Strategies for exploring mechanisms of polydatin against NSCLC based on experimentally validated network pharmacology and prognostic prediction of lipid metabolism gene expression.

Background: Polydatin (PD) is a glucan extracted from the plant Polygonum cuspidatum that possesses a wide range of pharmacological activities. However, the mechanism underlying its the influence of PD on NSCLC is not clear.

Objective: To explore the mechanism of action of PD against non-small cell lung cancer (NSCLC) using a combination of bioinformatics and experimental validation.

Methods: We utilized bioinformatics methods with the TCGA, ferroptosis, and lipid metabolism databases to assess the value, distribution, and potential role linkages of the core targets in NSCLC therapy. In vivo experiments were conducted using in situ tumor mouse models to confirm the inhibitory effect of PD on NSCLC.

Results: Network pharmacology analysis revealed that 76 PD-related genes associated with NSCLC and five hub targets, including EGFR, TNF, ALB, CASP3, ERBB2, lipids and atherosclerosis, and the TNF signaling pathway might play essential roles in the anti-NSCLC effect of PD. EGFR and TNF are potential driver genes for ferroptosis. LASSO regression analysis was used to screen potential genes and construct an independent prognostic model of 26 LMRGs. Six genes (PLIN1, ALPI, DECR1, GPAM, OSBPL5, and MED19) were further identified by multivariate Cox regression analysis. The construction of risk models associated with LMRGs has strong potential for the prognostic prediction of NSCCLC patients. Cell and animal experiments also confirmed that PD inhibits LLC cell invasion and propagation ability.

Conclusion: This study revealed that PD may regulate multiple signaling pathways by targeting genes such as EGFR, TNF, and LMRGS to inhibit NSCLC proliferation and metastasis.