A serum panel of three microRNAs may serve as possible biomarkers for kidney renal clear cell carcinoma

BACKGROUND

Although non-invasive radiological techniques are widely applied in kidney renal clear cell carcinoma (KIRC) diagnosis, more than 50% of KIRCs are detected incidentally during the diagnostic procedures to identify renal cell carcinoma (RCC). Thus, sensitive and accurate KIRC diagnostic methods are required. Therefore, in this study, we aimed to identify KIRC-associated microRNAs (miRNAs).

METHODS

This three-phase study included 224 participants (112 each of patients with KIRC and healthy controls (NCs)). RT-qPCR was used to evaluate miRNA expression in KIRC and NC samples. Receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to predict the usefulness of serum miRNAs in KIRC diagnosis. In addition, we performed survival and bioinformatics analyses.

RESULTS

We found that miR-1-3p, miR-129-5p, miR-146b-5p, miR-187-3p, and miR-200a-3p were significantly differentially expressed in patients with KIRC. A panel consisting of three miRNAs (miR-1-3p, miR-129-5p, and miR-146b-5p) had an AUC of 0.895, ranging from 0.848 to 0.942. In addition, using the GEPIA database, we found that the miRNAs were associated with CREB5. According to the survival analysis, miR-146b-5p overexpression was indicative of a poorer prognosis in patients with KIRC.

CONCLUSIONS

The identified three-miRNA panel could serve as a non-invasive indicator for KIRC and CREB5 as a potential target gene for KIRC treatment.

Diagnostic panel of serum miR-125b-5p, miR-182-5p, and miR-200c-3p as non-invasive biomarkers for urothelial bladder cancer

PURPOSE

This study aimed to identify a diagnostic panel of serum microRNAs (miRNAs) for the early detection of bladder cancer (BC).

METHODS

Serum samples were collected from 112 BC patients and 112 normal controls (NCs). A three-stage selection was conducted to identify differentially expressed miRNAs as candidates to construct the diagnostic panel. Further, to explore their potential roles in urothelial BC, bioinformatics analyses, including target genes prediction and functional annotation, were used.

RESULTS

Six downregulated miRNAs (miR-1-3p, miR-30a-5p, miR-100-5p, miR-125b-5p, miR-143-3p, and miR-200c-3p) and one upregulated, miR-182-5p, in BC patients' serum were detected compared to NCs and were selected to establish the diagnostic panel. Based on a backward stepwise logistic regression analysis, miR-125b-5p, miR-182-5p, and miR-200c-3p comprehended the diagnostic panel [area under the curve (AUC) = 0.959, sensitivity = 91.67%, specificity = 92.5%].

CONCLUSION

The panel of three miRNAs had an excellent diagnostic capability, representing a potential non-invasive method for early BC detection.

A Panel of Three Serum MicroRNAs as a Potential Diagnostic Biomarker for Urothelial Carcinoma

OBJECTIVE

Urothelial carcinoma (UCa) is one of the most common malignancies of the genitourinary system, and its early diagnosis is vital to improve the survival of UCa patients. Therefore, novel noninvasive markers are urgently needed to improve the diagnosis of UCa. The present study aims to identify microRNAs (miRNAs) relevant for the diagnosis of UCa.

MATERIALS AND METHODS

We enrolled a total of 152 UCa patients and 135 healthy controls at a single institution, between 2012 and 2020. The expression levels of candidate miRNAs were calculated from serum samples based on quantitative reverse transcription-polymerase chain reaction. miRNAs with a good diagnostic value were selected and confirmed step by step in a four-phase test. The area under the curve (AUC) of each miRNA was obtained by analyzing the receiver operating characteristic (ROC) curve, which was used to evaluate the sensitivity, specificity, and corresponding cutoff values of miRNAs. Backward stepwise logistic regression was used to identify a panel of miRNAs that could distinguish UCa from healthy controls.

RESULTS

Four miRNAs were relevant for diagnosis: miR17-5p (AUC = 0.786, p < 0.001), miR-125a-5p (AUC = 0.681, p < 0.01), miR145-5p (AUC = 0.737, p < 0.001), and miR-224-5p (AUC = 0.872, p < 0.001). These miRNAs were used to construct a diagnostic panel. The final optimal combination to diagnose UCa included three miRNAs, namely, miR17-5p, miR145-5p, and miR-224-5p. The ROC curve of the panel was constructed, and its AUC was 0.961 (95% CI: 0.931-0.991; sensitivity = 93.8%, and specificity = 87.5%).

CONCLUSION

In this study, we discovered four miRNAs (miR17-5p, miR-125a-5p, miR145-5p, and miR-224-5p) that were relevant for UCa diagnosis, and successfully developed a panel using three of these miRNAs. This panel may serve as a new biomarker tool with high sensitivity and specificity to diagnose UCa in patients.