We used the HERB (http://herb.ac.cn/) database to retrieve all chemical components of FOA by searching for “A LI HONG. “The PubChem IDs of all components were then copied into the PubChem (https://pubchem.ncbi.nlm.nih.gov/) database, In this way, the structural information of the compounds could be obtained. We screened primary components using gastrointestinal (GI) absorption and Lipinski’s Rule of Five (miLogP ≤5, nOHNH ≤5, nOH ≤10), then further identified effective active components via the SwissADME database, incorporating additional criteria: GI absorption, and Ghose, Veber, Egan,and Muegge rules. After applying these filtering conditions, we identified a total of five effective active components from FOA. Next, we used the Swiss Target Prediction database to predict the targets of these selected active components, resulting in 379 drug-target interactions. Using “gastric cancer” as a keyword, we searched the GeneCards database and obtained a total of 14,092 gastric cancer-related targets. Drug and disease targets were used to draw a Venn diagram on the SRplot (http://www.bioinformatics.com.cn/), and 329 drug-disease common targets were obtained after taking their intersection.

These overlapping genes represent potential therapeutic targets for drug-disease treatment. The intersecting targets between FOA and gastric cancer (GC) were then inputted into the STRING (https://string-db.org/) database for multi-protein interaction searches. We set the species as “Homo sapiens” and the interaction threshold at 0.9 to obtain a more tightly connected protein network with higher confidence. This process resulted in the construction of a protein-protein interaction (PPI) network, which included 328 nodes and 4,486 edges. Subsequently, we used Cytoscape 3.10.3 software to visualize and perform network topology analysis on this PPI network. Isolated nodes (genes) were removed from the network. In the resulting network, the larger and darker-colored nodes indicate higher degree values (i.e., more connections), suggesting that these targets play critical roles within the network.

The collected common targets were imported into the DAVID (https://david.ncifcrf.gov/) database to perform Gene Ontology (GO) functional enrichment analysis and KEGG pathway enrichment analysis, followed by visualization. The results were sorted by p-values for cellular components (CC), molecular functions (MF), and biological processes (BP). The data were downloaded, and the top 10 core targets were selected. These targets were then imported into the MicroSignal platform for GO analysis, generating bubble plots, and KEGG pathway analysis.

First, five active ingredients were retrieved from the PubChem database and saved in SDF format. Chem3D 2020 software was used to optimize the molecular structure of these small molecules via molecular force field optimization, resulting in the lowest energy state optimal molecular structures. Five core targets closely related to these five active ingredients were identified: AKT1 (PDB ID: 1H10), SRC (PDB ID: 1A07), EGFR (PDB ID: 1M14), BCL2 (PDB ID: 1QX3), and CASP3 (PDB ID: 1GFW). To preliminarily validate the network prediction results, the five main active ingredients and the five core targets were subjected to molecular docking using AutoDock Vina 3.10.3. A binding affinity of less than −7.00 kcal/mol indicated satisfactory binding strength. The top six molecular docking binding energies were selected for visualization analysis using PyMOL.

Take an appropriate amount of FOA medicinal material in chunks, and reflux extract it twice with 10 times its volume of 90% ethanol for 2 h each time. Combine the extraction solutions, filter them, and concentrate under reduced pressure to 1/5 of the original volume. This gives the crude extract of FOA triterpenic acid. Load the crude extract into a certain volume of pretreated D101 macroporous adsorption resin. Apply the previously prepared sample solution onto the column at a flow rate of 2 mL/min, and elute with 90% ethanol. After collecting the eluate, evaporate the solvent to obtain the purified FOA triterpenic acid. The contents of dehydrosulphurenic acid and dehydroeburicoic acid were used as evaluation indicators. The preparation method was finally determined by HPLC analysis. The results showed that the method is feasible and the process is stable and reliable.

Human gastric cancer MKN-45 cells were purchased from Zishan Biotechnology Co., Ltd. The cells were cultured in RPMI 1640 medium supplemented with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin at 37 °C in a humidified incubator containing 5% CO2. The effect of FOA triterpenic acid extract on cell proliferation was evaluated using the CCK-8 assay. The highly sensitive cell proliferation detection reagent (CCK-8) was purchased from Yacoen Biotechnology Co., Ltd. and used to assess cell viability in response to different concentrations of FOA triterpenic acid extract. Various concentrations of FOA triterpenic acid extract (0, 7.5, 15, 30, 60, 120 μ g/mL) were added to the respective groups to evaluate cell viability. The control group (0 μg/mL) received RPMI 1640 medium supplemented with 10% FBS. After treatment with FOA triterpenic acid extract for 24 and 48 h, 10%CCK-8 cell proliferation-toxicity detection reagent was added to each well, and the plates were incubated at 37 °C for 2 h.

