UPLC-Q-TOF/MS-based urine metabolomics for the diagnosis and staging of bladder cancer

Background

Bladder cancer (BC) is a common malignant tumour of the urinary system. Currently, the gold standard for diagnosing BC is cystoscopy, but it is an invasive examination that can lead to a certain psychological burden on the patient. In this study, we aimed to identify non-invasive potential metabolic biomarkers that could improve the diagnostic accuracy of bladder cancer.

Methods

Urine from 30 healthy people and 50 BC patients, including 40 non-muscle-invasive bladder cancer (NMIBC) patients and 10 muscle-invasive bladder cancer (MIBC) patients, were analyzed by liquid chromatography coupled with mass spectrometry to identify potential diagnostic metabolites. Binary Logistic regression was used to construct biomarker panels. Correlation analysis and construction of compound-reaction-enzyme-gene network were also performed to explore the possible mechanisms of BC development.

Results

Twenty-six metabolites were identified for differentiating BC patients from healthy controls, and eight metabolites were identified for differentiating NMIBC patients form MIBC patients. The biomarker panel consisting of urate, 4-Androstene-3α, 17β-diol and 3-Indoxyl sulfate can distinguish well between BC patients and healthy controls, with an area under the ROC curve (AUC) value of 0.983. And the biomarker panel consisting of L-Octanoylcarnitine, γ-Glutamylleucine, and heptanoylcarnitine for distinguishing NMIBC patients from MIBC patients had an AUC value of 0.941.

Conclusions

The diagnostic capability of the biomarker panels are superior to that of any single potential biomarker. This panel significantly benefits bladder cancer diagnostics and reveals insight into bladder cancer pathogenesis.