Benign Hepatobiliary Diseases Research Articles

Data privacy-aware machine learning approach in pancreatic cancer diagnosis

ProblemPancreatic ductal adenocarcinoma (PDAC) is considered a highly lethal cancer due to its advanced stage diagnosis. The five-year survival rate after diagnosis is less than 10%. However, if diagnosed early, the five-year survival rate can reach up to 70%. Early diagnosis of PDAC can aid treatment and improve survival rates by taking necessary precautions. The challenge is to develop a reliable, data privacy-aware machine learning approach that can accurately diagnose pancreatic cancer with biomarkers.AimThe study aims to diagnose a patient’s pancreatic cancer while ensuring the confidentiality of patient records. In addition, the study aims to guide researchers and clinicians in developing innovative methods for diagnosing pancreatic cancer.MethodsMachine learning, a branch of artificial intelligence, can identify patterns by analyzing large datasets. The study pre-processed a dataset containing urine biomarkers with operations such as filling in missing values, cleaning outliers, and feature selection. The data was encrypted using the Fernet encryption algorithm to ensure confidentiality. Ten separate machine learning models were applied to predict individuals with PDAC. Performance metrics such as F1 score, recall, precision, and accuracy were used in the modeling process.ResultsAmong the 590 clinical records analyzed, 199 (33.7%) belonged to patients with pancreatic cancer, 208 (35.3%) to patients with non-cancerous pancreatic disorders (such as benign hepatobiliary disease), and 183 (31%) to healthy individuals. The LGBM algorithm showed the highest efficiency by achieving an accuracy of 98.8%. The accuracy of the other algorithms ranged from 98 to 86%. In order to understand which features are more critical and which data the model is based on, the analysis found that the features “plasma_CA19_9”, REG1A, TFF1, and LYVE1 have high importance levels. The LIME analysis also analyzed which features of the model are important in the decision-making process.ConclusionsThis research outlines a data privacy-aware machine learning tool for predicting PDAC. The results show that a promising approach can be presented for clinical application. Future research should expand the dataset and focus on validation by applying it to various populations.

Serum ITIH5 as a novel diagnostic biomarker in cholangiocarcinoma.

Cholangiocarcinoma often remains undetected until advanced stages due to the lack of reliable diagnostic markers. Our goal was to identify a unique secretory protein for cholangiocarcinoma diagnosis and differentiation from other malignancies, benign hepatobiliary diseases, and chronic liver conditions. We conducted bulk RNA-seq analysis to identify genes specifically upregulated in cholangiocarcinoma but not in most other cancers, benign hepatobiliary diseases, and chronic liver diseases focusing on exocrine protein-encoding genes. Single-cell RNA sequencing examined subcellular distribution. Immunohistochemistry and enzyme-linked immunosorbent assays assessed tissue and serum expression. Diagnostic performance was evaluated via receiver-operating characteristic (ROC) analysis. Inter-alpha-trypsin inhibitor heavy chain family member five (ITIH5), a gene encoding an extracellular protein, is notably upregulated in cholangiocarcinoma. This elevation is not observed in most other cancer types, benign hepatobiliary diseases, or chronic liver disorders. It is specifically expressed by malignant cholangiocytes. ITIH5 expression in cholangiocarcinoma tissues exceeded that in nontumorous bile duct, hepatocellular carcinoma, and nontumorous hepatic tissues. Serum ITIH5 levels were elevated in cholangiocarcinoma compared with controls (hepatocellular carcinoma, benign diseases, chronic hepatitis B, and healthy individuals). ITIH5 yielded areas under the ROC curve (AUCs) from 0.839 to 0.851 distinguishing cholangiocarcinoma from controls. Combining ITIH5 with carbohydrate antigen 19-9 (CA19-9) enhanced CA19-9's diagnostic effectiveness. In conclusion, serum ITIH5 may serve as a novel noninvasive cholangiocarcinoma diagnostic marker.

