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.

Effect of Lanreotide Depot/Autogel on Urinary 5-Hydroxyindoleacetic Acid and Plasma Chromogranin A Biomarkers in Nonfunctional Metastatic Enteropancreatic Neuroendocrine Tumors.

BACKGROUND: Urinary 5-hydroxyindoleacetic acid (5-HIAA) is an established biomarker in neuroendocrine tumors and carcinoid syndrome; however, its role in nonfunctional neuroendocrine tumors is not defined. We present post hoc data on urinary 5-HIAA and plasma chromogranin A (CgA) from the CLARINET study. METHODS: Patients with well- or moderately differentiated, nonfunctioning, locally advanced or metastatic enteropancreatic neuroendocrine tumors were randomized to deep subcutaneous lanreotide depot/autogel 120 mg or placebo once every 28 days for 96 weeks. Tumor response, evaluated centrally (RECIST 1.0), and progression-free survival (PFS) were assessed by treatment and biochemical response, defined as (a) baseline >upper limit of normal (ULN, 41.6 µmol per day 5-HIAA; 98.1 µg/L CgA) and (b) ≥50% decrease from baseline and to ≤ULN value on study. RESULTS: Forty-eight percent (82 of 171; lanreotide, n = 45; placebo, n = 37) and 66% (129 of 195; lanreotide, n = 65; placebo, n = 64) of randomized patients had 5-HIAA and CgA > ULN at baseline. Among patients with >ULN baseline values who did not progress after 96 weeks of treatment, significantly greater reductions in 5-HIAA and CgA were observed in lanreotide-treated versus placebo-treated patients throughout the study (all p < .05). PFS was significantly prolonged among 5-HIAA responders versus nonresponders (median not reached vs. 16.2 months, p < .0001; hazard ratio [HR] = 0.21, 95% confidence interval [CI], 0.09-0.48) and CgA responders versus nonresponders (median not reached vs. 16.2 months, p = .0070; HR = 0.30, 95% CI, 0.12-0.76), regardless of treatment arm. PFS was also significantly prolonged among lanreotide-treated 5-HIAA responders versus nonresponders (p = .0071) but was not significantly different among placebo-treated 5-HIAA responders versus nonresponders. There were no significant differences in PFS between lanreotide-treated CgA responders versus nonresponders or between placebo-treated CgA responders versus nonresponders. CONCLUSIONS: The 5-HIAA findings are noteworthy because they occurred in patients with nonfunctioning enteropancreatic neuroendocrine tumors. Monitoring 5-HIAA and CgA may be useful when treating patients with nonfunctional neuroendocrine tumors. IMPLICATIONS FOR PRACTICE: Current guidelines focus only on the monitoring of 5-hydroxyindoleacetic acid (5-HIAA) in the diagnosis and management of functional neuroendocrine tumors with carcinoid syndrome. The current post hoc analysis of patients with nonfunctional enteropancreatic neuroendocrine tumors in the CLARINET study demonstrated that measuring and following both 5-HIAA and chromogranin A as biomarkers of disease progression may be useful in the management of patients with nonfunctional neuroendocrine tumors.

Detection of Pancreatic Cancer by Urine Volatile Organic Compound Analysis.

BACKGROUND/AIM: Most pancreatic cancer patients are diagnosed at an advanced stage, since the diagnosis is demanding. Field asymmetric waveform ion mobility spectrometry (FAIMS) is a sensitive technique used for the detection of volatile organic compounds (VOC). We evaluated the ability of FAIMS to discriminate between pancreatic cancer and healthy controls from a urine sample. PATIENTS AND METHODS: For a proof-of-concept study in three Finnish hospitals, 68 patients with pancreatic cancer, 36 with acute pancreatitis, 18 with chronic pancreatitis, 8 with pancreatic pre-malign lesions and 52 healthy controls were prospectively recruited. Urine samples were collected at the time of diagnosis and stored at -70°C. The samples were subsequently measured with FAIMS. The data were processed with linear discriminant analysis and cross-validated with leave-one-out cross-validation. RESULTS: FAIMS distinguished pancreatic cancer from controls with a sensitivity of 79% and specificity of 79%. CONCLUSION: As a non-invasive and rapid urine test, FAIMS can discriminate patients with pancreatic cancer from healthy controls.

Prognostic Utility of 24-Hour Urinary 5-HIAA Doubling Time in Patients With Neuroendocrine Tumors.

