Exploring the Action Mechanism of Yadanzi (Brucea javanica) in the Treatment of Glioblastoma Based on Bioinformatics and Network Pharmacology

Abstract

Abstract Objective The aim of the study is to explore the molecular mechanism of Yadanzi (Brucea javanica) in the treatment of glioblastoma (GBM) by using the methods of bioinformatics and network pharmacology. Methods The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and literature retrieval method were applied to obtain the active ingredients of Yadanzi (Brucea javanica), and to predict the relevant targets of the active ingredients. The GBM-related targets were retrieved and screened through the Gene Expression Profiling Interactive Analysis (GEPIA) database, and mapped to each other with the targets of the components of Yadanzi (Brucea javanica) to obtain the intersection targets. The GBM differentially expressed gene targets were imported into the String database to obtain the protein interaction relationship, the Cytoscape software was used to draw the protein interaction network, the Cytobba and MCODE plug-ins were used to screen the core genes and important protein interaction modules, and the GEPIA database was applied to make survival analysis of the core genes. The network map of “active ingredients-targets” was constructed through the Cytoscape 3.6.1 software. Gene Ontology (GO) biological function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis for GBM differentially expressed genes were performed through the DAVID database. Results Through TCMSP and literature retrieval, 23 potential active ingredients and 129 related targets were obtained from Yadanzi (Brucea javanica). In the GEPIA database, 247 GBM differentially expressed genes were screened, including 113 up-regulated genes and 134 downregulated genes. After mapping with the targets related to the active ingredients of Yadanzi (Brucea javanica), six intersection targets were obtained, that is, the potential action targets of Yadanzi (Brucea javanica) in treating GBM, including MMP2, HMOX1, BIRC5, EGFR, CCNB2, and TOP2A. Cytoscape software was applied to build an “active ingredient-action target” network. Two active ingredients and five action targets of β-sitosterol (BS) and luteolin were found, and the targets were mainly concentrated in BS. It was found by KEGG pathway enrichment analysis that GBM differentially expressed genes were mainly involved in signaling pathways related to Staphylococcus aureus infection, phagosome formation, tuberculosis and systemic lupus erythematosus and other infectious and autoimmune diseases. It was found by GO enrichment analysis that the GBM differentially expressed genes mainly involved such biological processes (BP) as the processing and presentation of exogenous antigenic peptides and polysaccharide antigens through MHC II molecules, γ-interferon-mediated signaling pathways, extracellular matrix composition, and chemical synapses transmission; it involved cellular components such as cell junctions, axon terminal buttons, extracellular space, vesicle membranes for endocytosis, and MHC II protein complexes; molecular functions such as calcium-mediated ionic protein binding, MHC II molecular receptor activity, immunoglobulin binding, and phospholipase inhibitor activity were also involved. Survival analysis was conducted by GEPIA on the top 37 core targets in degree value, and a total of five genes related to GBM prognosis were obtained. Among them, FN1 and MMP2 were highly expressed while GABRD (γ-aminobutyric acid A receptor delta subunit), RBFOX1, and SLC6A7 were expressed at a low level in cancer patients. Conclusion The pathogenesis of GBM is closely related to the human immune system, and BS and luteolin may be the main material basis of Yadanzi (Brucea javanica) for the treatment of GBM and the improvement of prognosis. The molecular mechanism may be related to the physical barrier formed by destroying the tumor cell stromal molecules and its involvement in tumor immune response.