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Prostate cancer (PCa) is a common male malignancy and early diagnosis is crucial for successful treatment. The current study aims to validate results from a pilot study that demonstrated an inverse association between urine tyrosine and tryptophan levels and the severity of PCa. This study comprised a cohort of 97 patients with benign prostatic hyperplasia, 93 patients diagnosed with localized PCa, 75 patients diagnosed with locally advanced PCa, and 68 patients diagnosed with metastatic PCa. The tyrosine and tryptophan levels in the samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and electrochemical sensors in accordance with the pilot to maintain uniformity for accurately evaluating the data. One-way ANOVA with post Tukey test as well as the Wilcoxon Rank Sum Test were performed. Analyzing 333 patients across PCa stages with consistent methods, we observed no significant differences in tyrosine and tryptophan levels between PCa patients and controls, finally rejecting the use of tyrosine and tryptophan as PCa biomarkers. We did, however, verify the strong correlation between the urinary concentrations of tyrosine and tryptophan found in the pilot study., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Alatraktchi owns PreDiagnose (supplier of screen-printed sensors). This had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Low accuracy of diagnosing prostate cancer (PCa) was easily caused by only assaying single prostate specific antigen (PSA) biomarker. Although conventional reported methods for simultaneous detection of two specific PCa biomarkers could improve the diagnostic efficiency and accuracy, low detection sensitivity restrained their use in extreme early-stage PCa clinical assay applications. In order to overcome above drawbacks, this paper herein proposed a multiplexed dual optical microfibers separately functionalized with gold nanorods (GNRs) and Au nanobipyramids (Au NBPs) nanointerfaces with strong localized surface plasmon resonance (LSPR) effects. The sensors could simultaneously detect PSA protein biomarker and long noncoding RNA prostate cancer antigen 3 (lncRNA PCA3) with ultrahigh sensitivity and remarkable specificity. Consequently, the proposed dual optical microfibers multiplexed biosensors could detect the PSA protein and lncRNA PCA3 with ultra-low limit-of-detections (LODs) of 3.97 × 10 -15  mol/L and 1.56 × 10 -14  mol/L in pure phosphorus buffer solution (PBS), respectively, in which the obtained LODs were three orders of magnitude lower than existed state-of-the-art PCa assay technologies. Additionally, the sensors could discriminate target components from complicated physiological environment, that showing noticeable biosensing specificity of the sensors. With good performances of the sensors, they could successfully assay PSA and lncRNA PCA3 in undiluted human serum and urine simultaneously, respectively. Consequently, our proposed multiplexed sensors could real-time high-sensitivity simultaneously detect complicated human samples, that providing a novel valuable approach for the high-accurate diagnosis of early-stage PCa individuals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The sensitivity of currently available screening tools for urothelial carcinoma (UC) remains unsatisfactory particularly at early stages. Hence, we aimed to establish a novel blood-based screening tool for urothelial carcinoma. We measured serum d-amino acid levels in 108 and 192 patients with and without UC individuals in the derivation cohort, and 15 and 25 patients with and without UC in the validation cohort. Serum d-asparagine levels were significantly higher in patients with UC than in those without UC (p < 0.0001). We developed a novel screening equation for the diagnosis of urothelial carcinoma using d-asparagine in serum and estimated the glomerular filtration rate (eGFR). Serum d-asparagine levels adjusted for eGFR exhibited high performance in the diagnosis of UC (AUC-ROC, 0.869; sensitivity, 80.6 %; specificity, 82.7 %), even in early-stage UC (AUC-ROC: 0.859, sensitivity: 83.3 %, specificity: 82.3 %), which were previously misdiagnosed via urinary occult blood or urine cytology. This established strategy combined with urinary occult blood, improves diagnostic ability (sensitivity: 93.7 %, specificity: 70.1 %)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Bladder cancer (BCa) exhibits the escalating incidence and mortality due to the untimely and inaccurate early diagnosis. Urinary exosome metabolites, carrying critical tumor cell information and directly related to bladder, emerge as promising non-invasive diagnostic biomarkers of BCa. Herein, the magnetic 3D ordered macroporous zeolitic imidazolate framework-8 (magMZIF-8) is synthesized and used for efficient urinary exosome isolation. Notably, beyond retaining the single crystals and micropores of conventional ZIF-8, MZIF-8 is further enhanced with highly oriented and ordered macropores (150 nm) and the large specific surface area (973 m 2 ·g -1 ), which could enable the high purity and yield separation of exosomes via leveraging the combination of size exclusion, affinity, and electrostatic interactions between magMZIF-8 and the surfaces of exosome. Furthermore, the magnetic and hydrophilic properties of magMZIF-8 will further simplify the process and enhance the efficiency of separation. After conditional optimization, a 50 mL of urine is sufficient for exosome metabolomics analysis, and the time for isolating exosomes from 42 urine samples was 2 hours only. Incorporating machine learning algorithms with LC-MS/MS analysis of the metabolic patterns obtained from isolated exosomes, early-stage BCa patients were differentiated from healthy controls, with area under the curve (AUC) value of 0.844-0.9970 in the training set and 0.875-1.00 in the test set, signifying its potential as a reliable diagnostic tool. This study offers a promising approach for the non-invasive and efficient diagnosis of BCa on a large scale via exosome metabolomics., (© 2024. The Author(s).)

This study explored the soluble forms of PD-1 and sPD-L1/2 in serum and urine of patients with head and neck cancer (HNCs) and associated the data with clinical state and 5-year survival. The sPD-1 and sPD-L1/2 levels were evaluated by ELISA in sufferers (N=110) and normal controls (N=82). Patients in the case group were more likely to be male smokers or former smokers. Compared with the normal control group, the serum levels of sPD-1, sPD-L1 and sPD-L2 and the urine level of sPD-L1 in patients with HNCs were increased. Furthermore, sPD-1 and sPD-L1 serum levels existed a positive connection, and sPD-1 and sPD-L2 serum levels positively correlated in HNCs sufferers. The urine sPD-1 and sPD-L1 had a positive relationship. sPD-1 serum levels had a positive connection with urine sPD-1, sPD-L1 urine levels had a positive relationship with sPD-L1, and sPD-L2 serum levels positively connected to urine sPD-L2. Lower serum sPD-1 and sPD-L1/L2 were associated with disease progression and survival at the examination time. sPD-1 and sPD-L1/L2 serum levels above median were markedly related to a decreased probability of 5-years OS in patients with HNCs. The sPD-1 and sPD-L1/2 were complementary markers representing clinical condition and illness outcomes for HNCs patients. The sPD-L1 might accelerate the characterization of high-risk patients with disapproving illness outcomes. sPD-1 and sPD-L1/2 could be easily accessed through liquid biopsy. The incorporation of them as indicators for risk evaluation throughout treatment scheduling and follow-up seems to be an appreciated method.

Purpose: Cancer statistics demonstrate leading growth of prostate cancer. As a rule, radical prostatectomy (RP) is a mandatory option in the treatment of localized prostate cancer (PCa). Over 30% of patients develop biochemical resistance after the surgery and over 30% of these patients experience prostate cancer recurrence and metastasis. Currently used PCa patient's diagnostic features fail to identify PCa recurrence. To identify the risk group of PCa patients after RP we attempt to apply miRNAs which were shown as promising liquid biopsy markers for PCa diagnosis and prognosis., Materials and Methods: Expression of 14 miRNAs closely involved in the development of prostate cancer from urine extracellular vesicles (uEV) of PCa patients before as well as 3, 6 and 12 months after radical prostatectomy was assessed using RT PCR and compared with their expression from uEV of healthy donors in the current study., Results: It was shown that 22 miRNA pairs prognostic ratios (MPPRs) significantly changed after radical prostatectomy. MPPRs the most promising in terms of evaluating the effectiveness of radical prostatectomy have been identified. These include two groups: MPPRs significantly changed after surgery towards that in healthy donors; and MPPRs, which divided PCa patients into two significantly different subgroups 3 or 6 months after radical prostatectomy., Conclusions: The obtained data indicate that urine EVs represent a valuable source of both MPDR and MPPR for prostate cancer., Competing Interests: Declaration of competing interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript or in the decision to publish the results., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Introduction: Urine-derived exosomes could potentially be biomarkers for bladder cancer (BC) diagnosis. This study aimed to systematically evaluate the diagnostic worth of urine-derived exosomes in BC patients through a meta-analysis of diverse studies., Methods: A systematic search was carried out in PubMed, Web of Science, Embase, Cochrane, and CNKI databases to obtain the literature concerning the diagnosis of BC via urine-derived exosomes. A literature retrieval strategy was devised to pick articles and extract needed data from the literature. QUADS-2 was used to evaluate the quality of the included literatures, and the aggregated diagnostic effect was assessed by calculating the area under the aggregated SROC curve. All statistical analyses and plots were conducted with STATA 14.0 and RevMan5.3., Results: A total of 678 articles were retrieved by means of the search strategy of the online database. Through screening, 21 articles were obtained, involving 3348 participants and 77 studies. The meta-analysis of the results indicated that urinary exosomes had a combined sensitivity of 0.75, a specificity of 0.77, and a combined AUC of 0.83 for the diagnosis of BC, suggesting that urine-derived exosomes have a relatively satisfactory diagnostic effect in the detection of BC. Among the subgroups classified by biomarker, long non-coding RNAs (lncRNAs) had the highest comprehensive sensitivity (SEN = 0.78), and miRNAs had the highest comprehensive specificity (SPN = 0.81). In other subgroup analyses, the biomarker panel for multiple exosomes combined diagnosis demonstrated the best diagnostic efficacy, with a combined the area under the curve ( AUC) of 0.87., Conclusions: As a novel biomarker, urine-derived exosomes have significant diagnostic prospects in the diagnosis of BC. Nevertheless, their application in clinical settings still demands a considerable number of clinical trials to confirm their clinical feasibility and practicability., (© 2024. The Author(s).)

