Diagnosis of renal lymphoma by Wright-Giemsa-stained cytocentrifuged urine evaluation in a cat.

Lymphoma represents up to 30% of neoplasms diagnosed in cats. Diagnosis of lymphoma in the urinary system by examination of urine sediment has been described in a dog, but apparently not previously in cats. Concurrent samples of serum, EDTA whole blood, and urine were submitted from a 15-year-old spayed female domestic shorthair cat exhibiting weight loss, polyuria, and polydipsia. Hematology and biochemical abnormalities included a mild normocytic, normochromic, non-regenerative anemia; an inflammatory leukogram; and azotemia. Urinalysis evaluation revealed inadequate urine concentration and marked proteinuria. Wet-mount urine sediment examination revealed moderate numbers of leukocytes and erythrocytes. A uniform population of intermediate-to-large lymphocytes was observed on a fresh, Wright-Giemsa-stained preparation from cytocentrifuged urine. The cat was euthanized and necropsy was completed. Bilateral renomegaly was identified and characterized by multifocal, pale-yellow, coalescing, poorly defined, homogenous nodules. Microscopically, these nodules were composed of dense sheets of CD3-positive round cells, consistent with T-cell renal lymphoma. Key clinical message: Lymphoma is a common neoplasm in cats that can affect many organ systems, including the upper urinary tract. This case represents an uncommon method of identifying neoplastic lymphocytes via evaluation of cytocentrifuged urine, and emphasizes the benefits of examining Romanowsky-stained urine sediment in animals.

Diagnostic du lymphome rénal chez un chat par évaluation d'urine cytocentrifugée avec coloration Wright-Giemsa. Le lymphome représente jusqu'à 30 % des néoplasmes diagnostiqués chez le chat. Le diagnostic d'un lymphome du système urinaire par examen des sédiments urinaires a été décrit chez un chien, mais apparemment pas à ce jour chez le chat. Des échantillons simultanés de sérum, de sang total dans un tube avec EDTA et d'urine ont été soumis provenant d'une chatte domestique à poils courts stérilisée de 15 ans présentant une perte de poids, une polyurie et une polydipsie. Les anomalies hématologiques et biochimiques comprenaient une légère anémie normocytaire, normochrome et non régénérative; une formule leucocytaire inflammatoire; et une azotémie. L'analyse d'urine a révélé une concentration urinaire insuffisante et une protéinurie marquée. L'examen microscopique des sédiments urinaires a révélé un nombre modéré de leucocytes et d'érythrocytes. Une population uniforme de lymphocytes de taille intermédiaire à grande a été observée sur une préparation fraîche colorée au Wright-Giemsa à partir d'urine cytocentrifugée. Le chat a été euthanasié et une autopsie a été réalisée. Une rénomégalie bilatérale a été identifiée et caractérisée par des nodules multifocaux, jaune pâle, coalescents, mal définis et homogènes. Au microscope, ces nodules étaient composés de feuilles denses de cellules rondes CD3-positives, compatibles avec un lymphome rénal à cellules T.Message clinique clé :Le lymphome est une tumeur courante chez le chat qui peut affecter de nombreux systèmes organiques, y compris les voies urinaires supérieures. Ce cas représente une méthode rare d'identification des lymphocytes néoplasiques via l'évaluation de l'urine cytocentrifugée et met l'emphase sur les avantages de l'examen des sédiments urinaires avec coloration de Romanowsky chez les animaux.(Traduit par Dr Serge Messier).

Automated Machine Learning and Explainable AI (AutoML-XAI) for Metabolomics: Improving Cancer Diagnostics.