Evaluation of urinary C-reactive protein as an early detection biomarker for pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death worldwide. Up to now, no specific screening or diagnostic tests are available for early PDAC detection. As a result, most patients are diagnosed with advanced or metastatic disease, which leads to a poor prognosis. In this study, we aimed to evaluate the diagnostic value of urinary CRP (uCRP) alone and in combination with our previously established urine biomarker panel (REG1B, LYVE1 and TFF1) for early detection of PDAC. A total of 534 urine samples from multiple centres were analysed: 93 from healthy individuals, 265 from patients with benign hepatobiliary diseases and 176 from PDAC patients. The uCRP and the urinary biomarker panel were assessed using commercial ELISA assays, while plasma CA19-9 and blood CRP (bCRP) were measured using Roche Cobas platform. Multiple logistic regression and nonparametric Kruskal-Wallis test were used for statistical analysis. An internal validation approach was applied, and the validated AUC estimators were reported to ensure accuracy. A significant difference was observed in the medians of uCRP between healthy and benign controls and PDAC sample groups (p < 0.001). uCRP levels were not dependent on gender and age, as well as cancer stage. When uCRP was combined with the urinary biomarker panel, it achieved AUCs of 0.878 (95% CI: 0.802-0.931), 0.798 (95% CI: 0.738-0.859) and 0.813 (95% CI: 0.758-0.869) in healthy vs PDAC, benign vs PDAC and healthy and benign vs PDAC sample groups, respectively. However, adding plasma CA19-9 to the urinary biomarker panel yielded a better performance, with AUCs of 0.978 (95% CI: 0.959-0.996), 0.911 (95% CI: 0.873-0.949) and 0.919 (95% CI: 0.883-0.955) in the healthy vs PDAC, benign vs PDAC and healthy and benign vs PDAC comparisons, respectively. In conclusion, we show that measuring CRP in urine is a feasible analytical method, and that uCRP could potentially be a promising biomarker in various diseases including other cancer types.

Comparison of single and combination risk factors in pancreatic ductal adenocarcinoma with control and benign hepatobiliary disease groups

Comparison of single and combination risk factors in pancreatic ductal adenocarcinoma with control and benign hepatobiliary disease groups

Automated classification of urine biomarkers to diagnose pancreatic cancer using 1-D convolutional neural networks

BackgroundEarly diagnosis of Pancreatic Ductal Adenocarcinoma (PDAC) is the main key to surviving cancer patients. Urine proteomic biomarkers which are creatinine, LYVE1, REG1B, and TFF1 present a promising non-invasive and inexpensive diagnostic method of the PDAC. Recent utilization of both microfluidics technology and artificial intelligence techniques enables accurate detection and analysis of these biomarkers. This paper proposes a new deep-learning model to identify urine biomarkers for the automated diagnosis of pancreatic cancers. The proposed model is composed of one-dimensional convolutional neural networks (1D-CNNs) and long short-term memory (LSTM). It can categorize patients into healthy pancreas, benign hepatobiliary disease, and PDAC cases automatically.ResultsExperiments and evaluations have been successfully done on a public dataset of 590 urine samples of three classes, which are 183 healthy pancreas samples, 208 benign hepatobiliary disease samples, and 199 PDAC samples. The results demonstrated that our proposed 1-D CNN + LSTM model achieved the best accuracy score of 97% and the area under curve (AUC) of 98% versus the state-of-the-art models to diagnose pancreatic cancers using urine biomarkers.ConclusionA new efficient 1D CNN-LSTM model has been successfully developed for early PDAC diagnosis using four proteomic urine biomarkers of creatinine, LYVE1, REG1B, and TFF1. This developed model showed superior performance on other machine learning classifiers in previous studies. The main prospect of this study is the laboratory realization of our proposed deep classifier on urinary biomarker panels for assisting diagnostic procedures of pancreatic cancer patients.