Prognostic tests and treatment approaches for optimized clinical care of prostatic neoplasms are an unmet need. Prostate cancer (PCa) and derived extracellular vesicles (EVs) proteome changes occur during initiation and progression of the disease. PCa tissue proteome has been previously characterized, but screening of tissue samples constitutes an invasive procedure. Consequently, we focused this study on liquid biopsies, such as urine samples. More specifically, urinary small extracellular vesicle and particles proteome profiles of 100 subjects were analyzed using liquid chromatography coupled to high-resolution mass spectrometry (LC-MS/MS). We identified 171 proteins that were differentially expressed between intraductal prostate cancer/cribriform (IDC/Crib) and non-IDC/non-Crib after correction for multiple testing. However, the strong correlation between IDC/Crib and Gleason Grade complicates the disentanglement of the underlying factors driving this association. Nevertheless, even after accounting for multiple testing and adjusting for ISUP (International Society of Urological Pathology) grading, two proteins continued to exhibit significant differential expression between IDC/Crib and non-IDC/non-Crib. Functional enrichment analysis based on cancer hallmark proteins disclosed a clear pattern of androgen response down-regulation in urinary EVs from IDC/Crib compared to non-IDC/non-Crib. Interestingly, proteome differences between IDC and cribriform were more subtle, suggesting high proteome heterogeneity. Overall, the urinary EV proteome reflected partly the prostate pathology., (© 2024. The Author(s).)

Purpose: Although cystoscopy is a reliable tool for detecting bladder cancer, it poses a high burden on patients and entails high costs. This highlights the need for non-invasive and cost-effective alternatives. This study aimed to validate a previously developed urinary methylation marker panel containing GHSR and MAL., Methods: We enrolled 134 patients who underwent cystoscopy because of hematuria, including 63 individuals with primary bladder cancer and 71 with non-malignant findings. Urine samples were self-collected at home and sent via regular mail. Subsequently, DNA was extracted and the hypermethylation of GHSR and MAL was evaluated using quantitative methylation-specific polymerase chain reaction. The performance of methylation markers was assessed using area-under-the-curve (AUC) analysis and sensitivity and specificity based on pre-established cut-off values., Results: Validation of the marker panel GHSR/MAL resulted in an AUC of 0.87 at 79% sensitivity and 80% specificity. Sensitivity was comparable to the previous investigation (P > 0.9), though specificity was significantly lower (P = 0.026). Sensitivity was higher for high-grade tumors compared to low-grade tumors (94% vs. 60%, P = 0.002)., Conclusion: Validation of the GHSR/MAL methylation marker panel on at home collected urine samples confirms its robust performance for bladder cancer detection in a hematuria population, and underscores the diagnostic potential for future clinical application., (© 2024. The Author(s).)

Ovarian cancer is the 8th most common malignancy in women and the deadliest gynecological cancer. Due to the non-specific symptoms and the lack of effective diagnostic methods, late diagnosis remains the main barrier for improving the poor prognosis. Human epididymis protein 4 (HE4) is a protein overexpressed in ovarian cancer, but not in healthy individuals or benign conditions. The aim of this review article is to evaluate the laboratory aspect and potential clinical application of urine HE4. The methodology is presented, together with discussion on preanalytical, analytical and postanalytical phase of HE4 detection using urine. Moreover, we present the diagnostic role of urine HE4 in differential diagnosis, chemotherapy response, detection of recurrence and detection of low-malignant potential tumors. It has been found that urine HE4 presents as a promising, non-invasive tumor marker for detection and monitoring of ovarian cancer. However, standardization of the HE4 detection process is needed prior to implementation in clinical diagnostics., Competing Interests: Potential conflict of interest None declared., (Croatian Society of Medical Biochemistry and Laboratory Medicine.)

Background: On-site monitoring of vanillylmandelic acid (VMA), homovanillic acid (HVA), and dopamine (DA) as key diagnostic biomarkers for a wide range of neurological disorders holds utmost significance in clinical settings. Numerous colorimetric sensors with mechanistic approaches based on aggregation or silver metallization have been introduced for this purpose. However, these mechanisms have drawbacks, such as sensitivity to environmental factors and probe toxicity. Therefore, there is a great demand for a robust yet non-toxic colorimetric sensor that employs a novel route to monitor these biomarkers effectively., Results: Here, we present a single-component multi-colorimetric probe based on the controllable etching suppression of gold nanorods (AuNRs) upon exposure to the mild etchant N-bromosuccinimide (NBS), designed to accurately detect and discriminate VMA, HVA, DA, and their corresponding mixtures, i.e., , Vma: HVA, VMA:DA, HVA:DA, and VMA:HVA:DA. To enhance the sensitivity and automation capabilities of the designed multi-colorimetric sensor, two machine learning techniques were employed: linear discriminant analysis (LDA) for the qualitative classification and partial least-squares regression (PLSR) for the quantitative analysis of pure biomarkers and their mixtures. The outcomes revealed a high correlation between measured and predicted values, covering a linear range of 0.8-25, 1.2-25, and 2.7-100 μmol L -1 , with remarkably low detection limits of 0.260, 0.397, and 0.913 μmol L -1 for VMA, HVA, and DA, respectively. Lastly, the performance of the probe was validated by successfully detecting the neuroblastoma biomarker VMA:HVA in human urine., Significance: Our designed multi-colorimetric probe introduces a rapid, cost-effective, user-friendly, non-toxic, and non-invasive approach to detecting and discriminating not only the pure biomarkers but also their corresponding binary and ternary mixtures. The distinctive response profiles produced by the probe in the presence of different mixture ratios can indicate various disease states in patients, which is highly crucial in clinical diagnostics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Renal cell carcinoma (RCC) is the most common malignant tumor in the urinary system, accounting for 80 % to 90 % for all renal malignancies. Traditional diagnostic methods like magnetic resonance imaging (MRI) and computed tomography (CT) lack the sensitivity and specificity as they lack specific biomarkers. These limitations impede effective monitoring of tumor recurrence. This study aims to employ Attenuated Total Reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy, an optical technology sensitive to molecular groups, to analyze the potential optical biomarkers in urine and plasma samples from RCC patients pre- and post-surgery. The results reveal distinctive spectral information from both plasma and urine samples. Post-surgery urine spectra exhibit complexity compared to plasma, showing reduced content at 1072 cm -1 , 1347 cm -1 and 1654 cm -1 bands, while increased content at 1112 cm -1 , 1143 cm -1 , 1447 cm -1 , 3334 cm -1 and 3420 cm -1 bands. Utilizing machine learning models such as eXtreme Gradient Boosting (XGBoost), support vector machine (SVM), partial least squares (PLS), and artificial neural network (ANN), the study evaluated plasma and urine samples pre- and post-surgery. Remarkably, the XGBoost method excelled in distinguishing between tumor conditions and recovery, achieving an impressive AUC value of 0.99. These results underscore the potential of ATR-FTIR technology in identifying RCC optical biomarkers, with XGBoost showing promise as a valuable screening tool for RCC recurrence diagnosis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Aromatic caninurine formamase (AFMID) is an enzyme involved in the tryptophan pathway, metabolizing N-formylkynurenine to kynurenine. AFMID had been found significantly downregulated in clear cell renal cell carcinoma (ccRCC) in both tissue and urine samples. Although ccRCC is characterized by a typical Warburg-like phenotype, mitochondrial dysfunction, and elevated fat deposition, it is unknown whether AFMID plays a role in tumorigenesis and the development of ccRCC. In the present study, AFMID overexpression had inhibitory effects for ccRCC cells, decreasing the rate of cell proliferation. Quantitative proteomics showed that AFMID overexpression altered cellular signaling pathways involved in cell growth and cellular metabolism pathways, including lipid metabolism and inositol phosphate metabolism. Further urine proteomic analysis indicated that cellular function dysfunction with AFMID overexpression could be reflected in the urine. The activity of predicted upregulators DDX58, TREX1, TGFB1, SMARCA4, and TNF in ccRCC cells and urine showed opposing change trends. Potential urinary biomarkers were tentatively discovered and further validated using an independent cohort. The protein panel of APOC3, UMOD, and CILP achieved an AUC value of 0.862 for the training cohort and 0.883 for the validation cohort. The present study is of significance in terms of highlighting various aspects of pathway changes associated with AFMID enzymes, discovering potential specific biomarkers for potential patient diagnosis, and therapeutic targeting.

