Ability of a urine gene expression classifier to reduce the number of follow-up cystoscopies in bladder cancer patients.

Abstract

This study aimed to improve our previous urine gene expression classifiers focusing on the detection of non-high-risk non-muscle-invasive bladder cancer (NMIBC), and develop a new classifier able to decrease the frequency of cystoscopies during bladder cancer (BC) patients' surveillance. A total of 597 urines from BC patients, controls and patients in follow-up for BC (PFBC) were included. The study has 3 phases. In the urinary biomarker discovery phase, 84 urines from BC and control patients were retrospectively included and analyzed by Ribonucleic Acid (RNA) sequencing. In the classifier development phase, a total of 132 selected genes from previous phase were evaluated by nCounter in 214 prospectively collected urines from PFBC (98 with tumor). A diagnostic classifier was generated by logistic regression. Finally, in the classifier validation phase, a multicentric and international cohort of 248 urines (134 BC and 114 nonrecurrent PFBC) was used to validate classifier performance. A total of 521 genes were found differentially expressed between non-high-risk NMIBC samples and all other groups (P