The optical density (OD) was measured at 450 nm using a microplate reader. The half-maximal inhibitory concentration (IC50) of FOA triterpenic acid extract on MKN-45 cells was calculated based on these measurements.

A sterile 200 μL pipette tip was used to create straight lines across the cell monolayer. After scratching, the old culture medium was discarded, and the cells were washed with PBS buffer. The starved cells in each group were treated with different concentrations of FOA triterpenic acid extract (20, 40, 80 μg/mL) for 24 h, while the control group (0 μg/mL) received RPMI 1640 medium supplemented with 10% FBS. Microscopic images were taken immediately after adding the treatment (time recorded as 0 h). The cells were then returned to the incubator for further culture. After 24 h, additional microscopic images were taken to observe the migration of the cells.

Transwell Assay experiment was divided into a control group (0 μg/mL) and three concentration treatment groups (20, 40, 80 μg/mL). Matrigel was thawed overnight at 4 °C and kept on ice during the operation. RPMI 1640 medium was mixed with Matrigel matrix at a ratio of 1:8. Then, 50 µL of the diluted Matrigel was added to the upper chamber of the Transwell insert and allowed to solidify. MKN-45 cells were seeded at a density of 5 × 10⁵ cells per insert containing the solidified Matrigel. The lower chamber was filled with 500 µL of culture medium containing 20% FBS for both the control and treatment groups. The cells were incubated for 48 h. After 48 h, the upper chambers were removed, and the inner side of the membrane was gently wiped with a cotton swab to remove non-migrated cells. The membranes were washed twice, fixed, stained with crystal violet, washed again, and air-dried upside down. The number of MKN-45 cells that had migrated through the Matrigel to the outer side of the membrane was observed under a microscope. Three clear fields were randomly selected for imaging and cell counting.

After treating the cells with different concentrations of FOA triterpenic acid extract (20, 40, 80 μg/mL) for 24 h, the control group (0 μg/mL) was also collected for flow cytometry analysis. The cell cycle detection kit (2024R1E) and the cell apoptosis detection kit (2024F2K) were purchased from Beijing Pulilai Gene Technology Co., Ltd. For cell cycle and apoptosis analysis, MKN-45 cells were stained according to the manufacturer’s instructions. Specifically, the cells were processed using the respective kits and then analyzed using a small flow cytometer-3F-3 (Apogee, United Kingdom).

Collect cells treated with different concentrations of Fomes officinalis Ames triterpenic acid extract (20, 40, 80 μg/mL) for 48 h. The control group (0 μg/mL) was also collected. The cells were digested with 0.25% trypsin, centrifuged, and the supernatant was discarded. The cells were washed with PBS, and the supernatant was discarded again. Next, 50 μL of lysis buffer was added to resuspend the cell pellet, which was then lysed on ice for 30 min with vortexing three times for 10 s each. The lysate was centrifuged at 4 °C at 12,000 rpm for 10 min. The supernatant was carefully collected and transferred to a new tube, kept on ice until use for Caspase-3 activity detection. For Caspase-3 activity analysis, follow the instructions provided by the Caspase-3 Activity Assay Kit (G015-1-1) from Nanjing Jiancheng Bioengineering Institute. Incubate the samples at 37 °C for 4 h. When the color change was evident, measure the absorbance at 405 nm (A405) using a microplate reader. The Caspase-3 activity unit (U) was calculated using the following formula. The experiment was repeated three times.

Statistical analysis was performed using GraphPad Prism software (version 9). Each gradient was set with three replicates, and the results were expressed as mean ± standard deviation (SD). For data that followed a normal distribution, one-way analysis of variance (ANOVA) was used to compare multiple groups. A p-value <0.05 was considered statistically significant.

The chemical structures of the effective active components of FOA (Figures 1A–E) were obtained from the PubChem database. Gastric cancer-related genes were retrieved from the GeneCards database, and the intersection was visualized, resulting in a total of 329 intersecting genes (Figure 1F). Subsequently, the Cytoscape 3.10.3 software was used to construct the PPI (protein-protein interaction) network for these intersecting genes. In this network, nodes with deeper colors indicate higher connectivity. The top five genes with the highest degree values are AKT1, SRC, EGFR, BCL2, and CASP3 (Figure 1G), suggesting that FOA may exert its anti-tumor effects by acting on multiple targets.

