ObjectiveTo investigate the expression and clinical significance of HIST1H1B gene in bladder cancer.MethodsInformation on HIST1H1B in the dataset GSE13507 was downloaded from the GEO database. Discrepancy in expression of HIST1H1B in normal tissues and bladder cancer tissues was analyzed by t-test. Survival analysis was performed by using Log-rank algorithm. The association between HIST1H1B gene expression and clinicpathological features was analyzed using Chi-square test. Gene enrichment analysis (GSEA) was performed to explore possible pathways of HIST1H1B involved in bladder cancer.ResultsHIST1H1B was down-regulated in normal tissues and highly expressed in bladder cancer tissues (P=0.002 5). The expression of HIST1H1B was associated with age, gender, T stage, M stage, N stage, disease stage, but not associated with invasiveness and progression. Whether in overall survival (HR=1.732, 95%CI 1.070 to 2.803) or tumor-specific survival (HR=2.000, 95%CI 0.996 to 4.017), patients with high expression of HIST1H1B were significantly lower than that in patients with low expression (P<0.05). GSEA results showed that HIST1H1B may influence the occurrence and development of bladder cancer by regulating MYC signaling pathway V2, G2M checkpoint, E2F signaling pathway, spermatogenesis, mitotic spindle, etc.ConclusionsHIST1H1B may be a biomarker for determining the prognosis of bladder cancer and a target for treatment of bladder cancer.
Objective To explore the pathogenesis of epilepsy (EP) and predict traditional Chinese medicine (TCM) prescriptions based on the concept of reverse network pharmacology. MethodsDifferentially expressed genes (DEGs) in EP were screened from the Gene Expression Omnibus (GEO) database. A weighted gene co-expression network analysis (WGCNA) was constructed to identify genes with the highest expression variability, which were then compared with EP target genes obtained from databases including GeneCards, Online Mendelian Inheritance in Man (OMIM), and Therapeutic Target Database (TTD). Core targets were screened using the STRING platform. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to elucidate the pathogenesis and signaling pathways of EP. After converting core targets using the UniProt database, active ingredients and corresponding TCM herbs were reversely collected from relevant databases. Cytoscape software was used for visualization and construction of the core target-active ingredient-TCM herb network. Molecular docking verification between core targets and core ingredients was conducted using CB-DOCK2 software, and TCM herbs with high degree values were finally determined. ResultsA total of 131 EP targets were obtained, and 30 key targets were selected based on degree values. GO enrichment analysis yielded 30 main entries, and KEGG enrichment analysis identified 10 signaling pathways. Seven blood-absorbable ingredients and 20 TCM herbs were matched from the Comparative Toxicogenomics Database (CTD) based on degree values. Molecular docking verification was performed between 6 core target proteins and 7 core ingredients with high degree values, and the results were stable and favorable. A total of 20 TCM herbs were screened out, including Corydalis Rhizoma, Daturae Flos, Bruceae Fructus, and Corydalis Decumbentis Rhizoma. ConclusionThe application of reverse network pharmacology thinking and molecular docking technology to predict targets, pathways, ingredients, and TCM prescriptions for epilepsy provides new ideas and theoretical basis for clinical treatment and research.