Urinary microRNA-210-3p as a novel and non-invasive biomarker for the detection of pancreatic cancer, including intraductal papillary mucinous carcinoma.

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.

Identification of a urinary CD276 fragment for detecting resectable pancreatic cancer using a C-terminal proteomics strategy.

This study aimed to confirm urinary protein fragments in relation to the presence of pancreatic ductal adenocarcinoma (PDAC) via a C-terminal proteomics strategy using exploratory and validation cohorts. Urinary fragments were examined by iTRAQ-labelling of tryptic peptides and concentrations of C-terminal fragments were evaluated. Only the urinary CD276 fragment showed a fold change (FC) of > 1.5 with a significant difference of P < 0.01 between healthy (H) and PDAC participants in both the exploratory (H, n = 42; PDAC, n = 39) and validation cohorts (H, n = 36; resectable PDAC, n = 28). The sensitivity and specificity of the CD276 fragment for diagnosing resectable PDAC were 75% and 89%, respectively, in the validation cohort. Postoperative urinary levels of the CD276 fragment were low as compared to those before surgery (n = 18, P < 0.01). Comprehensive C-terminus proteomics identified an increase in the urinary CD276 fragment level as a feature of patients with PDAC. The urinary CD276 fragment is a potential biomarker for detecting resectable PDAC.

Urinary metabolite prognostic biomarker panel for pancreatic ductal adenocarcinomas.

BACKGROUND: Patients with pancreatic ductal adenocarcinoma (PDAC) have a very low survival rate and surgical resection is the only curative intent treatment available. However, the majority of patients relapse after surgery and identification of biomarkers for accurate prognostication of PDAC patients is required. We have recently identified a six biomarker (i.e., trigonelline, glycolate, hippurate, creatine, myoinositol and hydroxyacetone) urinary metabolite panel with very high potential to diagnose PDAC (Int J Cancer 2021;148:1508-18). This study aimed to assess the prognostic ability of these previously identified diagnostic metabolites in the urine of PDAC patients. METHODS: Metabolite data from 88 PDAC patients was statistically assessed for their prognostic ability. RESULTS: A panel of three metabolites (i.e., trigonelline, hippurate and myoinositol) was able to stratify patients with good- or poor-prognosis based on overall survival. The PDAC patients with abnormal levels of 2 or more metabolites in their urine demonstrated significantly lower survival compared to patients with abnormal levels of one or less metabolites. CONCLUSION: These results demonstrate that the selected three metabolite panel could be used to stratify patients based on their prognostic outcomes and if independently validated may lead to the development of a urinary prognostic biomarker test for PDAC. GENERAL SIGNIFICANCE: This study highlights the potential of using 1H-nuclear magnetic resonance spectroscopy for the identification of novel metabolites which can prognosticate cancer patients.

A unique urinary metabolomic signature for the detection of pancreatic ductal adenocarcinoma.

Our study aimed to identify a urinary metabolite panel for the detection/diagnosis of pancreatic ductal adenocarcinoma (PDAC). PDAC continues to have poor survival outcomes. One of the major reasons for poor prognosis is the advanced stage of the disease at diagnosis. Hence, identification of a novel and cost-effective biomarker signature for early detection/diagnosis of PDAC could lead to better survival outcomes. Untargeted metabolomics was employed to identify a novel metabolite-based biomarker signature for PDAC diagnosis. Urinary metabolites from 92 PDAC patients (56 discovery cohort and 36 validation cohort) were compared with 56 healthy volunteers using 1 H nuclear magnetic resonance spectroscopy. Multivariate (partial-least squares discriminate analysis) and univariate (Mann-Whitney's U-test) analyses were performed to identify a metabolite panel which can be used to detect PDAC. The selected metabolites were further validated for their diagnostic potential using the area under the receiver operating characteristic (AUROC) curve. Statistical analysis identified a six-metabolite panel (trigonelline, glycolate, hippurate, creatine, myoinositol and hydroxyacetone), which demonstrated high potential to diagnose PDAC, with AUROC of 0.933 and 0.864 in the discovery and validation cohort, respectively. Notably, the identified panel also demonstrated very high potential to diagnose early-stage (I and II) PDAC patients with AUROC of 0.897. These results demonstrate that the selected metabolite signature could be used to detect PDAC and will pave the way for the development of a urinary test for detection/diagnosis of PDAC.