Metabolomics generates complex data necessitating advanced computational methods for generating biological insight. While machine learning (ML) is promising, the challenges of selecting the best algorithms and tuning hyperparameters, particularly for nonexperts, remain. Automated machine learning (AutoML) can streamline this process; however, the issue of interpretability could persist. This research introduces a unified pipeline that combines AutoML with explainable AI (XAI) techniques to optimize metabolomics analysis. We tested our approach on two data sets: renal cell carcinoma (RCC) urine metabolomics and ovarian cancer (OC) serum metabolomics. AutoML, using Auto-sklearn, surpassed standalone ML algorithms like SVM and k-Nearest Neighbors in differentiating between RCC and healthy controls, as well as OC patients and those with other gynecological cancers. The effectiveness of Auto-sklearn is highlighted by its AUC scores of 0.97 for RCC and 0.85 for OC, obtained from the unseen test sets. Importantly, on most of the metrics considered, Auto-sklearn demonstrated a better classification performance, leveraging a mix of algorithms and ensemble techniques. Shapley Additive Explanations (SHAP) provided a global ranking of feature importance, identifying dibutylamine and ganglioside GM(d34:1) as the top discriminative metabolites for RCC and OC, respectively. Waterfall plots offered local explanations by illustrating the influence of each metabolite on individual predictions. Dependence plots spotlighted metabolite interactions, such as the connection between hippuric acid and one of its derivatives in RCC, and between GM3(d34:1) and GM3(18:1_16:0) in OC, hinting at potential mechanistic relationships. Through decision plots, a detailed error analysis was conducted, contrasting feature importance for correctly versus incorrectly classified samples. In essence, our pipeline emphasizes the importance of harmonizing AutoML and XAI, facilitating both simplified ML application and improved interpretability in metabolomics data science.

Optical biomarker analysis for renal cell carcinoma obtained from preoperative and postoperative patients using ATR-FTIR spectroscopy.

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.

Identification of novel snoRNA-based biomarkers for clear cell renal cell carcinoma from urine-derived extracellular vesicles.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC with high rates of metastasis. Targeted therapies such as tyrosine kinase and checkpoint inhibitors have improved treatment success, but therapy-related side effects and tumor recurrence remain a challenge. As a result, ccRCC still have a high mortality rate. Early detection before metastasis has great potential to improve outcomes, but no suitable biomarker specific for ccRCC is available so far. Therefore, molecular biomarkers derived from body fluids have been investigated over the past decade. Among them, RNAs from urine-derived extracellular vesicles (EVs) are very promising. METHODS: RNA was extracted from urine-derived EVs from a cohort of 78 subjects (54 ccRCC patients, 24 urolithiasis controls). RNA-seq was performed on the discovery cohort, a subset of the whole cohort (47 ccRCC, 16 urolithiasis). Reads were then mapped to the genome, and expression was quantified based on 100 nt long contiguous genomic regions. Cluster analysis and differential region expression analysis were performed with adjustment for age and gender. The candidate biomarkers were validated by qPCR in the entire cohort. Receiver operating characteristic, area under the curve and odds ratios were used to evaluate the diagnostic potential of the models. RESULTS: An initial cluster analysis of RNA-seq expression data showed separation by the subjects' gender, but not by tumor status. Therefore, the following analyses were done, adjusting for gender and age. The regions differentially expressed between ccRCC and urolithiasis patients mainly overlapped with small nucleolar RNAs (snoRNAs). The differential expression of four snoRNAs (SNORD99, SNORD22, SNORD26, SNORA50C) was validated by quantitative PCR. Confounder-adjusted regression models were then used to classify the validation cohort into ccRCC and tumor-free subjects. Corresponding accuracies ranged from 0.654 to 0.744. Models combining multiple genes and the risk factors obesity and hypertension showed improved diagnostic performance with an accuracy of up to 0.811 for SNORD99 and SNORA50C (p = 0.0091). CONCLUSIONS: Our study uncovered four previously unrecognized snoRNA biomarkers from urine-derived EVs, advancing the search for a robust, easy-to-use ccRCC screening method.

Prospective evaluation of the RT-PCR based urinary marker Bladder Epicheck® as a diagnostic tool in upper urinary tract tumor.

