Specialized DNA arrays for the differentiation of pancreatic tumors

A perceptually optimised bivariate visualisation scheme for high-dimensional fold-change data

Visualising data as diagrams using visual attributes such as colour, shape, size, and orientation is challenging. In particular, large data sets demand graphical display as an essential step in the analysis. In order to achieve comprehension often different attributes need to be displayed simultaneously. In this work a comprehensible bivariate, perceptually optimised visualisation scheme for high-dimensional data is proposed and evaluated. It can be used to show fold changes together with confidence values within a single diagram. The visualisation scheme consists of two parts: a uniform, symmetric, two-sided colour scale and a patch grid representation. Evaluation of uniformity and symmetry of the two-sided colour scale was performed in comparison to a standard RGB scale by twenty-five observers. Furthermore, the readability of the generated map was validated and compared to a bivariate heat map scheme.

MOTA: Multi-omic integrative analysis for biomarker discovery

Recent advancement of omic technologies provides researchers with opportunities to search for disease biomarkers at the systems level. However, selection of biomarker candidates from a large number of molecules involved at various layers of the biological system is challenging. In this paper, we propose multi-omic integrative analysis (MOTA), a network-based method that uses information from multi-omic data to identify candidate disease biomarkers. We evaluated the performance of MOTA in selecting disease-associated molecules from four sets of multi-omic data representing three cohorts of hepatocellular carcinoma (HCC) cases and patients with liver cirrhosis. The results demonstrate that MOTA leads to selection of more biomarker candidates that shared by two different cohorts compared to traditional statistical methods. Also, the networks constructed by MOTA allow users to investigate biological significance of the selected biomarker candidates.

Imaging modalities for characterising focal pancreatic lesions

BACKGROUND

Increasing numbers of incidental pancreatic lesions are being detected each year. Accurate characterisation of pancreatic lesions into benign, precancerous, and cancer masses is crucial in deciding whether to use treatment or surveillance. Distinguishing benign lesions from precancerous and cancerous lesions can prevent patients from undergoing unnecessary major surgery. Despite the importance of accurately classifying pancreatic lesions, there is no clear algorithm for management of focal pancreatic lesions.

OBJECTIVES

To determine and compare the diagnostic accuracy of various imaging modalities in detecting cancerous and precancerous lesions in people with focal pancreatic lesions.

SEARCH METHODS

We searched the CENTRAL, MEDLINE, Embase, and Science Citation Index until 19 July 2016. We searched the references of included studies to identify further studies. We did not restrict studies based on language or publication status, or whether data were collected prospectively or retrospectively.

SELECTION CRITERIA

We planned to include studies reporting cross-sectional information on the index test (CT (computed tomography), MRI (magnetic resonance imaging), PET (positron emission tomography), EUS (endoscopic ultrasound), EUS elastography, and EUS-guided biopsy or FNA (fine-needle aspiration)) and reference standard (confirmation of the nature of the lesion was obtained by histopathological examination of the entire lesion by surgical excision, or histopathological examination for confirmation of precancer or cancer by biopsy and clinical follow-up of at least six months in people with negative index tests) in people with pancreatic lesions irrespective of language or publication status or whether the data were collected prospectively or retrospectively.

DATA COLLECTION AND ANALYSIS

Two review authors independently searched the references to identify relevant studies and extracted the data. We planned to use the bivariate analysis to calculate the summary sensitivity and specificity with their 95% confidence intervals and the hierarchical summary receiver operating characteristic (HSROC) to compare the tests and assess heterogeneity, but used simpler models (such as univariate random-effects model and univariate fixed-effect model) for combining studies when appropriate because of the sparse data. We were unable to compare the diagnostic performance of the tests using formal statistical methods because of sparse data.