A combination of urinary biomarker panel and PancRISK score for earlier detection of pancreatic cancer: A case-control study.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with around 9% of patients surviving >5 years. Asymptomatic in its initial stages, PDAC is mostly diagnosed late, when already a locally advanced or metastatic disease, as there are no useful biomarkers for detection in its early stages, when surgery can be curative. We have previously described a promising biomarker panel (LYVE1, REG1A, and TFF1) for earlier detection of PDAC in urine. Here, we aimed to establish the accuracy of an improved panel, including REG1B instead of REG1A, and an algorithm for data interpretation, the PancRISK score, in additional retrospectively collected urine specimens. We also assessed the complementarity of this panel with CA19-9 and explored the daily variation and stability of the biomarkers and their performance in common urinary tract cancers. METHODS AND FINDINGS: Clinical specimens were obtained from multiple centres: Barts Pancreas Tissue Bank, University College London, University of Liverpool, Spanish National Cancer Research Center, Cambridge University Hospital, and University of Belgrade. The biomarker panel was assayed on 590 urine specimens: 183 control samples, 208 benign hepatobiliary disease samples (of which 119 were chronic pancreatitis), and 199 PDAC samples (102 stage I-II and 97 stage III-IV); 50.7% were from female individuals. PDAC samples were collected from patients before treatment. The samples were assayed using commercially available ELISAs. Statistical analyses were performed using non-parametric Kruskal-Wallis tests adjusted for multiple comparisons, and multiple logistic regression. Training and validation datasets for controls and PDAC samples were obtained after random division of the whole available dataset in a 1:1 ratio. The substitution of REG1A with REG1B enhanced the performance of the panel to detect resectable PDAC. In a comparison of controls and PDAC stage I-II samples, the areas under the receiver operating characteristic curve (AUCs) increased from 0.900 (95% CI 0.843-0.957) and 0.926 (95% CI 0.843-1.000) in the training (50% of the dataset) and validation sets, respectively, to 0.936 in both the training (95% CI 0.903-0.969) and the validation (95% CI 0.888-0.984) datasets for the new panel including REG1B. This improved panel showed both sensitivity (SN) and specificity (SP) to be >85%. Plasma CA19-9 enhanced the performance of this panel in discriminating PDAC I-II patients from controls, with AUC = 0.992 (95% CI 0.983-1.000), SN = 0.963 (95% CI 0.913-1.000), and SP = 0.967 (95% CI 0.924-1.000). We demonstrate that the biomarkers do not show significant daily variation, and that they are stable for up to 5 days at room temperature. The main limitation of our study is the low number of stage I-IIA PDAC samples (n = 27) and lack of samples from individuals with hereditary predisposition to PDAC, for which specimens collected from control individuals were used as a proxy. CONCLUSIONS: We have successfully validated our urinary biomarker panel, which was improved by substituting REG1A with REG1B. At a pre-selected cutoff of >80% SN and SP for the affiliated PancRISK score, we demonstrate a clinically applicable risk stratification tool with a binary output for risk of developing PDAC ('elevated' or 'normal'). PancRISK provides a step towards precision surveillance for PDAC patients, which we will test in a prospective clinical study, UroPanc.

Urine metallomics signature as an indicator of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest types of cancer. Its high mortality rate is attributed largely to the difficulty of early diagnosis. Analysis of urine is an excellent non-invasive approach to trace changes in biochemical reactions due to cancer development. Here we show remarkable differences in concentration of several essential metals: significantly lower levels of urinary calcium and magnesium and increased levels of copper and zinc in PDAC when compared to healthy controls, and demonstrate that a combined analysis of these essential metals are accurate indicators (sensitivity = 99.5%) for metal dyshomeostasis in PDAC. In addition, natural stable zinc isotope composition (δ66/64Zn) in urine reveals the preferential excretion of isotopically light zinc in PDAC (δ66/64Znmedian = -0.15‰) compared to healthy controls (δ66/64Znmedian = +0.02‰), likely supporting the dysregulation of metalloproteins. These findings demonstrate for the first time that metallomics is a promising approach for discovery of biomarkers for detection of patients with PDAC, completely non-invasively, using urine samples.