BACKGROUND: Upper-tract-urothelial-carcinoma (UTUC) represents 5-10% of all urothelial-neoplasms with increasing incidence in the last decades. Current standard tools for diagnosis of UTUC include cytology, computed tomography (CT) urography and ureterorenoscopy (URS). The aim of this study was to evaluate the impact of Bladder Epicheck® Test as diagnostic tool for UTUC diagnosis and recurrence. METHODS: Overall, 136 urine samples, selective collected from upper-urinary-tract before URS for suspicion of UTUC were analyzed with cytology and Bladder Epicheck® Test. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of both markers were calculated and compared to URS and/or histology as reference. RESULTS: UTUC was detected in 40 cases (33.3%), among them 30 were classified as low-grade (LG) and 10 as high-grade (HG). Overall sensitivity of Bladder Epicheck® for UTUC detection was 65% compared to 42.5% for cytology, increasing to 100% for Bladder Epicheck® and 90% for cytology if considering only HG tumors. Overall specificity of Bladder Epicheck® was 81.2% and of cytology 93.7%. PPV and NPV were 63.4% and 82.2% for Bladder Epicheck® and 77.2% and 76.5% for cytology. Considering an EpiScore cut-off >75, instead of 60, specificity of Bladder Epicheck® improves to 89% and PPV to 74.2%. Limitations include the use of a marker validated only for bladder-cancer and the relatively small number of cases. CONCLUSIONS: Due to its high sensitivity for HG tumors, the Bladder Epicheck® Test can be used in diagnosis and treatment decision-making of UTUC. Furthermore, it could be very useful in follow-up of UTUC, after endoscopic treatment to postpone or avoid unnecessary endoscopic exploration. Even if further studies are needed to validate these findings, Bladder Epicheck® could be a promising clinical tool for detection of UTUC.

ARSENIC IN DRINKING WATER AND URINE AND ITS RELATIONSHIP WITH MALIGNANT TUMORS OF URINARY TRACT IN OSIJEK-BARANJA COUNTY, CROATIA.

Increased values of arsenic in potable water in eastern Croatia has been a matter of scientific interest for the past two decades due to numerous health effects, including carcinogenic ones. This study investigated whether prolonged exposure to increased arsenic from water could be detectable through increased arsenic in urine, and whether it influenced the incidence of kidney and bladder cancer in Osijek-Baranja County. Inductively coupled plasma mass spectrometry (ICP-MS) was used for analysis of water samples from available water sources (wells, aqueducts). In addition, examinees from Osijek, Nasice, Vladislavci, Cepin and Dalj gave their urine samples for analysis. Data on cancer incidence were obtained from the Institute for Public Health Registry and cumulative incidence of kidney and bladder cancer was calculated for the period between January 1, 2000 and December 31, 2018. Elevated arsenic concentration in drinking water was recorded in Vladislavci, Cepin and Osijek area with values above the allowed maximum according to the EU standards (10 µg L-1) and as a result, arsenic levels in urine of the inhabitants were also elevated. Cumulative incidence for bladder cancer showed correlation between increased arsenic in water and urine in the areas affected by increased arsenic in water. Epidemiologic data suggest a conclusion that elevated arsenic could be considered at least as a cofounding factor for urinary tract cancer.

Predictive model for recurrence of renal cell carcinoma by comparing pre- and postoperative urinary metabolite concentrations.

To improve treatment outcomes in real practice, useful biomarkers are desired when predicting postoperative recurrence for renal cell carcinoma (RCC). We collected data from patients who underwent definitive surgery for RCC and for benign urological tumor at our department between November 2016 and December 2019. We evaluated the differences in pre- and postoperative urinary metabolites with our precise quantitative method and identified predictive factors for RCC recurrence. Additionally, to clarify the significance of metabolites, we measured the intracellular metabolite concentration of three RCC cell lines. Among the 56 patients with RCC, nine had a recurrence (16.0%). When comparing 27 patients with T1a RCC and 10 with benign tumor, a significant difference was observed between pre- and postoperative concentrations among 10 urinary metabolites. In these 10 metabolites, multiple logistic regression analysis identified five metabolites (lactic acid, glycine, 2-hydroxyglutarate, succinic acid, and kynurenic acid) as factors to build our recurrence prediction model. The values of area under the receiver operating characteristic curve, sensitivity, and specificity in this predictive model were 0.894%, 88.9%, and 88.0%, respectively. When stratified into low and high risk groups of recurrence based on this model, we found a significant drop of recurrence-free survival rates among the high risk group. In in vitro studies, intracellular metabolite concentrations of metastatic tumor cell lines were much higher than those of primary tumor cell lines. By using our quantitative evaluation of urinary metabolites, we could predict postoperative recurrence with high sensitivity and specificity. Urinary metabolites could be noninvasive biomarkers to improve patient outcome.

