Background: The expression of homeobox A10 (HOXA10) in endometrial stromal cells is regulated by steroid hormones, especially by estrogen. As a precursor molecule of estrogen, abnormal cholesterol metabolism is significantly positively correlated with endometriosis. The purpose of this study was to explore the regulation of HOXA10 on cholesterol synthesis in endometrial stromal cells. Method: mRNA expression data of eutopic endometrial stromal cell (ESC) and ovarian endometriotic cysts stromal cell (OESC) were download from the Gene Expression Omnibus (GEO) databases. Overexpression and silence of HOXA10 were conducted in cultured ESC and subjected to mRNA sequencing. The differentially expressed genes (DEGs) were selected by analyzing the sequencing data. Weighted gene co-expression network analysis (WGCNA) was applied to identify the key genes associated with HOXA10. The methylation rate of HOXA10 CpGs and the correlation between HOXA10 expression and the methylation in eutopic endometrial tissue (EU) and ovarian cyst (OC) were analyzed. Results: HOXA10 in ESC was significantly higher expressed than that in OESC. Six key genes (HMGCR, MSMO1, ACAT2, HMGCS1, EBP, and SQLE), which were regulated by HOXA10, were identified from the salmon4 module by WGCNA. All these key genes were enriched in cholesterol synthesis. Moreover, the expression of HOXA10 was negatively related to its CpGs methylation rate. Conclusion: In this study, six key genes that were regulated by HOXA10 were selected, and all of them were enriched in cholesterol synthesis. This finding provided a new insight into the metabolic mechanism of cholesterol in ESC. It also provided a potential treatment strategy for cholesterol metabolism maladjustment in patients with ovarian endometriosis.

Adipose-derived mesenchymal stem cells (ADSCs) have been extensively explored as a promising therapeutic agent due to their differentiation, proliferation and migration abilities. The epigenetic mechanisms that regulate the fate of mesenchymal stem cells (MSCs) have been described in detail. However, the epigenetic modulation of ADSCs proliferation and migration is poorly understood. The present study examined histone demethylases roles and expression by RT-PCR, as well as through siRNA screening and ChIP-qPCR assay. Cellular proliferation and migration assays were employed in shRNA-mediated JMJD6 knockdown and control ADSCs. PDE1C inhibition studies were conducted to confirm its role in JMJD6-mediated epigenetic regulation of ADSCs. The data demonstrate that the histone demethylase JMJD6 plays a critical role in regulating the proliferation and migration of ADSCs by removing H4R3me2a at the promoter regions of PDEC1 and suppressing PDEC1 expression. Importantly, the depletion of JMJD6 in ADSCs significantly increased cellular proliferation and motility, which was associated with increases in PDE1C expression and decreases in the levels of both cAMP and cGMP. The increase in proliferation and migration was reversed by treatment with a PDE1C inhibitor, suggesting that JMJD6 attenuates the proliferation and migration of ADSCs as an epigenetic regulator and PDE1C partially contributes to the JMJD6-mediated regulation. Taken together, our results indicate for the first time that JMJD6 plays an important role in the regulation of ADSCs proliferation and migration through the modulation of PDE1C expression.

Autophagy plays an important role in cancer. Many studies have demonstrated that autophagy‐related genes (ARGs) can act as a prognostic signature for some cancers, but little has been known in low‐grade gliomas (LGG). In our study, we aimed to establish a prognostical model based on ARGs and find prognostic risk‐related key genes in LGG. In the present study, a prognostic signature was constructed based on a total of 8 ARGs (MAPK8IP1, EEF2, GRID2, BIRC5, DLC1, NAMPT, GRID1, and TP73). It was revealed that the higher the risk score, the worse was the prognosis. Time‐dependent ROC analysis showed that the risk score could precisely predict the prognosis of LGG patients. Additionally, four key genes (TGFβ2, SERPING1, SERPINE1, and TIMP1) were identified and found significantly associated with OS of LGG patients. Besides, they were also discovered to be strongly related to six types of immune cells which infiltrated in LGG tumor. Taken together, the present study demonstrated the promising potential of the ARG risk score formula as an independent factor for LGG prediction. It also provided the autophagy‐related signature of prognosis and potential therapeutic targets for the treatment of LGG.

Background: Epithelial-mesenchymal transition (EMT) is a complex event that drives polar epithelial cells transform from adherent cells to motile mesenchymal cells, in which are involved immune cells and stroma cells. EMT plays crucial roles in migration and invasion of endometriosis. The interaction of endometrial implants with the surrounding peritoneal micro-environment probably affects the development of peritoneal endometriosis. To date, very few studies have been carried out on peritoneal endometriosis sub-type classification and micro-environment analysis based on EMT. The purpose of this study is to investigate the potential application of EMT-based classification in precise diagnosis and treatment of peritoneal endometriosis.Method: Based on EMT hallmark genes, 76 peritoneal endometriosis samples were classified into two clusters by consistent cluster classification. EMT scores, which calculated by Z score of 8 epithelial cell marker genes and 8 mesenchymal cell marker genes, were compared in two clusters. Then, immune scores and the abundances of corresponding immune cells, stroma scores and the abundances of corresponding stroma cells were analyzed by the “xCell” package. Futhermore, a diagnostic model was constructed based on 9 diagnostic markers which related to immune score and stroma score by Lasso-Logistic regression analysis. Finally, based on EMT classification, a total of 8 targeted drugs against two clusters were screened out by drug susceptibility analysis via “pRRophetic” package.Results: Hallmark epithelial-mesenchymal transition was the mainly enriched pathway of differentially expressed genes between peritoneal endometriosis tissues and endometrium tissues. Compared with cluster 2, EMT score and the abundances of most infiltrating stroma cell were significantly higher, while the abundances of most infiltrating immune cells were dramatically less. The diagnostic model could accurately distinguish cluster 1 from cluster 2. Pathway analysis showed drug candidates targeting cluster 1 mainly act on the IGF-1 signaling pathway, and drug candidates targeting cluster 2 mainly block the EGFR signaling pathway.Conclusion: In peritoneal endometriosis, EMT was probably promoted by stroma cell infiltration and inhibited by immune cell infiltration. Besides, our study highlighted the potential uses of the EMT classification in the precise diagnosis and treatment of peritoneal endometriosis.