Differentially Expressed Urine and Plasma miRNAs between CKD and CKD + UC
In order to discover an ancillary diagnostic tool for UC in patients with CKD, all samples were collected from ten hospitals throughout Taiwan from 2013 to 2018. We matched the patients with CKD and CKD + UC by sex, age, and CKD stage to select the difference in miRNA expression levels in this study (Table 1). For CKD + UC, blood and urine samples were collected within three days before surgery. For the control group, blood and urine samples were collected after tracking their renal functions as CKD. Next, we detected 754 miRNA expression levels from 22 (11 CKD and 11 CKD + UC) and 16 (8 CKD and 8 CKD + UC) samples of urine and plasma, respectively, by high-throughput and quantitative real-time PCR arrays. We not only calculated the relative expression levels by RNU6 but also calculated the miRNA expression of the ratio value of two different miRNAs from the same sample to remove the normalization problem in cell-free biofluids. To date, no literature has noted that any miRNA is a competent internal control in biofluids, and we found that the ratio value method could reduce individual sample differences. We compared CKD and CKD + UC samples in several ways, and 17 candidate miRNAs were selected (Table 2).
Next, we validated the expression levels of 17 candidate miRNAs from a screening set by the single qRT-PCR method and measured 200 urine samples (100 CKD and 100 CKD + UC) and 138 plasma samples (74 CKD and 64 CKD + UC) in training and testing set. Our results showed that the expression of seven miRNAs was significantly different between the CKD and CKD + UC samples (Fig. 1). In urine samples, miR-1274a and miR-30a-5p expression levels were significantly decreased (p = 0.0243 and 0.0356, respectively), but the miR-19a-5p expression level was significantly increased (p < 0.001) (Fig. 1A). In the plasma samples, miR-155-5p, miR-19b-1-5p, miR-378 and miR-636 expression levels were significantly decreased (p = 0.0324, 0.043, 0.287 and 0.0288, respectively) (Fig. 1B). Interestingly, previous study has shown that miR-30a-5p had significantly low expression levels in plasma samples of patients with BC (27). In addition, miR-155-5p expression was also reported to be significantly decreased in the urine sediment cells of patients with BC (28).
Many studies have compared the different miRNA expression levels between the healthy group and patients with UC (29–31). Unlike previous studies, we tried to compare miRNA expression differences to identify UC from patients with CKD. To determine whether these candidate miRNAs from this study also have the potential to distinguish from the healthy group, we further collected 50 healthy cases to analyze the differences within the healthy, CKD and CKD + UC groups. miR-1274a and miR-30a-5p had significant differences between healthy cases and CKD + UC (p < 0.001). Interestingly, we found that three miRNAs, namely, miR-30a-5p, miR-19a-5p and miR-708-5p, not only can provide a reliable ability to distinguish patients who were CKD or CKD + UC (AUC = 0.64, 0.61 and 0.63, respectively) but also had significantly different expression levels between healthy subjects and CKD (p = 0.007, 0.0326 and 0.009, respectively) (Table 3 and Fig. 2).
miRNA Expression Levels as a Prognostic Marker of Bladder Cancer and Kidney Cancer
It has been known that miRNA expression is associated with cancer prognosis. Therefore, we investigated these 17 candidate miRNAs in a public database (http://kmplot.com) to analyze the association between newly identified miRNA expression levels and the 5-year survival rate by the Kaplan-Meier method. Among these miRNAs, lower expression levels of miR-19a, miR-19b, miR-636, and miR-378 and higher expression levels of miR-708-5p were associated with poor prognosis in BC (p = 0.0055, 0.014, 0.041, 0.02 and 0.027, respectively) (Fig. 3A). In addition, lower expression of miR-30a and or higher miR-155 was associated with poor prognosis in urinary cancer, such as papillary cell carcinoma and clear cell renal cell carcinoma (Fig. 3B).
The Prediction Models to Predict UC for Patients with CKD
To develop a miRNA signature-based predicative model for UC of patients with all stages of CKD, receiver operating characteristic curve (ROC) analysis was performed. 17 candidate miRNA expression levels in urine or plasma from the training set samples were examined. The area under the receiver operating characteristic curve (AUC) is the most commonly used performance measure to indicate the discriminative ability of a prediction mode, and an AUC value higher than 0.6 could be a potential marker. Four miRNAs expressed in urine and four miRNAs expressed in plasma had AUC values above 0.6. The AUC values of miR-1274a, miR-19a-5p, miR-30a-5p and miR-708-5p in urine were 0.71, 0.61, 0.64 and 0.628, respectively (95% confidence intervals: 0.6113 to 0.8198, 0.5016 to 0.7304, 0.5980 to 0.8073 and 0.5136 to 0.7424, respectively) (Table 3A). In plasma samples, miR-155-5p, miR-19b-1-5p, miR-210 and miR-636 could be potential markers, and their AUC values were 0.65, 0.66, 0.64 and 0.61, respectively (95% confidence intervals: 0.5168 to 0.7773, 0.5327 to 0.7875, 0.5107 to 0.7704 and 0.4758 to 0.7431, respectively) (Table 3B). Interestingly, these miRNAs have been reported in previous studies to play key functions not only in BC but also in clear cell renal cell carcinoma (32–35).
The combination of multiple factors compared to a single factor always presents more reliable prediction results for clinical classification. Therefore, we utilized multiple logistic regression calculation formulas to produce the prediction model combining different miRNA expression levels from the training group (Table 1). In the urine sample, the top four AUC values for miR-1274A, miR-30a-5p, miR-19b-3p and miR-708-5p were combined and calculated together, and the AUC was 0.8211 (95% confidence interval: 0.7359 to 0.9063). We also validated this panel in the testing group, and the data from 200 patients show that the accuracy of the 4-miRNA signature in urine was 70%, based on the cutoff value > 0.483 (Fig. 4A). Furthermore, we added another four miRNAs, namely, miR-155-5p, miR-19b-1-5p, miR-210 and miR-636, in plasma to increase the AUC value, and the AUC value increased up to 0.8507 (95% confidence interval: 0.7751 to 0.9439). The accuracy of the 8-miRNA signature was 72%, based on the cutoff value > -0.5940 (Fig. 4B)
Nomogram construction based on miRNAs expression signature
In order to validate the risk of UC, a nomogram integrated miRNAs expression signature was established. The miRNA expression level was transformed to the points based on the cutoff value from the training group. The cutoff of miR-1274a, miR-19a-5p, miR-30a-5p and miR-708-5p were < 34.41, > 2.24*10− 4, < 3.798 and > 2.235*10− 7, respectively. The AUC of the nomogram for urine samples were 0.7383 (n = 200, 95% confidence interval: to 0.6685 to 0.8080) (Fig. 5A). Furthermore, the cutoff of miR-155-5p, miR-19b-5p, miR-210-3p, miR-378 and miR-636 were < 1.21, < 0.5107, < 4.766 and < 0.5722, respectively. The AUC of the nomogram for urine and plasma samples were 0.8096 (n = 138, 95% confidence interval: 0.7365 to 0.8827) (Fig. 5B).