Network pharmacology and transcriptomics reveal the mechanisms of FFBZL in the treatment of oral squamous cell carcinoma

Abstract

BackgroundFFBZL is composed of three herbs: Scutellaria barbata D. Don (SBD), Astragali Radix (AR), and Ligusticum chuanxiong Hort (CX). FFBZL has been reported to be effective in the treatment of oral squamous cell carcinoma (OSCC). However, the molecular mechanism involved remains unclear. Based on network pharmacology combined with bioinformatics and molecular docking, the effect and molecular mechanism of action of FFBZL in treating OSCC were explored.Materials and methodsThis study employed an integrated approach using various databases and literature sources to identify the effective components of FFBZL, with a specific emphasis on screening active ingredients that align with traditional Chinese medicine principles. The TCMSP, ETCM, and SymMap databases were utilized to collect information on the active constituents and targets of FFBZL, while the PharmMapper database was used to predict targets. Key components were selected based on the degree value of the ‘active component−target’ network. Transcriptome data for OSCC samples were obtained from the TCGA and GEO databases. Differential gene expression analysis was conducted to identify targets associated with OSCC, and these targets were subsequently aligned with targets of the effective components of FFBZL to identify common targets. Subsequently, the STRING database was utilized to construct a protein‒protein interaction (PPI) network of these common targets, which was subsequently visualized using Cytoscape. Next, 71 targets were rescreened using the PPI network, and GO and KEGG enrichment analyses were performed; the PI3K-Akt signaling pathway was the top-ranking pathway related to cell apoptosis. Next, the expression of 19 genes enriched in the PI3K-Akt signaling pathway was analyzed using OSCC transcriptome data from the TCGA and GEO databases. The targets were subsequently mapped to the PI3K-Akt signaling pathway using the KEGG database, and the GSEA algorithm was used to assess the overall expression trend of the genes in this pathway. The 71 common targets were subsequently imported into the STRING database and visualized using Cytoscape. The DEGREE and MCC algorithms were used to select the corresponding targets within the PPI network. The intersection of these targets and the 19 targets mapped to the PI3K-Akt signaling pathway led to the identification of 6 key targets associated with cell apoptosis: GSK3B, PIK3CA, FN1, MET, SPP1, and MAPK3. Subsequently, the UALCAN database was utilized to analyze the expression levels and survival associations of the key genes related to cell apoptosis, and the transcriptome data from the GEO database were used to assess the correlations among the 6 key genes. Finally, molecular docking studies were conducted to explore the relationships between these targets and the active components with predicted associations.ResultsThis study identified six key components of FFBZL (quercetin, wogonin, carthamidin, scutellarein, senkyunolide K and astragalosidei: astragaloside I) as well as 820 potential target genes of these components. Intersection of these targets with those related to OSCC yielded 151 common targets. GO and KEGG enrichment analyses revealed that most of the top-ranked functions and pathways were associated with apoptosis, with the PI3K-Akt signaling pathway playing a critical role. Transcriptome analysis of data from the TCGA and GEO databases indicated that the genes enriched in the PI3K-Akt signaling pathway were strongly upregulated, and the GSEA algorithm indicated an overall upregulation trend for the PI3K-Akt signaling pathway. By intersecting the targets with the 19 genes mapped to the PI3K-Akt signaling pathway using the DEGREE and MCC algorithms, six key targets related to cell apoptosis were identified. The mRNA and protein expression levels of most these targets in head and neck squamous cell carcinoma were higher than those in normal tissues. Survival analysis revealed that low expression of SPP1 and FN1 was associated with increased patient survival time. Additionally, the molecular docking results indicated strong binding potential between the six identified key components and the six key targets.