MN/CA9 gene expression as a potential tumor marker for renal cell carcinoma.

MN/CA9 is a cell surface glycoprotein and a tumor-associated antigen. It plays a crucial role in the regulation of cell proliferation and oncogenesis. There is no ideal tumor marker currently available for renal cell carcinoma (RCC) with sufficient sensitivity and specificity. Therefore, we studied MN/CA9 gene expression in the tumor tissue, apparently normal kidney tissue, preoperative blood, and urine samples of patients with RCC. We included thirty cases of renal tumors (26 RCC and 4 benign tumors) in the study. We applied an RT-PCR assay for MN/CA9 gene expression to 26 RCC kidney tumor samples and four benign kidney tumor tissue samples. We also evaluated MN/CA9 gene expression in preoperative blood and urine samples of 15 of these cases. Additionally, thirty-five grossly normal renal tissue samples, including 21 from kidneys with RCC, were also evaluated for gene expression. The RT-PCR analysis revealed that twenty-one out of 26 RCC tissue samples showed MN/CA9 gene expression compared to three out of 35 non-malignant renal tissue samples (p < 0.05). Two out of four benign renal tissue samples also expressed this gene. We also observed MN/CA9 gene expression in nine out of 15 blood samples and four out of 15 urine samples. All patients with urinary MN/CA9 gene expression showed expression in blood and tumor tissue samples. We found a correlation in terms of MN/CA9 expression between blood and tumor tissue samples of RCC patients as those who exhibit MN/CA9 expression in blood were also positive at the tumor tissue levels. The difference in MN/CA9 gene expression in tumor tissue, blood, and urine samples in relation to the stage of the disease, nuclear grade, and histological cell-type was not statistically significant. However, all the three patients who had metastatic RCC had MN/CA9 gene expression in their blood. The existence of a tumor-associated antigen such as MN/CA9 may present a possible target for molecular diagnosis and management of RCC.

Circulating RNA in Kidney Cancer: What We Know and What We Still Suppose.

Renal cancer represents the 7th most common tumor worldwide, affecting 400,000 people annually. This malignancy, which is the third most frequent cancer among urological diseases, displays a completely different prognosis if the tumor is detected in the early stages or advance phases. Unfortunately, more than 50% of renal cancers are discovered incidentally, with a consistent percentage of cases where the tumor remains clinically silent till the metastatic process is established. In day-to-day clinical practice, no available predictive biomarkers exist, and the existent imaging diagnostic techniques harbor several gaps in terms of diagnosis and prognosis. In the last decade, many efforts have been reported to detect new predictive molecular biomarkers using liquid biopsies, which are less invasive in comparison to renal biopsy. However, until now, there has been no clear evidence that a liquid biopsy biomarker could be relevant to the creation of a precise and tailored medical management in these oncological patients, even though circulating RNA biomarkers remain among the most promising. Given the idea that liquid biopsies will play a future key role in the management of these patients, in the present review, we summarize the current state of circulating RNA (miRNA, lncRNAs, and circRNAs) as possible biomarkers of renal cancer presence and aggressiveness in patients.

Non-invasive urine markers for the differentiation between RCCs and oncocytoma.