Background: For early detection and postoperative monitoring of upper tract urothelial carcinoma (UTUC), the traditional detection method was limited to its invasiveness and insufficient sensitivity. We aim to use urine tumour DNA (utDNA) for detecting minimal residual disease (MRD), early diagnosis and perioperative monitoring in UTUC., Method: We previously established a utDNA multidimensional bioinformatic valuation model, named utLIFE, using low-coverage whole-genome sequencing and targeted deep sequencing. This prospective cohort enrolled 93 patients diagnosed with UTUC without metastasis. We collected morning urine samples on the day of surgery and the discharge day after the operation for utLIFE testing. In addition, we also enrolled 80 healthy controls to further validate the specificity of the utLIFE model in the study., Results: The utLIFE of preoperative samples could discriminate UTUC with high specificity (96.25%, 77/80), and high sensitivity (96.77%, 90/93) regardless of stage and grade. The sensitivity of utLIFE was significantly higher than urine cytology (p < 0.001) and fluorescence in situ hybridisation (FISH) (p < 0.001) (N = 19), especially in early-stage and low-grade UTUC. Postoperative utLIFE scores were significantly decreased compared with those of preoperative samples (79 vs. 36, p < 0.001), indicating its association with tumour burden. For special pathology types, utLIFE performed less well in sensitivity and perioperative alteration., Conclusion: In conclusion, we established a bioinformatic utDNA valuation model, utLIFE, which was validated to be a rapid and noninvasive approach with high sensitivity for early detection and MRD monitoring for UTUC., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

Background and Aims: Pancreatic ductal adenocarcinoma (PDAC) is infrequent. Currently, non-invasive biomarkers for early detection of PDAC are not accessible. Here, we intended to identify a set of urine markers able to discriminate patients with early-stage PDAC from healthy individuals., Patients and Methods: Seventy-five urine samples from PDAC patients and 50 healthy controls were assayed using quantitative real-time PCR (qPCR). The chosen biomarkers were lymphatic vessel endothelial HA receptor (LYVE-1), regenerating islet-derived 1 alpha (REG1A), and trefoil factor family (TFF1)., Results: LYVE-1, REG1A, and TFF1 expression in PDAC proved to be significantly elevated compared to healthy individuals (p < 0.05). Determination of these markers' expression might be useful for early tumor diagnosis with a sensitivity of 96 %, 100 %, and 73.33 % respectively, and a specificity of 100 %, 82 %, and 100 % respectively., Conclusion: We have recognized three diagnostic biomarkers REG1A, TFF1, and LYVE1 that can detect patients with early-stage pancreatic cancer in non-invasive urine specimens with improved sensitivity and specificity. To the best of our knowledge, there have been no prior investigations examining the mRNA expression levels of them in urine within the Egyptian population., Competing Interests: Declaration of Competing Interest The authors declare there is no conflict of interest., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Developing a standardized screening tool for the detection of early and small hepatocellular carcinoma (HCC) through urinary metabolic analysis poses a challenging yet intriguing research endeavor. In this study, a range of intricately interlaced 2D rough nanosheets featuring well-defined sharp edges is fabricated, with the aim of constructing diverse trimetal oxide heterojunctions exhibiting multiscale structures. By carefully engineering synergistic effects in composition and structure, including improved adsorption, diffusion, and other surface-driven processes, the optimized heterojunctions demonstrate a substantial enhancement in signal intensity compared to monometallic or bimetallic oxides, as well as fragmented trimetallic oxides. Additionally, optimal heterojunctions enable the extraction of high-quality urinary metabolic fingerprints using high-throughput mass spectrometry. Leveraging machine learning, discrimination of HCC patients from high-risk and healthy populations achieves impressive performance, with area under the curve values of 0.940 and 0.916 for receiver operating characteristic and precision-recall curves, respectively. Six crucial metabolites are identified, enabling accurate detection of early, small-tumor, alpha-fetoprotein-negative HCC (93.3%-97.3%). A comprehensive screening strategy tailored to clinical reality yields precision metrics (accuracy, precision, recall, and F1 score) exceeding 95.0%. This study advances the application of cutting-edge matrices-based metabolic phenotyping in practical clinical diagnostics., (© 2024 Wiley‐VCH GmbH.)

Introduction: In recent years, different urinary markers such as the Bladder Epicheck® have been developed in an attempt to reduce the number of cystoscopies in the follow-up of non-muscle invasive bladder cancer (NMIBC)., Aim: To provide a systematic review of Bladder Epicheck® and its current clinical utility in the follow-up and detection of recurrence of NMIBC., Material and Methods: Systematic review based on a literature search of PubMed, Web of Science and Scopus databases until October 2023, according to PRISMA and Quadas-2 criteria. Sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) of the marker were calculated. Diagnostic performance was evaluated by the area under the curve (AUC)., Results: Fifteen studies were analyzed (n = 3761) including 86.7% prospective studies. Of the patient series, 53.2% had received previous intravesical instillations. The mean Se of the biomarker in the detection of recurrence varied according to tumor grade (87.9%-high grade/HG vs. 44.9%-low grade/LG, respectively). Their weighted mean Se and Sp were 71.6% and 84.5%, respectively. The mean recurrence rate was 29.1%. The weighted mean PPV and NPV were 56.4% and 92.8% (97.7% non-LG), respectively. The mean AUC was 85.63%., Conclusion: Bladder Epicheck® is a useful urinary marker in the follow-up of NMIBC, with significantly high Se and NPV in the detection of recurrences, especially in cases of HG disease. Its use can reduce the number of cystoscopies required in the follow-up of NMIBC, improving the quality of life of patients and potentially increasing health economic savings., (Copyright © 2024 AEU. Published by Elsevier España, S.L.U. All rights reserved.)

Introduction: Current diagnostic approaches for bladder cancer (BLCA) are often invasive or lack the required sensitivity and specificity. This underscores the need for an early non-invasive diagnostic test for BLCA. This work aimed to explore the potential of molecular markers in urine-exfoliated cells for the diagnosis of non-muscle-invasive bladder cancer (NMIBC)., Materials and Methods: Urine specimens (n = 140) were collected from NMIBC patients (n = 68) and control subjects (31 healthy volunteers and 41 non-cancer patients with common urological diseases [CUD]. Total RNA was extracted from the cells isolated from urine specimens. mRNA expression of selected genes: CDC20, KRT15, FOXM1, CXCR2, UPK1B, MDK, KRT20, and KRT17 was determined using RT-qPCR. The receiver operating characteristic (ROC) curve was then plotted to obtain the area under the curve (AUC), specificity, and sensitivity of the urinary mRNA markers., Results: The expression of CDC20, MDK, UPK1B, FOXM1, KRT17, and KRT20 was up-regulated in samples obtained from low- and high-grade pathological grades of NMIBC compared to that measured in healthy subjects. Notably, MDK and KRT17 mRNA levels in the low- and high-grade cases were substantially higher than in normal and CUD groups. The AUC of the KRT17 and MDK combination in diagnosing NMIBC was 0.92, surpassing that of single genes. The sensitivity and specificity of the KRT17 and MDK combination were 74% and 94%, respectively. In diagnosing low-grade from healthy and CUD groups, analysis of the KRT17 and MDK combination yielded AUCs of 0.94 and 0.95, respectively, with sensitivities of 85% and 97%, and specificities of 93% and 85%., Conclusion: The findings of this study revealed that KRT17 and MDK together are potential urine-based biomarkers for early diagnosis of NMIBC., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.)

Laminin, fibronectin, and collagen IV are pivotal extracellular matrix (ECM) components. The ECM environment governs the fundamental properties of tumors, including proliferation, vascularization, and invasion. Given the critical role of cell-matrix adhesion in malignant tumor progression, we hypothesize that the concentrations of these proteins may be altered in the plasma of patients with clear cell renal cell carcinoma (ccRCC). This study aimed to evaluate the serum, urine, and tissue levels of laminin-5, collagen IV, and fibronectin among a control group and ccRCC patients, with the latter divided into stages T1-T2 and T3-T4 according to the TNM classification. We included 60 patients with histopathologically confirmed ccRCC and 26 patients diagnosed with chronic cystitis or benign prostatic hyperplasia (BPH). Collagen IV, laminin-5, and fibronectin were detected using Surface Plasmon Resonance Imaging biosensors. Significant differences were observed between the control group and ccRCC patients, as well as between the T1-T2 and T3-T4 subgroups. Levels were generally higher in plasma and tissue for fibronectin and collagen IV in ccRCC patients and lower for laminin. The ROC (Receiver operating characteristic) analysis yielded satisfactory results for differentiating between ccRCC patients and controls (AUC 0.84-0.93), with statistical significance for both fibronectin and laminin in plasma and urine. Analysis between the T1-T2 and T3-T4 groups revealed interesting findings for all examined substances in plasma (AUC 0.8-0.95). The results suggest a positive correlation between fibronectin and collagen levels and ccRCC staging, while laminin shows a negative correlation, implying a potential protective role. The relationship between plasma and urine concentrations of these biomarkers may be instrumental for tumor detection and staging, thereby streamlining therapeutic decision-making.