An Efficient Novel Approach with Multi Class Label Classification through Machine Learning Models for Pancreatic Cancer

Pancreatic cancer is right now the fourth largest cause of cancer-related deaths. Early diagnosis is one good solution for pancreatic cancer patients and reduces the mortality rate. Accurate and earlier diagnosis of the pancreatic tumor is a demanding task due to several factors such as delayed diagnosis and absence of early warning symptoms. The conventional distributed machine learning techniques such as SVM and logistic regression were not efficient to minimize the error rate and improve the classification of pancreatic cancer with higher accuracy. Therefore, a novel technique called Distributed Hybrid Elitism gene Quadratic discriminant Reinforced Learning Classifier System (DHEGQDRLCS) is developed in this paper. First, the number of data samples is collected from the repository dataset. This repository contains all the necessary files for the identification of prognostic biomarkers for pancreatic cancer. After the data collection, the separation of training and testing samples is performed for the accurate classification of pancreatic cancer samples. Then the training samples are considered and applied to Distributed Hybrid Elitism gene Quadratic discriminant Reinforced Learning Classifier System. The proposed hybrid classifier system uses the Kernel Quadratic Discriminant Function to analyze the training samples. After that, the Elitism gradient gene optimization is applied for classifying the samples into multiple classes such as non-cancerous pancreas, benign hepatobiliary disease i.e., pancreatic cancer, and Pancreatic ductal adenocarcinoma. Then the Reinforced Learning technique is applied to minimize the loss function based on target classification results and predicted classification results. Finally, the hybridized approach improves pancreatic cancer diagnosing accuracy. Experimental evaluation is carried out with pancreatic cancer dataset with Hadoop distributed system and different quantitative metrics such as Accuracy, balanced accuracy, F1-score, precision, recall, specificity, TN, TP, FN, FP, ROC_AUC, PRC_AUC, and PRC_APS. The performance analysis results indicate that the DHEGQDRLCS provides better diagnosing accuracy when compared to existing methods.

Advances in the management of liver and biliary tumors.

Over the past 50 years, the management of liver and biliary tumors has evolved significantly. Initially considered highly morbid and lethal, resection is now the treatment of choice for a significant proportion of patients with malignant and benign hepatobiliary disease. Improved operative/anesthetic techniques, use of parenchymal-sparing approaches, better patient selection for surgery, effective liver-directed therapies, and new insights into tumor biology are significant contributors to our transformed approach to hepatobiliary neoplasms.

Role of Robotic Surgery in the Management of Benign Hepatobiliary Diseases

Background: Recently robotic surgery has emerged as one of the most promising surgical advances. Despite its worldwide acceptance in many different surgical specialties, the use of robotic assistance in the field of hepatobiliary (HBP) surgery remains relatively unexplored. Our study presents single institution´s initial experience of robotic assisted surgery for treatment of benign hepatobiliary pathologies. Methods: A retrospective analysis of a prospectively maintained database on clinical outcomes was performed for 26 consecutive patients that underwent robotic assisted surgery for benign HBP disease at Rambam Medical Center during 2013-2015. Results: There were 26 robotic assisted surgical procedures performed for benign HBP pathologies during the study period. There were 3 anatomical robotic liver resections for symptomatic hemangiomas , 9 cases of giant liver cyst, 5 robotic assisted surgery for type I choledochal cyst, 2 case of benign (iatrogenic) common bile duct (CBD) stricture, 3 cases of robotic (CBD) exploration due to large intra choledochal stones and 6 cases of cholecystectomy for cholelithiasis. The median postoperative hospital stays for all procedures were 3.5 days (range 1-6 days). General morbidity (minor) was 2%. There was no mortality in our series. Conclusions: Robotic surgery is feasible and can be safely performed in patients with different benign HBP pathologies. Further evaluation with clinical trials is required to validate it´s real benefits.

