Identification of Novel Biomarkers and Targets for Natural Products in Inhibiting Prostate Cancer

Abstract Background: Prostate cancer (PCa) is a common urinary system malignancy. The lack of specific and sensitive biomarkers for the diagnosis and prognosis of PCa makes it important to seek alternatives. Meanwhile, targeted PCa inhibitors are limited. Natural products that potentially target PCa may offer a useful approach. Methods: Expression profile datasets about PCa from GEO were analyzed. Core differential genes were identified by String and Cytoscape. GEPIA and HPA were utilized to further validate the key genes. The targets of natural products were obtained from the Drugbank, Therapeutic Target Database, BindingDB, PubChem, and chEMBL databases, and PCa therapeutic targets were generated from the GeneCards, OMIM, and PharmGkb databases. Cytoscape was also used to screen the core modules and disease-drug targets. Construction of molecular docking models of drug-core targets was performed by Autodock to confirm the accuracy of the targets. Results: Four identified biomarkers, CENPF, TPX2, TK1 and CCNB1 were verified by HPA. Five novel PCa biomarkers, RRM2, UBE2C, TOP2A, BIRC5 and ZWINT were also identified. All the nine markers indicated poor prognosis for PCa patients were verified by GEPIA. PCa carcinogenesis is found to be mainly associated with hepatic fibrosis pathway, ILK signaling, NRF2-mediated oxidative stress response and many others. Four key PCa targets for curcumin (EP300, RELA, EGFR, NFKB1), seven for taxol (PTEN, EGFR, ERBB2, TP53, KRAS, AR, AKT1) and two for ursolic acid (GSK3B, RELA) were identified by Cytoscape combined KEGG and verified by Autodock. Conclusions: The novel identified biomarkers in our study would be valuable for the diagnosis and prognosis of PCa. Key targets of curcumin, paclitaxel, and ursolic acid in PCa could lay a solid foundation for precise treatment and molecularly targeted therapy for PCa.