Background: To establish the pathological diagnosis of UTUC before treatment is profitable. At present, the conventional pathological diagnostic methods have certain problems. Besides, the urine-based DNA methylation test have been already utilized to detect bladder cancer., Objective: To evaluate the sensitivity and specificity of DNA methylation plus 17 genes mutation test and compare the combined test with cytology., Materials and Methods: We included 45 patients from April 2019 to May 2022, all of whom underwent radical nephroureterectomy (RNU), nephrectomy, diagnostic ureteroscopy or tissue biopsy. Before surgery, the urine samples were collected for DNA methylation plus 17 genes mutation test and cytology. The test performance was calculated, and comparative ROC curves were drawn., Results: The median age of the patients was 67 years. The Kappa value of the DNA methylation plus 17 genes mutation test and tissue pathology was 0.59 (p<0.001). The sensitivity/specificity/PPV/NPV of DNA methylation plus 17 genes mutation test was 86/80/94/62% compared with 29/100/100/29% for cytology. The AUC of DNA methylation plus 17 genes mutation test was 0.829 (p<0.001).The mutated gene proportion of UTUC patients was 51.43% for TERT and 25.71% for TP53., Conclusion: The test performance of DNA methylation plus 17 genes mutation test was satisfactory, which may replace cytology in the future. Further multicenter studies with larger samples are needed to confirm the clinical value of this promising method., Novelty & Impact Statements: We evaluated the diagnostic efficacy of a urine-based liquid biopsy for the detection of UTUC and compared the combined test with cytology. We found satisfactory results and concluded that the test could partly replace cytology. Further studies are needed., (© 2024. The Author(s).)

Recent interest in noninvasive diagnostic approaches has highlighted the potential of urinary microbiota as a novel biomarker for bladder cancer. This study investigated the urinary microbiota of 30 bladder cancer patients and 32 healthy controls using a specific NGS protocol that sequences eight hypervariable regions of the 16S rRNA gene, providing detailed insights into urinary microbiota composition. The relative abundance of microbial compositions in urine samples from cancer patients and healthy controls was analyzed across various taxonomic levels. No notable differences were highlighted at the phylum, class, order, and family levels. At the genus level, 53% of detected genera were represented in either cancer patients or healthy controls. Microbial diversity was significantly lower in cancer patients. The differential analysis identified five genera, Rhodanobacter , Cutibacterium , Alloscardovia , Moryella , and Anaeroglobus , that were significantly more abundant in cancer patients. Notably, Rhodanobacter was present in 20 cancer samples but absent in healthy controls. Conversely, 40 genera, including Lactobacillus, Propionibacterium , and Bifidobacterium , exhibited reduced abundance in cancer patients. These findings suggest that some genera may serve as potential biomarkers for bladder cancer, highlighting the need for further research to explore their roles in disease pathogenesis and their potential applications in diagnostics and therapeutics.

RNAs, especially non-coding RNAs (ncRNAs), are crucial players in regulating cellular mechanisms due to their ability to interact with and regulate other molecules. Altered expression patterns of ncRNAs have been observed in prostate cancer (PCa), contributing to the disease's initiation, progression, and treatment response. This study aimed to evaluate the ability of a specific set of RNAs, including long ncRNAs (lncRNAs), microRNAs (miRNAs), and mRNAs, to discriminate between PCa and the non-neoplastic condition benign prostatic hyperplasia (BPH). After selecting by literature mining the most relevant RNAs differentially expressed in biofluids from PCa patients, we evaluated their discriminatory power in samples of unfiltered urine from 50 PCa and 50 BPH patients using both real-time PCR and droplet digital PCR (ddPCR). Additionally, we also optimized a protocol for urine sample manipulation and RNA extraction. This two-way validation study allowed us to establish that miRNAs (i.e., miR-27b-3p, miR-574-3p, miR-30a-5p, and miR-125b-5p) are more efficient biomarkers for PCa compared to long RNAs (mRNAs and lncRNAs) (e.g., PCA3, PCAT18, and KLK3), as their dysregulation was consistently reported in the whole urine of patients with PCa compared to those with BPH in a statistically significant manner regardless of the quantification methodology performed. Moreover, a significant increase in diagnostic performance was observed when molecular signatures composed of different miRNAs were considered. Hence, the abovementioned circulating ncRNAs represent excellent potential non-invasive biomarkers in urine capable of effectively distinguishing individuals with PCa from those with BPH, potentially reducing cancer overdiagnosis.

Colorectal cancer (CRC) is a common malignant tumor in the gastrointestinal tract. Changes in amino acid metabolites have been implicated in tumorigenesis and disease progression. Biomarkers on the basis of chiral amino acids, especially D-amino acids, have not been established for early diagnosis of CRC. Quantification of chiral amino acids, especially very low concentrations of endogenous D-amino acids, is technically challenging. We report here the quantification of L- and D-amino acids in urine samples collected from 115 CRC patients and 155 healthy volunteers, using an improved method. The method of chiral labeling, liquid chromatography, and tandem mass spectrometry enabled separation and detection of 28 amino acids (14 L-amino acids, 13 D-amino acids and Gly). Orthogonal partial least squares discriminant analysis identified 14 targeted variables among these chiral amino acids that distinguished the CRC from the healthy controls. Binary logistic regression analysis revealed that D-α-aminobutyric acid (D-AABA), L-alanine (L-Ala), D-alanine (D-Ala), D-glutamine (D-Gln) and D-serine (D-Ser) could be potential biomarkers for CRC. A receiver operating characteristic curve analysis of combined multi-variables contributed to an area under the curve (AUC) of 0.995 with 98.3 % sensitivity and 96.8 % specificity. A model constructed with D-AABA, D-Ala, D-Gln, and D-Ser achieved an AUC of 0.988, indicating important contributions of D-amino acids to the association with CRC. Further analysis also demonstrated that the metabolic aberration was associated with age and the development of CRC, D-methionine (D-Met) was decreased in CRC patients with age over 50, and D/L-Gln in patients at stage IV was higher than patients at stage I. This study provides the signature of D-amino acids in urine samples and offers a promising strategy for developing non-invasive diagnosis of CRC., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Renal cell carcinoma (RCC) is the sixth most common cancer in men and is often asymptomatic, leading to incidental detection in advanced disease stages that are associated with aggressive histology and poorer outcomes. Various cancer biomarkers are found in urine samples from patients with RCC. In this study, we propose to investigate the use of Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy (ATR-FTIR) on dried urine samples for distinguishing RCC. We analyzed dried urine samples from 49 patients with RCC, confirmed by histopathology, and 39 healthy donors using ATR-FTIR spectroscopy. The vibrational bands of the dried urine were identified by comparing them with spectra from dried artificial urine, individual urine components, and dried artificial urine spiked with urine components. Urea dominated all spectra, but smaller intensity peaks, corresponding to creatinine, phosphate, and uric acid, were also identified. Statistically significant differences between the FTIR spectra of the two groups were obtained only for creatinine, with lower intensities for RCC cases. The discrimination of RCC was performed through Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) and Support Vector Machine (SVM). Using PCA-LDA, we achieved a higher discrimination accuracy (82%) (using only six Principal Components to avoid overfitting), as compared to SVM (76%). Our results demonstrate the potential of urine ATR-FTIR combined with machine learning techniques for RCC discrimination. However, further studies, especially of other urological diseases, must validate this approach.

Background: Prostate cancer is the most common cancer in men and represents a major public health problem. The current method for the diagnosis or screening of prostate cancer is invasive and costly. There have been renewed and innovative studies searching for urinary biomarkers to aid in the diagnosis of prostate cancer, especially with technologies based on urinary exosomes. However, technologies based on urine exosomes usually need expensive machines such as an ultracentrifuge and they are difficult to standardize, which hinder their application in clinical laboratories. We have optimized and standardized the isolation of urinary exosomes with the precipitation method. We have found that urinary exosomal prostate-specific antigen (PSA) can be quantified by automatic Elecsys total PSA technique., Objective: In this study, our objective is to utilize urinary exosomes from prostate cancer for the development of a test to aid in its diagnosis., Methods: Exosomes from the prostate cancer cell line LNCaP was used to set up the technique. To analyze urine samples from patients, the methods include the collection of first-void urine using the Colli-Pee device, the isolation of urine exosomes using the optimized precipitation method, and the quantification of exosomal PSA by Elecsys total PSA., Results: This will be a 2-year study. We will start including patients and controls in the last quarter of 2024. We expect the results to be published in the second quarter of 2027., Conclusions: This is the first study to quantify urinary exosomal PSA using the Elecsys total PSA technique for the diagnosis of prostate cancer. This study emphasizes techniques that are suitable for implementation in clinical laboratories, which will facilitate the application of urinary exosomes to simplify and improve the diagnosis and screening of prostate cancer., International Registered Report Identifier (irrid): PRR1-10.2196/63551., (©Guorong Li, Yannick Tholance, Nora Mallouk, Louis Waeckel, Pascale Flandrin, Bruno Bali, Lionel Badet, Pierre Cornillon. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 11.09.2024.)

