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Bladder cancer is a common malignant tumor of the urinary system. The progression of the condition is associated with a poor prognosis, so it is necessary to identify new biomarkers to improve the diagnostic rate of bladder cancer. In this study, 338 urine samples (144 bladder cancer, 123 healthy control, 32 cystitis, and 39 upper urinary tract cancer samples) were collected, among which 238 samples (discovery group) were analyzed by LC-MS. The urinary proteome characteristics of each group were compared with those of bladder cancer, and the differential proteins were defined by bioinformatics analysis. The pathways and functional enrichments were annotated. The selected proteins with the highest AUC score were used to construct a diagnostic panel. One hundred samples (validation group) were used to test the effect of the panel by ELISA. Compared with the healthy control, cystitis and upper urinary tract cancer samples, the number of differential proteins in the bladder cancer samples was 325, 158 and 473, respectively. The differentially expressed proteins were mainly related to lipid metabolism and iron metabolism and were involved in the proliferation, metabolism and necrosis of bladder cancer cells. The AUC of the panel of APOL1 and ITIH3 was 0.96 in the discovery group. ELISA detection showed an AUC of 0.92 in the validation group. This study showed that urinary proteins can reflect the pathophysiological changes in bladder cancer and that important molecules can be used as biomarkers for bladder cancer screening. These findings will benefit the application of the urine proteome in clinical research.
Zhou et al. (2024) studied this question.
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