Performance of candidate urinary biomarkers for pancreatic cancer - Correlation with pancreatic cyst malignant progression?

BACKGROUND: Intraductal papillary mucinous neoplasms (IPMN) are precursors of pancreatic cancer. Potential biomarkers of IPMN progression have not been identified in urine. A few urinary biomarkers were reported to be predictive of pancreatic ductal adenocarcinoma (PDAC). Here, we seek to assess their ability to detect high-risk IPMN. METHODS: Urine was collected from patients undergoing pancreatic resection and healthy controls. TIMP-1(Tissue Inhibitor of Metalloproteinase-1), LYVE-1(Lymphatic Vessel Endothelial Receptor 1), and PGEM(Prostaglandin E Metabolite) levels were determined by ELISA and analyzed by Kruskal-Wallis. RESULTS: Median urinary TIMP-1 levels were significantly lower in healthy controls (n = 9; 0.32 ng/mg creatinine) compared to PDAC (n = 13; 1.95) but not significantly different between low/moderate-grade (n = 20; 0.71) and high-grade/invasive IPMN (n = 20; 1.12). No significant difference in urinary LYVE-1 was detected between IPMN low/moderate (n = 16; 0.37 ng/mg creatinine) and high/invasive grades (n = 21; 0.09). Urinary PGEM levels were not significantly different between groups. CONCLUSIONS: Urinary TIMP-1, LYVE-1, and PGEM do not correlate with malignant potential of pancreatic cysts.

Development of PancRISK, a urine biomarker-based risk score for stratified screening of pancreatic cancer patients.

BACKGROUND: An accurate and simple risk prediction model that would facilitate earlier detection of pancreatic adenocarcinoma (PDAC) is not available at present. In this study, we compare different algorithms of risk prediction in order to select the best one for constructing a biomarker-based risk score, PancRISK. METHODS: Three hundred and seventy-nine patients with available measurements of three urine biomarkers, (LYVE1, REG1B and TFF1) using retrospectively collected samples, as well as creatinine and age, were randomly split into training and validation sets, following stratification into cases (PDAC) and controls (healthy patients). Several machine learning algorithms were used, and their performance characteristics were compared. The latter included AUC (area under ROC curve) and sensitivity at clinically relevant specificity. RESULTS: None of the algorithms significantly outperformed all others. A logistic regression model, the easiest to interpret, was incorporated into a PancRISK score and subsequently evaluated on the whole data set. The PancRISK performance could be even further improved when CA19-9, commonly used PDAC biomarker, is added to the model. CONCLUSION: PancRISK score enables easy interpretation of the biomarker panel data and is currently being tested to confirm that it can be used for stratification of patients at risk of developing pancreatic cancer completely non-invasively, using urine samples.

Utility of liquid biopsy using urine in patients with pancreatic ductal adenocarcinoma.

In recent years, liquid biopsy for blood and body fluid in cancer patients has attracted attention. However, there have been few reports of liquid biopsy focusing on urine of pancreatic ductal adenocarcinoma (PDAC). In 56 patients with PDAC, DNA was extracted from urine and plasma prior to treatment, and KRAS mutations were analyzed with droplet digital PCR to examine the mutation detection rate. Our study showed that KRAS mutations were found in 27 cases (48%) in urine and 27 cases (48%) in plasma. The detection rate of urine KRAS mutations varied by renal functions. The rates were 70% (14/20) and 36% (13/36) in the creatinine clearance rate (CCr) < 70 mL/min group and in the CCr ≥ 70 mL/min group, respectively (P = .024). Whereas, no influence of the CCr was observed in the detection rates of plasma KRAS mutations. The rates were 50% (10/20) and 47% (17/36) in cases with the CCr < 70 mL/min group and the CCr ≥ 70 mL/min group, respectively. Although the sample size was small, this study clearly indicated a new possibility of less invasive urine liquid biopsy in PDAC patients.

