Background Growing evidence has indicated the vital parts of long non-coding RNAs (lncRNAs) in modulating the progression of assorted human cancers, including cervical cancer (CC). Nevertheless, the role and mechanism of aspartyl-tRNA synthetase antisense RNA 1 (DARS-AS1) have been not comprehensively illustrated in CC yet. Methods Real-time quantitative polymerase chain reaction (RT-qPCR) was exploited for assessing RNA expression while western blot for protein expression in CC cells. The cell counting kit-8 (CCK-8), colony formation and TdT-mediated dUTP Nick-End Labeling (TUNEL) assays, as well as flow cytometry analysis, were employed to evaluate the modulation of DARS-AS1 on the proliferation and apoptosis of CC cells. In addition, RNA immunoprecipitation (RIP), RNA pull down assay and luciferase reporter assay confirmed the interactivity among DARS-AS1, miR-628-5p and jagged canonical Notch ligand 1 (JAG1). RBP-JK luciferase reporter assay determined the activity of Notch pathway. Results DARS-AS1 level was significantly increased in CC cells. Moreover, down-regulation of DARS-AS1 hampered cell the proliferation and accelerated the apoptosis of CC cells. Importantly, DARS-AS1 was a competing endogenous RNA (ceRNA) to elevate JAG1 level through sequestering miR-628-5p, leading to activated Notch pathway to aggravate CC tumorigenesis. Conclusions DARS-AS1/miR-628-5p/JAG1/Notch signaling accelerates CC progression, indicating DARS-AS1 as a novel therapeutic target for patients with CC.
BackgroundEndometriosis (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.MethodsThree 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.ResultsThe 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.ConclusionsIn 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.
Objectives:The aim of this study was to investigate the influence of advanced maternal age on the maternal and neonatal outcomes of preterm pregnancies.
DC-directed rLV/MAGE-A3 efficiently induced antigen-specific immune responses, indicating the possibility of DC-based MAGE-A3 antigen vaccine as a promising strategy for treatment of MAGE-A3-associated cancer.
High proportions of placental lymphocytes expressing DX5+/CD25+/FOXP3+/CD45+/CD4+ are beneficial to maintain immune tolerance and improve pregnancy outcomes. This study aimed to compare and evaluate the therapeutic effects of aspirin, vitamin D3 (VitD3), and progesterone on the autoimmune recurrent spontaneous abortion (RSA) model. The autoimmune RSA mouse model was constructed, and the embryo loss rate was calculated for each group. Then, primary mouse placental lymphocytes were isolated, and the expression of DX5+/CD25+/FOXP3+/CD45+/CD4+ was detected through flow cytometry. The serum levels of anti-cardiolipin antibody (ACA), β2-GP1, CXCL6, IFN-γ, and IL-6 were measured by ELISA to evaluate the proportion of Th1 and Th2 cells. Autoimmune RSA significantly increased the embryo loss rate, which was improved by aspirin, VitD3, and progesterone treatment, and progesterone treatment had the best effect among the three treatments. The positive expression of DX5+/CD25+/FOXP3+/CD45+/CD4+ in the VitD3 and progesterone groups was significantly higher than that in the autoimmune RSA group, and the expression was highest in the progesterone treatment group. In the plasma of autoimmune RSA mice, the ACA, β2-GP1, CXCL6, and IFN-γ levels were significantly higher and the IL-6 level was lower than the levels in control mice. All these changes could be reversed by aspirin and progesterone treatment. In conclusion, aspirin, VitD3 and progesterone treatment improved pregnancy outcomes in autoimmune RSA mice by regulating the Th1/Th2 balance and cytokines, and progesterone had the best effect of the three treatments.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.