Problem: Pancreatic ductal adenocarcinoma (PDAC) is considered a highly lethal cancer due to its advanced stage diagnosis. The five-year survival rate after diagnosis is less than 10%. However, if diagnosed early, the five-year survival rate can reach up to 70%. Early diagnosis of PDAC can aid treatment and improve survival rates by taking necessary precautions. The challenge is to develop a reliable, data privacy-aware machine learning approach that can accurately diagnose pancreatic cancer with biomarkers., Aim: The study aims to diagnose a patient's pancreatic cancer while ensuring the confidentiality of patient records. In addition, the study aims to guide researchers and clinicians in developing innovative methods for diagnosing pancreatic cancer., Methods: Machine learning, a branch of artificial intelligence, can identify patterns by analyzing large datasets. The study pre-processed a dataset containing urine biomarkers with operations such as filling in missing values, cleaning outliers, and feature selection. The data was encrypted using the Fernet encryption algorithm to ensure confidentiality. Ten separate machine learning models were applied to predict individuals with PDAC. Performance metrics such as F1 score, recall, precision, and accuracy were used in the modeling process., Results: Among the 590 clinical records analyzed, 199 (33.7%) belonged to patients with pancreatic cancer, 208 (35.3%) to patients with non-cancerous pancreatic disorders (such as benign hepatobiliary disease), and 183 (31%) to healthy individuals. The LGBM algorithm showed the highest efficiency by achieving an accuracy of 98.8%. The accuracy of the other algorithms ranged from 98 to 86%. In order to understand which features are more critical and which data the model is based on, the analysis found that the features "plasma&#95;CA19&#95;9", REG1A, TFF1, and LYVE1 have high importance levels. The LIME analysis also analyzed which features of the model are important in the decision-making process., Conclusions: This research outlines a data privacy-aware machine learning tool for predicting PDAC. The results show that a promising approach can be presented for clinical application. Future research should expand the dataset and focus on validation by applying it to various populations., (© 2024. The Author(s).)

Detection of circulating tumor DNA (ctDNA) mutations, which are molecular biomarkers present in bodily fluids of cancer patients, can be applied for tumor diagnosis and prognosis monitoring. However, current profiling of ctDNA mutations relies primarily on polymerase chain reaction (PCR) and DNA sequencing and these techniques require preanalytical processing of blood samples, which are time-consuming, expensive, and tedious procedures that increase the risk of sample contamination. To overcome these limitations, here the engineering of a DNA/γPNA (gamma peptide nucleic acid) hybrid nanoreporter is disclosed for ctDNA biosensing via in situ profiling and recording of tumor-specific DNA mutations. The low tolerance of γPNA to single mismatch in base pairing with DNA allows highly selective recognition and recording of ctDNA mutations in peripheral blood. Owing to their remarkable biostability, the detached γPNA strands triggered by mutant ctDNA will be enriched in kidneys and cleared into urine for urinalysis. It is demonstrated that the nanoreporter has high specificity for ctDNA mutation in peripheral blood, and urinalysis of cleared γPNA can provide valuable information for tumor progression and prognosis evaluation. This work demonstrates the potential of the nanoreporter for urinary monitoring of tumor and patient prognosis through in situ biosensing of ctDNA mutations., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Renal cell carcinoma (RCC) is a substantial pathology of the urinary system with a growing prevalence rate. However, current clinical methods have limitations for managing RCC due to the heterogeneity manifestations of the disease. Metabolic analyses are regarded as a preferred noninvasive approach in clinics, which can substantially benefit the characterization of RCC. This study constructs a nanoparticle-enhanced laser desorption ionization mass spectrometry (NELDI MS) to analyze metabolic fingerprints of renal tumors (n = 456) and healthy controls (n = 200). The classification models yielded the areas under curves (AUC) of 0.938 (95% confidence interval (CI), 0.884-0.967) for distinguishing renal tumors from healthy controls, 0.850 for differentiating malignant from benign tumors (95% CI, 0.821-0.915), and 0.925-0.932 for classifying subtypes of RCC (95% CI, 0.821-0.915). For the early stage of RCC subtypes, the averaged diagnostic sensitivity of 90.5% and specificity of 91.3% in the test set is achieved. Metabolic biomarkers are identified as the potential indicator for subtype diagnosis (p < 0.05). To validate the prognostic performance, a predictive model for RCC participants and achieve the prediction of disease (p = 0.003) is constructed. The study provides a promising prospect for applying metabolic analytical tools for RCC characterization., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Gliomas, particularly glioblastomas (GBMs), pose significant challenges due to their aggressiveness and poor prognosis. Early detection through biomarkers is critical for improving outcomes. This study aimed to identify novel biomarkers for gliomas, particularly GBMs, using chiral amino acid profiling. We used chiral amino acid analysis to measure amino acid L- and D-isomer levels in resected tissues (tumor and non-tumor), blood, and urine from 33 patients with primary gliomas and 24 healthy volunteers. The levels of D-amino acid oxidase (DAO), a D-amino acid-degrading enzyme, were evaluated to investigate the D-amino acid metabolism in brain tissue. The GBM mouse model was created by transplanting GBM cells into the brain to confirm whether gliomas affect blood and urine chiral amino acid profiles. We also assessed whether D-amino acids produced by GBM cells are involved in cell proliferation. D-asparagine (D-Asn) levels were higher and DAO expression was lower in glioma than in non-glioma tissues. Blood and urinary D-Asn levels were lower in patients with GBM than in healthy volunteers (p < 0.001), increasing after GBM removal (p < 0.05). Urinary D-Asn levels differentiated between healthy volunteers and patients with GBM (area under the curve: 0.93, sensitivity: 0.88, specificity: 0.92). GBM mouse model validated the decrease of urinary D-Asn in GBM. GBM cells used D-Asn for cell proliferation. Gliomas induce alterations in chiral amino acid profiles, affecting blood and urine levels. Urinary D-Asn emerges as a promising diagnostic biomarker for gliomas, reflecting tumor presence and severity., (© 2024. The Author(s).)

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer and a major cause of cancer-related mortality worldwide. Small extracellular vesicles (sEVs) are heterogeneous populations of membrane-structured vesicles that can be found in many biological fluids and are currently considered as a potential source of disease-associated biomarkers for diagnosis. The purpose of this study was to define the proteomic and phosphoproteomic landscape of urinary sEVs in patients with HCC. Mass spectrometry-based methods were used to detect the global proteome and phosphoproteome profiles of sEVs isolated by differential ultracentrifugation. Label-free quantitation analysis showed that 348 differentially expressed proteins (DEPs) and 548 differentially expressed phosphoproteins (DEPPs) were identified in the HCC group. Among them, multiple phosphoproteins related to HCC, including HSP90AA1, IQGAP1, MTOR, and PRKCA, were shown to be upregulated in the HCC group. Pathway enrichment analysis indicated that the upregulated DEPPs participate in the regulation of autophagy, proteoglycans in cancer, and the MAPK/mTOR/Rap1 signaling pathway. Furthermore, kinase-substrate enrichment analysis revealed activation of MTOR, AKT1, MAP2Ks, and MAPKs family kinases in HCC-derived sEVs, indicating that dysregulation of the MAPK and mTOR signaling pathways may be the primary sEV-mediated molecular mechanisms involved in the development and progression of HCC. This study demonstrated that urinary sEVs are enriched in proteomic and phosphoproteomic signatures that could be further explored for their potential use in early HCC diagnostic and therapeutic applications.

Monitoring drug efficacy is significant in the current concept of companion diagnostics in metastatic breast cancer. Trastuzumab, a drug targeting human epidermal growth factor receptor 2 (HER2), is an effective treatment for metastatic breast cancer. However, some patients develop resistance to this therapy; therefore, monitoring its efficacy is essential. Here, we describe a deep learning-assisted monitoring of trastuzumab efficacy based on a surface-enhanced Raman spectroscopy (SERS) immunoassay against HER2-overexpressing mouse urinary exosomes. Individual Raman reporters bearing the desired SERS tag and exosome capture substrate were prepared for the SERS immunoassay; SERS tag signals were collected to prepare deep learning training data. Using this deep learning algorithm, various complicated mixtures of SERS tags were successfully quantified and classified. Exosomal antigen levels of five types of cell-derived exosomes were determined using SERS-deep learning analysis and compared with those obtained via quantitative reverse transcription polymerase chain reaction and western blot analysis. Finally, drug efficacy was monitored via SERS-deep learning analysis using urinary exosomes from trastuzumab-treated mice. Use of this monitoring system should allow proactive responses to any treatment-resistant issues., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: Nonsmokers account for 10% to 13% of all lung cancer cases in the United States. Etiology is attributed to multiple risk factors including exposure to secondhand smoking, asbestos, environmental pollution, and radon, but these exposures are not within the current eligibility criteria for early lung cancer screening by low-dose CT (LDCT)., Experimental Design: Urine samples were collected from two independent cohorts comprising 846 participants (exploratory cohort) and 505 participants (validation cohort). The cancer urinary biomarkers, creatine riboside (CR) and N-acetylneuraminic acid (NANA), were analyzed and quantified using liquid chromatography-mass spectrometry to determine if nonsmoker cases can be distinguished from sex and age-matched controls in comparison with tobacco smoker cases and controls, potentially leading to more precise eligibility criteria for LDCT screening., Results: Urinary levels of CR and NANA were significantly higher and comparable in nonsmokers and tobacco smoker cases than population controls in both cohorts. Receiver operating characteristic analysis for combined CR and NANA levels in nonsmokers of the exploratory cohort resulted in better predictive performance with the AUC of 0.94, whereas the validation cohort nonsmokers had an AUC of 0.80. Kaplan-Meier survival curves showed that high levels of CR and NANA were associated with increased cancer-specific death in nonsmokers as well as tobacco smoker cases in both cohorts., Conclusions: Measuring CR and NANA in urine liquid biopsies could identify nonsmokers at high risk for lung cancer as candidates for LDCT screening and warrant prospective studies of these biomarkers., (©2024 The Authors; Published by the American Association for Cancer Research.)