Nano-biotinylated liposome-based immunoassay for the ultrasensitive detection of protein biomarker in urine.

With the development of proteomics and the continuous discovery of biomarkers of trace proteins, it is important to accurately quantify low abundance protein, especially in urine for clinical diagnostics. In this paper, we reported a novel nano-biotinylated liposome-based immuno-loop-mediated isothermal amplification (LI-LAMP) for the ultrasensitive detection of REG1A (a biomarker for pancreatic ductal adenocarcinoma (PDAC) in urine) with high specificity. The detection range was 1µg/mL to 1fg/mL, with a detection limit of 1fg/mL, and no cross-reactivity was observed to occur in this assay. Compared with the amount of REG1A added, REG1A recovery using this method was 130% and 89%. Detection of REG1A concentrations using the LI-LAMP assay from real samples were in good agreement with those determined using ELISA, and relative deviations were not more than 10%. LI-LAMP shows good potential as a clinical diagnostic assay.

Urinary TIMP-1 and MMP-2 levels detect the presence of pancreatic malignancies.

BACKGROUND: A majority of patients with pancreatic malignancies, including both pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine tumours (pNETs), present with advanced disease due to a lack of specific symptoms and current diagnostic limitations, making this disease extremely difficult to detect. Our goal was to determine whether urinary matrix metalloproteases (uMMPs) and/or their endogenous inhibitors, urinary tissue inhibitor of metalloproteases (uTIMPs), could be detected in the urine of patients with pancreatic malignancies and whether they may serve as independent predictors of disease status. METHODS: Retrospective analyses of urine samples (n=139) from PDAC and pNET patients as well as age- and sex-matched controls were conducted. Urinary MMP-2 and uTIMP-1 levels were determined using ELISA and zymography. Biomarker expression in tumour and normal pancreatic tissues was analysed via immunohistochemistry (IHC). RESULTS: Multivariable logistic regression analyses indicated that, when controlling for age and sex, uMMP-2 (P<0.0001) and uTIMP-1 (P<0.0001) but not uMMP-9, were significant independent predictors for distinguishing between PDAC patients and healthy controls. Our data also indicated that uMMP-2 was an independent predictor of the presence of pNET. In addition, uTIMP-1 levels could differentiate the two cancer groups, PDAC and pNET, respectively. Immunohistochemistry analysis confirmed that MMP-2 and TIMP-1 protein expression is significantly upregulated in PDAC tissue compared with the normal pancreas. CONCLUSIONS: Taken together, our results suggest that the detection of uMMP-2 and uTIMP-1 may have diagnostic value in the detection of pancreatic malignancies and that uTIMP-1 may be useful in distinguishing between pancreatic adenocarcinoma and neuroendocrine tumours.

Pancreatic ductal adenocarcinoma is associated with a distinct urinary metabolomic signature.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with poor prognosis in part due to the lack of early detection and screening methods. Metabolomics provides a means for noninvasive screening of tumor-associated perturbations in cellular metabolism. METHODS: Urine samples of PDAC patients (n = 32), healthy age and gender-matched controls (n = 32), and patients with benign pancreatic conditions (n = 25) were examined using (1)H-NMR spectroscopy. Targeted profiling of spectra permitted quantification of 66 metabolites. Unsupervised (principal component analysis, PCA) and supervised (orthogonal partial-least squares discriminant analysis, OPLS-DA) multivariate pattern recognition techniques were applied to discriminate between sample spectra using SIMCA-P(+) (version 12, Umetrics, Sweden). RESULTS: Clear distinction between PDAC and controls was noted when using OPLS-DA. Significant differences in metabolite concentrations between cancers and controls (p < 0.001) were noted. Model parameters for both goodness of fit, and predictive capability were high (R (2) = 0.85; Q (2) = 0.59, respectively). Internal validation methods were used to confirm model validity. Sensitivity and specificity of the multivariate OPLS-DA model were summarized using a receiver operating characteristics (ROC) curve, with an area under the curve (AUROC) = 0.988, indicating strong predictive power. Preliminary analysis revealed an AUROC = 0.958 for the model of benign pancreatic disease compared with PDAC, and suggest that the cancer-associated metabolomic signature dissipates following RO resection. CONCLUSIONS: Urinary metabolomics detected distinct differences in the metabolic profiles of pancreatic cancer compared with healthy controls and benign pancreatic disease. These preliminary results suggest that metabolomic approaches may facilitate discovery of novel pancreatic cancer biomarkers.

