Hypoxia-hindered methylation of PTGIS in endometrial stromal cells accelerates endometriosis progression by inducing CD16- NK-cell differentiation

Hypoxia and the endometrium: An indispensable role for HIF-1α as therapeutic strategies

Hypoxia-inducible factor 1 alpha (HIF-1α) is a major molecular mediator of the hypoxic response. In the endometrium, local hypoxic conditions induced by hormonal fluctuations and endometrial vascular remodeling contribute to the production of HIF-1α, which plays an indispensable role in a series of physiological activities, such as menstruation and metamorphosis. The sensitive regulation of HIF-1α maintains the cellular viability and regenerative capacity of the endometrium against cellular stresses induced by hypoxia and excess reactive oxygen species. In contrast, abnormal HIF-1α levels exacerbate the development of various endometrial pathologies. This knowledge opens important possibilities for the development of promising HIF-1α-centered strategies to ameliorate endometrial disease. Nonetheless, additional efforts are required to elucidate the regulatory network of endometrial HIF-1α and promote the applications of HIF-1α-centered strategies in the human endometrium. Here, we summarize the role of the HIF-1α-mediated pathway in endometrial physiology and pathology, highlight the latest HIF-1α-centered strategies for treating endometrial diseases, and improve endometrial receptivity.

Identification of Prostaglandin I2 Synthase Rare Variants in Patients With Williams Syndrome and Severe Peripheral Pulmonary Stenosis

BACKGROUND

Peripheral pulmonary stenosis (PPS) is a condition characterized by the narrowing of the pulmonary arteries, which impairs blood flow to the lung. The mechanisms underlying PPS pathogenesis remain unclear. Thus, the aim of this study was to investigate the genetic background of patients with severe PPS to elucidate the pathogenesis of this condition.

METHODS AND RESULTS

We performed genetic testing and functional analyses on a pediatric patient with PPS and Williams syndrome (WS), followed by genetic testing on 12 patients with WS and mild-to-severe PPS, 50 patients with WS but not PPS, and 21 patients with severe PPS but not WS. Whole-exome sequencing identified a rare PTGIS nonsense variant (p.E314X) in a patient with WS and severe PPS. Prostaglandin I2 synthase (PTGIS) expression was significantly downregulated and cell proliferation and migration rates were significantly increased in cells transfected with the PTGIS p.E314X variant-encoding construct when compared with that in cells transfected with the wild-type PTGIS-encoding construct. p.E314X reduced the tube formation ability in human pulmonary artery endothelial cells and caspase 3/7 activity in both human pulmonary artery endothelial cells and human pulmonary artery smooth muscle cells. Compared with healthy controls, patients with PPS exhibited downregulated pulmonary artery endothelial prostaglandin I2 synthase levels and urinary prostaglandin I metabolite levels. We identified another PTGIS rare splice-site variant (c.1358+2T>C) in another pediatric patient with WS and severe PPS.

CONCLUSIONS

In total, 2 rare nonsense/splice-site PTGIS variants were identified in 2 pediatric patients with WS and severe PPS. PTGIS variants may be involved in PPS pathogenesis, and PTGIS represents an effective therapeutic target.

Vaginal extracellular vesicles impair fertility in endometriosis by favoring Th17/Treg imbalance and inhibiting sperm activity

Extracellular vesicles (EVs) play a key role in various diseases. However, their effect on endometriosis (EMs)-associated infertility is poorly understood. We co-cultured EVs from the female vaginal secretions with human sperm and also generated a mouse model of EMs by allogenic transplant to explore the effect of EVs on fertility. EVs from individuals with EMs-associated infertility (E-EVs) significantly inhibited the total motility (26.46% vs. 47.1%), progressive motility (18.78% vs. 41.06%), linear velocity (21.98 vs. 41.91 µm/s) and the acrosome reaction (AR) rate (5% vs. 22.3%) of human sperm in contrast to the control group (PBS). Furthermore, E-EVs dose-dependently decreased the intracellular Ca2+ ([Ca2+]i), a pivotal regulator of sperm function. Conversely, healthy women (H-EVs) increased human sperm motion parameters, the AR rate, and sperm [Ca2+]i. Importantly, the mouse model of EMs confirmed that E-EVs further decreased the conception rate and the mean number of embryo implantations (7.6 ± 3.06 vs. 4.5 ± 3.21) compared with the control mice by inducing the production of inflammatory cytokines leading to a Th17/Treg imbalance. H-EVs could restore impaired fertility by restoring the Th17/Treg balance. We determined the impact of EVs derived from the female genital tract on human sperm function and studied the possible mechanisms by which it affects fertility. Our findings provide a novel rationale to ameliorate EMs-associated infertility.

