Elevated Urinary Levels of Fungal and Environmental Toxins in Patients with Pancreatic Ductal Adenocarcinoma.

BACKGROUND: Risk factors for pancreatic ductal adenocarcinoma (PDAC) include tobacco/alcohol abuse, genetic predisposition, insulin resistance, and pancreatic cysts. Despite these well-established risk factors and the screening of high-risk individuals, some people still develop PDAC. This study aims to explore a potential risk factor for PDAC by investigating the association between fungal toxins (FT) and environmental toxins (ET) and the disease. We predicted that individuals with PDAC would have higher levels of these toxins compared to healthy controls. The rationale behind this hypothesis is that exposure to FT and ET might contribute to the development of PDAC by elevating cancer risk. METHODS: A pilot retrospective cohort study was conducted at Moffitt Cancer Center from 2022 to 2023. This study compared FT and ET levels, demographic data, and PDAC features between subjects with PDAC and healthy controls. RESULTS: Forty subjects were enrolled in the study, comprising 20 with pancreatic ductal adenocarcinoma (PDAC) and 20 healthy controls. Baseline demographics were similar between the two groups. Among the PDAC subjects, the most common tumor location was the head of the pancreas (55%); 30% had locally advanced disease, 45% were borderline resectable, and 10% had metastatic disease. Compared to the controls, subjects with PDAC had significantly higher levels of fungal toxins (FTs) including ochratoxin, gliotoxin, and citrinin (p < 0.05). Additionally, PDAC patients had significantly elevated levels of environmental toxins (ETs) such as methyl tert-butyl ether (MTBE), xylene, styrene, acrylonitrile, perchlorate, diphenyl phosphate, bromopropane, organophosphates, acrolein, tiglylglycine, and diethylphosphate (p < 0.05). CONCLUSION: Our study demonstrates that subjects with PDAC, without other risk factors, have higher FT and ET levels than controls. Further studies are needed to evaluate whether ET and FT exposure can be clinically utilized as a risk factor for PDAC development.

Urinary biomarkers analysis as a diagnostic tool for early detection of pancreatic adenocarcinoma: Molecular quantification approach.

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

Association between pancreatic adenocarcinoma risk and concentration of organochlorine pesticides in adipose tissue and urine: A targeted-screening analysis case-control study (PESTIPAC).

BACKGROUND: Knowledge about environmental pancreatic adenocarcinoma (PA) risk factors, including pesticide exposure, remains limited. Organochlorine (OC) accumulates in adipose tissue and can help reflect long-term exposure. PATIENTS AND METHODS: Age and body mass index (BMI) of patients with PA were matched with those undergoing a surgery for a benign disease on age and BMI (1:1). Targeted analyses screened 345 pesticides and metabolites, including 29 OC, in adipose tissue and urine samples. The primary aim was to investigate the association between organochlorine concentrations in visceral fat or urine, and PA. Adjusted conditional logistic regressions were carried out accounting for multiple testing. RESULTS: Trans-nonachlor (odds ratio [OR] = 1.325, 95% confidence interval [CI] [1.108-1.586]), cis-nonachlor (OR = 15.433, 95% CI [2.733-87.136]), Mirex (OR = 2.853, 95% CI [1.213-6.713]) and 4,4 DDE (OR = 1.019, 95% CI [1.005-1.034]) in fat and a greater number of positive samples (OR = 1.758 95% CI [1.11-2.997]) were significantly associated with higher odds of PA. In contrast, as awaited, urine samples did not yield any statistically significant associations for all tested pesticides. CONCLUSION: Some OCs were associated with higher odds of PA. The underlying mechanisms of pancreatic aggression need to be investigated to refine these findings. TRIAL REGISTRATION: Clinicaltrials.gov NCT04429490.

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.

24-Hour Urinary Sodium Excretion Is Associated With Increased Risk of Pancreatic Cancer: A Prospective Cohort Study.