Urine metabolic signature of pancreatic ductal adenocarcinoma by (1)h nuclear magnetic resonance: identification, mapping, and evolution.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis and is highly chemoresistant. Early detection is the only means to impact long-term survival, but screening methods are lacking. Given the complex and heterogeneous nature of pancreatic cancer, unbiased analytical methods such as metabolomics by nuclear magnetic resonance (NMR) spectroscopy show promise to identify disease-specific molecular fingerprints. NMR profiles constitute a fingerprint of the biofluid, reporting quantitatively on all detectable small biomolecules. NMR spectroscopy was applied to investigate the urine metabolome of PDAC patients (n = 33) and to detect altered metabolic profiles in comparison with healthy matched controls (n = 54). The spectral data were analyzed using multivariate statistical techniques. Statistically significant differences were found between urine metabolomic profiles of PDAC and control individuals (p < 10(-5)). Group discrimination was possible due to average concentration differences of several metabolite signals, pointing to a multimolecular signature of the disease. The robustness of the determined statistical model is confirmed by its predictive performance (sensitivity = 75.8%, specificity = 90.7%). Additionally, the method allowed for a neat separation between spectral profiles of individuals with intermediate and advanced pathologic staging, as well as for the discrimination of samples based on tumor localization. NMR spectroscopy analysis of urinary metabolic profiles proved successful in identifying a complex molecular signature of PDAC. Furthermore, results of a descriptive-level analysis show the possibility to follow disease evolution and to carry out tumor site mapping. Given the high reproducibility and the noninvasive nature of the analytical procedure, the described method bears potential to impact large-scale screening programs.

Elevated urinary levels of urokinase-type plasminogen activator receptor (uPAR) in pancreatic ductal adenocarcinoma identify a clinically high-risk group.

BACKGROUND: The urokinase plasminogen activator receptor is highly expressed and its gene is amplified in about 50% of pancreatic ductal adenocarcinomas; this last feature is associated with worse prognosis. It is unknown whether the level of its soluble form (suPAR) in urine may be a diagnostic-prognostic marker in these patients. METHODS: The urinary level of suPAR was measured in 146 patients, 94 pancreatic ductal adenocarcinoma and 52 chronic pancreatitis. Urine from 104 healthy subjects with similar age and gender distribution served as controls. suPAR levels were normalized with creatinine levels (suPAR/creatinine, ng/mg) to remove urine dilution effect. RESULTS: Urinary suPAR/creatinine values of pancreatic ductal adenocarcinoma patients were significantly higher (median 9.8; 25th-75th percentiles 5.3-20.7) than those of either healthy donors (median 0; 0-0.5) or chronic pancreatitis patients (median 2.7; 0.9-4.7). The distribution of values among cancer patients was widespread and asymmetric, 53% subjects having values beyond the 95th percentile of healthy donors. The values of suPAR/creatinine did not correlate with tumour stage, Ca19-9 or CEA levels. Higher values correlated with poor prognosis among non-resected patients at univariate analysis; multivariate Cox regression identified high urinary suPAR/creatinine as an independent predictor of poor survival among all cancer patients (odds ratio 2.10, p = 0.0023), together with tumour stage (stage III odds ratio 2.65, p = 0.0017; stage IV odds ratio 4.61, p < 0.0001) and female gender (odds ratio 1.85, p = 0.01). CONCLUSIONS: A high urinary suPAR/creatinine ratio represents a useful marker for the identification of a subset of patients with poorer outcome.