Hypoxia-Derived Exosomes Promote Lung Adenocarcinoma by Regulating HS3ST1-GPC4-Mediated Glycolysis

OBJECTIVE

The diagnosis of lung adenocarcinoma (LUAD) is often delayed due to the typically asymptomatic nature of the early-stage disease, causing advanced-stage LUAD diagnosis in most patients. Hypoxia is widely recognized as a driving force in cancer progression. Exosomes originating from hypoxic tumor cells promote tumorigenesis by influencing glycolysis, migration, invasion, and immune infiltration. Given these insights, our study aimed to explore the role of hypoxia-derived exosomal long non-coding RNA (lncRNA) OIP5-AS1 in LUAD cell lines and mouse models.

MATERIALS AND METHODS

Exosomes were meticulously isolated and authenticated based on their morphology and biomarkers. The interaction between heparan sulfate (glucosamine) 3-O-sulfotransferase 1 (HS3ST1) and Glypican 4 (GPC4) was examined using immunoprecipitation. The influence of the hypoxia-derived exosomal lncRNA OIP5-AS1 on glycolysis was assessed in LUAD cell lines. The effect of the hypoxia-derived exosomal lncRNA OIP5-AS1 on cell proliferation and metastasis was evaluated using colony formation, cell viability, cell cycle, and apoptosis analyses. Its effects on tumor size were confirmed in xenograft animal models.

RESULTS

Our study revealed the mechanism of the hypoxia-derived exosomal lncRNA OIP5-AS1 in LUAD progression. We discovered that GPC4 promotes HS3ST1-mediated glycolysis and that the hypoxia-derived exosomal lncRNA OIP5-AS1 enhances glycolysis by regulating miR-200c-3p in LUAD cells. Notably, this lncRNA stimulates LUAD cell proliferation and metastasis and fosters LUAD tumor size via miR-200c-3p. Our findings underscore the potential role of the hypoxia-derived exosomal lncRNA OIP5-AS1 in LUAD progression.

CONCLUSIONS

The hypoxia-derived exosomal lncRNA OIP5-AS1 promotes LUAD by regulating HS3ST1-GPC4-mediated glycolysis via miR-200c-3p.

Tumor-suppressive functions of protein lysine methyltransferases

Protein lysine methyltransferases (PKMTs) play crucial roles in histone and nonhistone modifications, and their dysregulation has been linked to the development and progression of cancer. While the majority of studies have focused on the oncogenic functions of PKMTs, extensive evidence has indicated that these enzymes also play roles in tumor suppression by regulating the stability of p53 and β-catenin, promoting α-tubulin-mediated genomic stability, and regulating the transcription of oncogenes and tumor suppressors. Despite their contradictory roles in tumorigenesis, many PKMTs have been identified as potential therapeutic targets for cancer treatment. However, PKMT inhibitors may have unintended negative effects depending on the specific cancer type and target enzyme. Therefore, this review aims to comprehensively summarize the tumor-suppressive effects of PKMTs and to provide new insights into the development of anticancer drugs targeting PKMTs.

Analysis and experimental validation of fatty acid metabolism-related genes prostacyclin synthase (PTGIS) in endometrial cancer

The deregulation of fatty acid metabolism plays a pivotal role in cancer. Our objective is to construct a prognostic model for patients with endometrial carcinoma (EC) based on genes related to fatty acid metabolism-related genes (FAMGs). RNA sequencing and clinical data for EC were obtained from The Cancer Genome Atlas (TCGA). Lasso-Penalized Cox regression was employed to derive the risk formula for the model, the score = esum(corresponding coefficient × each gene's expression). Gene set enrichment analysis (GSEA) was utilized to examine the enrichment of KEGG and GO pathways within this model. Correlation analysis of immune function was conducted using Single-sample GSEA (ssGSEA). The "ESTIMATE" package in R was utilized to evaluate the tumor microenvironment. The support vector machine recursive feature elimination (SVM-RFE) and randomforest maps were employed to identify key genes. The effects of PTGIS on the malignant biological behavior of EC were assessed through CCK-8 assay, transwell invasion assay, cell cycle analysis, apoptosis assay, and tumor xenografts in nude mice. A novel prognostic signature comprising 10 FAMGs (INMT, ACACB, ACOT4, ACOXL, CYP4F3, FAAH, GPX1, HPGDS, PON3, PTGIS) was developed. This risk score serves as an independent prognostic marker validated for EC. According to ssGSEA analysis, the low- and high-risk groups exhibited distinct immune enrichments. The key gene PTGIS was screened by SVM-RFE and randomforest method. Furthermore, we validated the expression of PTGIS through qRT-PCR. In vitro and in vivo experiments also confirmed the effect of PTGIS on the malignant biological behavior of EC.