MAIN RESULTS

We included 54 studies involving a total of 3,196 participants evaluating the diagnostic accuracy of various index tests. In these 54 studies, eight different target conditions were identified with different final diagnoses constituting benign, precancerous, and cancerous lesions. None of the studies was of high methodological quality. None of the comparisons in which single studies were included was of sufficiently high methodological quality to warrant highlighting of the results. For differentiation of cancerous lesions from benign or precancerous lesions, we identified only one study per index test. The second analysis, of studies differentiating cancerous versus benign lesions, provided three tests in which meta-analysis could be performed. The sensitivities and specificities for diagnosing cancer were: EUS-FNA: sensitivity 0.79 (95% confidence interval (CI) 0.07 to 1.00), specificity 1.00 (95% CI 0.91 to 1.00); EUS: sensitivity 0.95 (95% CI 0.84 to 0.99), specificity 0.53 (95% CI 0.31 to 0.74); PET: sensitivity 0.92 (95% CI 0.80 to 0.97), specificity 0.65 (95% CI 0.39 to 0.84). The third analysis, of studies differentiating precancerous or cancerous lesions from benign lesions, only provided one test (EUS-FNA) in which meta-analysis was performed. EUS-FNA had moderate sensitivity for diagnosing precancerous or cancerous lesions (sensitivity 0.73 (95% CI 0.01 to 1.00) and high specificity 0.94 (95% CI 0.15 to 1.00), the extremely wide confidence intervals reflecting the heterogeneity between the studies). The fourth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (dysplasia) provided three tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing invasive carcinoma were: CT: sensitivity 0.72 (95% CI 0.50 to 0.87), specificity 0.92 (95% CI 0.81 to 0.97); EUS: sensitivity 0.78 (95% CI 0.44 to 0.94), specificity 0.91 (95% CI 0.61 to 0.98); EUS-FNA: sensitivity 0.66 (95% CI 0.03 to 0.99), specificity 0.92 (95% CI 0.73 to 0.98). The fifth analysis, of studies differentiating cancerous (high-grade dysplasia or invasive carcinoma) versus precancerous (low- or intermediate-grade dysplasia) provided six tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing cancer (high-grade dysplasia or invasive carcinoma) were: CT: sensitivity 0.87 (95% CI 0.00 to 1.00), specificity 0.96 (95% CI 0.00 to 1.00); EUS: sensitivity 0.86 (95% CI 0.74 to 0.92), specificity 0.91 (95% CI 0.83 to 0.96); EUS-FNA: sensitivity 0.47 (95% CI 0.24 to 0.70), specificity 0.91 (95% CI 0.32 to 1.00); EUS-FNA carcinoembryonic antigen 200 ng/mL: sensitivity 0.58 (95% CI 0.28 to 0.83), specificity 0.51 (95% CI 0.19 to 0.81); MRI: sensitivity 0.69 (95% CI 0.44 to 0.86), specificity 0.93 (95% CI 0.43 to 1.00); PET: sensitivity 0.90 (95% CI 0.79 to 0.96), specificity 0.94 (95% CI 0.81 to 0.99). The sixth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (low-grade dysplasia) provided no tests in which meta-analysis was performed. The seventh analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) provided two tests in which meta-analysis was performed. The sensitivity and specificity for diagnosing cancer were: CT: sensitivity 0.83 (95% CI 0.68 to 0.92), specificity 0.83 (95% CI 0.64 to 0.93) and MRI: sensitivity 0.80 (95% CI 0.58 to 0.92), specificity 0.81 (95% CI 0.53 to 0.95), respectively. The eighth analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) or benign lesions provided no test in which meta-analysis was performed.There were no major alterations in the subgroup analysis of cystic pancreatic focal lesions (42 studies; 2086 participants). None of the included studies evaluated EUS elastography or sequential testing.

AUTHORS' CONCLUSIONS

We were unable to arrive at any firm conclusions because of the differences in the way that study authors classified focal pancreatic lesions into cancerous, precancerous, and benign lesions; the inclusion of few studies with wide confidence intervals for each comparison; poor methodological quality in the studies; and heterogeneity in the estimates within comparisons.

Transcriptomic analysis predicts survival and sensitivity to anticancer drugs of patients with a pancreatic adenocarcinoma

