Construction and analysis of competitive endogenous RNA networks and prognostic models associated with ovarian cancer based on the exoRBase database.

OBJECTIVE: To construct a competitive endogenous RNA (ceRNA) regulatory network in blood exosomes of patients with ovarian cancer (OC) using bioinformatics and explore its pathogenesis. METHODS: The exoRbase2.0 database was used to download blood exosome gene sequencing data from patients OC and normal controls and the expression profiles of exosomal mRNA, long non-coding RNA (lncRNA), and circular RNA (circRNA) were detected independently using R language for differential expression analysis. TargetScan and miRanda databases were combined for the prediction and differential expression of mRNA-binding microRNAs (miRNA). The miRcode and starBase databases were used to predict miRNAs that bind to differentially expressed lncRNAs and circRNAs repectively. The relevant mRNA, circRNA, lncRNA and their corresponding miRNA prediction data were imported into Cytoscape software for visualization of the ceRNA network. The R language and KEGG Orthology-based Annotation System (KOBAS) were used to execute and illustrate the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Hub genes were identified using The CytoHubba plugin. RESULTS: Thirty-one differentially expressed mRNAs, 17 differentially expressed lncRNAs, and 24 differentially expressed circRNAs were screened. Cytoscape software was used to construct the ceRNA network with nine mRNA nodes, two lncRNA nodes, eight circRNA nodes, and 51 miRNA nodes. Both GO and KEGG were focused on the Spliceosome pathway, indicating that spliceosomes are closely linked with the development of OC, while heterogenous nuclear ribonucleoprotein K and RNA binding motif protein X-linked genes were the top 10 score Hub genes screened by Cytoscape software, including two lncRNAs, four mRNAs, and four circRNAs. In patients with OC, the expression of eukaryotic translation initiation factor 4 gamma 2 (EIF4G2), SERPINE 1 mRNA binding protein 1 (SERBP1), ribosomal protein L15 (RPL15) and human leukocyte antigen complex P5 (HCP5) was significantly higher whereas that of testis expressed transcript, Y-linked 15 and DEAD-box helicase 3 Y-linked genes was lower compared to normal controls Immunocorrelation scores revealed that SERBP1 was significantly and negatively correlated with endothelial cells and CD4+ T cells and positively correlated with natural killer (NK) cells and macrophages, respectively; RPL15 was significantly positively correlated with macrophages and endothelial cells and negatively correlated with CD8+ T cells and uncharacterized cells, respectively. EIF4G2 was significantly and negatively correlated with endothelial cells and CD4+ T cells, and positively correlated with uncharacterized cells, respectively. Based on the survival data and the significant correlation characteristics derived from the multifactorial Cox analysis (P < 0.05), the survival prediction curves demonstrated that the prognostic factors associated with 3-year survival in patients with OC were The prognostic factors associated with survival were Macrophage, RPL15. CONCLUSION: This study successfully constructs a ceRNA regulatory network in blood exosomes of OV patients, which provides the specific targets for diagnosis and treatment of OC.

Biofilm Microenvironment Activated Antibiotic Adjuvant for Implant-Associated Infections by Systematic Iron Metabolism Interference.

Hematoma, a risk factor of implant-associated infections (IAIs), creates a Fe-rich environment following implantation, which proliferates the growth of pathogenic bacteria. Fe metabolism is a major vulnerability for pathogens and is crucial for several fundamental physiological processes. Herein, a deferiprone (DFP)-loaded layered double hydroxide (LDH)-based nanomedicine (DFP@Ga-LDH) that targets the Fe-rich environments of IAIs is reported. In response to acidic changes at the infection site, DFP@Ga-LDH systematically interferes with bacterial Fe metabolism via the substitution of Ga3+ and Fe scavenging by DFP. DFP@Ga-LDH effectively reverses the Fe/Ga ratio in Pseudomonas aeruginosa, causing comprehensive interference in various Fe-associated targets, including transcription and substance metabolism. In addition to its favorable antibacterial properties, DFP@Ga-LDH functions as a nano-adjuvant capable of delaying the emergence of antibiotic resistance. Accordingly, DFP@Ga-LDH is loaded with a siderophore antibiotic (cefiderocol, Cefi) to achieve the antibacterial nanodrug DFP@Ga-LDH-Cefi. Antimicrobial and biosafety efficacies of DFP@Ga-LDH-Cefi are validated using ex vivo human skin and mouse IAI models. The pivotal role of the hematoma-created Fe-rich environment of IAIs is highlighted, and a nanoplatform that efficiently interferes with bacterial Fe metabolism is developed. The findings of the study provide promising guidance for future research on the exploration of nano-adjuvants as antibacterial agents.