Prediction of Metastatic Site Based On Somatic Gene Mutations in Primary Tumors in Prostate Cancer

ObjectiveThe goal of this research is to predict the most likely metastatic site(s) of a primary prostate cancer tumor that has been resected via radical prostatectomy; its genome has been sequenced to obtain a list of gene mutations; and after initial inspection of pelvic lymph nodes, there is no clinical evidence of metastasis. However, micrometastases might already be growing in distant organs and cannot be detected at the time of surgery. BackgroundThe most common metastatic targets in prostate cancer (PCa) are the pelvic lymph nodes (PLN) and bones. The PLNs are routinely dissected by a procedure called pelvic lymph node dissection (PLND) simultaneously with the surgical removal of the prostate to detect the presence of metastatic growths. Additionally, the prostate-specific antigen (PSA) level is used to assess the existence of a metastatic stage. However, micrometastases in other organs and tissues might be overlooked. MethodsWe downloaded publicly available prostate cancer tumor data from the website www.CbioPortal.org. After choosing the 25 most commonly mutated genes by metastatic site (MS) and finding genes that are uniquely mutated on specific metastatic sites, we found that the mutational signature of a prostate cancer tumor is associated with its MS, and thus, we developed a method to numerically predict this association. ResultsAfter executing a computational algorithm on the data set of metastatic prostate tumors, it was found that we can predict metastatic sites with the following accuracies: bone (90.9%), retroperitoneum (87.5%), liver (83.0%), kidney (80.0%), pancreas (80.0%), adrenal glands (75.0%), lung (71.1%), and brain (72.5%). ConclusionsWe successfully developed a method and an algorithm that predict the most likely metastatic site of a primary prostate cancer tumor based on its genetic mutations. The accuracy of the predictions for eight metastatic sites ranges from 71.1% to 90.9%, with an average of 80.5%.