Background and Objective. The significance of microRNAs (miRNAs) in relation to neoplastic diseases; such as renal carcinoma carcinoma (RCC); has been brought to light by recent studies. Analyzing the main urinary miRNAs implicated in RCC and their potential diagnostic use was the goal of this systematic review of the literature. Methods. This systematic review was performed following the PROSPERO protocol CRD42024550716. Our literature search strategies were deciding which database to include (Pubmed; EMBASE and Clinicaltrial.gov) and composing strings with words related to urinary miRNA in patients with RCC. Key findings and limitations. After screening; 10 papers were included from the 593 records that the systematic review found. No miRNA was investigated in more than one paper by different authors. The miR-210 and let-7 family were the most investigated and resulted upregulated in RCC cases compared to controls. Five papers reported different expression of miRNAs in urine samples before and after surgery: miR-15a; miR-34a-5p; miR-200a-3p; miR-205-5p; miR-210; miR-210-3p; miR-365a-3p and let-7d-5p levels decreased after nephrectomy. Meta-analysis was not performed since the included studies were heterogeneous; in terms of studied miRNA; of the normalizer used during stabilization phase; and histologic type of RCC (clear cell RCC; papillary RCC; unspecified RCC). Conclusions. Considering the variability and heterogeneity of the obtained results; as well as the vastness of the topic; expanding research in this field appears highly promising. To support further advancements; it would be useful to establish a database that consolidates international findings.

Background: In recent years, research has highlighted the importance of microRNAs (miRNAs) in the context of oncological diseases, including renal cell carcinoma (RCC). The aim of this systematic review of the literature was to analyze the main serum miRNAs involved in RCC and their potential diagnostic power. Methods: This systematic review was performed following the PROSPERO protocol CRD42024550709. Literature search strategies were developed composing strings with text words related to serum miRNA in RCC for PubMed, EMBASE and Clinicaltrial.gov. The studies enrolling adult populations with RCC and healthy controls measuring circulating miRNAs were included. Results: We found 500 records, and 26 papers were included after screening. Four studies found that miR-210, the most investigated miRNA, was overexpressed in RCC patients compared to controls, while one reported no statistical difference. The expression of some miRNAs was consistently lower in cases compared to healthy controls, such as miR-1-3p and miR-129-5p, while others (miR-221, miR-222, miR-224-5p and miR-1233) were consistently upregulated. Conclusions: Circulating miRNAs represent a promising avenue for the non-invasive diagnosis of RCC. Future research should focus on standardization, validation in larger cohorts and the development of multi-marker diagnostic panels to address these current limitations and pave the way for miRNA-based diagnostics in RCC.

Background: Clear cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer subtype and, in most cases, it is incidentally diagnosed, as early-stage disease is often asymptomatic. Therefore, the identification of stable, noninvasive biomarkers is a major unmet clinical need. Urinary microRNAs (miRNAs) have emerged as promising candidates since they are extraordinarily stable in urine and show a close relationship with tumour biology. Methods: In this study, urinary expression levels of five miRNAs (miR-15a, miR-15b, miR-16, miR-210, and miR-let-7b) were analysed in RCC patients before surgery, 5 days after, and one month after surgery, and compared to healthy controls. Results: Non-parametric analyses revealed significant postoperative decreases for miR-15a (p = 0.002), miR-16 (p = 0.025), miR-210 (p = 0.030), and in the overall miRNA Sum (p = 0.002), suggesting that these miRNAs are directly linked to tumour presence. In the comparison between preoperative and one-month postoperative samples, miR-let-7b (p = 0.049) and the global miRNA Sum (p = 0.037) remained significantly reduced after intervention, indicating a partial normalisation of urinary miRNA profiles. Correlation analyses demonstrated positive associations between specific miRNAs and clinical parameters such as age, ischemia time, and surgical time, reinforcing their potential relevance to tumour biology and treatment response. Conclusions: These findings support urinary miRNAs as promising, minimally invasive biomarkers for ccRCC diagnosis and postoperative monitoring.

Urinary microRNAs (miRNAs) are promising noninvasive biomarkers for cancer detection, but their clinical utility is reduced by inconsistent normalization strategies, reducing reproducibility and comparability across studies. In this study, we assessed the stability of miR-20a as an endogenous normalizer for urinary miRNA profiling in clear cell renal cell carcinoma (ccRCC) while standardizing the pre-analytical phase using a urine stabilizing solution. Ninety-nine urine samples were analyzed: 47 from healthy individuals, 30 from ccRCC patients pre-surgery, and 22 post-operative patients. Six candidate miRNAs—miR-20a, miR-15b, miR-16, miR-15a, miR-210-3p, and miR-let-7b—were quantified via RT-qPCR. Stability analysis with RefFinder, integrating multiple algorithms (geNorm, normFinder, BestKeeper, and ΔCt methods), identified miR-20a as the most stable among the six candidates. Raw Ct values of miR-20a were normally distributed (Shapiro–Wilk test, p > 0.05), with no significant intergroup differences (one-way ANOVA, F(2.96) = 2.324, p = 0.103) and minimal intragroup variability (CV% 4.98–6.38). MiR-20a expression remained stable across different tumor staging, grading, and urine storage durations. These findings confirm miR-20a as a robust endogenous normalizer for urinary miRNA analyses and support the feasibility of developing reproducible urinary liquid biopsy workflows for ccRCC, even in settings where immediate sample processing is not feasible.