Mechanisms of Jisheng-Wumei tablet in laryngeal cancer treatment: a network pharmacology analysis of baicalein's targeting of cytochrome C for laryngeal cancer inhibition

Abstract

Objectives: Jisheng-Wumei Tablet (JSWMT) is traditionally used in Chinese medicine for cancer therapy and shows potential efficacy against laryngeal cancer. This study aimed to elucidate the active components of JSWMT, with a specific focus on the role of baicalein in targeting cytochrome C (CYCS) to inhibit laryngeal cancer.

Methods: Utilizing network pharmacology, we identified the active ingredients of JSWMT and their corresponding drug targets by leveraging data from the TCMSP and GeneCards databases to pinpoint laryngeal cancer-related targets. Key targets were identified through survival analysis of TCGA expression data, and molecular docking was employed to evaluate the binding affinity between JSWMT compounds and these targets.

Results: Our research identified 35 effective JSWMT ingredients that interact with 132 drug targets, which intersect with 421 targets related to laryngeal cancer. Survival analysis highlighted IL2, CYCS, and CTNNB1 as critical targets significantly correlated with patient survival. Molecular docking demonstrated a strong affinity between CYCS and baicalein, indicating that baicalein is JSWMT's principal active component against laryngeal cancer.

Conclusion: Baicalein is identified as the key active ingredient in JSWMT, targeting CYCS to inhibit the growth of laryngeal cancer cells. This investigation highlights baicalein's potential mechanism of action and underscores the importance of integrating traditional Chinese medicine with contemporary cancer treatment strategies, offering a novel approach to laryngeal cancer therapy.

Keywords: Baicalin; Curcuma zedoary; Cytochrome C; Dark plums; Effective active ingredient; Jisheng-Wumei Tablet (JSWMT); Laryngeal cancer; Network pharmacology; Safflower; Zombie silkworm.

Fig. 1

Overlay of the JSWMTs’ ingredients and disease targets of laryngeal cancer. The main ingredients of JSWMTs are dark plums, silkworms, curcuma zedoary, and safflower. From the TCMSP database, 352 active ingredients were obtained. According to OB ≥ 30% and DL ≥ 0.18 setting, 35 effective ingredients were screened in the TCMSP database. Among them, 24 active ingredients act on 132 drug targets (light green). Using the Genecards (https://www.genecards.org/) database, 421 disease targets were predicted related to the keyword "laryngeal squamous cell carcinoma" from the GeneCards database. By R language VennDiagram package, intersection analysis was performed on the drug and disease targets, resulting in 85 intersection objects

Fig. 2

Functional and Pathway Enrichment Analysis of Intersected Targets. A GO enrichment analysis of the intersected targets. The default background gene set from the ClusterProfiler package was applied to analyze the intersection between drug targets and disease targets (see Fig. 1A). The enrichment results were visualized by drawing a bar chart using the enrichplot package (version 1.10.2). It enriched 2164 GO processes (p.adjust < 0.05&count > 2), including 2012 biological processes (BP) directories, 43 cellular components (CC) directories, and 108 Molecular Function (MF) directories. The figure shows each of the top 10 BP (up panel), MF (middle panel), and CC (lower panel). B KEGG enrichment analysis of the intersected targets. The default background gene set from the ClusterProfiler package was applied to analyze the intersection between drug targets and disease targets (see Fig. 1A). The enrichment results were visualized by drawing a bar chart using the enrichplot package (version 1.10.2). KEGG was enriched in 160 pathways (p.adjust < 0.05 & count > 2). The top 20 pathways are shown in the figure

Fig. 3

Network pharmacology (NP) analysis of Jiwu-Shengmei tablets (JSWMT) in treating laryngeal cancer. A A pharmacological regulatory network was constructed for TCM using active ingredients corresponding to intersecting targets, which were visualized by Cytoscape. The network contains four drugs (orange), 22 active ingredients (blue), 85 intersecting targets (light platinum omitted), and a total of 385 relationship pairs. B Utilizing STRING, a PPI network was created for the 85 intersecting targets. With confidence = 0.4, 85 protein interaction networks were screened out, including 85 nodes and 555 edges. The protein network diagram was beautified using Cytoscape. The dimension and color depth of nodes reflect their grade of connectivity

Fig. 4

Survival analysis of key targets in laryngeal squamous cell carcinoma. The expressed crucial protein data for laryngeal squamous cell carcinoma were downloaded from TCGA. The samples were classified into high (red line) and low (blue) expressive groups based on the median of the gene expression. Kaplan–Meier curves were prepared using R package survival for the overall survival of the interesting targets according to low (blue line) and high (red line) expression groups. Genes with significant survival (p < 0.05) were used as key targets. Among the 85 intersection targets, the expression levels of three target genes, IL2 (up panel), CYCS (middle panel), and CTNNB1 (lower panel), were significantly correlated with survival time

Fig. 5

Molecular docking of cytochrome C (CYCS) with baicalein. Molecular docking was performed between the CYCS with significant intersection target survival and active ingredients (quercetin, luteolin, baicalein, and beta-carotene). The crystal structure corresponding to CYCS was obtained from the PDB database. The 3-D structure of the active ingredient was downloaded from the TCMSP database. AutoDock vina was used for molecular docking. The docking affinity between CYCS and baicalein is -8.3 kcal/mol. The green stick model in the picture is the effective molecule baicalein, and the cyan stick structures closed to baicalein are amino acid residues that have hydrogen bond interactions with the effective molecule. Yellow dashed lines are the hydrogen bonds between the amino acid residues and active molecules. Among them, HIS-18 residue, THR-28 residue, and TYR-46 residue have hydrogen bonds associated with the baicalein molecule