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

BackgroundPancreatic 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 findingsClinical 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.ConclusionsWe 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.

Characterisation of the Serum Metabolic Signature of Cholangiocarcinoma in a United Kingdom Cohort

A distinct serum metabonomic pattern has been previously revealed to be associated with various forms of liver disease. Here, we aimed to apply mass spectrometry to obtain serum metabolomic profiles from individuals with cholangiocarcinoma and benign hepatobiliary diseases to gain an insight into pathogenesis and search for potential early-disease biomarkers. Serum samples were profiled using a hydrophilic interaction liquid chromatography platform, coupled to a mass spectrometer. A total of 47 serum specimens from 8 cholangiocarcinoma cases, 20 healthy controls, 8 benign disease controls (bile duct strictures)and 11 patients with hepatocellular carcinoma (as malignant disease controls) were included. Data analysis was performed using univariate and multivariate statistics. The serum metabolome disparities between the metabolite profiles from healthy controls and patients with hepatobiliary disease were predominantly related to changes in lipid and lipid-derived compounds (phospholipids, bile acids and steroids) and amino acid metabolites (phenylalanine). A metabolic pattern indicative of inflammatory response due to cirrhosis and cholestasis was associated with the disease groups. The abundance of phospholipid metabolites was altered in individuals with liver disease, particularly cholangiocarcinoma, but no significant difference was seen between profiles from patients with benign biliary strictures and cholangiocarcinoma. The serum metabolome in cholangiocarcinoma exhibited changes in metabolites related to inflammation, altered energy production and phospholipid metabolism. This study serves to highlight future avenues for biomarker research in large-scale studies.

Clinical value of combined detection of four common tumor markers in benign and malignant hepatobiliary system diseases

Clinical value of combined detection of four common tumor markers in benign and malignant hepatobiliary system diseases

Raised CA 19-9 Levels in Choledocholithiasis: A Case Report

Introduction: CA 19-9 has been used as a prognostic marker in pancreatic adenocarcinoma.1 CA 19-9 can also be raised to moderate levels in several benign hepatobiliary diseases like Choledocholithiasis, cholangitis and cholestasis of any cause.3 However, very high levels of CA 19-9 have been described in benign condition in several case reports. Case summary: A 73 years old gentleman, known case of hypertension, diabetes mellitus, ischemic heart disease and stroke, presented with complains of jaundice, anorexia and weight loss for 3 weeks. On examination he was deeply icteric. He lost around 9lb weight. There was no palpable mass in the abdomen. On his lab investigations Bilirubin was 19.3 g/dl, ALT 59 U/L, AST 106, Alkaline phosphatase 552 U/L CA 19-9 level was 32,000 IU. USG abdomen and CT scan abdomen showed dilated CBD with mildly dilated intrahepatic ducts and a stone in distal CBD. ERCP was attempted which was unsuccessful. Percutaneous transhepatic biliary drainage(PTBD) was carried out and a draining catheter was placed. Patient improved clinically after biliary drainage. ERCP was performed after 5 days of PTBD. A 1.8 cm stone was seen that could not be removed and a stent was placed for draiange. CBD brushings taken for cytology were negative for atypical cells. Patient was referred for surgery. Discussion: CA 19-9 levels have been extensively studied in diagnostic as well as prognostic value in pancreatic carcinoma with well established sensitivity, specificity, positive predictive and negative predictive values.1,2. Several studies, however, described raised levels of CA 19-9 is benign hepatobiliary conditions. Mao et al described a mean value of 401.92 ± 483.92 in patient with benign biliary obstruction while 826.83 ± 557.38 were seen in malignant group.4 Michael B et al reported raised CA 19-9 levels seen in acute cholangitis but not in Choledocholithiasis, cholangitis or benign CBD obstruction. Only one case among all acute cholangitis patients however showed very high levels (32000 IU) rest were in the range of 1000 IU .Other case reports have shown values of 60-90000 IU/L Several other case reports showed very high levels of CA 19-9 in benign CBD obstruction with normalization of the levels after relieving the obstruction. Further studies are needed to better define the role of CA 19-9 in bilairy disease. However caution is advised in interpreting high leveles of CA19-9 in biliary disease.