INTRODUCTION: This study builds on previous research and its limitations, which indicate the need for further investigation in prospective cohorts. Our aim was to explore the association between estimated 24-hour urinary sodium excretion (indicative of daily sodium consumption) and the occurrence of pancreatic cancer in the UK Biobank's large prospective cohort. METHODS: Using the INTERSALT equation, the study computed estimated 24-hour urinary sodium excretion by analyzing the baseline spot urine sodium measurements of 434,372 individuals enrolled in the UK Biobank. Pancreatic cancer cases were identified through UK cancer registries. Adjusted Cox proportional hazards models were used to evaluate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between estimated 24-hour urinary sodium excretion and the risk of pancreatic cancer. RESULTS: Over a median follow-up period of 13.8 years, 1,765 cases of pancreatic cancer were detected. The multivariable adjusted Cox model showed that each 1-gram rise in estimated 24-hour urinary sodium excretion corresponded to a 1.12 HR for incident pancreatic cancer (95% CI: 1.03, 1.22). The estimated HR for 24-hour urinary sodium excretion in binary form was 1.23 (95% CI: 1.05, 1.44). Compared with the lowest group, the group with the highest estimated 24-hour urinary sodium excretion exhibited an HR of 1.38 (95% CI: 1.21, 1.58). DISCUSSION: These results propose an association between elevated sodium consumption and a heightened risk of pancreatic cancer. Further validation and exploration of potential mechanisms are warranted.

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.

Analysis of urinary potassium isotopes and association with pancreatic health: healthy, diabetic and cancerous states.

Background: More than 700 million people worldwide suffer from diseases of the pancreas, such as diabetes, pancreatitis and pancreatic cancer. Often dysregulation of potassium (K+) channels, co-transporters and pumps can promote development and progression of many types of these diseases. The role of K+ transport system in pancreatic cell homeostasis and disease development remains largely unexplored. Potassium isotope analysis (δ41K), however, might have the potential to detect minute changes in metabolic processes relevant for pancreatic diseases. Methods: We assessed urinary K isotope composition in a case-control study by measuring K concentrations and δ41K in spot urines collected from patients diagnosed with pancreatic cancer (n=18), other pancreas-related diseases (n=14) and compared those data to healthy controls (n=16). Results: Our results show that urinary K+ levels for patients with diseased pancreas (benign and pancreatic cancer) are significantly lower than the healthy controls. For δ41K, the values tend to be higher for individuals with pancreatic cancer (mean δ41K = -0.58 ± 0.33‰) than for healthy individuals (mean δ41K = -0.78 ± 0.19‰) but the difference is not significant (p=0.08). For diabetics, urinary K+ levels are significantly lower (p=0.03) and δ41K is significantly higher (p=0.009) than for the healthy controls. These results suggest that urinary K+ levels and K isotopes can help identify K disturbances related to diabetes, an associated factors of all-cause mortality for diabetics. Conclusion: Although the K isotope results should be considered exploratory and hypothesis-generating and future studies should focus on larger sample size and δ41K analysis of other K-disrupting diseases (e.g., chronic kidney disease), our data hold great promise for K isotopes as disease marker.

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.

Caenorhabditis elegans as a Diagnostic Aid for Pancreatic Cancer.

OBJECTIVES: Early detection of pancreatic cancer is notoriously difficult. A novel cancer diagnostic method using the ability of nematodes to detect odor of urine samples has been developed (N-NOSE). This method has a high sensitivity and specificity for various cancers; however, it has not yet been verified in pancreatic cancer. We examined the usefulness of this method to aid early diagnosis of pancreatic cancer in a cancer center. METHODS: We collected urine samples and clinical data from patients hospitalized in our division, between July 2017 and February 2019. We excluded patients with a known current or past history of other cancers. We investigated the relationship between the results of N-NOSE and the presence of pancreatic cancer. RESULTS: There were 95 noncancer cases and 104 pancreatic cancer cases. The sensitivity and specificity of N-NOSE for pancreatic cancer were 84.6% (88/104) and 60% (57/95), respectively. N-NOSE was able to detect stages 0 to I pancreatic cancer and had a higher correlation with early-stage pancreatic cancer than advanced stage. CONCLUSIONS: N-NOSE has sufficient sensitivity and specificity for use in clinical practice, and it holds great potential as a diagnostic aid for pancreatic cancer, especially for early-stage pancreatic cancer.

