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The lack of symptoms at the early stages of clear cell renal cell carcinoma (ccRCC) allows the tumour to metastasize, leading to a dramatic reduction in patient survival. Therefore, we studied and set up a method based on urinary microRNAs (miRNAs) for the diagnosis of ccRCC. First, miRNA expression in ccRCC specimens and kidney tissues from healthy subjects (HSs) was investigated through analysis of data banks and validated by comparing expression of miRNAs in ccRCC and adjacent non-cancerous kidney tissue specimens by RT-qPCR. Subsequently, we developed an algorithm to establish which miRNAs are more likely to be found in the urine of ccRCC patients that indicated miR-122, miR-1271, and miR-15b as potential interesting markers. The evaluation of their levels and three internal controls in the urine of 13 patients and 14 HSs resulted in the development of a score (7p-urinary score) to evaluate the presence of ccRCC in patients. The resulting area under the Receiver Operating Characteristic (ROC) curve, sensitivity, and specificity were equal to 0.96, 100% (95% CI 75–100%), and 86% (95% CI 57–98%), respectively. In conclusion, our study provides a proof of concept that combining the expression values of some urinary miRNAs might be useful in the diagnosis of ccRCC. [ABSTRACT FROM AUTHOR]

Simple Summary: The survival of patients with the most common type of kidney cancer (called Clear cell renal cell carcinoma—ccRCC) would dramatically improve if it was diagnosed earlier. Early diagnosis can be achieved using imaging techniques, but they are too expensive and therefore cannot be used to screen the population at risk for ccRCC. A few months ago, we published a study that evaluated the amount of certain small RNAs present in urine and showed that they are present at different levels in the urine of ccRCC patients vs. healthy subjects, and based on this discrepancy, we developed an algorithm that can anticipate the presence of kidney cancer. Such studies, however, can suffer from a technical bias called overfitting, such that the method may seem predictive even when it is not. In the present study, we sought to address this possibility and evaluate the amount of the same small RNAs in the urine of an independent cohort. As a result, we demonstrate that the previously developed algorithm has a sensitivity of 96% and specificity of 65%, thus validating this technique for potential application in the early diagnosis of ccRCC with a noninvasive assay. Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma, and the absence of symptoms in the early stages makes metastasis more likely and reduces survival. To aid in the early diagnosis of ccRCC, we recently developed a method based on urinary miR-122-5p, miR-1271-5p, and miR-15b-5p levels and three controls. The study here presented aimed to validate the previously published method through its application on an independent cohort. The expression of miRNAs in urine specimens from 28 ccRCC patients and 28 healthy subjects (HSs) of the same sex and age was evaluated by RT-qPCR. Statistical analyses were performed, including the preparation of receiver operating characteristic (ROC) curves. The mean ccRCC diameter in ccRCC patients was 4.2 ± 2.4 mm. Urinary miRNA levels were higher in patients than in HSs. The data were processed using the previously developed algorithm (7p-urinary score), and the area under the curve (AUC) of the algorithm's ROC curve was 0.81 (p-value = 0.0003), with a sensitivity of 96% and specificity of 65%. Therefore, the 7p-urinary score is a potential tool for the early diagnosis of ccRCC. [ABSTRACT FROM AUTHOR]