CA‐S27: A novel Lewis a associated carbohydrate epitope is diagnostic and prognostic for cholangiocarcinoma

Early and specific diagnosis is critical for treatment of cholangiocarcinoma (CCA). In this study, a carbohydrate antigen-S27 (CA-S27) monoclonal antibody (mAb) was established using pooled CCA tissue-extract as immunogen. The epitope recognized by CA-S27-mAb was a new Lewis-a (Le(a)) associated modification of MUC5AC mucin. A Soybean agglutinin/CA-S27-mAb sandwich ELISA to determine CA-S27 in serum was successfully developed. High level of CA-S27 was detected in serum of CCA patients and could differentiate CCA patients from those of gastro-intestinal cancers, hepatomas, benign hepatobiliary diseases and healthy subjects with high sensitivity (87.5%) and high negative predictive value (90.4%). The level of serum CA-S27 was dramatically reduced after tumor removal, indicating tumor origin of CA-S27. Patients with high serum CA-S27 had significantly shorter survivals than those with low serum CA-S27 regardless of serum MUC5AC levels. Fucosyltransferase-III (FUT3) was shown to be a regulator of CA-S27 expression. Suppression of CA-S27 expression with siRNA-FUT3 or neutralization with CA-S27 mAb significantly reduced growth, adhesion, invasion and migration potentials of CCA cells in vitro. In summary, we demonstrate that serum CA-S27, a novel carbohydrate antigen, has potential as diagnostic and prognostic markers for CCA patients. CA-S27 involves in promoting cell growth, adhesion, migration and invasion of CCA cells.

Plasma Concentrations of Angiogenesis-related Molecules in Patients with Pancreatic Cancer

Anti-angiogenic agents are now being clinically evaluated for the treatment of pancreatic cancer and a detailed investigation of the angiogenic profile of pancreatic cancer is needed. The aim of this study was to evaluate the plasma concentrations of angiogenesis-related molecules in patients with pancreatic cancer, compared with those with other diseases. Plasma samples obtained from 45 patients with pancreatic cancer were analyzed and compared with those from 9 patients with pancreatitis, 16 patients with benign hepatobiliary diseases and 58 patients with colorectal cancers. The plasma levels of angiogenesis-related molecules including angiopoietin-2, follistatin, granulocyte-colony stimulating factor, hepatocyte growth factor, interleukin-8, leptin, platelet-derived growth factor beta polypeptide, platelet endothelial cell adhesion molecule-1 and vascular endothelial growth factor were determined using an antibody suspension bead arrays system. The plasma levels of all the angiogenesis-related molecules were not increased in patients with pancreatic cancer, compared with those with pancreatitis and benign hepatobiliary diseases, whereas the levels of those with colorectal cancer were markedly increased. The plasma interleukin-8 concentration was significantly elevated in patients with distant metastases and was associated with a poor treatment outcome of chemotherapy in patients with pancreatic cancer. The plasma levels of angiogenesis-related molecules were not elevated in patients with pancreatic cancer, compared with those with benign diseases or colorectal cancer. The plasma interleukin-8 level may be a novel biomarker for the response to chemotherapy in patients with pancreatic cancer and warrants further prospective study.

