A Novel Genes Signature Associated with the Progression of Polycystic Ovary Syndrome

Assessment of the Effect of Leonurine Hydrochloride in a Mouse Model of PCOS by Gene Expression Profiling

Polycystic ovary syndrome (PCOS) is an endocrine disease commonly associated with metabolic disorders in females. Leonurine hydrochloride (Leo) plays an important role in regulating immunity, tumours, uterine smooth muscle, and ovarian function. However, the effect of Leo on PCOS has not been reported. Here, we used dehydroepiandrosterone to establish a mouse model of PCOS, and some mice were then treated with Leo by gavage. We found that Leo could improve the irregular oestros cycle of PCOS mice, reverse the significantly greater serum testosterone (T) and luteinising hormone (LH) levels, significantly reduce the follicle-stimulating hormone (FSH) level, and significantly increase the LH/FSH ratio of PCOS mice. Leo could also change the phenomenon of ovaries in PCOS mice presented with cystic follicular multiplication and a lacking corpus luteum. Transcriptome analysis identified 177 differentially expressed genes related to follicular development between the model and Leo groups. Notably, the cAMP signalling pathway, neuroactive ligand-receptor interactions, the calcium signalling pathway, the ovarian steroidogenesis pathway, and the Lhcgr, Star, Cyp11a, Hsd17b7, Camk2b, Calml4, and Phkg1 genes may be most related to improvements in hormone levels and the numbers of ovarian cystic follicles and corpora lutea in PCOS mice treated by Leo, which provides a reference for further study of the mechanism of Leo.

An insight into the state of nanotechnology-based electrochemical biosensors for PCOS detection

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders affecting many women of reproductive age all over the world. PCOS is associated with the onset of enduring health complications, notably diabetes and cardiovascular diseases. Furthermore, PCOS escalates the propensity for conditions such as obesity, insulin resistance, and dyslipidemia, which can potentially culminate in life-threatening scenarios. A pervasive predicament surrounding PCOS pertains to its underdiagnosis due to discrepancies in diagnostic criteria and the intricacy of available testing methodologies. Consequently, many women encounter substantial delays in diagnosis with traditional diagnostic approaches. Prompt identification is imperative, as any delay can precipitate severe consequences. The conventional techniques employed for PCOS detection typically suffer from suboptimal accuracy, protracted assay times, and inherent limitations, thereby constraining their widespread applicability and accessibility. In response to these challenges, various electrochemical methods leveraging nanotechnology have been documented. In this concise review, we endeavor to delineate the deficiencies associated with established conventional methodologies while accentuating the distinctive attributes and benefits inherent to contemporary biosensors. We place particular emphasis on elucidating the pivotal advancements and recent breakthroughs in the realm of nanotechnology-facilitated biosensors for the detection of PCOS.

Screening of potential biomarkers for polycystic ovary syndrome and identification of expression and immune characteristics

BACKGROUND

Polycystic ovary syndrome (PCOS) seriously affects the fertility and health of women of childbearing age. We look forward to finding potential biomarkers for PCOS that can aid clinical diagnosis.

METHODS

We acquired PCOS and normal granulosa cell (GC) expression profiles from the Gene Expression Omnibus (GEO) database. After data preprocessing, differentially expressed genes (DEGs) were screened by limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Gene Set Enrichment Analysis (GSEA) were performed. Recursive feature elimination (RFE) algorithm and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to acquire feature genes as potential biomarkers. Time-dependent receiver operator characteristic curve (ROC curve) and Confusion matrix were used to verify the classification performance of biomarkers. Then, the expression characteristics of biomarkers in PCOS and normal cells were analyzed, and the insulin resistance (IR) score of samples was computed by ssGSEA. Immune characterization of biomarkers was evaluated using MCP counter and single sample gene set enrichment analysis (ssGSEA). Finally, the correlation between biomarkers and the scores of each pathway was assessed.

RESULTS

We acquired 93 DEGs, and the enrichment results indicated that most of DEGs in PCOS group were significantly enriched in immune-related biological pathways. Further screening results indicated that JDP2 and HMOX1 were potential biomarkers. The area under ROC curve (AUC) value and Confusion matrix of the two biomarkers were ideal when separated and combined. In the combination, the training set AUC = 0.929 and the test set AUC = 0.917 indicated good diagnostic performance of the two biomarkers. Both biomarkers were highly expressed in the PCOS group, and both biomarkers, which should be suppressed in the preovulation phase, were elevated in PCOS tissues. The IR score of PCOS group was higher, and the expression of JDP2 and HMOX1 showed a significant positive correlation with IR score. Most immune cell scores and immune infiltration results were significantly higher in PCOS. Comprehensive analysis indicated that the two biomarkers had strong correlation with immune-related pathways.

CONCLUSION

We acquired two potential biomarkers, JDP2 and HMOX1. We found that they were highly expressed in the PCOS and had a strong positive correlation with immune-related pathways.

