Abstract
Lung cancer is one of the most devastating diseases worldwide, with high incidence and mortality worldwide, and the anticancer potential of traditional Chinese medicine (TCM) has been gradually recognized by the scientific community. Astragali Radix (AR) is commonly used in traditional Chinese medicine in the treatment of lung cancer and has a certain clinical effect, but effective components and targets are still unclear. In the study, we established an integrated strategy for effective-component discovery of AR in the treatment of lung cancer based on a variety of techniques. First, the effective components and potential targets of AR were deciphered by the "component-target-disease" network using network pharmacology, and potential signal pathways on lung cancer were predicted by Gene Ontology (GO) biological function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Then, the therapeutic effects of AR in the treatment of lung cancer were evaluated in vivo using A/J mice, and the potential targets related to autophagy and potential signal pathway were verified by Western blot analysis, immunofluorescence staining, and real-time PCR technology at protein and gene expression level. Finally, metabolism in vitro by rat intestinal flora and cell membrane immobilized chromatography technology were used to screen the effective components of AR in the treatment of lung cancer, and remaining components from the cell immobilized chromatography were collected and analyzed by ultra-performance liquid chromatography-electrospray quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). The screening results of the integrated strategy showed that calycosin-7-O-β-D-glucoside, ononin, calycosin, astragaloside IV, astragaloside II, cycloastragenol, and formononetin may be effective components of AR in the treatment of lung cancer, and they may play a role in the treatment of lung cancer through autophagy and p53/AMPK/mTOR signaling pathway. The integrated strategy for effective-component discovery provided a valuable reference mode for finding the pharmacodynamic material basis of complex TCM systems. In addition, the prediction for targets and signal pathways laid a foundation for further study on the mechanism of AR in the treatment of lung cancer.