Zinc stable isotopes in urine as diagnostic for cancer of secretory organs.

Breast, prostate, and pancreatic cancers alter the zinc (Zn) metabolism. Combined analyses of urinary Zn concentrations [Zn] and Zn stable isotope compositions (δ66Zn) may provide a non-invasive approach for tracing malignancy-induced Zn dyshomeostasis. In this study, we measured [Zn] and δ66Zn in urine from prostate (n = 22), breast (n = 16), and from women with benign breast disease (n = 14) and compared those with age-matched healthy controls (22-49 years or 50+ years) and published data for pancreatic cancer (n = 17). Our results show that cancer-induced changes are reflected in higher urinary [Zn] and lower urinary δ66Zn for pancreatic and prostate cancer and benign breast disease when compared with healthy controls. For prostate cancer, the progression of low [Zn] and high δ66Zn for patients of low-risk disease toward high [Zn] and low δ66Zn for the higher risk patients demonstrates that [Zn] and δ66Zn in urine could serve as a reliable prognostic tool. Urinary excretion of isotopically light Zn by patients with prostatic and pancreatic cancer is probably the result of increased reactive oxygen species in cancerous cells, which limits the scavenging of hydroxyl radicals and thus facilitates the oxidation of metalloproteins with sulfur-rich ligands. Urine from breast cancer patients shows undistinguishable δ66Zn to healthy controls, implying that the expression of metalloproteins with sulfur-rich ligands is stronger in breast cancer tissues. In conclusion, urinary δ66Zn may provide a non-invasive diagnostic tool for pancreatic cancer and support disease prognosis for prostate cancer. These findings should translate to comprehensive transverse and longitudinal cohort studies in future.

Urinary Metabolic Biomarkers in Cancer Patients: An Overview.

The pathogenesis of cancer involves multiple molecular alterations at the level of genome, epigenome, and stromal environment, resulting in several deregulated signal transduction pathways. Metabolites are not only end products of gene and protein expression but also a consequence of the mutual relationship between the genome and the internal environment. Considering that metabolites serve as a comprehensive chemical fingerprint of cell metabolism, metabolomics is emerging as the method able to discover metabolite biomarkers that can be developed for early cancer detection, prognosis, and response to treatment. Urine represents a noninvasive source, available and rich in metabolites, useful for cancer diagnosis, prognosis, and treatment monitoring. In this chapter, we reported the main published evidences on urinary metabolic biomarkers in the studied cancers related to hepatopancreatic and urinary tract with the aim at discussing their promising role in clinical practice.

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.

Sensitive mass spectrometric analysis of carbonyl metabolites in human urine and fecal samples using chemoselective modification.

Metabolites with ketone or aldehyde functionalities comprise a large proportion of the human metabolome, most notably in the form of sugars. However, these reactive molecules are also generated through oxidative stress or gut microbiota metabolism and have been linked to disease development. The discovery and structural validation of this class of metabolites over the large concentration range found in human samples is crucial to identify their links to pathogenesis. Herein, we have utilized an advanced chemoselective probe methodology alongside bioinformatic analysis to identify carbonyl-metabolites in urine and fecal samples. In total, 99 metabolites were identified in urine samples and the chemical structure for 40 metabolites were unambiguously validated using a co-injection procedure. We also describe the preparation of a metabolite-conjugate library of 94 compounds utilized to efficiently validate these ketones and aldehydes. This method was used to validate 33 metabolites in a pooled fecal sample extract to demonstrate the potential for rapid and efficient metabolite detection over a wide metabolite concentration range. This analysis revealed the presence of six metabolites that have not previously been detected in either sample type. The constructed library can be utilized for straightforward, large-scale, and expeditious analysis of carbonyls in any sample type.