BACKGROUND: Recently, our group showed that Vim3 is overexpressed in tissue samples of renal oncocytomas and Mxi-2 in clear cell renal carcinoma (ccRCC). The mechanism leading to the truncation of both proteins is known and involves with two miRs, both detectable in urine. Since the analysis of miRs is time-consuming, our aim was to identify the truncated proteins in urine instead. Furthermore, urine samples from small renal masses (SRMs) (n = 45, <4 cm) were analyzed to get a pre-surgical differentiation of the cancer subtypes. METHODS: Urines were accessed from the urological biobank (n = 350). Proteins were isolated from urine samples, and Western blots were performed. Each sample was analyzed with ELISA for the expression of Vim3 and Mxi-2. A lateral flow assay was established. For the detection of SRMs, the miRs were isolated and qRT-PCR was performed. RESULTS: A significant increase of Vim3 in urines from patients with oncocytoma (n = 20) was detectable with ELISA compared to all other subtypes of RCCs (chromophobe (n = 50), papillary (n = 40), ccRCC (n = 200), and controls (n = 40) (***p < 0.0001)). Mxi-2 was predominantly overexpressed in ccRCCs (***p < 0.0001). Lateral flow assay of Vim3 and Mxi-2 shows two bands in the case of oncocytoma and ccRCC indicating the specificity of this test. For SRMs, an overexpression of miR-15a/Mxi2 was detectable in urine samples from ccRCC and chromoRCC patients. In contrast to that, miR-498/Vim3 were predominantly overexpressed in oncocytoma patients. CONCLUSION: Both proteins (Vim3 and Mxi-2) were detectable in patients' urines and can be used for the non-invasive differentiation of kidney cancers.

Renal metastases from esophageal cancer and retroperitoneal lymphoma detected via chromosome duplications identified by fluorescence in situ hybridization in urine exfoliated cells: First 2 case reports.

RATIONALE: Renal-occupying lesions positive for urine fluorescence in situ hybridization (FISH) are usually considered urothelial carcinomas. Here, we describe 2 cases of renal metastases with chromosome duplications in urine exfoliated cells. PATIENT SYMPTOMS: Patient 1, a 56-year-old male with a history of esophageal cancer, was admitted to our hospital on May 2017 after presenting with right back pain with microscopic hematuria for 1 month. Magnetic resonance imaging (MRI) showed right renal space-occupying lesions (5.4 cm × 4.6 cm) and multiple enlarged lymph nodes in the right renal hilum and retroperitoneum. The cystoscopy results were negative, and FISH analysis of urine exfoliated cells was positive, indicative of chromosome 3, 7, and 17 amplifications. Patient 2 was a 50-year-old male who was admitted to our hospital on May 2019 with no obvious cause of abdominal pain and abdominal distension (lasting for 7 days), with a serum creatinine level of 844 µmol/L. Patient 2 had no hematuria or fever, and MRI showed left renal inferior and medial space-occupying lesions, and multiple mesenteric nodules at the junction of the left adrenal gland, retroperitoneum, abdomen, and pelvis, which were partially fused. The tumor lesions were approximately 3.1 cm × 2.3 cm in size. The urine FISH results were positive, indicating chromosome 3, 7, and 17 amplifications. DIAGNOSES: Both patients were diagnosed with renal tumors with unknown pathology. INTERVENTIONS: Patient 1 underwent laparoscopic resection of the kidney and ureter, and sleeve cystectomy. The postoperative pathological diagnosis was metastatic keratinized squamous cell carcinoma, with squamous cell carcinoma in the right hilar lymph node. Histological FISH of the primary esophageal cancer and renal metastases were consistent with the urine FISH test results. Patient 2 underwent a biopsy of the left renal inferior and retroperitoneal areas, and was diagnosed with diffuse large B-cell lymphoma. OUTCOMES: Patient 1 survived 6 months after urological surgery. After treating patient 2 with the R-CHOP regimen and kinase inhibitors, his renal function recovered significantly and the mass become undetectable. LESSONS: Our results imply that FISH-positive renal occupying lesions should be considered as potential renal metastases with chromosome aberrations when making a differential diagnosis.

ARCHITECT® urine-neutrophil gelatinase-associated lipocalin (u-NGAL) assay as new prognostic marker for clear cell Renal Cell Carcinoma (ccRCC) (preliminary results).