Nuclear matrix protein 22 (NMP22) is one of the most important tumor markers of bladder cancer and is significantly elevated in the urine of bladder cancer patients. Therefore, in this work, a highly sensitive ratiometric electrochemical immunosensor was constructed to detect NMP22 based on ZIF-8@MWCNTs@Chit@Fc@AuNPs composites. ZIF-8 had a large surface area and good adsorption ability. Multi-Walled Carbon Nanotubes (MWCNTs) can optimize the electrical conductivity of ZIF-8, so that the electrode surface of ferrocene (Fc) obtains a stable and strong electrochemical signal. In addition, AuPt-MB provided another strong detection signal methylene blue (MB) while immobilizing the secondary antibody (Ab 2 ) through Au-N and Pt-N bonds. A ratiometric electrochemical sensor was formed based on ZIF-8@MWCNTs@Chit@Fc@AuNPs and AuPt-MB, which showed a great linear connection between I MB / I Fc and the logarithmic concentration of NMP22 with a detection limit of 3.33 fg mL -1 (S/N = 3) under optimized specifications in the concentration interval of 0.01 pg mL -1 to 1000 ng mL -1 . In addition, the ratiometric immunosensor showed good selectivity and stability.

Prostate-Specific Antigen (PSA) based screening of prostate cancer (PCa) needs refinement. The aim of this study was the identification of urinary biomarkers to predict the Prostate Imaging-Reporting and Data System (PI-RADS) score and the presence of PCa prior to prostate biopsy. Urine samples from patients with elevated PSA were collected prior to prostate biopsy (cohort = 99). The re-analysis of mass spectrometry data from 45 samples was performed to identify urinary biomarkers to predict the PI-RADS score and the presence of PCa. The most promising candidates, i.e. SPARC-like protein 1 (SPARCL1), Lymphatic vessel endothelial hyaluronan receptor 1 (LYVE1), Alpha-1-microglobulin/bikunin precursor (AMBP), keratin 13 (KRT13), cluster of differentiation 99 (CD99) and hornerin (HRNR), were quantified by ELISA and validated in an independent cohort of 54 samples. Various biomarker combinations showed the ability to predict the PI-RADS score (AUC = 0.79). In combination with the PI-RADS score, the biomarkers improve the detection of prostate carcinoma-free men (AUC = 0.89) and of those with clinically significant PCa (AUC = 0.93). We have uncovered the potential of urinary biomarkers for a test that allows a more stringent prioritization of mpMRI use and improves the decision criteria for prostate biopsy, minimizing patient burden by decreasing the number of unnecessary prostate biopsies., (© 2024. The Author(s).)

Current diagnostic methods for canine urothelial carcinoma (UC) are technically challenging or can lack specificity, hence there is a need for novel biomarkers of UC. To this end, we analysed the microRNA (miRNA) cargo of extracellular vesicles (EVs) from urine samples of dogs with UC to identify candidate miRNA biomarkers. Urine was fractionated using ultrafiltration combined with size-exclusion chromatography and small RNA sequencing analysis was performed on both the EV enriched and (EV free) protein fractions. A greater number of candidate miRNA biomarkers were detected in the EV fraction than the protein fraction, and further validation using droplet digital PCR (ddPCR) was performed on the EV enriched fraction of a second cohort of dogs with UC which indicated that miR-182, miR-221 and miR-222 were significantly overrepresented in dogs with UC when compared with healthy dogs and dogs with urinary tract infections. Pathway analysis confirmed that these three miRNAs are involved in cancer. In addition, their potential downstream gene targets were predicted and PIK3R1, a well-known oncogene is likely to be a shared target between miRNA-182 and miRNA-221/222. In summary, this study highlights the potential of urinary EV-associated miRNAs as a source of biomarkers for the diagnosis of canine UC., (© 2024. The Author(s).)

Genitourinary cancer (GUC) represents more than one fifth of all human cancers. This makes the development of approaches to its early diagnosis an important task of modern biomedicine. Circulating microRNAs, short (17-25 nucleotides) non-coding RNA molecules found in human biological fluids and performing a regulatory role in the cell, are considered as promising diagnostic and prognostic biomarkers of cancers, including GUC. In this review we have considered the current state of research aimed at assessing microRNAs as biomarkers of such human GUC types as malignant tumors of the bladder, kidney, prostate, testicles, ovaries, and cervix. A special attention has been paid to studies devoted to the identification of microRNAs in urine as a surrogate "liquid biopsy" that may provide the simplest and cheapest approach to mass non-invasive screening of human GUC. The use of microRNA panels instead of single types of microRNA generally leads to higher sensitivity and specificity of the developed diagnostic tests. However, to date, work on the microRNAs assessment as biomarkers of human GUC is still of a research nature, and the further introduction of diagnostic tests based on microRNAs into practice requires successful clinical trials.

Purpose of Review: This review sought to define the emerging roles of urinary tumor DNA (utDNA) for diagnosis, monitoring, and treatment of bladder cancer. Building from early landmark studies the focus is on recent studies, highlighting how utDNA could aid personalized care., Recent Findings: Recent research underscores the potential for utDNA to be the premiere biomarker in bladder cancer due to the constant interface between urine and tumor. Many studies find utDNA to be more informative than other biomarkers in bladder cancer, especially in early stages of disease. Points of emphasis include superior sensitivity over traditional urine cytology, broad genomic and epigenetic insights, and the potential for non-invasive, real-time analysis of tumor biology. utDNA shows promise for improving all phases of bladder cancer care, paving the way for personalized treatment strategies. Building from current research, future comprehensive clinical trials will validate utDNA's clinical utility, potentially revolutionizing bladder cancer management., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: After accounting for smoking history, lung cancer incidence is greater in African Americans than Whites. In the multiethnic cohort, total nicotine equivalents (TNE) are higher in African Americans than Whites at similar reported cigarettes per day. Greater toxicant uptake per cigarette may contribute to the greater lung cancer risk of African Americans., Methods: In a nested case-control lung cancer study within the Southern Community Cohort, smoking-related biomarkers were measured in 259 cases and 503 controls (40% White; 56% African American). TNE, the trans-3-hydroxycotinine/cotinine ratio, 4-(methylnitrosamino)-1-3-(pyridyl)-1-butanol (NNAL), mercapturic acid metabolites of volatile organic compounds, phenanthrene metabolites, cadmium (Cd), and (Z)-7-(1R,2R,3R,5S)-3,5-dihydroxy-2-[(E,3S)-3-hydroxyoct-1-enyl]cyclopenyl]hept-5-enoic acid were quantified in urine. Unconditional logistic regression was used to estimate the ORs and 95% confidence intervals (CI) for each biomarker and lung cancer risk., Results: TNE, NNAL, and Cd were higher in cases than controls (adjusted for age, race, sex, body mass index, and cigarettes per day). Among cases, these levels were higher in African Americans compared with Whites. After accounting for age, sex, body mass index, and pack-years, a one-SD increase in log-TNE (OR = 1.30; 95% CI, 1.10-1.54) and log-NNAL (OR = 1.27; 95% CI, 1.03-1.58 with TNE adjustment) was associated with lung cancer risk. In this study, in which NNAL concentration is relatively high, the association for log-TNE was attenuated after adjustment for log-NNAL., Conclusions: Smoking-related biomarkers provide additional information for lung cancer risk in smokers beyond smoking pack-years., Impact: Urinary NNAL, TNE, and Cd concentrations in current smokers, particularly African American smokers, may be useful for predicting lung cancer risk., (©2024 American Association for Cancer Research.)

Bladder cancer (BC) represents a prevalent malignancy in North America and Europe, posing significant health burdens. The identification of a reliable biomarker for early BC detection is imperative to enhance prognostic outcomes. Our aim for this study is to determine the diagnostic accuracy and potential clinical utility of Angiogenin/Ribonuclease 5 (ANG/RNase 5) as a biomarker for detection of BC. A systematic literature search across multiple databases up to March 20, 2024, was conducted. CMA 3.7 and Meta-disk 1.4 were used to analyze specificity, sensitivity, AUC, DOR, LR+, LR-, Q*index, and SROC for ANG as a urinary biomarker in BC patients. Publication bias was assessed using Egger's regression asymmetry and Begg's rank correlation tests. Additional diagnosing analyses were performed using Python programming language version 3.12.1. In this meta-analysis of seven case-control studies comprising 1,051 participants (576 cases and 481 controls), pooled sensitivity was 0.701 (95 % CI: 0.662-0.738), specificity was 0.787 (95 % CI: 0.752-0.819), LR + was 3.582 (95 % CI: 2.260-5.676), LR- was 0.398 (95 % CI: 0.327-0.485), and DOR was 10.637 (95 % CI: 6.106-18.529). The AUC and Q* index values were 0.823 and 0.756, respectively. Both Begg and Mazumdar Rank Correlation Test (p = 0.229) and Egger's Test of the Intercept (p = 0.135) revealed no significant evidence of publication bias. Our meta-analysis confirms ANG/RNase 5 as a reliable biomarker for early bladder cancer detection, showing strong diagnostic accuracy and no publication bias., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.)

