[Basement membrane-related gene signature to predict biochemical recurrence in patients with prostate cancer after radical prostatectomy].

OBJECTIVE: To construct and verify a key gene signature of the basement membrane of prostate cancer (PCa) to predict the progression and biochemical recurrence of the malignancy after radical prostatectomy. METHODS: Based on the PCa-related transcriptome, gene mutation and clinical data from the Cancer Genome Atlas Project (TCGA) database, we analyzed the differentially expressed genes (DEG) related to the basement membrane in the PCa and adjacent normal prostate tissues, and subjected them to GO function enrichment and KEGG pathway enrichment analyses. We identified prognosis-related genes from the DEGs and analyzed their mutations. According to the follow-up data and biochemical recurrence after prostatectomy, we established a prognostic risk scoring model, verified its accuracy using the Gene Expression Omnibus (GEO) database, and performed survival analysis, principal component analysis (PCA), independent prognostic analysis and ROC curve analysis of the model. We constructed a protein-protein interaction network after verifying the correctness of the model by immunohistochemistry. We also established a nomogram and tested its accuracy using ROC and calibration curves. RESULTS: Totally, 85 DEGs were identified, among which 18 were up-regulated and 67 down-regulated. The prognostic risk scoring model was established with 11 of the genes. The risk of biochemical recurrence PCa was significantly higher in the high-risk than in the low-risk group (HR: 3.51, 95% CI: 2.32－5.32, P < 0.01), which was verified with the GEO database data (P < 0.01). In addition, the patients in the high-risk group were older with higher clinical T-stage, higher Gleason score, higher positive rate, larger numbers of positive lymph nodes, and a larger proportion of residual tumors than those in the low-risk group (P < 0.05). The nomogram constructed with the patients' age, pN, pT and cT stages, Gleason score and prognostic risk score manifested that the area under the ROC curve was higher than the other predictors. The calibration chart showed consistency of the predicted outcomes to the actual results. CONCLUSION: A prognostic risk scoring model of basement membrane-related genes and an effective nomogram were successfully constructed, which can predict the risk of biochemical recurrence in PCa patients after radical prostatectomy.