INTRODUCTION: Biomarkers for the diagnosis and monitoring treatment response of kidney cancer are urgently needed. Neutrophil gelatinase-associated lipocalin (NGAL) is a relevant urinary biomarker for the diagnosis of a wide variety of acute and chronic kidney diseases. Its potential utility as a prognostic marker of kidney cancer is largely unknown and, therefore, was the subject of this investigation. MATERIALS AND METHODS: A retrospective study was done on 50 kidney tumor patients (urine samples prospectively collected before nephrectomy between 2004 and 2012, stored at Biobank Resource Center). The specificity, sensitivity and the predictive value of NGAL were determined for progression-free and disease-specific survival after nephrectomy in renal cell carcinoma (particularly, the clear cell renal cell carcinoma (ccRCC)). Urinary NGAL concentration (u-NGAL) was determined by CMIA technique (ARCHITECT® urine NGAL essay/ABBOTT®). RESULTS: Out of the 50 kidney tumor patients, 40 had clear cell carcinoma with a median u-NGAL excretion of 1.4 (IQR: 5.76) ng/mg urinary creatinine (Ucr). u-NGAL was correlated to tumor stage (p = 0.005), and Fuhrman grade (p = 0.0002). Multivariate Cox regression analysis showed a significant association between u-NGAL excretion and clear cell renal cell carcinoma progression free survival and disease specific survival (p = 0.002; p = 0.0001). CONCLUSIONS: Urinary NGAL was significantly associated with the stage and the grade of kidney cancer. u-NGAL excretion could be considered as a potential biomarker to identify ccRCC patients with the more pejorative outcomes.

Detection of urinary miRNAs for diagnosis of clear cell renal cell carcinoma.

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

Urinary Human Kidney Injury Molecule1- (hKIM1-) is not Increased in Patients with Renal Cell Carcinoma.

PURPOSE: Human Kidney Injury Molecule-1 (hKIM-1) was proposed as urinary biomarker of renal cell carcinoma (RCC). The aim of the study was to validate urinary hKIM-1 as a biomarker of RCC. MATERIAL AND METHODS: Forty-six participants were enrolled into the study, including 30 patients with clear-cell or papillary RCC and 16 matched patients in the comparison group. Preoperative urinary hKIM-1 levels were measured using commercially available ELISA kit and normalized to urinary creatinine levels. RESULTS: The concentrations of urinary hKIM-1 normalized to urinary creatinine in patients with RCC and comparison group did not differ significantly (1.35 vs. 1.32 ng/mg creatinine, p=.25). There was also no difference in urinary hKIM-1 concentration regarding stage or grade of renal cancer. Additional analysis of patients without chronic kidney disease (defined as eGFR ≥60mL/min/1.73m²) also did not reveal significant difference in urinary hKIM-1 concentrations between the groups (1.54 vs. 1.37; p=.47). CONCLUSION: Results of our study do not confirm recent suggestions that urinary hKIM-1 may be a biomarker of RCC.

Recognition of urinary N-linked glycopeptides in kidney cancer patients by hydrophilic carbohydrate functionalized magnetic metal organic framework combined with LC-MS/MS.

A hydrophilic carbohydrate functionalized magnetic metal organic framework (Mag Zr-MOF@G6P) was synthesized via a facile one-step modification strategy for selective glycopeptide capture in virtue of hydrophilic interaction chromatography technique. The inherently hydrophilic Zr-MOF layer not only provides selective size-sieving pore structures but also offers large specific surface area to afford abundant affinity sites. Hydroxyl-rich glucose-6-phosphate was immobilized onto the Zr-MOF via a straightforward coordination manner to regulate its surface property, for the purpose of enhancing its hydrophilicity. Benefitting from the merits of Zr-MOF and glucose-6-phosphate, the as-designed composite exhibits good selectivity (the mass ratio of HRP digests to BSA digests was up to1:200) and low limit of detection (0.1 fmol µL-1) towards the recognition of glycopeptides from standard samples. More excitingly, glycopeptides in urine of healthy people and patients with kidney cancer were successfully enriched and identified by the combined liquid chromatography-mass spectrometry/mass spectrometry technology (LC-MS/MS). Further gene ontology analysis of molecular function and biological process revealed that 13 original glycoproteins of the identified glycopeptides from urine of patients significantly participate in diverse cancer-associated events, including collagen binding, immunoglobulin receptor binding, antigen binding, and complement activation process. Graphical abstract.

Evaluation of Proteinuria Using Urine Protein : Creatine Ratio in Treatment with Molecular Targeted Agents for Advanced Renal Cell Carcinoma.