Abstract 4185: Serum concentrations of angiogenesis-related molecules in patients with pancreatic cancer

Abstract Objectives: A number of antiangiogenic inhibitors have been studied in clinical settings, some of which are now under clinical evaluation in pancreas cancers (PC), therefore, prognostic marker of angiogenesis-related molecules in PC is needed. The aim of this study is to evaluate the serum levels of angiogenesis-related factors in patients with pancreas cancer. Methods: The plasma samples obtained from 45 pancreas cancers (PC) were analyzed compared with 9 pancreatitis (P), 16 benign hepatobiliary diseases (HD) and 58 colorectal cancers (CC). Serum angiogenesis-related factors including Angiopoietin-2, Follistatin, G-CSF, HGF, IL-8, Leptin, PDGF-BB, PECAM-1 and VEGF were determined by antibody suspension bead arrays system. Results: All of the serum angiogenesis-related factors were not increased in PC compared with P and HD, while those of CC were markedly increased. Although IL-8 levels were not increased in most samples of PC, it was significantly increased in patients with distant metastases and there was a trend toward to a shorter survival. Conclusions: Serum levels of angiogenesis-related factors were basically not increased in patients with PC, however, serum IL-8 levels may reflect PC progression and shorter survival. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4185. doi:10.1158/1538-7445.AM2011-4185

Achieving a pathological diagnosis in biliary tract cancer

IntroductionDiagnosing BTC is challenging because of a lack of reliable tumour markers and radiological similarities with benign hepatobiliary disease. Current guidelines advise confirmatory histology and/or cytology should be sought for...

A novel serum carbohydrate marker on mucin 5AC

The incidence of cholangiocarcinoma (CCA) is increasing globally. Currently, there is no powerful marker for the diagnosis of CCA, which has led to late diagnosis and poor patient outcome. This study was designed to establish a new monoclonal antibody (MoAb) for detecting a serum marker associated with CCA. Pooled CCA tissue extracts were immunized to germinal center associated nuclear protein (GANP)-transgenic mice. The antibody-producing hybridomas were prepared and initially screened by using an indirect enzyme-linked immunosorbent assay (ELISA). A positive clone that reacted strongly with CCA serum or tumor tissue extract and failed to react with normal human serum and liver extract was selected. An S121 immunoglobulin M MoAb that recognized a novel glycan epitope was obtained. Immunohistochemistry of CCA tissues revealed that the MoAb reacted strongly with hyperplastic/dysplastic and neoplastic bile ducts but not with normal bile ducts. In addition, experiments demonstrated that mucin 5AC (MUC5AC) is a core glycoprotein for the S121 epitope. A sandwich ELISA using soybean agglutinin and an S121 MoAb was developed for detecting S121 reactive antigen in patient sera. The level of serum S121 from patients with CCA was reduced significantly after tumor removal, indicating the tumor origin of this antigen. The test was able to distinguish patients with CCA from healthy individuals, active Opisthorchis viverrini-infected individuals and patients with various gastrointestinal cancers, hepatoma, and benign hepatobiliary diseases with 87.63% sensitivity, 89.58% specificity, an 80.95% positive predictive value, and a 93.47% negative predictive value. Moreover, high serum S121 levels were related to a poor patient outcome. The sugar antigen recognized by S121 MoAb is a new serum marker for the diagnosis and prognosis of CCA.

Feasibility of Identifying Pancreatic Cancer Based on Serum Metabolomics

We postulated that the abundance of various metabolites in blood would facilitate the diagnosis of pancreatic and biliary lesions, which could potentially prevent unnecessary surgery. Serum samples from patients with benign hepatobiliary disease (n = 43) and from patients with pancreatic cancer (n = 56) were examined by ¹H NMR spectroscopy to quantify 58 unique metabolites. Data were analyzed by "targeted profiling" followed by supervised pattern recognition and orthogonal partial least-squares discriminant analysis (O-PLS-DA) of the most significant metabolites, which enables comparison of the whole sample spectrum between groups. The metabolomic profile of patients with pancreatic cancer was significantly different from that of patients with benign disease (AUROC, area under the ROC curve, = 0.8372). Overt diabetes mellitus (DM) was identified as a possible confounding factor in the pancreatic cancer group. Thus, diabetics were excluded from further analysis. In this more homogeneous pancreatic cancer group, compared with benign cases, serum concentrations of glutamate and glucose were most elevated on multivariate analysis. In benign cases, creatine and glutamine were most abundant. To examine the usefulness of this test, a comparison was made to age- and gender-matched controls with benign lesions that mimic cancer, controlling also for presence of jaundice and diabetes (n = 14 per group). The metabolic profile in patients with pancreatic cancer remained distinguishable from patients with benign pancreatic lesions (AUROC = 0.8308). The serum metabolomic profile may be useful for distinguishing benign from malignant pancreatic lesions. Further studies will be required to study the effects of jaundice and diabetes. A more comprehensive metabolomic profile will be evaluated using mass spectrometry.

