Integrated Bioinformatics Reveals PLK1 as a Driver and Rapamycin as a Drug Candidate in Stage III–IV Prostate Cancer

Abstract

Background: Prostate cancer is one of the most commonly diagnosed malignancies in men worldwide. This study aimed to identify differentially expressed genes associated with prostate cancer progression by integrating tumor stage and prostate-specific antigen (PSA) levels.

Methods: Microarray data from the GEO dataset (GSE116918) were analyzed using GEO2R based on gene expression levels, tumor stage, and PSA categories. The dataset comprised 51 stage I, 76 stage II, 92 stage III, and 4 stage IV tumors. Survival-associated genes were identified using GEPIA2. Receiver operating characteristic (ROC) curve analysis was performed using OriginPro software. Copy number variation analysis and immune infiltration profiling were performed using GISTIC and TIMER tools. Molecular docking and dynamic simulations were performed using PyRx and NAMD, respectively.

Results: PLK1 expression was significantly higher in stage IV than in stage II prostate cancer, indicating its potential role in tumor progression. Survival and ROC analyses further supported the prognostic significance of PLK1 in this context, demonstrating its strong predictive accuracy in advanced-stage disease. In addition to its association with disease stage and PSA levels, PLK1 expression was linked to molecular characteristics, including CpG methylation and copy number alterations, as well as immune cell infiltration involving CD8⁺ and CD4⁺ T-cells, macrophages, dendritic cells, and monocytes. Drug screening highlighted rapamycin as a potent PLK1 inhibitor, with strong binding affinity and structural stability, as confirmed by docking and molecular dynamics simulations.

Conclusion: These findings suggest that PLK1 may serve as a stage-specific biomarker and therapeutic target, particularly in advanced-stage prostate cancer.