Molecular basis of AR and STK11 genes associated pathogenesis via AMPK pathway and adipocytokine signalling pathway in the development of metabolic disorders in PCOS women

Background

One of the most common hormonal disorders in women of reproductive age is polycystic ovary syndrome (PCOS). In recent years, it has been found that insulin resistance is a common metabolic abnormality in women with PCOS and leads to an elevated risk of type 2 diabetes mellitus. To explore the differentially expressed genes (DEGs) that regulate these kinds of metabolic risks in PCOS women, we chose the gene expression profile of GSE8157 from the gene expression omnibus (GEO) database.

Results

Using the GEO2R tool, we identified a total of 339 DEGs between the case and the control sample groups. Gene ontology and Kyoto encyclopedia of gene and genome pathway enrichment analysis were subsequently conducted. High connectivity, betweenness centrality, bottleneck centrality, closeness centrality, and radiality measures were used to rank the ten hub genes. Furthermore, the overlap of these genes resulted in the development of two key genes, AR and STK11. The AMPK and adipocytokine signaling pathways are the two main pathways that these DEGs are involved.

Conclusions

The backbone genes, hub genes and pathways identified would assist us in further exploring the molecular basis of developing risk of type 2 diabetes mellitus in PCOS women and thus provide diagnostic or therapeutic clues.

Leptin Signaling in the Ovary of Diet-Induced Obese Mice Regulates Activation of NOD-Like Receptor Protein 3 Inflammasome

Obesity leads to ovarian dysfunction and the establishment of local leptin resistance. The aim of our study was to characterize the levels of NOD-like receptor protein 3 (NLRP3) inflammasome activation in ovaries and liver of mice during obesity progression. Furthermore, we tested the putative role of leptin on NLRP3 regulation in those organs. C57BL/6J female mice were treated with equine chorionic gonadotropin (eCG) or human chorionic gonadotropin (hCG) for estrous cycle synchronization and ovary collection. In diet-induced obesity (DIO) protocol, mice were fed chow diet (CD) or high-fat diet (HFD) for 4 or 16 weeks, whereas in the hyperleptinemic model (LEPT), mice were injected with leptin for 16 days (16 L) or saline (16 C). Finally, the genetic obese leptin-deficient ob/ob (+/? and −/−) mice were fed CD for 4 week. Either ovaries and liver were collected, as well as cumulus cells (CCs) after superovulation from DIO and LEPT. The estrus cycle synchronization protocol showed increased protein levels of NLRP3 and interleukin (IL)-18 in diestrus, with this stage used for further sample collections. In DIO, protein expression of NLRP3 inflammasome components was increased in 4 week HFD, but decreased in 16 week HFD. Moreover, NLRP3 and IL-1β were upregulated in 16 L and downregulated in ob/ob. Transcriptome analysis of CC showed common genes between LEPT and 4 week HFD modulating NLRP3 inflammasome. Liver analysis showed NLRP3 protein upregulation after 16 week HFD in DIO, but also its downregulation in ob/ob−/−. We showed the link between leptin signaling and NLRP3 inflammasome activation in the ovary throughout obesity progression in mice, elucidating the molecular mechanisms underpinning ovarian failure in maternal obesity.

Neurobehavioral alternations of the female offspring born to polycystic ovary syndrome model rats administered by Chinese herbal medicine

Background

Chinese herbal medicine (CHM) has significant effects that improve the reproductive functions of patients with polycystic ovary syndrome (PCOS). However, the intergenerational effects of CHM on offspring and the underlying mechanism of CHM remain unclear. This study aimed to explore the effects and the underlying mechanism of CHM, specifically the Bu-Shen-Tian-Jing formula (BSTJF), on model rats with polycystic ovary syndrome (PCOS) and the neurobehavioral alterations of female offspring born to PCOS rats administered BSTJF.

Methods

High-performance liquid chromatography-mass spectrometry (HPLC–MS) and network pharmacology analysis were performed to identify the active ingredients and potential targets of BSTJF. Moreover, PCOS model rats were used to validate the role of BSTJF in reproduction and progeny neural development and to confirm the network pharmacological targets.

Results

A total of 91 constituents were characterized from BSTJF. The 20 most significant KEGG pathways and the high-frequency genes of these pathways were predicted to be putative targets of these molecules. The rat experiment showed that the downregulation of FOS protein expression in the ovarian granulosa cells of the PCOS group was reversed by BSTJF. The target residence time of the 5-week-old female offspring of the BSTJF group was higher than that of the PCOS group in the water maze experiment. Compared to the PCOS group, the changes in dendritic spine density, ultrastructure of neurons and synapses, and Gabrb1 and Grin2b protein expression levels in the hippocampus of female offspring were partially reversed in the BSTJF group.

Conclusions

BSTJF can effectively improve ovarian follicle development in PCOS rats and has positive effects on pubertal neurobehavioral alterations in the female offspring of these rats by reversing dendritic spine density, the ultrastructure of neurons and synapses, and the Gabrb1 and Grin2b protein expression levels in the hippocampus.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13020-021-00512-4.