A major impediment to the effective treatment of patients with pancreatic ductal adenocarcinoma (PDAC) is the molecular heterogeneity of this disease, which is reflected in an equally diverse pattern of clinical outcome and in responses to therapies. We developed an efficient strategy in which PDAC samples from 17 consecutive patients were collected by endoscopic ultrasound-guided fine-needle aspiration or surgery and were preserved as breathing tumors by xenografting and as a primary culture of epithelial cells. Transcriptomic analysis was performed from breathing tumors by an Affymetrix approach. We observed significant heterogeneity in the RNA expression profile of tumors. However, the bioinformatic analysis of these data was able to discriminate between patients with long- and short-term survival corresponding to patients with moderately or poorly differentiated PDAC tumors, respectively. Primary culture of cells allowed us to analyze their relative sensitivity to anticancer drugs in vitro using a chemogram, similar to the antibiogram for microorganisms, establishing an individual profile of drug sensitivity. As expected, the response was patient dependent. We also found that transcriptomic analysis predicts the sensitivity of cells to the five anticancer drugs most frequently used to treat patients with PDAC. In conclusion, using this approach, we found that transcriptomic analysis could predict the sensitivity to anticancer drugs and the clinical outcome of patients with PDAC.

Recurrence of early stage colon cancer predicted by expression pattern of circulating microRNAs

Systemic treatment of patients with early-stage cancers attempts to eradicate occult metastatic disease to prevent recurrence and increased morbidity. However, prediction of recurrence from an analysis of the primary tumor is limited because disseminated cancer cells only represent a small subset of the primary lesion. Here we analyze the expression of circulating microRNAs (miRs) in serum obtained pre-surgically from patients with early stage colorectal cancers. Groups of five patients with and without disease recurrence were used to identify an informative panel of circulating miRs using quantitative PCR of genome-wide miR expression as well as a set of published candidate miRs. A panel of six informative miRs (miR-15a, mir-103, miR-148a, miR-320a, miR-451, miR-596) was derived from this analysis and evaluated in a separate validation set of thirty patients. Hierarchical clustering of the expression levels of these six circulating miRs and Kaplan-Meier analysis showed that the risk of disease recurrence of early stage colon cancer can be predicted by this panel of miRs that are measurable in the circulation at the time of diagnosis (P = 0.0026; Hazard Ratio 5.4; 95% CI of 1.9 to 15).

Human equilibrative nucleoside transporter 1 and Notch3 can predict gemcitabine effects in patients with unresectable pancreatic cancer

Background:

Pancreatic ductal carcinoma (PDC) is one of the most lethal human carcinomas. Expression patterns of some genes may predict gemcitabine (GEM) treatment efficacy. We examined predictive indicators of survival in GEM-treated patients by quantifying the expression of several genes in pre-treatment endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) samples from patients with PDC.

Methods:

The expressions of human equilibrative nucleoside transporter 1 (hENT1), deoxycitidine kinase, ribonucleoside reductase 1, ribonucleoside reductase 2 and Notch3 in EUS-FNA tissue samples from 71 patients with unresectable PDC were quantified using real-time reverse transcription–polymerase chain reactions and examined for correlations with GEM sensitivity.

Results:

The log-rank test detected no significant differences in overall survival between GEM-treated patients with low and high mRNA levels of all genes examined. However, low Notch3 mRNA expression was significantly associated with longer overall survival in a multivariate analysis for survival (P=0.0094). High hENT1 expression level was significantly associated with a longer time to progression (P=0.039). Interaction tests for GEM administration and hENT1 or Notch3 mRNA expression were statistically significant (P=0.0054 and 0.0047, respectively).

Conclusion:

hENT1 and Notch3 mRNA expressions in EUS-FNA specimens were the key predictive biomarkers of GEM effect and GEM sensitivity in patients with unresectable PDC.

Immunoassay-based proteome profiling of 24 pancreatic cancer cell lines

Pancreatic ductal adenocarcinoma is one of the most deadly forms of cancers, with a mortality that is almost identical to incidence. The inability to predict, detect or diagnose the disease early and its resistance to all current treatment modalities but surgery are the prime challenges to changing the devastating prognosis. Also, relatively little is known about pancreatic carcinogenesis. In order to better understand relevant aspects of pathophysiology, differentiation, and transformation, we analysed the cellular proteomes of 24 pancreatic cancer cell lines and two controls using an antibody microarray that targets 741 cancer-related proteins. In this analysis, 72 distinct disease marker proteins were identified that had not been described before. Additionally, categorizing cancer cells in accordance to their original location (primary tumour, liver metastases, or ascites) was made possible. A comparison of the cells' degree of differentiation (well, moderately, or poorly differentiated) resulted in unique marker sets of high relevance. Last, 187 proteins were differentially expressed in primary versus metastatic cancer cells, of which the majority is functionally related to cellular movement.

