and therapy for PCOS.