Cervical cancer (CA) continues to be a female malignant tumor with limited therapeutic options, resulting in a high mortality rate. Sanguinarine (SANG), a naturally occurring alkaloid, has demonstrated notable efficacy in preclinical treatment of CA. However, the mechanism through which SANG acts against CA is not fully understood. To address this, utilizing nine drug target prediction databases, we have successfully identified 379 potential targets for SANG. Venn diagram analysis compared 2367 CA-related targets from the GeneCards disease database, 2618 CA-closely related targets derived from multiple datasets in GEO through WGCNA analysis, and the 379 potential targets of SANG, resulting in 35 shared targets. Subsequently, by employing PPI network analysis, the Cytohubba plugin, the Human Protein Atlas, TCGA database data, and ROC curve analysis, we have identified AURKA and CDK2 as key targets of SANG in combating CA. Single-gene GSEA results suggest that the overexpression of AURKA and CDK2 is closely correlated with DNA replication, cell cycle progression, and various DNA repair pathways in CA. Molecular docking and molecular simulation dynamics analyses have confirmed the stable binding of both AURKA and CDK2 to SANG. In summary, by integrating diverse methodological approaches, this study discovered that SANG potentially inhibits the malignant features of CA by targeting AURKA and CDK2, thereby regulating DNA replication, cell cycle progression, and multiple DNA repair pathways. This lays a solid foundation for further exploring the pharmacological role of SANG in CA therapy. However, further in-depth in vitro and in vivo experiments are required to corroborate our findings.
Keywords: AURKA; CDK2; Cervical cancer; Molecular dynamics simulation; Sanguinarine; Weighted gene co-expression network analysis.
© 2024. The Author(s).