Diagnosis of pancreatic ductal adenocarcinoma and chronic pancreatitis by measurement of microRNA abundance in blood and tissue

A solid process for diagnosis could have a substantial impact on the successful treatment of pancreatic cancer, for which currently mortality is nearly identical to incidence. Variations in the abundance of all microRNA molecules from peripheral blood cells and pancreas tissues were analyzed on microarrays and in part validated by real-time PCR assays. In total, 245 samples from two clinical centers were studied that were obtained from patients with pancreatic ductal adenocarcinoma or chronic pancreatitis and from healthy donors. Utilizing the minimally invasive blood test, receiver operating characteristic (ROC) curves and the corresponding area under the curve (AUC) analysis demonstrated very high sensitivity and specificity of a distinction between healthy people and patients with either cancer or chronic pancreatitis; respective AUC values of 0.973 and 0.950 were obtained. Confirmative and partly even more discriminative diagnosis could be performed on tissue samples with AUC values of 1.0 and 0.937, respectively. In addition, discrimination between cancer and chronic pancreatitis was achieved (AUC = 0.875). Also, several miRNAs were identified that exhibited abundance variations in both tissue and blood samples. The results could have an immediate diagnostic value for the evaluation of tumor reoccurrence in patients, who have undergone curative surgical resection, and for people with a familial risk of pancreatic cancer.

Road to early detection of pancreatic cancer: Attempts to utilize epigenetic biomarkers

The prognosis of pancreatic cancer is extremely poor, mainly because of its aggressive biological behavior and late onset of symptoms for clinical diagnosis; these impose limitations on therapeutic intervention. Deeper genomic sequencing analyses of pancreatic cancers revealed 12 core pathways and a long duration, nearly 20 years from initiation to distant metastases. This evidence will offer a broader aspect and time window of opportunity for early detection, thus preventing deaths from this cruel cancer. Epigenetic biomarkers can be utilized for assessing cancer risk, early detection, and predicting prognosis and therapeutic responses. In this review, we briefly summarize relevant issues associated with pancreatic cancer progression and recent advances in epigenetic biomarkers such as DNA methylation, miRNAs, satellite repeats, and histone modifications for early diagnosis.

Differentiation of multiple types of pancreatico-biliary tumors by molecular analysis of clinical specimens

Timely and accurate diagnosis of pancreatic ductal adenocarcinoma (PDAC) is critical in order to provide adequate treatment to patients. However, the clinical signs and symptoms of PDAC are shared by several types of malignant or benign tumors which may be difficult to differentiate from PDAC with conventional diagnostic procedures. Among others, these include ampullary cancers, solid pseudopapillary tumors, and adenocarcinomas of the distant bile duct, as well as inflammatory masses developing in chronic pancreatitis. Here, we report an approach to accurately differentiate between these different types of pancreatic masses based on molecular analysis of biopsy material. A total of 156 bulk tissue and fine needle aspiration biopsy samples were analyzed using a dedicated diagnostic cDNA array and a composite classification algorithm developed based on linear support vector machines. All five histological subtypes of pancreatic masses were clearly separable with 100% accuracy when using all 156 individual samples for classification. Generalized performance of the classification system was tested by 10 × 10-fold cross validation (100 test runs). Correct classification into the five diagnostic groups was demonstrated for 81.5% of 1,560 test set predictions. Performance increased to 85.3% accuracy when PDAC and distant bile duct carcinomas were combined in a single diagnostic class. Importantly, overall sensitivity of detection of malignant disease was 92.2%. The molecular diagnostic approach presented here is suitable to significantly aid in the differential diagnosis of undetermined pancreatic masses. To our knowledge, this is the first study reporting accurate differentiation between several types of pancreatico-biliary tumors in a single molecular analytical procedure.

