A prognostic four-gene signature based on circulating tumor cells predicts recurrence free survival of patients with bladder cancer

Introduction Bladder cancer is the most common genitourinary malignancy, associated with substantial morbidity, mortality and cost. Currently there are no reliable specific serum markers for diagnosing and evaluating risk profiles of bladder cancer. Our study aims to establish a reliable prognostic signature closely related to the recurrence that can predict prognosis and possibly help with individual monitoring of bladder cancer patients. Material and Methods Among 55 patients with diagnosis of bladder cancer, CTCs were isolated from the peripheral blood before TURBT using a micro-pore size selection method (ScreenCell®) and diagnosed microscopically. The Cancer Genome Atlas (TCGA) dataset was used to identify genes modulated in bladder cancer respect to normal tissues. Thus, a selected panel of 15 genes was evaluated through the digital droplet PCR and analyzed by stratifying patients in low or high tumor grade. Data established the presence of two well-defined clusters of strong association. Among the involved genes, thanks to univariate and multivariate cox regression analysis, we identified the candidate prognostic genes and construct the risk score model. Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic power and performance of the signature. Results and Discussions A prognostic signature consisting of four prognostic-related genes was constructed. Cox regression analysis (univariate and multivariate) demonstrated that the gene signature is an independent prognostic biomarker for predicting the recurrence free survival of bladder cancer patients. The 4-gene signature significantly grouped patients in high and low-risk groups in terms of recurrent free survival (hazard ratio, HR = 2.704, 95% confidence interval: 1.010-7.313, Log-rank p<0.050). ROC curves revealed that the 4-gene prognostic signature achieved a good performance (AUC = 0.6863) in predicting recurrence for bladder cancer patients. Conclusion Our pilot study suggested a new and reliable prognostic signature that has a significant implication in predicting recurrence free survival for bladder cancer patients and may help with early diagnosis and making effective clinical decisions regarding potential individual treatment.