A potential panel of five mRNAs in urinary extracellular vesicles for the detection of bladder cancer.

BACKGROUND

Extracellular vesicles (EVs) have showed promising potential in liquid biopsy of cancer. In present study, we evaluate the feasibility to diagnose bladder cancer using EVs RNA markers identified from public tissue RNA sequencing data.

METHODS

We used urine samples from a cohort of population with suspected bladder cancer. Disease status (i.e., primary or recurrent bladder cancer) was diagnosed by cystoscopy. A prediction model including the expression of multiple RNAs in urinary EVs were developed in training cohort (n=368, 126 bladder cancer and 242 negative controls). The performance of optimal model (ExoPanel) consists of five mRNAs (MYBL2, TK1, UBE2C, KRT7, S100A2) was further assessed by a validation cohort (n=155, 56 bladder cancer and 99 negative controls).

RESULTS

The performance of ExoPanel in training cohort was AUC 0.7759 (95% CI: 0.7259-0.8260), NPV 90.34% (95% CI: 84.04-94.42%), SN 88.89% (95% CI: 81.75-93.57%), and SP 54.13% (95% CI: 47.63-60.50%) respectively. In the validation cohort, the performance of this model was AUC 0.8402 (95% CI: 0.7690-0.9114), NPV 90.91% (95% CI: 79.29-96.60%), SN 91.07% (95% CI: 79.63-96.67%), and SP 50.51% (95% CI: 40.34-60.63%). Using this model, it is possible to rule out a significant number of non cancer patients, thus reduce the unnecessary operation of cystoscopy.

CONCLUSIONS

We discovered a panel of five mRNAs, and evaluated its potential to facilitate bladder cancer diagnosis by analyzing their expression in urinary EVs.