Introduction: Aberrant glycosylation of proteins is an important hallmark in multiple cancers. Prostate-specific membrane antigen (PSMA), a highly glycosylated protein with 10 N-linked glycosylation sites, is an Food and Drug Administration approved theranostic for prostate cancer. However, glycosylation changes in PSMA that are associated with prostate cancer disease progression have not been fully characterized., Methods: We investigated whether urinary PSMA sialylation correlate with high-grade prostate cancer. Urine samples were collected from men after digital rectal examination (DRE) before prostate biopsy. Lectin-antibody enzyme-linked immunoassay was used to quantify α2,3-sialyl PSMA in post-DRE urine samples from subjects with benign prostate tumors, Grade Group 1 prostate cancer and those with Grade Group ≥2 disease., Results: There are significant increases in α2,3-sialylated PSMA in patients with Grade Group ≥2 disease compared to benign (p = 0.0009) and those with Grade Group 1 disease (p = 0.0063). There were no significant differences in α2,3-sialyl PSMA levels between Grade Group 1 and benign prostate tumors (p = 0.7947)., Conclusions: Our study shows that there are significant differences in the abundance of α2,3-sialylated PSMA in post-DRE urines from disease stratified prostate cancer patients, and the increase is correlated with progression and disease severity. The detection of increased PSMA sialyation in post-DRE urines from patients with higher Grade Group ≥2 disease states provides novel untapped potential for the development of prognostic biomarkers for prostate cancer. Specifically, quantitation of α2,3-sialylated PSMA shows potential for discriminating between benign to intermediate grade disease, which is a significant clinical challenge in staging and risk stratification of prostate cancer., (© 2024 The Authors. The Prostate published by Wiley Periodicals LLC.)

In the quest for efficient tumor diagnosis via liquid biopsy, extracellular vesicles (EVs) have shown promise as a source of potential biomarkers. This study addresses the gap in biomarker efficacy for predicting clinically significant prostate cancer (csPCa) between the Western and Chinese populations. We developed a urinary extracellular vesicles-based prostate score (EPS) model, utilizing the EXODUS technique for EV isolation from 598 patients and incorporating gene expressions of FOXA1, PCA3, and KLK3. Our findings reveal that the EPS model surpasses prostate-specific antigen (PSA) testing in diagnostic accuracy within a training cohort of 234 patients, achieving an area under the curve (AUC) of 0.730 compared to 0.659 for PSA (p = 0.018). Similarly, in a validation cohort of 101 men, the EPS model achieved an AUC of 0.749, which was significantly better than PSA's 0.577 (p < 0.001). Our model has demonstrated a potential reduction in unnecessary prostate biopsies by 26%, with only a 3% miss rate for csPCa cases, indicating its effectiveness in the Chinese population., (© 2024 The Author(s). Journal of Extracellular Vesicles published by Wiley Periodicals LLC on behalf of International Society for Extracellular Vesicles.)

Background: This study investigated the use of urinary exosomal mRNA as a potential biomarker for the early detection of prostate cancer (PCa)., Methods: Next-generation sequencing was utilized to analyze exosomal RNA from 10 individuals with confirmed PCa and 10 individuals without cancer. Subsequent validation through qRT-PCR in a larger sample of 43 PCa patients and 92 healthy controls revealed distinct mRNA signatures associated with PCa., Results: Notably, mRNAs for RAB5B, WWP1, HIST2H2BF, ZFY, MARK2, PASK, RBM10, and NRSN2 showed promise as diagnostic markers, with AUC values between 0.799 and 0.906 and significance p values. Combining RAB5B and WWP1 in an exoRNA diagnostic model outperformed traditional PSA tests, achieving an AUC of 0.923, 81.4% sensitivity, and 89.1% specificity., Conclusions: These findings highlight the potential of urinary exosomal mRNA profiling, particularly focusing on RAB5B and WWP1, as a valuable strategy for improving the early detection of PCa., (© 2024. The Author(s).)

A plethora of urine markers for the management of patients with bladder cancer has been developed and studied in the past. However, the clinical impact of urine testing on patient management remains obscure. The goal of this manuscript is to identify scenarios for the potential use of molecular urine markers in the follow-up of patients with high-risk non-muscle-invasive BC (NMIBC) and estimate potential risks and benefits. Information on the course of disease of patients with high-risk NMIBC and performance data of a point-of-care test (UBC rapid™), an MCM-5 directed ELISA (ADXBLADDER™), and 2 additional novel assays targeting alterations of mRNA expression and DNA methylation (Xpert bladder cancer monitor™, Epicheck™) were retrieved from high-quality trials and/or meta-analyses. In addition, the sensitivity of white light cystoscopy (WLC) and the impact of a urine marker result on the performance of WLC were estimated based on fluorescence cystoscopy data and information from the CeFub trial. This information was applied to different scenarios in patient follow-up and sensitivity, estimated number of cystoscopies, and the numbers needed to diagnose were calculated. The sensitivity of guideline-based regular follow-up (SOC) at 1 year was calculated at 96%. For different marker-supported strategies sensitivities ranging from 77% to 97.9% were estimated. Calculations suggest that several strategies are effective for the SOC. While for the SOC 24.6 WLCs were required to diagnose 1 tumor recurrence (NND), this NND dropped below 5 in some marker-supported strategies. Based on the results of this simulation, a marker-supported follow-up of patients with HR NMIBC is safe and offers the option to significantly reduce the number of WLCs. Further research focusing on prospective randomized trials is needed to finally find a way to implement urine markers into clinical decision-making., Competing Interests: Declaration of competing interest Thorsten Ecke is trialist for Concile GmbH, Germany. Florian Roghmann is trialist for Cepheid, CA, USA. Bas W.G. van. Rhijn is consultant for QED Therapeutics, CA, USA and Incyte International Biosciences, DE, USA. Arnulf Stenzl is trialist and consultant for Arquer Ltd, UK, Cepheid, CA, USA and Nucleix Inc., Israel. J. Alfred Witjes is trialist and consultant for Arquer Ltd, UK, Cepheid, CA, USA and Nucleix Inc., Israel. Peter J. Goebell is trialist for Cepheid, CA, USA. Jorgen Bjerggaard Jensen is trialist and consultant for Cepheid, CA, USA and Nucleix Inc., Israel. Bernd J. Schmitz-Dräger is trialist and consultant for Arquer Ltd, UK, Cepheid, CA, USA, Concile GmbH, Germany and Nucleix Inc., Israel. Remaining authors have no conflict of interest to disclose., (Copyright © 2024. Published by Elsevier Inc.)

Purpose: T1 bladder cancer is known for its high progression and recurrence rates. Identifying aggressive tumours at the non-muscle-invasive stage is crucial to allow early interventions and subsequently increase patient survival. This study aimed to investigate the potential of the cubilin/myeloperoxidase (CUBN/MPO) ratio as a high-grade T1 bladder cancer biomarker., Methods: Urine samples were collected from 30 patients who underwent transurethral resection of the tumour with high-grade T1 bladder cancer (June 2015 to December 2019) before surgery. The urinary proteome was analysed using high-resolution mass spectrometry and the CUBN/MPO ratio was calculated. The primary outcome was the recurrence during the follow-up (around 31.5 months after resection). Univariate Cox regression and Kaplan-Meier curves were used for data analysis., Results: Patients with a low CUBN/MPO ratio exhibited upregulated MPO and/or downregulated CUBN. This group of patients had a higher incidence of disease recurrence and progression. Low CUBN/MPO ratio was significantly associated with a higher likelihood of recurrence, progression, and death. It is worth noting that this study was exploratory and conducted on a small sample size, so further research is needed to validate these findings in larger cohorts., Conclusion: This study highlights the potential of the CUBN/MPO ratio as a prognostic biomarker for high-grade T1 bladder cancer., (© 2024. The Author(s).)

Background: We aimed to identify plasma and urinary metabolites related to colorectal cancer (CRC) risk and elucidate their mediator role in the associations between modifiable risk factors and CRC., Methods: Metabolite quantitative trait loci were derived from 2 published metabolomics genome-wide association studies, and summary-level data were extracted for 651 plasma metabolites and 208 urinary metabolites. Genetic associations with CRC were obtained from a large-scale genome-wide association study meta-analysis (100 204 cases, 154 587 controls) and the FinnGen cohort (4957 cases, 304 197 controls). Mendelian randomization and colocalization analyses were performed to evaluate the causal roles of metabolites in CRC. Druggability evaluation was employed to prioritize potential therapeutic targets. Multivariable Mendelian randomization and mediation estimation were conducted to elucidate the mediating effects of metabolites on the associations between modifiable risk factors and CRC., Results: The study identified 30 plasma metabolites and 4 urinary metabolites for CRC. Plasma sphingomyelin and urinary lactose, which were positively associated with CRC risk, could be modulated by drug interventions (ie, olipudase alfa, tilactase). Thirteen modifiable risk factors were associated with 9 metabolites, and 8 of these modifiable risk factors were associated with CRC risk. These 9 metabolites mediated the effect of modifiable risk factors (Actinobacteria, body mass index, waist to hip ratio, fasting insulin, smoking initiation) on CRC., Conclusion: This study identified key metabolite biomarkers associated with CRC and elucidated their mediator roles in the associations between modifiable risk factors and CRC. These findings provide new insights into the etiology and potential therapeutic targets for CRC and the etiological pathways of modifiable environmental factors with CRC., (© The Author(s) 2024. Published by Oxford University Press.)