The usefulness of the urine protein : creatine ratio (UPCR) in management of molecular targeted therapy and immunotherapy has not been studied, although urine protein dipstick testing (uPr) is widely used in the clinical setting. The aim of this study was to investigate the usefulness of UPCR as compared to uPr in patients undergoing molecular targeted therapy for advanced renal cell carcinoma (RCC). A total of 25 patients (median age 68 years) with advanced RCC were included. Sunitinib, pazopanib, axitinib, sorefenib, everolimus, and nivolumab were administered to 15, 9, 16, 3, 7, and 13 patients, respectively, with duplication. Proteinuria was managed according to the grade determined by UPCR. Data at every treatment visit were retrospectively collected and uPr and UPCR were compared. The overall incidences of any grade of proteinuria associated with sunitinib, pazopanib, axitinib, sorafenib and everolimus were 86.7, 88.9, 93.8, 100, and 85.7%, respectively. There were discordances between the uPr-based grade and UPCR-based grade. UPCR did not meet the criteria of Grade 3 in 70.6, 100, 83.3, and 83.3% at visits in cases with uPr 3+ for sunitinib, pazopanib, sorafenib, and everolimus, respectively. In axitinib treatment, UPCR did not meet the criteria for withholding in 46.2% of the cases of uPr 2+ and more. Our study suggests that UPCR may be useful tool in management of adverse events associated with tyrosine kinase inhibitors, everolimus and can provide patients with optimal opportunities for receiving treatment.

Screening of Urinary Renal Cancer Metabolic Biomarkers with Gold Nanoparticles-assisted Laser Desorption/Ionization Mass Spectrometry.

Renal cell carcinoma is a very aggressive and often fatal disease for which there are no specific biomarkers found to date. The purpose of this work was to find features that differentiate urine metabolic profiles of healthy people and cancer patients. Laser desorption/ionization mass spectrometry on gold nanostructures-based techniques were used for the metabolic analysis of urine of 50 patients with kidney cancer. Comparison with data from 50 healthy volunteers led to the discovery of several compounds that may be considered potential renal cell carcinoma (RCC) biomarkers. Statistical analysis of data allowed for the discovery of m/z values that had the greatest impact on group differentiation. A database search enabled the assignment of signals for the most promising 15 features among them: serine, heptanol, 3-methylene-indolenine, 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate, phosphodimethylethanolamine, 4-methoxyphenylacetic acid, N-acetylglutamine, 3,5-dihydroxyphenylvaleric acid, hydroxyhexanoylglycine, valyl-leucine, leucyl-histidine, oleamide, 9,12,13-trihydroxyoctadecenoic acid, stearidonyl carnitine and squalene. Differences of metabolite profiles of human urine could be identified by gold nanoparticle-enhanced target (AuNPET) LDI MS method and used for the detection of renal cancer.

MicroRNA-30a-5pme: a novel diagnostic and prognostic biomarker for clear cell renal cell carcinoma in tissue and urine samples.

BACKGROUND: The rising incidence of renal cell carcinomas (RCC) constitutes a significant challenge owing to risk of overtreatment. Because aberrant microRNA (miR) promoter methylation contributes to cancer development, we investigated whether altered miR-30a-5p expression associates with DNA promoter methylation and evaluated the usefulness as clear cell RCC (ccRCC) diagnostic and prognostic markers. METHODS: Genome-wide methylome and RNA sequencing data from a set of ccRCC and normal tissue samples from The Cancer Genome Atlas (TCGA) database were integrated to identify candidate CpG loci involved in cancer onset. MiR-30a-5p expression and promoter methylation were quantitatively assessed by PCR in a tissue set (Cohort #1) and urine sets (Cohorts #2 and 3) from IPOPorto and Homburg University Hospital. Non-parametric tests were used for comparing continuous variables. MiR-30a-5p promoter methylation (miR-30a-5pme) performance as diagnostic (receiver operator characteristics [ROC] - validity estimates) and prognostic [metastasis-free (MFS) and disease-specific survival (DSS)] biomarker was further validated in urine samples from ccRCC patients by Kaplan Meier curves (with log rank) and both univariable and multivariable analysis. RESULTS: Two significant hypermethylated CpG loci in TCGA ccRCC samples, correlating with miR-30a-5p transcriptional downregulation, were disclosed. MiR-30a-5pme in ccRCC tissues was confirmed in an independent patient's cohort of IPOPorto and associated with shorter time to relapse. In urine samples, miR-30a-5pme levels identified cancer both in testing and validation cohorts, with 83% sensitivity/53% specificity and 63% sensitivity/67% specificity, respectively. Moreover, higher miR-30a-5pme levels independently predicted metastatic dissemination and survival. CONCLUSION: To the best of our knowledge, this is the first study validating the diagnostic and prognostic potential of miR-30a-5pme for ccRCC in urine samples, providing new insights for its clinical usefulness as non-invasive cancer biomarker.