Tissue and serum microRNAs in the Kras(G12D) transgenic animal model and in patients with pancreatic cancer

microRNAs (miRs) modulate the expression levels of mRNAs and proteins and can thus contribute to cancer initiation and progression. In addition to their intracelluar function, miRs are released from cells and shed into the circulation. We postulated that circulating miRs could provide insight into pathways altered during cancer progression and may indicate responses to treatment. Here we focus on pancreatic cancer malignant progression. We report that changes in miR expression patterns during progression of normal tissues to invasive pancreatic adenocarcinoma in the p48-Cre/LSL-Kras^G12D mouse model mirrors the miR changes observed in human pancreatic cancer tissues. miR-148a/b and miR-375 expression were found decreased whereas miR-10, miR-21, miR-100 and miR-155 were increased when comparing normal tissues, premalignant lesions and invasive carcinoma in the mouse model. Predicted target mRNAs FGFR1 (miR-10) and MLH1 (miR-155) were found downregulated. Quantitation of nine microRNAs in plasma samples from patients distinguished pancreatic cancers from other cancers as well as non-cancerous pancreatic disease. Finally, gemcitabine treatment of control animals and p48-Cre/LSL-Kras^G12D animals with pancreatic cancer caused distinct and up to 60-fold changes in circulating miRs that indicate differential drug effects on normal and cancer tissues. These findings support the significance of detecting miRs in the circulation and suggests that circulating miRs could serve as indicators of drug response.

Dual-color proteomic profiling of complex samples with a microarray of 810 cancer-related antibodies

Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses.

Gemcitabine sensitivity-related mRNA expression in endoscopic ultrasound-guided fine-needle aspiration biopsy of unresectable pancreatic cancer

Background

The aim of this study was to determine a predictive indicator of gemcitabine (GEM) efficacy in unresectable pancreatic cancer using tissue obtained by endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA).

Methods

mRNAs extracted from 35 pancreatic tubular adenocarcinoma tissues obtained by EUS-FNA before GEM-treatment were studied. mRNAs were amplified and applied to a Focused DNA Array, which was restricted to well-known genes, including GEM sensitivity-related genes, deoxycytidine kinase (dCK), human equilibrative nucleoside transporter 1 (hENT1), hENT2, dCMP deaminase, cytidine deaminase, 5'-nucleotidase, ribonucleotide reductase 1 (RRM1) and RRM2. mRNA levels were classified into high and low expression based on a cut-off value defined as the average expression of 35 samples. These 35 patients were divided into the following two groups. Patients with partial response and those with stable disease whose tumor markers decreased by 50% or more were classified as the effective group. The rest of patients were classified as the non-effective group. The relationship between GEM efficacy and mRNA expression was then examined by chi-squared test.

Results

Among these GEM sensitivity-related genes, dCK alone showed a significant correlation with GEM efficacy. Eight of 12 patients in the effective group had high dCK expression, whereas 16 of 23 patients in non-effective group had low dCK expressions (P = 0.0398).

Conclusion

dCK mRNA expression is a candidate indicator for GEM efficacy in unresectable pancreatic cancer. Quantitative mRNA measurements of dCK using EUS-FNA samples are necessary for definitive conclusions.

Basic principles and technologies for deciphering the genetic map of cancer

The progress achieved in the field of genomics in recent years is leading medicine to adopt a personalized model in which the knowledge of individual DNA alterations will allow a targeted approach to cancer. Using pancreatic cancer as a model, we discuss herein the fundamentals that need to be considered for the high throughput and global identification of mutations. These include patient-related issues, sample collection, DNA isolation, gene selection, primer design, and sequencing techniques. We also describe the possible applications of the discovery of DNA changes to the approach of this disease and cite preliminary efforts where the knowledge has been translated into the clinical or preclinical setting.

Identification of malignancy factors by analyzing cystic tumors of the pancreas

AIM

The diversity in the aggressiveness of cystic tumors of the pancreas - ranging from the usually benign serous cystadenoma to lesions of variable degrees of malignancy - was utilized for the identification of molecular factors that are involved in the occurrence of malignancy.

METHODS

We analyzed the transcript profiles of different cystic tumor types. The results were confirmed at the protein level by immunohistochemistry. Also, functional studies with siRNA silencing were performed.

RESULTS

Expression variations at the RNA and protein level were identified that are closely correlated with the degree of malignancy. Besides, all tumors could be classified effectively by this means. Many of the identified factors had not previously been known to be associated with malignant cystic lesions. siRNA silencing of the gene with the most prominent variation - the anti-apoptotic factor FASTK (Fas-activated serine/threonine kinase) - revealed a regulative effect on several genes known to be relevant to the development of tumors.

