Abstract
Urothelial carcinoma is a common urological cancer in chronic kidney disease patients. Cystoscopy and urine cytology are the clinical diagnostic tools for UC. However, cystoscopy is an invasive procedure, while urine cytology showed low sensitivity for low-grade urothelial tumors. High accuracy with non-invasive tools for UC is needed for CKD patients. Our study collected a total of 272 urine and 138 plasma samples to detect the miRNA expression levels for establishing UC signatures from CKD patients. Seventeen candidate miRNAs of biofluids were selected and confirmed by qRT-PCR. Our results showed that urinary miR-1274a and miR-30a-5p expression levels were significantly lower but miR-19a-5p expression levels were higher in UC when compared with CKD. In plasma samples, miR-155-5p, miR-19b-1-5p, miR-378, and miR-636 showed significantly lower expression in UC compared to those with CKD. The Kaplan-Meier curve showed that lower expression of miR-19a, miR-19b, miR-636 and miR-378, and higher expression of miR-708-5p were associated with poor prognosis in patients with bladder cancer. In addition, we produced classifiers for predicting UC by multiple logistic regression. The urine signature was developed with four miRNAs, and the AUC was 0.8211. Eight miRNA expression levels from both urine and plasma samples were examined, and the AUC was 0.8595. Two miRNA classifiers and the nomograms could improve the drawbacks of current UC biomarker screenings for patients with CKD.