Explore the potential molecular mechanism of polycystic ovarian syndrome by protein-protein interaction network analysis

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders prevailing in reproductive age women, present in 3-15% population of women worldwide. Although there are many studies on PCOS, its underlying mechanism remains to be determined. The present study was to construct protein-protein interaction networks based on the potential disease-causing genes for PCOS and characterize the underlying molecular mechanisms of PCOS using the networks. PCOS-associated genes were extracted from DisGeNet and the protein-protein interaction networks (PPIN) of PCOS were constructed using the String Database. Then we utilized MCODE algorithm to analyse the hub-gene modules from the PPIN. Finally, the major biological functions and signaling pathways involved in the hub modules were explored by functional enrichment analysis. A total of 522 candidate genes associated to PCOS were extracted from DisGeNET database. The PPIN constructed using the genes we have collected above included 488 genes and 2767 interaction relationships. Moreover, seven major gene modules were obtained after analyzing the PPIN with the use of MCODE plug-in. The major modules generated were enriched in certain biological functions such as cancer and cell proliferation and apoptosis, regulation of lipid and glucose metabolism, cell cycle and so on. The integrated analysis performed in the current study revealed that these hub modules and their related genes are closely associated to the pathogenesis of PCOS, which may probably provide novel insights for the treatment of PCOS and the study of its latent pathogenic mechanism. The relationship between several of the key genes including ALB, TOP2A, PTGER3, NPB and BRD2 in the modules and PCOS has not been investigated previously and it remains to be verified by further research of large sample, multi-center and multi-ethnic.

The Identification of Three Key Genes Related to Stemness in Thyroid Carcinoma through Comprehensive Analysis

BACKGROUND

Tumor heterogeneity imposes great challenges on cancer treatment. Cancer stem cells (CSCs) are a leading factor contributing to tumor occurrence. However, the mechanisms underlying the growth of thyroid cancer (TCHA) are still unclear.

METHODS

Key genes regulating the characteristics of THCA, such as stemness were identified by combining gene expressions of samples downloaded from the Cancer Genome Atlas (TCGA) and were used to establish an mRNA expression stemness index (mRNAsi) through machine learningbased methods. The relationships of mRNAsi, THCA clinical features and molecular subtypes were analyzed. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to obtain mRNAsi-related gene modules and determine mRNAsi-related differentially co-expressed genes. Key genes related to mRNAsi were screened by protein interaction network. Functional analysis was conducted and expressions of key genes were verified in multiple external data sets.

RESULTS

The mRNAsi score, which was found to be lower in the TCHA tissues than that in normal tissues (p<0.05), was positively correlated with a slow progression of tumor prognosis (p=0.0085). We screened a total of 83 differentially co-expressed genes related to mRNAsi and multiple tumor pathways such as apoptosis, tight junction, cytokine-cytokine receptor interaction, and cAMP signaling pathway (p<0.05). Finally, 28 protein interaction networks incorporating 32 genes were established, and 3 key genes were identified through network mining. 3 core genes were finally determined, as their low expressions were strongly correlated with the progression of THCA.

CONCLUSION

The study found that NGF, FOS, and GRIA1 are closely related to the characteristics of THCA stem cells. These genes, especially FOS, are highly indicative of the prognosis of THCA patients. Thus, screening therapy could be used to inhibit the stemness of TCHA.

Exploring Molecular Mechanism of Huangqi in Treating Heart Failure Using Network Pharmacology

Heart failure (HF), a clinical syndrome with a high incidence due to various reasons, is the advanced stage of most cardiovascular diseases. Huangqi is an effective treatment for cardiovascular disease, which has multitarget, multipathway functions. Therefore, we used network pharmacology to explore the molecular mechanism of Huangqi in treating HF. In this study, 21 compounds of Huangqi, which involved 407 targets, were obtained and reconfirmed using TCMSP and PubChem databases. Moreover, we used Cytoscape 3.7.1 to construct compound-target network and screened the top 10 compounds. 378 targets related to HF were obtained from CTD and GeneCards databases and HF-target network was constructed by Cytoscape 3.7.1. The 46 overlapping targets of HF and Huangqi were gotten by Draw Venn Diagram. STRING database was used to set up a protein-protein interaction network, and MCODE module and the top 5 targets with the highest degree for overlapping targets were obtained. GO analysis performed by Metascape indicated that the overlapping targets were mainly enriched in blood vessel development, reactive oxygen species metabolic process, response to wounding, blood circulation, and so on. KEGG analysis analyzed by ClueGO revealed that overlapping targets were mainly enriched in AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, HIF-1 signaling pathway, c-type lectin receptor signaling pathway, relaxin signaling pathway, and so on. Finally, molecular docking showed that top 10 compounds of Huangqi also had good binding activities to important targets compared with digoxin, which was carried out in CB-Dock molecular docking server. In conclusion, Huangqi has potential effect on regulating overlapping targets and GE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, HIF-1 signaling pathway, and so on to be a latent multitarget, multipathway treatment for HF.