Pathway-guided monitoring of the disease course in bladder cancer with longitudinal urine proteomics

Abstract

Background Monitoring bladder cancer over time requires invasive and costly procedures. Less invasive approaches are required using readily available biological samples such as urine. In this study, we demonstrate a method for longitudinal analysis of the urine proteome to monitor the disease course in patients with bladder cancer. Methods We compared the urine proteomes of patients who experienced recurrence and/or progression (n = 13) with those who did not (n = 17). We identified differentially expressed proteins within various pathways related to the hallmarks of cancer. The variation of such pathways during the disease course was determined using our differential personal pathway index (dPPi) calculation, which could indicate disease progression and the need for medical intervention. Results Seven hallmark pathways are used to develop the dPPi. We demonstrate that we can successfully longitudinally monitor the disease course in bladder cancer patients through a combination of urine proteomic analysis and the dPPi calculation, over a period of 62 months. Conclusions Using the information contained in the patient’s urinary proteome, the dPPi reflects the individual’s course of bladder cancer, and helps to optimise the use of more invasive procedures such as cystoscopy.