OBJECTIVE: New clinical prognostic tools are needed to select the population of patients with neuroendocrine tumors (NETs) that have a high risk of disease progression and disease-specific mortality (DSM). Biochemical biomarker doubling time (DT) is used clinically for prognosis prediction in several solid malignancies. The aim of the current study was to determine whether 24-hour urinary 5-hydroxyindoleacetic acid (5-HIAA) level DT has any prognostic utility in patients with NETs. METHODS: Patients with NETs were enrolled in a prospective study with comprehensive biochemical analysis. The current analysis included 90 subjects with increasing 5-HIAA levels in two consecutive measurements. DT was calculated using the Schwartz equation. The primary outcome measures were DSM and disease progression. RESULTS: 5-HIAA DT of <434 days was associated with a higher rate of DSM ( P = .02), with positive and negative predictive values for DSM of 75 and 77%, respectively. The difference in DSM was accounted for mainly by patients with small intestine or unknown primary NET ( P = .01). In addition, a shorter 5-HIAA DT in patients with small intestine or unknown primary NET was associated with a higher risk of disease progression both in univariate ( P = .001) and multivariable analyses (hazard ratio, 15.8; 95% confidence interval, 1.3 to 198.0; P = .03). CONCLUSION: 5-HIAA DT may be used as a risk stratification tool in patients with small intestine NET or NET of unknown primary after it is validated in an independent cohort and can assist in identifying patients with a high risk for disease progression and DSM. ABBREVIATIONS: CT = computed tomography; DSM = disease-specific mortality; DT = doubling time; 5-HIAA = 5-hydroxyindoleacetic acid; MRI = magnetic resonance imaging; NET = neuroendocrine tumor; NETUP = neuroendocrine tumor of unknown primary; PET = positron emission tomography; PFS = progression-free survival; PNET = pancreatic neuroendocrine tumor; ROC = receiver operating characteristic; SINET = small-intestine neuroendocrine tumor.

NMR-based metabolic profiling of urine, serum, fecal, and pancreatic tissue samples from the Ptf1a-Cre; LSL-KrasG12D transgenic mouse model of pancreatic cancer.

Pancreatic cancer is the third leading cause of cancer deaths in the United States with more than 53,000 expected to be diagnosed with the disease in 2018. The median survival time after diagnosis is four to six months. The poor survival statistics are due in part to the fact that pancreatic cancer is typically asymptomatic until it reaches advanced stages of the disease. Although surgical resection provides the best chance of survival, pancreatic cancer is rarely detected when surgery is still possible due, in part, to lack of effective biomarkers for early detection. The goal of the research reported here was to determine if it was possible to identify metabolic biomarkers for detection of pre-cancerous pancreatic intraepithelial neoplasia (PanIN) that precede pancreatic adenocarcinoma. The transgenic Ptf1a-Cre; LSL-KrasG12D mouse strain was used as a model of pancreatic cancer progression. Nuclear magnetic resonance (NMR) spectroscopy was employed to compare metabolic profiles of urine, sera, fecal extracts, and pancreatic tissue extracts collected from control and study mice aged 5, 11, and 15 months, including 47 mice with tumors. We were able to identify the following potential biomarkers: decreased 3-indoxylsulfate, benzoate and citrate in urine, decreased glucose, choline, and lactate in blood, and decreased phenylalanine and benzoate and increased acetoin in fecal extracts. Potential biomarkers were validated by p-values, PLS-DA VIP scores, and accuracies based on area under ROC curve analyses. Essentially, all of the metabolic profiling changes could be explained as being associated with the consequences of bicarbonate wasting caused by a complete substitution of the normal pancreatic acinar tissue by tissue entirely composed of PanIN. Given the nature of the mouse model used here, our results indicate that it may be possible to use NMR-based metabolic profiling to identify biomarkers for detection of precancerous PanIN that immediately precede pancreatic cancer.

Urinary CE-MS peptide marker pattern for detection of solid tumors.

Urinary profiling datasets, previously acquired by capillary electrophoresis coupled to mass-spectrometry were investigated to identify a general urinary marker pattern for detection of solid tumors by targeting common systemic events associated with tumor-related inflammation. A total of 2,055 urinary profiles were analyzed, derived from a) a cancer group of patients (n = 969) with bladder, prostate, and pancreatic cancers, renal cell carcinoma, and cholangiocarcinoma and b) a control group of patients with benign diseases (n = 556), inflammatory diseases (n = 199) and healthy individuals (n = 331). Statistical analysis was conducted in a discovery set of 676 cancer cases and 744 controls. 193 peptides differing at statistically significant levels between cases and controls were selected and combined to a multi-dimensional marker pattern using support vector machine algorithms. Independent validation in a set of 635 patients (293 cancer cases and 342 controls) showed an AUC of 0.82. Inclusion of age as independent variable, significantly increased the AUC value to 0.85. Among the identified peptides were mucins, fibrinogen and collagen fragments. Further studies are planned to assess the pattern value to monitor patients for tumor recurrence. In this proof-of-concept study, a general tumor marker pattern was developed to detect cancer based on shared biomarkers, likely indicative of cancer-related features.