PTGIS May Be a Predictive Marker for Ovarian Cancer by Regulating Fatty Acid Metabolism

Background

Ovarian cancer tends to metastasize to the omentum, which is an organ mainly composed of adipose tissue. Many studies have found that fatty acid metabolism is related to the occurrence and metastasis of cancers. Therefore, it is possible that fatty acid metabolism-related genes (FAMRG) affect the prognosis of ovarian cancer patients.

Methods

First, profiles of ovarian cancer and normal ovarian tissue transcriptomes were acquired from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. A LASSO regression predictive model was developed via the "glmnet" R package. The nomogram was created via the "regplot." Gene Set Variation Analysis (GSVA), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) analyses were conducted to determine the FAMRGs' roles. The percentage of immunocyte infiltration was calculated via CIBERSORT. Using "pRRophetic," the sensitivity of eight regularly used medications and immunotherapy was anticipated.

Results

125 genes were determined as different expression genes (DEGs). Based on RXRA, ECI2, PTGIS, and ACACB, a prognostic model is created and the risk score is calculated. Analyses of univariate and multivariate regressions revealed that the risk score was a distinct prognostic factor (univariate: HR: 2.855, 95% CI: 1.756-4.739, P < 0.001; multivariate: HR: 2.943, 95% CI: 1.800-4.812, P < 0.001). The nomogram demonstrated that it properly predicted the 1-year survival rate. The expression of memory B molecular units, follicular helper T molecular units, regulatory T molecular units, and M1 macrophages differed remarkably between the groups at high and low risk (P < 0.05). Adipocytokine signaling pathways, cancer pathways, and degradation of valine, leucine, and isoleucine vary between high- and low-risk populations. The findings of the GO enrichment revealed that the extracellular matrix and cellular structure were the two most enriched pathways. PTGIS, which is an important gene in fatty acid metabolism, was identified as the hub gene. This result was verified in ovarian cancer and ovarian tissues. The connection between the gene and survival was statistically remarkable (P = 0.015). The pRRophetic algorithm revealed that the low-risk group was more adaptable to cisplatin, doxorubicin, 5-fluorouracil, and etoposide (P < 0.001).

Conclusion

PTGIS may be an indicator of prognosis and a possible therapeutic target for the therapy of ovarian cancer patients. The fatty acid metabolism of immune cells may be controlled, which has an indirect effect on cancer cell growth.

Bioinformatics identification and validation of biomarkers and infiltrating immune cells in endometriosis

Background

Endometriosis (EM) is a common gynecological disorder that often leads to irregular menstruation and infertility. The pathogenesis of EM remains unclear and delays in diagnosis are common. Thus, it is urgent to explore potential biomarkers and underlying molecular mechanisms for EM diagnosis and therapies.

Methods

Three EM-related datasets (GSE11691, GSE25628, and GSE86534) were downloaded from the Gene Expression Omnibus (GEO) which were integrated into a combined dataset after removing batch effect. Differentially expressed immune cell-related genes were obtained by CIBERSORT, WGCNA, and the identification of differentially expressed genes. Random forest model (RF), support vector machine model (SVM), and generalized linear model (GLM) were then constructed and the biomarkers for EM were determined. A nomogram evaluating the risk of disease was constructed and the validity was assessed by the calibration curve, DCA curve, and clinical impact curve. Single-gene Gene Set Enrichment Analysis (GSEA)was performed to explore the molecular mechanisms of biomarkers. The ceRNA regulatory network of biomarkers was created by Cytoscape and potential target drugs were obtained in the DGIdb database (Drug-Gene Interaction database).The expression levels of biomarkers from clinical samples was quantified by RT-qPCR.

Results

The ratio of eight immune cells was significantly different between the eutopic and ectopic endometrium samples. A total of eight differentially expressed immune cell-related genes were investigated. The SVM model was a relatively suitable model for the prediction of EM and five genes (CXCL12, PDGFRL, AGTR1, PTGER3, and S1PR1) were selected from the model as biomarkers. The calibration curve, DCA curve, and clinical impact curve indicated that the nomogram based on the five biomarkers had a robust ability to predict disease. Single gene GSEA result suggested that all five biomarkers were involved in labyrinthine layer morphogenesis and transmembrane transport-related biological processes in EM. A ceRNA regulatory network containing 184 nodes and 251 edges was constructed. Seven drugs targeting CXCL12, 49 drugs targeting AGTR1, 16 drugs targeting PTGER3, and 21 drugs targeting S1PR1 were extracted as potential drugs for EM therapy. Finally, the expression of PDGFRL and S1PR1 in clinical samples was validated by RT-qPCR, which was consistent with the result of public database.

Conclusions

In summary, we identified five biomarkers (CXCL12, PDGFRL, AGTR1, PTGER3, and S1PR1) and constructed diagnostic model, furthermore predicted the potential therapeutic drugs for EM. Collectively, these findings provide new insights into EM diagnosis and treatment.