Language：English   Publisher：Frontiers in Oncology  

Pancreatic cancer (PaC), which is characterized by a high mortality rate, is often diagnosed at an advanced stage, significantly limiting treatment effectiveness. Early detection is crucial for improving survival rates, especially for individuals at high risk (HR) for PaC. Traditional diagnostic methods, including ultrasound, computed tomography, and magnetic resonance imaging (MRI), have limited sensitivity, especially for detecting early-stage PaC. We explored the potential of miRNA from urinary extracellular vesicles (EVs) as a noninvasive diagnostic marker for PaC. An exploratory case–control study was conducted across multiple Japanese institutions. The study included 248 samples from patients with pancreatic ductal adenocarcinoma (PDAC), the most common type of PaC, and HR patients. Differential expression analysis revealed significant differences in 16 miRNAs between the PDAC and HR samples. A machine learning-based algorithm was developed based on these miRNAs to distinguish between PDAC and HR. The algorithm exhibited an AUC of 0.89, a sensitivity of 0.80, and a specificity of 0.79. The algorithm detected the early-stage PDAC (stage 0-IIA) with a sensitivity of 0.73. These findings highlight the potential of the urinary miRNA algorithm as a noninvasive tool to aid in the detection of PDAC, including early-stage cases, in high-risk populations.

DOI： 10.3389/fonc.2025.1682072

Open Access

Web of Science

Scopus

PubMed

Language：English   Publisher：Npj Aging  

We aimed to develop and validate a urinary miRNA aging clock, positioning urine as a scalable, non-invasive aging-biomarker source. Using machine learning on 6331 adults, our clock achieved MAE ≈ 4.4 years (R² ≈ 0.79) in independent validation. The clock’s key biomarkers included well-established geromiRs miR-34a-5p, miR-31-5p, miR-146a-5p, and miR-155-5p. While slightly less accurate than DNA-methylation clocks, our model outperformed blood-based miRNA and mRNA clocks, underscoring urinary miRNAs as promising, truly non-invasive biomarkers of biological age and disease risk.

DOI： 10.1038/s41514-025-00311-3

Open Access

Web of Science

Scopus

PubMed

Language：English   Publisher：Scientific Reports  

Urinary extracellular vesicle (uEV)-derived microRNAs (miRNAs) have emerged as promising noninvasive biomarkers for disease prediction. However, fluctuations in urine concentration throughout the day may influence miRNA abundance and profiles, potentially limiting their clinical utility. To ensure the broader applicability of uEV-derived miRNAs in disease prediction, it is essential that their profiles remain stable regardless of collection time. In this study, we systematically examined factors influencing miRNA abundance in uEVs and assessed the stability of miRNA profiles. We collected serial urine samples from healthy individuals over three days and performed small RNA sequencing to analyze uEV-derived miRNA profiles in relation to various urine concentration parameters. Total miRNA counts were negatively correlated with urine volume and positively correlated with urine concentration indicators, including specific gravity and creatinine levels. miRNA profiles remained stable across different times and days when samples with low miRNA counts were excluded. These findings indicate that urine dilution is a major cause of variation in miRNA abundance. Our results highlight the importance of collecting adequately concentrated samples and provide foundational insights for developing standardized urine collection protocols, thereby facilitating the use of urinary uEV-derived miRNAs as robust and reliable biomarkers for disease prediction.

DOI： 10.1038/s41598-025-16728-5

Open Access

Web of Science

Scopus

PubMed

Language：English   Publisher：Cancers  

Background: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of urothelial carcinoma (UC); however, their efficacy varies among patients. Identifying reliable biomarkers to predict response to ICIs remains challenging. We aimed to explore urinary microRNAs (miRNAs) as potential biomarkers for predicting ICI efficacy in patients with UC. Methods: We prospectively collected urinary samples from patients with UC before ICI initiation and investigated the predictive value of urinary miRNAs in patients with UC receiving ICIs. The expression levels of these miRNAs in pretreated urine samples were analyzed using next-generation sequencing. The patients were categorized as responders (those with stable disease or better for >6 months) or nonresponders (those who experienced disease progression within 6 months of treatment initiation). Urinary miRNA levels were compared between the groups to assess their potential as predictive biomarkers. Results: Elevated expression of miR-185-5p and miR-425-5p in the responder group was significantly associated with improved overall and progression-free survival in patients with bladder cancer treated with ICIs (p < 0.05). Conversely, higher levels of miR-30a-5p and miR-542-3p in the nonresponder group were correlated with a poorer response to ICIs, suggesting a potential role in immune resistance. Conclusions: miR-185-5p and miR-425-5p can serve as predictive biomarkers of favorable ICI efficacy in bladder cancer, whereas miR-30a-5p and miR-542-3p could be associated with resistance mechanisms. These findings highlight the potential of miRNA-based biomarkers, particularly those found in urine samples, to guide personalized immunotherapeutic strategies for UC treatment.

DOI： 10.3390/cancers17162640

Open Access

Web of Science

Scopus

PubMed

Language：Japanese   Publisher：The Japanese Society of Gastrointestinal Cancer Screening  

<p><b>Objective:</b> The study aimed to evaluate the utility of N1,N12-diacetylspermine (DiAcSpm) as a noninvasive urinary biomarker for early screening of various gastrointestinal cancers, including gastric, colorectal, and pancreatic cancers. Given the high costs and logistical barriers to endoscopic screening, a targeted approach focusing on high-risk populations is necessary to optimize resource allocation and enhance early cancer detection.</p><p><b>Subjects and Methods:</b> This study analyzed urinary DiAcSpm levels in 78 healthy adults and 125 cancer patients, with samples obtained from biobanks and stored at -80°C. DiAcSpm concentration was measured using ELISA and normalized by urinary creatinine (Cre) levels. Cancer detection performance was assessed using the receiver operating characteristic (ROC) curve, and sensitivity and specificity were calculated based on the Youden index.</p><p><b>Results:</b> Urinary DiAcSpm/Cre levels were significantly higher in the cancer group (median 398.1 nM/g Cre) than in the non-cancer group (median 158.1 nM/g Cre, p<0.001), with an AUC of 0.82 indicating strong diagnostic potential. Sensitivity and specificity were 0.78 and 0.82, respectively. DiAcSpm/Cre levels increased with the cancer stage. They showed varying detection performance by cancer type, with high areas under the curve (AUC) for colorectal and gastric cancers at early stages but lower for early-stage pancreatic cancer.</p><p><b>Conclusions:</b> Urinary DiAcSpm is a promising biomarker for gastrointestinal cancers, potentially improving early detection in noninvasive screening. Its diagnostic efficiency varies by cancer type and stage, highlighting the need for further refinement to maximize clinical application.</p>

DOI： 10.11404/jsgcs.63.83

Open Access

CiNii Research