In silico determinaton of candidate genes related to the pathogenesis of prostate diseases and their analyses

Objective: Candidate genes functioning in prostate cancer-associated pathways were pre-determined by in silico analyses. PRKACA and STK11 genes were investigated to determine their correlation with prostatic diseases and clinical parameters. Methods: Two groups of sixty patients operated for benign prostatic hyperplasia (BPH) or clinically localized prostate cancer between January 2016 and June 2017, were included in study. Gene expression analyses of both STK11 and PRKACA were performed using both fresh normal and pathological prostate tissues from all patients. Results: Relevant gene expression could be determined in 50/60 of patients with BPH and 57/60 of patients with prostate cancer. STK11 gene expression was increased and PRKACA gene expression decreased in approximately 60% of both BPH and prostate cancer tissues. Regardless of pathology, a correlation between prostate volume and expression was noted for both genes. In larger prostates, PRKACA gene expression was significantly increased (p=0,01) while STK11 gene expression significantly decreased (p=0,046). With ROC analyses including clinical parameters, labaratory and qPCR parameters to predict prostate cancer, ratio of PSA Density/cycle threshold for STK11 {AUC=0,895 p=0,001) (95% CI 0,836-0,953)} was found to predict prostate cancer more effectively when compared to PSA density or PSA alone. Conclusions: Similar but inverse rates of changes in the expression of STK11 and PRKACA genes were observed for both BPH and prostate cancer. Expression of STK11 and PRKACA genes were correlated with the volume of the prostate. The ratio defined by the PSA Density/cycle threshold for STK11 gene was found as an effective parameter to predict prostate cancer. Keywords : Prostate, Adenocarcinoma, Benign Prostate Hyperplasia, STK11,PRKACA, Gene Expression