Serum levels of variants of transthyretin down‐regulation in cholangiocarcinoma

Cholangiocarcinoma (CC) is devastating neoplasm and very few specific biomarkers could be used in clinical diagnosis. A study was taken to find novel serum biomarkers for CC. Surface enhanced laser desorption/ionization (SELDI) technology was used to analyze 427 serum samples including 56 CCs, 49 hepatobiliary diseases, 269 other cancer control, and 53 healthy individuals. The candidates were isolated and identified by SDS-PAGE, ESI/MS-MS, Western blot, and immunoprecipitation. Liver functions of CC patients were examined and enzyme-linked immunosorbent assay (ELISA) of transthyretin (TTR) and CA19-9 were further performed in some sets of serum samples. 13.76, 13.88, and 14.04 k m/z peaks in sera were significantly decreased in CC compared with the control groups (P < 0.001). Subsequently, these three peaks were identified as native TTR and its two variants. ELISA assay indicated that TTR levels were consistent with SELDI analysis in CC compared with healthy control and benign diseases of hepatobiliary (P < 0.001). Liver function test levels were obviously elevated for CC patients. TTR combining with CA19-9 to differentiate CC from benign hepatobiliary diseases showed sensitivity and specificity were 98.2% and 100%, respectively. The levels of TTR were significantly down-regulated in sera of CC patients and may be complementary markers of CA19-9 in diagnosis for CC.

Expression of Intestinal Trefoil Factor (TFF-3) in Hepatocellular Carcinoma

Trefoil peptides (TFF-1, 2, 3) are a family of protease-resistant regulatory factors that play a role in mucosal restitution, angiogenesis, apoptosis, and tumor progression. Intestinal trefoil peptide (TFF-3) expression has been demonstrated in benign hepatobiliary diseases, but there are limited data regarding its expression in HCC. Thirty consecutive cases of HCC from 1998 to 2003 were studied. Immunohistochemistry was performed on formalin-fixed paraffin-embedded blocks of HCC using polyclonal antibody to TFF-3. TFF-3 expression was classified as strong, moderate, weak, focal, and negative. Clinical data were obtained per an IRB-approved protocol. Median age was 69 yr (range: 39-83 yr). Twenty- three patients were males and 7 were females. Treatments included hepatic resection (n = 16), chemo-embolization (n = 4), combined modality therapy (n = 5) and no treatment (n = 4). HCC was well differentiated in 12 (40%), moderately differentiated in 13 (43%), and poorly differentiated in 5 (17%) patients. TFF-3 expression was detected in 28/30 (93.3%) patient samples. Sixteen patients (53%) had moderate and 1 (3%) patient had strong TFF-3 expression. Tumor/ normal tissue interface was assessable in 21 cases; 11 cases expressed TFF-3 at the interface. There was a strong correlation between tumor grade and TFF-3 expression, wherein poorly differentiated tumors had moderate/strong TFF-3 expression (p = 0.008). There was no correlation between TFF-3 expression and survival (p = 0.77). Furthermore, there was no correlation among age, disease stage, and survival. TFF-3 is commonly expressed in HCC and its expression correlates with tumor grade.