Background/Objectives: Hemophilia A (HA) is caused by coagulation factor VIII (FVIII) deficiency, but its clinical heterogeneity suggests that biological alterations beyond impaired hemostasis may contribute to disease expression. This study aimed to characterize F8 knockout (F8-KO)-associated molecular changes and identify drug repositioning candidates with therapeutic potential for HA. Methods: An F8-KO human umbilical vein endothelial cell model was generated using CRISPR/Cas9 and profiled by RNA sequencing and data-independent acquisition (DIA) proteomics. Integrated multi-omics, enrichment, and protein–protein interaction analyses informed drug repositioning using Connectivity Map (CMap), EpiMed, and DrugBank. Valproic acid (VPA) was evaluated using cell viability assays, RT-qPCR, transcriptomic profiling, and H3K27ac CUT&Tag. Results: Integrated transcriptomic and proteomic analysis identified 113 shared genes with predominantly concordant changes, and network-based analysis prioritized genes involved in endothelial homeostasis and inflammatory regulation. Drug repositioning identified VPA and irbesartan across three screening sources. VPA increased CD274 mRNA expression, partially reversed F8-KO-associated transcriptional alterations, and remodeled H3K27ac-associated regulatory programs involving vascular homeostasis- and inflammation-related pathways. Conclusions: VPA may modulate F8 deficiency-associated endothelial molecular alterations and represents a drug-repositioning candidate for HA. These findings may offer a new perspective for exploring potential therapeutic strategies beyond conventional correction of the coagulation defect.

Background: Paroxysmal nocturnal haemoglobinuria (PNH) is a clonal haematopoietic stem cell disease, characterized primarily by intravascular hemolysis, thrombosis, and bone marrow failure. Complement inhibitors are commonly used in clinical treatment, showing limited efficacy, thus highlighting the urgent need to identify new therapeutic targets and explore alternative treatment strategies to provide theoretical guidance for clinical practice. Methods: We established a PNH cell model and constructed a miRNA–mRNA regulatory network to identify key miRNAs and core target genes. Single-cell sequencing data were analyzed to further clarify the critical genes. Drug prediction was then performed using multiple databases to identify potential therapeutic agents for PNH, which were subsequently validated through molecular docking and molecular dynamics simulations. Results: Using CRISPR/RNP technology, we successfully constructed a PIGA-knockout (PIGA-KO) THP-1 cell model. Differential expression analysis identified 1979 differentially expressed mRNAs (DEmRNAs) and 97 differentially expressed miRNAs (DEmiRNAs). The multiMiR package in R was used to predict the target genes of DEmiRNAs, from which those experimentally validated through dual-luciferase reporter assays were selected. After integrating with the DEmRNAs, a miRNA–mRNA regulatory network was constructed, comprising 26 miRNAs and 38 mRNAs. Prediction of miRNA pathway enrichment analysis identified hsa-miR-23a-3p as a key miRNA, with CXCL12, CXCL8, HES1, and TRAF5 as core target genes. Integration of single-cell sequencing datasets (PRJNA1061334 and GSE157344) was performed, followed by cell communication and enrichment analysis. This approach, combined with clinical relevance, identified neutrophil cluster as a key cluster. Intersection analysis of neutrophil cluster differential analysis result with key modules from hdWGCNA further clarified the critical genes. Drug prediction using the EpiMed, CMap, and DGIdb identified Leflunomide, Dipyridamole, and Pentoxifylline as potential therapeutic agents. Molecular docking and molecular dynamics simulations showed stable binding of these potential drugs to the critical molecules, indicating a strong molecular interaction foundation. Conclusion: Leflunomide, Dipyridamole, and Pentoxifylline may serve as promising therapeutic agents for PNH, and the hsa-miR-23a-3p/CXCL8 regulatory axis could play a pivotal role in the pathogenesis and progression of PNH.

Background: Paroxysmal nocturnal hemoglobinuria (PNH) is a clonal hematopoietic stem cell disease characterized primarily by intravascular hemolysis, thrombosis, and bone marrow failure. Complement inhibitors are commonly used in clinical treatment and show limited efficacy, highlighting the urgent need to identify new therapeutic targets and explore alternative treatment strategies to provide theoretical guidance for clinical practice. Methods: We established a PNH cell model and constructed an miRNA–mRNA regulatory network to identify key miRNAs and core target genes. Single-cell sequencing data were analyzed to further clarify the critical genes. Finally, integrated drug database analysis identified potential therapeutic agents for PNH, which were validated by molecular docking and molecular dynamics simulations. Results: Using CRISPR/RNP technology, we successfully constructed a PIGA-knockout (PIGA-KO) THP-1 cell model. Differential expression analysis identified 1979 differentially expressed mRNAs (DEmRNAs) and 97 differentially expressed miRNAs (DEmiRNAs). The multiMiR package in R was used to predict the target genes of DEmiRNAs, from which those experimentally validated through dual-luciferase reporter assays were selected. After integration with the DEmRNAs, an miRNA–mRNA regulatory network was constructed, comprising 26 miRNAs and 38 mRNAs. Subsequent miRNA pathway enrichment analysis identified hsa-miR-23a-3p as a key miRNA, with CXCL12, CXCL8, HES1, and TRAF5 serving as core target genes. The integration of single-cell sequencing datasets (PRJNA1061334 and GSE157344) was performed, followed by cell communication and enrichment analysis. This approach, combined with clinical relevance, identified the neutrophil cluster as the key cluster. Intersection analysis of neutrophil cluster differential analysis results with key modules from hdWGCNA further clarified the critical genes. Drug prediction using EpiMed, CMap, and DGIdb identified Leflunomide, Dipyridamole, and Pentoxifylline as potential therapeutic agents. Molecular docking and molecular dynamics simulations showed stable binding of these potential drugs to the critical molecules, indicating a viable molecular interaction foundation. Conclusions: Leflunomide, Dipyridamole, and Pentoxifylline may serve as promising therapeutic agents for PNH, and the hsa-miR-23a-3p/CXCL8 regulatory axis could play a pivotal role in the pathogenesis and progression of PNH.