High-grade serous ovarian cancer (HGSOC) is one of the most common histologic types of ovarian cancer. The purpose of this study was to identify potential prognostic biomarkers in urine specimens from patients with HGSOC. First, 56 urine samples with information on relapse-free survival (RFS) months were collected and classified into good prognosis (RFS ≥ 12 months) and poor prognosis (RFS < 12 months) groups. Next, data-independent acquisition (DIA)-based mass spectrometry (MS) analysis was combined with MSFragger-DIA workflow to identify potential prognostic biomarkers in a discovery set (n = 31). With the aid of parallel reaction monitoring (PRM) analysis, four candidate biomarkers (ANXA1, G6PI, SPB3, and SPRR3) were finally validated in both the discovery set and an independent validation set (n = 25). Subsequent RFS and Cox regression analyses confirmed the utility of these candidate biomarkers as independent prognostic factors affecting RFS in patients with HGSOC. Regression models were constructed to predict the 12-month RFS rate, with area under the receiver operating characteristic curve (AUC) values ranging from 0.847 to 0.905. Overall, candidate prognostic biomarkers were identified in urine specimens from patients with HGSOC and prediction models for the 12-month RFS rate constructed. SIGNIFICANCE: OC is one of the leading causes of death due to gynecological malignancies. HGSOC constitutes one of the most common histologic types of OC with aggressive characteristics, accounting for the majority of advanced cases. In cases where patients with advanced HGSOC potentially face high risk of unfavorable prognosis or disease advancement within a 12-month period, intensive medical monitoring is necessary. In the era of precision cancer medicine, accurate prediction of prognosis or 12-month RFS rate is critical for distinguishing patient groups requiring heightened surveillance. Patients could significantly benefit from timely modifications to treatment regimens based on the outcomes of clinical monitoring. Urine is an ideal resource for disease surveillance purposes due to its easy accessibility. Furthermore, molecules excreted in urine are less complex and more stable than those in other liquid samples. In the current study, we identified candidate prognostic biomarkers in urine specimens from patients with HGSOC and constructed prediction models for the 12-month RFS rate., Competing Interests: Declaration of competing interest There are no potential conflicts of interest to declare. The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: This study aims to explore novel microRNAs in urine for screening and predicting clinical characteristics in pancreatic cancer (PC) patients using a microRNA array-based approach., Methods: We used the Toray ® 3D-Gene microRNA array-based approach to compare urinary levels between PC patients and healthy volunteers., Results: (1) Four oncogenic microRNAs (miR-744-5p, miR-572, miR-210-3p, and miR-575) that were highly upregulated in the urine of PC patients compared to healthy individuals were identified by comprehensive microRNA array analysis. (2) Test-scale analysis by quantitative RT-PCR for each group of 20 cases showed that miR-210-3p was significantly upregulated in the urine of PC patients compared to healthy individuals (P = 0.009). (3) Validation analysis (58 PC patients and 35 healthy individuals) confirmed that miR-210-3p was significantly upregulated in the urine of PC patients compared to healthy individuals (P < 0.001, area under the receiver operating characteristic curve = 0.79, sensitivity: 0.828, specificity: 0.743). We differentiated PC patients into invasive ductal carcinoma (IDCa) and intraductal papillary mucinous carcinoma (IPMC) groups. In addition to urinary miR-210-3p levels being upregulated in IDCa over healthy individuals (P = 0.009), urinary miR-210-3p levels were also elevated in IPMC over healthy individuals (P = 0.0018). Urinary miR-210-3p can differentiate IPMC from healthy individuals by a cutoff of 8.02 with an AUC value of 0.762, sensitivity of 94%, and specificity of 63%. (4) To test whether urinary miR210-3p levels reflected plasma miR-210-3p levels, we examined the correlation between urinary and plasma levels. Spearman's correlation analysis showed a moderate positive correlation (ρ = 0.64, P = 0.005) between miR-210-3p expression in plasma and urine., Conclusions: Urinary miR-210-3p is a promising, non-invasive diagnostic biomarker of PC, including IPMC., Trial Registration: Not applicable., (© 2024. The Author(s).)

Objectives: Urinary sex hormones are investigated as potential biomarkers for the early detection of breast cancer, aiming to evaluate their relevance and applicability, in combination with supervised machine-learning data analysis, toward the ultimate goal of extensive screening., Methods: Sex hormones were determined on urine samples collected from 250 post-menopausal women (65 healthy - 185 with breast cancer, recruited among the clinical patients of Candiolo Cancer Institute FPO-IRCCS (Torino, Italy). Two analytical procedures based on UHPLC-MS/HRMS were developed and comprehensively validated to quantify 20 free and conjugated sex hormones from urine samples. The quantitative data were processed by seven machine learning algorithms. The efficiency of the resulting models was compared., Results: Among the tested models aimed to relate urinary estrogen and androgen levels and the occurrence of breast cancer, Random Forest (RF) proved to underscore all the other supervised classification approaches, including Partial Least Squares - Discriminant Analysis (PLS-DA), in terms of effectiveness and robustness. The final optimized model built on only five biomarkers (testosterone-sulphate, alpha-estradiol, 4-methoxyestradiol, DHEA-sulphate, and epitestosterone-sulphate) achieved an approximate 98% diagnostic accuracy on replicated validation sets. To balance the less-represented population of healthy women, a Synthetic Minority Oversampling TEchnique (SMOTE) data oversampling approach was applied., Conclusions: By means of tunable hyperparameters optimization, the RF algorithm showed great potential for early breast cancer detection, as it provides clear biomarkers ranking and their relative efficiency, allowing to ground the final diagnostic model on a restricted selection five steroid biomarkers only, as desirable for noninvasive tests with wide screening purposes., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Marco Vincenti reports financial support was provided by CRT Foundation. Marco Vincenti reports financial support was provided by Italian Ministry of Education, Universities, and Research. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Renal cell carcinoma is one of the ten more common malignant tumors worldwide, with a high incidence and mortality rate. Kidney cancer frequently presents at an advanced stage, and it is almost invariably fatal. Much progress has been made in identifying molecular targets for therapy in the hope of improving survival rates, but still, we have no good markers for early detection or progression of the disease. Von Hippel Lindau syndrome (VHL) is an autosomal dominant cancer hereditary syndrome in which affected individuals are at risk of developing bilateral and multifocal renal cell carcinomas (RCC) as well as other tumors. These patients provide an ideal platform to investigate the potential of urinary exosomal miRNA biomarkers in the early development of ccRCC, as these patients are regularly imaged and tumors are actively monitored until the tumor reaches 3 cm before surgical excision. This allows for pre- and post-surgical urine collection and comparison to excised tumor tissues. Studying different biomarkers in urine can provide comprehensive molecular profiling available to patients and physicians and can be a great source of additional tumor genetic information., Methods: Pre- and postoperative urine samples were obtained from a cohort of VHL patients undergoing surveillance and surgical excision of ccRCCs, and exosomes were extracted. MicroRNA-Seq analysis was performed on miRNA extracted from both urine-derived exosomes and FFPE material from excised ccRCCs., Results: MicroRNA-Seq analysis highlighted a significant difference in the urinary exosome-derived miRNA expression profiles between VHL patients and normal control individuals. This included decreased expression of the miR-320 family, such as miR-320a, known to be decreased in sporadic ccRCC and suppressed by the HIF1α transcription factor activated by the loss of the VHL gene. MiR-542-5p represented a potential marker of VHL-associated ccRCC that was lowly expressed in normal control urinary exosomes, significantly increased in the preoperative urinary exosomes of tumor-bearing VHL patients, and subsequently reduced to normal levels of expression after tumor excision. In concordance with this, the expression of miR-542-5p was increased in the VHL-associated ccRCC in comparison to the normal kidney., Conclusions: This study shows the potential for miRNA profiling of exosomes from readily available biofluids to both distinguish VHL patient urine from normal control urine microRNAs and to provide biomarkers for the presence of VHL syndrome-associated ccRCC. Further validation studies are necessary to demonstrate the utility of urinary exosome-derived miRNAs as biomarkers in kidney cancer.

Background: Urothelial carcinoma (UC) is the second most common urological malignancy. Despite numerous molecular markers have been evaluated during the past decades, no urothelial markers for diagnosis and recurrence monitoring have shown consistent clinical utility., Methods: The methylation level of tissue samples from public database and clinical collected were analyzed. Patients with UC and benign diseases of the urinary system (BUD) were enrolled to establish TAGMe (TAG of Methylation) assessment in a training cohort (n = 567) using restriction enzyme-based bisulfite-free qPCR. The performance of TAGMe assessment was further verified in the validation cohort (n = 198). Urine samples from 57 UC patients undergoing postoperative surveillance were collected monthly for six months after surgery to assess the TAGMe methylation., Results: We identified TAGMe as a potentially novel Universal-Cancer-Only Methylation (UCOM) marker was hypermethylated in multi-type cancers and investigated its application in UC. Restriction enzyme-based bisulfite-free qPCR was used for detection, and the results of which were consistent with gold standard pyrosequencing. Importantly, hypermethylated TAGMe showed excellent sensitivity of 88.9% (95% CI: 81.4-94.1%) and specificity of 90.0% (95% CI: 81.9-95.3%) in efficiently distinguishing UC from BUD patients in urine and also performed well in different clinical scenarios of UC. Moreover, the abnormality of TAGMe as an indicator of recurrence might precede clinical recurrence by three months to one year, which provided an invaluable time window for timely and effective intervention to prevent UC upstaging., Conclusion: TAGMe assessment based on a novel single target in urine is effective and easy to perform in UC diagnosis and recurrence monitoring, which may reduce the burden of cystoscopy. Trial registration ChiCTR2100052507. Registered on 30 October 2021., (© 2024. The Author(s).)