CONCLUSION

By a molecular analysis of rare types of pancreatic cancer, which are less frequent in terms of disease, variations could be identified that could be critical for the regulation of malignancy and thus relevant to the treatment of also the majority of pancreatic tumors.

[Diagnostics and therapy of chronic pancreatitis]

Chronic pancreatitis (CP) is characterized by progressive, chronic inflammation of the pancreas, resulting in loss of exocrine and endocrine function and chronic abdominal pain. In most cases, CP is induced by long-term alcoholism. The second most frequent diagnosis is idiopathic CP, in the absence of known causes of CP. However, the identification of genetic and immunological causes continuously reduces the number of cases classified as idiopathic pancreatitis. Common symptoms of CP comprise abdominal pain radiating to the back, diarrhea, steatorrhea and the development of diabetes. The diagnosis is mainly based on clinical features, typical morphological findings such as pancreatic calcifications, duct stenoses and dilatations, as well as pathologic pancreatic function tests. Treatment of CP includes watch and wait strategies in asymptomatic patients, symptomatic treatment of the clinical features such as pain, exocrine and endocrine insufficiency, as well as interventional or surgical therapy of complications such as pseudocysts, pancreatic duct stenosis, stones or biliary obstruction.

Differential diagnosis of pancreatic tumors by molecular analysis of clinical specimens

OBJECTIVE

To describe the capabilities and limitations of the current state of the art in pancreatic cancer diagnostics and to discuss recent progress in the development of novel, highly accurate molecular diagnostic approaches.

RESULTS

Molecular analyses currently under evaluation as novel diagnostic tests include detection of point mutations, genomic imbalances, aberrant methylation patterns and gene expression changes on the mRNA and protein levels in pancreatic juice, fine needle aspiration biopsies and brush cytologies.

CONCLUSIONS

In exploratory studies, several candidate molecular markers show great potential to serve as general indicators of malignancy, but need to be validated in large, controlled, prospective studies. Multiplexing of diagnostic tests, e.g. in the form of specialized DNA microarrays, may provide more differentiated diagnoses such as the distinction of various tumor types or prognostic information for individual patients. The MolDiag-Paca consortium is strongly engaged in advancing these developments on a European level.

Endoscopic ultrasound-guided fine needle aspiration cytology of the pancreas: a morphological and multimodal approach to the diagnosis of solid and cystic mass lesions

Cytological evaluation of pancreatic masses and cysts is the preferred pre-operative diagnostic modality and is increasingly being performed by endoscopic ultrasound. This review focuses on the multimodal approach at the Massachusetts General Hospital that utilizes clinical, cytological, radiological and ancillary studies in rendering a final cytological diagnosis.

Quantitative proteomics analysis reveals that proteins differentially expressed in chronic pancreatitis are also frequently involved in pancreatic cancer

The effective treatment of pancreatic cancer relies on the diagnosis of the disease at an early stage, a difficult challenge. One major obstacle in the development of diagnostic biomarkers of early pancreatic cancer has been the dual expression of potential biomarkers in both chronic pancreatitis and cancer. To better understand the limitations of potential protein biomarkers, we used ICAT technology and tandem mass spectrometry-based proteomics to systematically study protein expression in chronic pancreatitis. Among the 116 differentially expressed proteins identified in chronic pancreatitis, most biological processes were responses to wounding and inflammation, a finding consistent with the underlining inflammation and tissue repair associated with chronic pancreatitis. Furthermore 40% of the differentially expressed proteins identified in chronic pancreatitis have been implicated previously in pancreatic cancer, suggesting some commonality in protein expression between these two diseases. Biological network analysis further identified c-MYC as a common prominent regulatory protein in pancreatic cancer and chronic pancreatitis. Lastly five proteins were selected for validation by Western blot and immunohistochemistry. Annexin A2 and insulin-like growth factor-binding protein 2 were overexpressed in cancer but not in chronic pancreatitis, making them promising biomarker candidates for pancreatic cancer. In addition, our study validated that cathepsin D, integrin beta1, and plasminogen were overexpressed in both pancreatic cancer and chronic pancreatitis. The positive involvement of these proteins in chronic pancreatitis and pancreatic cancer will potentially lower the specificity of these proteins as biomarker candidates for pancreatic cancer. Altogether our study provides some insights into the molecular events in chronic pancreatitis that may lead to diverse strategies for diagnosis and treatment of these diseases.