Objective: To explore the molecular markers related to lymph node metastasis of prostate cancer (PCa) based on bioinformatics technology and carry out clinical verification. Methods: The differentially expressed genes of PCa with lymph node metastasis were screened from geo data, and the hub genes of the gene co expression network were constructed. The hub genes were incorporated into the support vector machine model to evaluate its prediction efficiency. The hub genes were verified in the TCGA data set and analyzed for immune infiltration. The clinical data of 80 patients with prostate cancer in the Fourth Hospital of Hebei Medical University from January 2019 to December 2022 were collected. The logistic risk model was used to evaluate the prediction efficiency of hub gene metastasis. Results: Five hub genes (GSK3B, TP53, PSMC6, SUMO1, PIK3CA) were identified, and the support vector machine model constructed by them had good diagnostic value (the accuracy rate was 83.87%). TCGA validation results showed that only PSMC6 was significantly differentially expressed in PCa tissues with lymph node metastasis (P<0.001). The results of immune infiltration analysis showed that the expression of PSMC6 was significantly correlated with 9 kinds of immune cells (B cells, DC, IDC, etc.). Clinical information analysis showed that the expression of PSMC6 was significantly correlated with lymph node metastasis, PSA value, T stage and Gleason score (P<0.01). Univariate logistic results showed that T stage (OR=3.230, 95%CI:1.192-8.757, P=0.021), Gleason score (OR=4.627, 95%CI:2.212-9.677, P<0.001), PSMC6 (OR=25.235, 95%CI:5.326-119.560, P<0.001) could be used as predictors of lymph node metastasis. Multivariate logistic analysis showed that PSMC6 (OR=16.537, 95%CI:2.928-93.393, P=0.001) could be used as an independent risk factor for predicting lymph node metastasis. Conclusion: PSMC6 may be used as a potential molecular marker for judging lymph node metastasis in patients with PCa.