Urinary metabolomic signature of muscle-invasive bladder cancer: A multiplatform approach

Bladder cancer (BCa) is ninth amongst the most common types of cancer in the human population worldwide. The statistics of incidence and mortality of BCa are alarming and the currently applied diagnostic methods are still not sensitive enough. This leads to a large number of undiagnosed BCa cases, usually among patients in the early stages of the disease. Despite the fact that many risk factors of BCa have been recognized, the pathomechanism of development of bladder cancer has not been fully explained yet. Therefore, in the present study, multiplatform urinary metabolomics has been implemented in order to scrutinize potential diagnostic indicators of BCa that might help to explain its pathomechanism and be potentially useful in diagnosis and determination of stage of the disease. Urine samples collected from muscle-invasive high grade BCa patients (n = 24) and healthy volunteers (n = 24) were matched in terms of most common BCa risk factors i.e. gender, age, BMI and smoking status. They were analyzed by high performance liquid chromatography coupled with time of flight mass spectrometry detection (HPLC-TOF/MS) using RP and HILIC chromatography, gas chromatography hyphenated with triple quadruple mass spectrometry detection (GC-QqQ/MS) in scan mode, and proton nuclear magnetic resonance (¹H NMR). The six datasets obtained were submitted to univariate and multivariate statistical analyses. 17 metabolites significantly discriminated urinary profiles of BCa patients from urinary profiles of healthy volunteers. These metabolites are mainly involved in amino acid metabolism, pyrimidine and purine metabolism, as well as energy metabolism and might play a crucial role in the pathogenesis of BCa.