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.

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.

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.

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.

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.

Detection of renal cell carcinoma using plasma and urine cell-free DNA methylomes.

Improving early cancer detection has the potential to substantially reduce cancer-related mortality. Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) is a highly sensitive assay capable of detecting early-stage tumors. We report accurate classification of patients across all stages of renal cell carcinoma (RCC) in plasma (area under the receiver operating characteristic (AUROC) curve of 0.99) and demonstrate the validity of this assay to identify patients with RCC using urine cell-free DNA (cfDNA; AUROC of 0.86).

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.

Polymorphism of nucleotide binding domain-like receptor protein 3 (NLRP3) increases susceptibility of total urinary arsenic to renal cell carcinoma.

Our study showed that total urinary arsenic concentrations were positively correlated with renal cell carcinoma (RCC). Chronic inflammation is a key player in the development of RCC. This study explored the association between nucleotide-binding domain-like receptor protein 3 (NLRP3) genotypes and the development of RCC. We also investigated whether any of the NLRP3 genotypes modified the risk between arsenic and RCC. We recruited 350 RCC patients and 700 age-sex matched controls. RCC was confirmed by pathological assessment following surgical resection or image-guided biopsy of a renal tumor. Fifteen sites of NLRP3 gene polymorphisms were identified using the Agena Bioscience MassARRAY platform. The concentrations of the urinary arsenic species were determined by HPLC-HG-AAS. There was a significant dose-dependent association between arsenic and RCC. In addition, six of thirteen NLRP3 alleles, including rs12239046 C, rs10925025 G, rs1539019 C, rs10925026 A, rs10157379 T, and rs12143966 A, had increased odds ratios (ORs) for RCC than other NLRP3 alleles. Among these sites, we found the novel haplotype of five tag-SNPs (C-A-A-A-A) was significantly related to RCC, the OR and 95% confidence interval was 1.44 (1.08-1.92). Furthermore, participants with high total urinary arsenic levels and the NLRP3 rs1539019 C allele had significantly multiplicative and additive interactions for the risk of RCC (p interaction = 0.012). This study is the first to identify the modified effects of NLRP3 risk alleles involved in the association between arsenic and RCC risk in a population with low arsenic exposure.

Urinary microRNAs: Looking for a New Tool in Diagnosis, Prognosis, and Monitoring of Renal Cancer.

PURPOSE OF REVIEW: Renal cell carcinoma (RCC) is the third most common urologic malignancy. First symptoms are usually unspecific and belated causing the stages to be high when diagnosed. As compensation, incidental detection of RCC by abdominal imaging techniques for other medical purposes is a reality that favours a decrease in the stage of new diagnosed tumours. Therefore, identifying novel predictive biomarkers for diagnosis, progression and prognosis of RCC is fundamental. RECENT FINDINGS: To date, several studies have demonstrated that microRNAs (miRNAs) play a role in the particular scenario of urologic tumors, and alterations at miRNA level are involved in the initiation, progression and metastases formation of renal cancer. In the present review, we have summarized the up­to­date preliminary clinical works on the role of urinary miRNA profiling in RCC, including an evaluation of its value as a potential biomarker for diagnosis, prognosis and follow up of RCC patients.

Searching for prognostic biomarkers for small renal masses in the urinary proteome.

Renal cell carcinoma (RCC) is frequently diagnosed incidentally as an early-stage small renal mass (SRM; pT1a, ≤4 cm). Overtreatment of patients with benign or clinically indolent SRMs is increasingly common and has resulted in a recent shift in treatment recommendations. There are currently no available biomarkers that can accurately predict clinical behavior. Therefore, we set out to identify early biomarkers of RCC progression. We employed a quantitative label-free liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) proteomics approach and targeted parallel-reaction monitoring to identify and validate early, noninvasive urinary biomarkers for RCC-SRMs. In total, we evaluated 115 urine samples, including 33 renal oncocytoma (≤4 cm) cases, 30 progressive and 26 nonprogressive clear cell RCC (ccRCC)-SRM cases, in addition to 26 healthy controls. We identified six proteins, which displayed significantly elevated expression in clear cell RCC-SRMs (ccRCC-SRMs) relative to healthy controls. Proteins C12ORF49 and EHD4 showed significantly elevated expression in ccRCC-SRMs compared to renal oncocytoma (≤4 cm). Additionally, proteins EPS8L2, CHMP2A, PDCD6IP, CNDP2 and CEACAM1 displayed significantly elevated expression in progressive relative to nonprogressive ccRCC-SRMs. A two-protein signature (EPS8L2 and CCT6A) showed significant discriminatory ability (areas under the curve: 0.81, 95% CI: 0.70-0.93) in distinguishing progressive from nonprogressive ccRCC-SRMs. Patients (Stage I-IV) with EPS8L2 and CCT6A mRNA alterations showed significantly shorter overall survival (p = 1.407 × 10-6 ) compared to patients with no alterations. Our in-depth proteomic analysis identified novel biomarkers for early-stage RCC-SRMs. Pretreatment characterization of urinary proteins may provide insight into early RCC progression and could potentially help assign patients to appropriate management strategies.