To elucidate the role of FOA in gastric cancer treatment, we performed GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses on the 329 co-expressed genes using the DAVID database. GO Enrichment Analysis Results (Figure 2A). The GO enrichment analysis revealed the following biological processes associated with the core common targets of FOA-gastric cancer (ranked by relevance): Positive regulation of MAPK kinase activity, Response to external stimuli, G protein-coupled receptor-cyclic nucleotide signaling pathway, Phospholipase C-activating G protein-coupled receptor signaling pathway, Positive regulation of the extracellular signal-regulated kinase 1/2 (ERK1/2) cascade; The core drug-disease common target gene set was mainly enriched in cellular components such as: Plasma membrane, Cytoplasm, Receptor complexes, Dendrites, Synapses; The molecular functions primarily involved were histone H2AX Y142 phosphorylation activity, Histone H3 T41 phosphorylation activity, Protein tyrosine kinase activity, Protein serine kinase activity, Enzyme binding. KEGG Pathway Enrichment Analysis Results (Figure 2B). The KEGG pathway enrichment analysis selected pathways with a p-value <0.05. The representative enriched signaling pathways included neuroactive ligand-receptor pathways, cancer, the calcium signaling pathway, the cAMP signaling pathway, and serotonergic synapse.

Based on the results of the PPI network analysis, five key target genes were selected for molecular docking with the five effective components of FOA. The docking results are shown in Figure 3A. The binding energies between the five target proteins and the five active components of FOA were all below −6 kcal/mol. Specifically, ergotamine formed hydrogen bonds with CASP3 (3 hydrogen bonds), EGFR (2 hydrogen bonds), BCL2 (5 hydrogen bonds), and SRC (5 hydrogen bonds). Officinalic acid formed hydrogen bonds with CASP3 (2 hydrogen bonds) and EGFR (4 hydrogen bonds). These results indicate strong binding affinities between the key active components and the core targets (Figures 3B,C).

The HPLC analysis was performed using an Analytical column (4.6 mm × 250 mm, 5 μm). The mobile phase consisted of acetonitrile (A) and 0.4% phosphoric acid (B) with a gradient elution program: 80%–90% A from 0 to 8 min, and 90%–95% A from 8 to 20 min. The injection volume was 10 μL, and the detection wavelength was set at 242 nm. The flow rate was 1.0 mL/min, and the column temperature was maintained at 30 °C. The analysis results are shown in Figure 4. The retention times of the two index components were 4.37 min and 16.71 min, respectively, with well-defined peak shapes, indicating that the method is free from interference in the determination of dehydrosulphurenic acid and dehydroeburicoic acid in the FOA triterpenic acid extract. Peak 1: Dehydrosulphurenic acid (65.45 mg/g); Peak 2: Dehydroeburicoic acid (27.05 mg/g).

The effect of FOA triterpenic acid extract on the proliferation of MKN-45 gastric cancer cells was evaluated using the CCK-8 assay. After treating the cells with different concentrations of FOA triterpenic acid extract (0, 7.5, 15, 30, 60, and 120 μg/mL) for 24 and 48 h, cell proliferation ability decreased with increasing drug concentration and time, indicating that FOA triterpenic acid extract inhibited theproliferation of MKN-45 cells. Additionally, the IC50 values of FOA triterpenic acid extract on MKN-45 cells at 24 and 48 h were calculated using GraphPad Prism as 41.26 μg/mL and 16.21 μg/mL, respectively (Figures 5A,B). Therefore, concentrations of 20, 40, and 80 μg/mL were selected for subsequent experiments. The wound healing assay showed that cell migration significantly decreased with increasing concentrations of FOA triterpenic acid extract (Figure 5C). Similar results were observed in the Transwell invasion assay (Figure 5D).

Additionally, gastric cancer cells were treated with FOA triterpenic acid extract at concentrations of 20, 40, and 80 μg/mL to investigate changes in the cell cycle and apoptosis. As expected, SSA (presumably a typo for FOA) induced cell cycle arrest at the G1 phase (Figure 6A) and promoted apoptosis (Figure 6B). The apoptosis rate increased with increasing concentrations of the extract. These results collectively indicate that FOA triterpenic acid extract can inhibit the proliferation of MKN-45 cells and promote apoptosis.

Caspase-3 is a crucial initiator in the death receptor-mediated apoptosis pathway (Chen et al., 2016). Caspase-3 can activate itself through oligomerization and cleavage, subsequently activating downstream cysteine proteases to produce apoptotic effects. Caspase-3 plays a significant role in inducing apoptosis and inhibiting cell proliferation. It is widely expressed in normal human tissues as well as in various tumor tissues such as lung cancer, gastric cancer, ampullary cancer, and breast cancer (Jiang et al., 2015). Experimental results showed that after treating MKN-45 cells with FOA triterpenic acid extract at concentrations of 20, 40, and 80 μg/mL, the expression levels of Caspase-3 in MKN-45 cells increased gradually with increasing concentrations. Compared to the control group, these differences were statistically significant (P < 0.001), as shown in Table 1. These findings suggest that FOA triterpenic acid extract induces apoptosis in gastric cancer cells by enhancing the expression of Caspase-3.