Assessment of somatic mutations in urine and plasma of Wilms tumor patients.

Tumor DNA has been detected in body fluids of cancer patients. Somatic tumor mutations are being used as biomarkers in body fluids to monitor chemotherapy response as a minimally invasive tool. In this study, we evaluated the potential of tracking somatic mutations in free DNA of plasma and urine collected from Wilms tumor (WT) patients for monitoring treatment response. Wilms tumor is a pediatric renal tumor resulting from cell differentiation errors during nephrogenesis. Its mutational repertoire is not completely defined. Thus, for identifying somatic mutations from tumor tissue DNA, we screened matched tumor/leukocyte DNAs using either a panel containing 16 WT-associated genes or whole-exome sequencing (WES). The identified somatic tumor mutations were tracked in urine and plasma DNA collected before, during and after treatment. At least one somatic mutation was identified in five out of six WT tissue samples analyzed. Somatic mutations were detected in body fluids before treatment in all five patients (three patients in urine, three in plasma, and one in both body fluids). In all patients, a decrease of the variant allele fraction of somatic mutations was observed in body fluids during neoadjuvant chemotherapy. Interestingly, the persistence of somatic mutations in body fluids was in accordance with clinical parameters. For one patient who progressed to death, it persisted in high levels in serial body fluid samples during treatment. For three patients without disease progression, somatic mutations were not consistently detected in samples throughout monitoring. For one patient with bilateral disease, a somatic mutation was detected at low levels with no support of clinical manifestation. Our results demonstrated the potential of tracking somatic mutations in urine and plasma DNA as a minimally invasive tool for monitoring WT patients. Additional investigation is needed to check the clinical value of insistent somatic mutations in body fluids.

Accurate quantification of urinary metabolites for predictive models manifest clinicopathology of renal cell carcinoma.

Using surgically resected tissue, we identified characteristic metabolites related to the diagnosis and malignant status of clear cell renal cell carcinoma (ccRCC). Specifically, we quantified these metabolites in urine samples to evaluate their potential as clinically useful noninvasive biomarkers of ccRCC. Between January 2016 and August 2018, we collected urine samples from 87 patients who had pathologically diagnosed ccRCC and from 60 controls who were patients with benign urological conditions. Metabolite concentrations in urine samples were investigated using liquid chromatography-mass spectrometry with an internal standard and adjustment based on urinary creatinine levels. We analyzed the association between metabolite concentration and predictability of diagnosis and of malignant status by multiple logistic regression and receiver operating characteristic (ROC) curves to establish ccRCC predictive models. Of the 47 metabolites identified in our previous study, we quantified 33 metabolites in the urine samples. Multiple logistic regression analysis revealed 5 metabolites (l-glutamic acid, lactate, d-sedoheptulose 7-phosphate, 2-hydroxyglutarate, and myoinositol) for a diagnostic predictive model and 4 metabolites (l-kynurenine, l-glutamine, fructose 6-phosphate, and butyrylcarnitine) for a predictive model for clinical stage III/IV. The sensitivity and specificity of the diagnostic predictive model were 93.1% and 95.0%, respectively, yielding an area under the ROC curve (AUC) of 0.966. The sensitivity and specificity of the predictive model for clinical stage were 88.5% and 75.4%, respectively, with an AUC of 0.837. In conclusion, quantitative analysis of urinary metabolites yielded predictive models for diagnosis and malignant status of ccRCC. Urinary metabolites have the potential to be clinically useful noninvasive biomarkers of ccRCC to improve patient outcomes.