Emerging role of secreted miR-210-3p as potential biomarker for clear cell Renal Cell Carcinoma metastasis.

BACKGROUND: MicroRNAs (miRNAs) are emerging as promising molecules in the diagnosis, prognosis and treatment of urological tumours. Recently, our group performed two independent studies highlighting that miR-210-3p may be a useful biomarker not only for diagnosis but also for post-surgery clear cell Renal Cell Carcinoma (ccRCC) management. OBJECTIVE: The aim of this study is to further explore the effectiveness of miRNA as non-invasive biomarker for clinical outcomes and ccRCC response to the treatment. METHODS: We analyzed miR-210-3p levels in neoplastic and healthy tissue and in urine specimens collected at surgery and during follow-up of 21 ccRCC patients by RTqPCR. RESULTS: Firstly, we confirmed that the expression of miR-210-3p was upregulated in tumor tissues and in urine samples of analyzed cohort. Of note is that miR-210-3p expression was significantly reduced in urine samples from disease-free patients during follow-up (from 3 to 12 months) compared to the baseline levels observed at the time of surgery. In a small subgroup of patients presenting metastatic progression (such as bone, intestinal or lung metastasis), the urine levels of miR-210-3p correlated with responsiveness to the therapy. CONCLUSIONS: This pilot study highlights the relevance of secreted miR-210-3p as powerful non-invasive prognostic and predictive biomarker for the evaluation of clinical outcomes and treatment response during ccRCC follow up.

PTRF/CAVIN1, regulated by SHC1 through the EGFR pathway, is found in urine exosomes as a potential biomarker of ccRCC.

Polymerase I and transcript release factor (PTRF)/Cavin1 regulates RNA polymerase I during transcription and plays a critical role in endocytosis. Abnormal expressions of PTRF were detected in multiple cancers according to increasing research. PTRF has been showed to involve in the formation and secretion of exosomes and can be detected in the exosomes, which suggests that PTRF would be a potential biomarker for diagnosis of clear cell renal cell carcinoma (ccRCC) using urine samples. Approximately 50-90% of ccRCC cases suffered abnormal epidermal growth factor receptor (EGFR), which activates a variety of signaling pathways, including the mitogen-activated protein kinase/extracellular signal-regulated kinase and Phosphoinositide 3-Kinase/Akt pathway. According to bioinformatic analysis of gene expression arrays of kidney clear cell carcinoma from The Cancer Genome Atlas, we found SHC1 was significantly overexpressed in high-grade ccRCC and correlated to poor prognosis, and also SHC1 was annotated in extracellular matrix process, which was regulated by EGFR. Further studies showed that the expression of PTRF was regulated by SHC1 through EGFR-Phosphoinositide 3-Kinase/Akt pathway. PTRF was detected in the exosomes isolated from ccRCC patients' urine and ccRCC cancer cells culture medium. It suggested that the abnormal SHC1-increased PTRF, which is detected in exosomes from urine, would be a potential marker for ccRCC diagnose and treatment.

Prognostic urinary miRNAs for the assessment of small renal masses.

BACKGROUND: Renal cell carcinoma (RCC) is often detected incidentally as a small renal mass (SRM; pT1a, ≤4 cm). It is clinically challenging to predict progression in patients with SRMs. This is largely due to the recent recognition of clinically progressive and non-progressive RCC-SRMs. It is critical to accurately stratify SRM patients according to risk to avoid unnecessary treatment. This is especially significant for elderly and infirm patients, where the risk of surgery outweighs mortality from SRMs. METHODS: We employed a qRT-PCR array-based approach and targeted qRT-PCR to identify and validate early, non-invasive diagnostic and prognostic biomarkers of RCC-SRMs. In total, we evaluated eighty urine samples, including 30 renal oncocytoma (≤4 cm) cases, 26 progressive and 24 non-progressive clear cell RCC-SRM (ccRCC-SRM) cases. RESULTS: We identified nine urinary miRNAs which displayed significantly elevated expression in ccRCC-SRMs (pT1a; ≤4 cm) relative to renal oncocytoma (≤4 cm). Additionally, miR-328-3p displayed significantly down-regulated expression in progressive relative to non-progressive ccRCC-SRMs. Patients with elevated miR-328-3p expression had significantly longer overall survival (HR = 0.29, 95% CI = 0.08-1.03, p = 0.042) compared to patients with low miR-328-3p expression. We also found no significant association between miR-328-3p expression levels and gender, age, laterality, tumor size, or grade, suggesting that miR-328-3p is an independent prognostic biomarker. CONCLUSIONS: Our in-depth miRNA profiling approach identified novel biomarkers for early-stage ccRCC-SRMs. Pretreatment characterization of urinary miRNAs may provide insight into early RCC progression and could potentially aid clinical decision-making, improving patient management and reducing overtreatment.

UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma.

BACKGROUND: To discover biomarker panels that could distinguish cancers (BC and RCC) from healthy controls (HCs) and bladder cancers (BC) from renal cell carcinoma (RCC), regardless of whether the patients have haematuria. In addition, we also explored the altered metabolomic pathways of BC and RCC. METHODS: In total, 403 participants were enrolled in our study, which included 146 BC patients (77 without haematuria and 69 with haematuria), 115 RCC patients (94 without haematuria and 21 with haematuria) and 142 sex- and age-matched HCs. Their midstream urine samples were collected and analysed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarker panels and altered metabolic pathways. RESULTS: The panel of α-CEHC, ß-cortolone, deoxyinosine, flunisolide, 11b,17a,21-trihydroxypreg-nenolone and glycerol tripropanoate could distinguish the patients with cancer from the HCs (the AUC was 0.950) and the external validation also displayed a good predictive ability (the AUC was 0.867). The panel of 4-ethoxymethylphenol, prostaglandin F2b, thromboxane B3, hydroxybutyrylcarnitine, 3-hydroxyphloretin and N'-formylkynurenine could differentiate BC from RCC without haematuria. The AUC was 0.829 in the discovering group and 0.76 in the external validation. The metabolite panel comprising 1-hydroxy-2-oxopropyl tetrahydropterin, 1-acetoxy-2-hydroxy-16-heptadecyn-4-one, 1,2-dehydrosalsolinol and L-tyrosine could significantly discriminate BC from RCC with haematuria (AUC was 0.913). Pathway analyses revealed altered lipid and purine metabolisms between cancer patients and HCs, together with disordered amino acid and purine metabolisms between BC and RCC with haematuria. CONCLUSIONS: UPLC-MS urine metabolomic analyses could not only differentiate cancers from HCs but also discriminate BC from RCC. In addition, pathway analyses demonstrated a deeper metabolic mechanism of BC and RCC.

Identification of Prognostic Biomarkers in the Urinary Peptidome of the Small Renal Mass.

Renal cell carcinoma (RCC) is often diagnosed incidentally as a small renal mass (SRM; pT1a, ≤4 cm). Increasing concerns surrounding the overtreatment of patients with benign or clinically silent SRMs has resulted in a recent shift in treatment recommendations, especially in elderly and infirm patients. There are currently no biomarkers that can predict progression. We used a quantitative label-free liquid chromatography-tandem mass spectrometry peptidomics approach and targeted parallel-reaction monitoring to identify early, noninvasive diagnostic and prognostic biomarkers for early-stage RCC-SRMs. In total, 115 urine samples, including 33 renal oncocytoma (≤4 cm) cases, 30 progressive and 26 nonprogressive clear cell RCC-SRM cases, and 26 healthy controls were evaluated. Nine endogenous peptides that displayed significantly elevated expression in clear cell RCC-SRMs relative to healthy controls were identified. Peptides NVINGGSHAGNKLAMQEF, VNVDEVGGEALGRL, and VVAGVANALAHKYH showed significantly elevated expression in clear cell RCC-SRMs relative to renal oncocytoma. Additionally, peptides SHTSDSDVPSGVTEVVVKL and IVDNNILFLGKVNRP displayed significantly elevated expression in progressive relative to nonprogressive clear cell RCC-SRMs. Peptide SHTSDSDVPSGVTEVVVKL showed the most significant discriminatory utility (area under the curve, 0.76; 95% CI, 0.62-0.90; P = 0.0027). Patients with elevated SHTSDSDVPSGVTEVVVKL expression had significantly shorter overall survival (hazard ratio, 4.13; 95% CI, 1.09-15.65; P = 0.024) compared to patients with low expression. Pretreatment characterization of urinary peptides can provide insight into early RCC progression and may aid clinical decision-making and improve disease management.