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.

Effects of Alkalization Therapy on Chemotherapy Outcomes in Metastatic or Recurrent Pancreatic Cancer.

BACKGROUND/AIM: The acidic tumor microenvironment is associated both with the progression and drug resistance of cancer. We aimed to investigate the effects of alkalization therapy performed concurrently with chemotherapy on the survival of advanced pancreatic cancer patients (study registration: UMIN 000035659). PATIENTS AND METHODS: Twenty-eight patients with metastatic or recurrent pancreatic cancer were assessed in this study. Alkalization therapy consisted of an alkaline diet with supplementary oral sodium bicarbonate (3.0-5.0 g/day). RESULTS: The mean urine pH was significantly higher after the alkalization therapy (6.85±0.74 vs. 6.39±0.92; p<0.05). The median overall survival from the start of alkalization therapy of the patients with high urine pH (>7.0) was significantly longer than those with low urine pH (≤ 7.0) (16.1 vs. 4.7 months; p<0.05). CONCLUSION: An alkalization therapy may be associated with better outcomes in advanced pancreatic cancer patients treated with chemotherapy.

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.

[Determination of thresholds values for platelet serotonin and urinary 5-HIAA concentrations for the biological diagnosis of digestive neuroendocrine tumors]. / Quelles valeurs de référence pour la concentration de la sérotonine plaquettaire et du 5-HIAA urinaire pour le diagnostic des tumeurs neuroendocrines digestives ?

OBJECTIVES: Platelet serotonin and its urinary metabolite 5-HIAA (5-hydroxyindolacetic acid) are the main biomarkers measured for the detection of neuroendocrine tumors (NET). We observe in our laboratory many false positives or false negatives for the 2 assays using threshold values given by the manufacturer. We aim to determine our own local threshold values for a better detection of gastrointestinal NETs. METHODS: We studied patients with measurement of platelet serotonin and/or urinary 5-HIAA in University Hospital of Tours between January 2005 and June 2016. We established an « index ¼ cohort with 75% of patients to determine local threshold value for the 2 parameters. A "validation" cohort constituted with 25% of remaining patients allowed us to compare the performances of manufacturer's values with local threshold values. RESULTS: Two hundred ninety patients were included, with 19 suffering from NETs. Local threshold value for platelet serotonin was determined at 5.13 amol/platelet, the one for urinary 5-HIAA at 3.60 µmol/mmol urinary creatinine. Platelet serotonin specificity was better with local threshold value for identical sensibility (0.75). Urinary 5-HIAA sensibility was improved with local threshold value (1 vs 0.667) for identical specificity (0.902). CONCLUSION: Using our local threshold value for platelet serotonin and urinary 5-HIAA improved diagnostic performances of these biochemical markers to detect NETs.

Pancreatic cancer biomarker detection by two support vector strategies for recursive feature elimination.

AIM: Pancreatic cancer is one of the worst malignant tumors in prognosis. Therefore, to reduce the mortality rate of pancreatic cancer, early diagnosis and prompt treatment are particularly important. RESULTS: We put forward a new feature-selection method that was used to find clinical markers for pancreatic cancer by combination of Support Vector Machine Recursive Feature Elimination (SVM-RFE) and Large Margin Distribution Machine Recursive Feature Elimination (LDM-RFE) algorithms. As a result, seven differentially expressed genes were predicted as specific biomarkers for pancreatic cancer because of their highest accuracy of classification on cancer and normal samples. CONCLUSION: Three (MMP7, FOS and A2M) out of the seven predicted gene markers were found to encode proteins secreted into urine, providing potential diagnostic evidences for pancreatic cancer.