Background::Yishan formula (YSF) has a significant effect on the treatment of breast
cancer, which can improve the quality of life and prolong the survival of patients with breast
cancer; however, its mechanism of action is unknown.
Objective::In this study, network pharmacology and molecular docking methods have been used
to explore the potential pharmacological effects of the YSF, and the predicted targets have been
validated by in vitro experiments.
Methods::Active components and targets of the YSF were obtained from the TCMSP and Swiss
target prediction website. Four databases, namely GeneCards, OMIM, TTD, and DisGeNET,
were used to search for disease targets. The Cytoscape v3.9.0 software was utilized to draw the
network of drug-component-target and selected core targets. DAVID database was used to analyze
the biological functions and pathways of key targets. Finally, molecular docking and in
vitro experiments have been used to verify the hub genes.
Results::Through data collection from the database, 157 active components and 618 genes implicated
in breast cancer were obtained and treated using the YSF. After screening, the main active
components (kaempferol, quercetin, isorhamnetin, dinatin, luteolin, and tamarixetin) and
key genes (AKT1, TP53, TNF, IL6, EGFR, SRC, VEGFA, STAT3, MAPK3, and JUN) were obtained.
Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment
analysis indicated that the YSF could affect the progression of breast cancer by regulating
biological processes, such as signal transduction, cell proliferation and apoptosis, protein phosphorylation,
as well as PI3K-Akt, Rap1, MAPK, FOXO, HIF-1, and other related signaling
pathways. Molecular docking suggested that IL6 with isorhamnetin, MAPK3 with kaempferol,
and EGFR with luteolin have strong binding energy. The experiment further verified that YSF
can control the development of breast cancer by inhibiting the expression of the hub genes.
Conclusion::This study showed that resistance to breast cancer may be achieved by the synergy
of multiple active components, target genes, and signal pathways, which can provide new avenues
for breast cancer-targeted therapy.