Bioinformatics searching of diagnostic markers and immune infiltration in polycystic ovary syndrome

Homeobox regulator Wilms Tumour 1 is displaced by androgen receptor at cis-regulatory elements in the endometrium of PCOS patients

Decidualisation, the process whereby endometrial stromal cells undergo morphological and functional transformation in preparation for trophoblast invasion, is often disrupted in women with polycystic ovary syndrome (PCOS) resulting in complications with pregnancy and/or infertility. The transcription factor Wilms tumour suppressor 1 (WT1) is a key regulator of the decidualization process, which is reduced in patients with PCOS, a complex condition characterized by increased expression of androgen receptor in endometrial cells and high presence of circulating androgens. Using genome-wide chromatin immunoprecipitation approaches on primary human endometrial stromal cells, we identify key genes regulated by WT1 during decidualization, including homeobox transcription factors which are important for regulating cell differentiation. Furthermore, we found that AR in PCOS patients binds to the same DNA regions as WT1 in samples from healthy endometrium, suggesting dysregulation of genes important to decidualisation pathways in PCOS endometrium due to competitive binding between WT1 and AR. Integrating RNA-seq and H3K4me3 and H3K27ac ChIP-seq metadata with our WT1/AR data, we identified a number of key genes involved in immune response and angiogenesis pathways that are dysregulated in PCOS patients. This is likely due to epigenetic alterations at distal enhancer regions allowing AR to recruit cofactors such as MAGEA11, and demonstrates the consequences of AR disruption of WT1 in PCOS endometrium.

Identification and validation of senescence-related genes in polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome (PCOS) is an exceedingly intractable issue affecting female endocrine and reproductive health. However, the etiology and intricate pathological mechanisms of PCOS remain unclear. Nowadays, aging was found to share multiple common pathological mechanisms with PCOS, which causes probing into the pathogenesis of PCOS from senescence. However, no bioinformatics analyses have specifically focused on connection between PCOS and ovarian aging.

METHODS

Differentially expressed aging-related genes in PCOS were identified and then analyzed using function enrichment method. Hub genes were determined based on multiple algorithms, and expression validation of hub genes was performed in both datasets and experiments (human granulosa-like tumor cell line, KGN; human Granulosa Cell, hGCs). Finally, a transcription factor-miRNA-gene network of hub genes was constructed.

RESULTS

Here, we identified 73 aging-related differential expression genes (ARDEGs) by intersecting DEGs in PCOS and senescence-related gene set. Furthermore, we performed biological functions and potential pathways of ARDEGs and potential hub genes were also screened by multiple algorithms. From the perspective of immune dysfunction, we analyzed the correlation between PCOS and immune cells. Finally, TF-miRNA-gene networks were constructed. Finally, TF-miRNA-gene networks were constructed.

CONCLUSIONS

Our work aimed to elucidate the relation between PCOS and cellular senescence based on bioinformatics strategy, deepening the understanding of mechanisms and to seek for novel therapy strategies for improving reproductive lifespan and female health. Exploring the potential molecular mechanism of cell aging in PCOS is expected to bring a new breakthrough for PCOS diagnosis and therapy strategies. And this, might deepen our understanding about intricate mechanisms of ovarian aging.

A novel model based on necroptosis to assess progression for polycystic ovary syndrome and identification of potential therapeutic drugs

Background

Polycystic ovary syndrome (PCOS), a common endocrine and reproductive disorder, lacks precise diagnostic strategies. Necroptosis was found to be crucial in reproductive and endocrine disorders, but its function in PCOS remains unclear. We aimed to identify differentially diagnostic genes for necroptosis (NDDGs), construct a diagnostic model to assess the progression of PCOS and explore the potential therapeutic drugs.

Methods

Gene expression datasets were combined with weighted gene co-expression network analysis (WGCNA) and necroptosis gene sets to screen the differentially expressed genes for PCOS. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a necroptosis-related gene signatures. Independent risk analyses were performed using nomograms. Pathway enrichment of NDDGs was conducted with the GeneMANIA database and gene set enrichment analysis (GSEA). Immune microenvironment analysis was estimated based on ssGSEA algorithm analysis. The Comparative Toxicogenomics Database (CTD) was used to explore potential therapeutic drugs for NDDGs. The expression of NDDGs was validated in GSE84958, mouse model and clinical samples.

Results

Four necroptosis-related signature genes, IL33, TNFSF10, BCL2 and PYGM, were identified to define necroptosis for PCOS. The areas under curve (AUC) of receiver operating characteristic curve (ROC) for training set and validation in diagnostic risk model were 0.940 and 0.788, respectively. Enrichment analysis showed that NDDGs were enriched in immune-related signaling pathways such as B cells, T cells, and natural killer cells. Immune microenvironment analysis revealed that NDDGs were significantly correlated with 13 markedly different immune cells. A nomogram was constructed based on features that would benefit patients clinically. Several compounds, such as resveratrol, tretinoin, quercetin, curcumin, etc., were mined as therapeutic drugs for PCOS. The expression of the NDDGs in the validated set, animal model and clinical samples was consistent with the results of the training sets.

Conclusion

In this study, 4 NDDGs were identified to be highly effective in assessing the progression and prognosis of PCOS and exploring potential targets for PCOS treatment.

N6-methyladenosine regulator-mediated methylation modification patterns and immune infiltration characterization in Polycystic Ovary Syndrome (PCOS)

BACKGROUND

Polycystic ovary syndrome (PCOS) is a multisystem-related disease whose pathophysiology is still unclear. Several regulators of N6-methyladenosine (m6A) modification were confirmed to play a regulatory role in PCOS. Nonetheless, the roles of m6A regulators in PCOS are not fully demonstrated.

MATERIALS AND METHODS

Four mRNA expression profiling microarrays were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed m6A regulators between PCOS and normal patients were identified by R software. A random forest modal and nomogram were developed to assess the relationship between m6A regulators and the occurrence risk of PCOS. A consensus clustering method was utilized to distinctly divide PCOS patients into two m6A subtypes (m6A cluster A/B). The patterns of differential expression and immune infiltration were explored between the two m6A clusters.

RESULTS

In this study, 22 significant m6A regulators were identified between healthy controls and PCOS patients. The random forest model determined three optimal m6A regulators which are related to the occurrence risk of PCOS, including YTHDF1, RBM15 and METTL14. A nomogram was established based on these genes, and its predictive reliability was validated by decision curve analysis. The consensus clustering algorithm distinctly divided PCOS cases into two m6A subtypes. The ssGSEA algorithm found that the immune infiltration was markedly enriched in m6A cluster B than in cluster A. The m6A-pattern related differentially expressed genes (DEGs) of the two m6A subtypes were demonstrated by differential expression analysis. We found that they were enriched in immune-related genes and various infection pathways. Based on the m6A-pattern related DEGs, the PCOS patients were classified into two m6A-pattern related genomic subtypes (gene clusters A and B).

CONCLUSIONS

The present study provided evidence concerning the different modification patterns of m6A regulators in PCOS compared with normal patients. This study will help clarify the overall impact of m6A modification patterns and related immune infiltration on PCOS.