Proteomics of pancreatic cancer

Predictive factors for survival in borderline resectable and locally advanced pancreatic cancer: are these really two different entities?

BACKGROUND

The treatment of borderline resectable (BR) and locally advanced (LA) pancreatic ductal adenocarcinoma (PDAC) has evolved with a wider application of neoadjuvant chemotherapy (NACHT). The aim of this study was to identify predictive factors for survival in BR and LA PDAC.

METHODS

Clinicopathologic data of patients with BR and LA PDAC who underwent surgical exploration between January 2011 and June 2021 were retrospectively collected. Survival from the date of surgery was estimated using the Kaplan-Meier method. Simple and multiple Cox proportional hazards models were fitted to identify factors associated with survival. Surgical resection was analyzed in combination with the involvement of lymph nodes as this last was only known after a formal resection.

RESULTS

Ninety patients were surgically explored (BR: 45, LA: 45), of which 51 (57%) were resected (BR: 31, LA: 20). NACHT was administered to 43 patients with FOLFIRINOX being the most frequent regimen applied (33/43, 77%). Major complications (Clavien-Dindo grade III and IV) occurred in 7.8% of patients and 90-day mortality rate was 3.3%. The median overall survival since surgery was 16 months (95% CI 12-20) in the group which underwent surgical resection and 10 months (95% CI 7-13) in the group with an unresectable tumor (p=0.001). Cox proportional hazards models showed significantly lower mortality hazard for surgical resection compared to no surgical resection, even after adjusting for National Comprehensive Cancer Network  (NCCN) classification and administration of NACHT [surgical resection with involved lymph nodes vs no surgical resection (cHR 0.49; 95% CI 0.29-0.82; p=0.007)]. There was no significant difference in survival between patients with BR and LA disease (cHR= 1.01; 95% CI 0.63-1.62; p=0.98).

CONCLUSIONS

Surgical resection is the only predictor of survival in patients with BR and LA PDAC, regardless of their initial classification as BR or LA. Our results suggest that surgery should not be denied to patients with LA PDAC a priori. Prospective studies including patients from the moment of diagnosis are required to identify biologic and molecular markers which may allow a better selection of patients who will benefit from surgery.

Evaluation of serum ATX and LPA as potential diagnostic biomarkers in patients with pancreatic cancer

BACKGROUND

Pancreatic cancer (PC) is a devastating disease that has a poor prognosis and a total 5-year survival rate of around 5%. The poor prognosis of PC is due in part to a lack of suitable biomarkers that can allow early diagnosis. The lysophospholipase autotaxin (ATX) and its product lysophosphatidic acid (LPA) play an essential role in disease progression in PC patients and are associated with increased morbidity in several types of cancer. In this study, we evaluated both the potential role of serum LPA and ATX as diagnostic markers in PC and their prognostic value for PC either alone or in combination with CA19-9.

METHODS

ATX, LPA and CA19-9 levels were evaluated using ELISA of serum obtained from PC patients (n = 114) healthy volunteers (HVs: n = 120) and patients with benign pancreatic diseases (BPDs: n = 94).

RESULTS

Serum levels of ATX, LPA and CA19-9 in PC patients were substantially higher than that for BPD patients or HVs (p < 0.001). The sensitivity of LPA in early phase PC was 91.74% and the specificity of ATX was 80%. The levels of ATX, LPA and CA19-9 were all substantially higher for early stage PC patients compared to levels in serum from BPD patients and HVs. The diagnostic efficacy of CA19-9 for PC was significantly enhanced by the addition of ATX and LPA (p = 0.0012).

CONCLUSION

Measurement of LPA and ATX levels together with CA19-9 levels can be used for early detection of PC and diagnosis of PC in general.

A Low-Cost Nanomaterial-based Electrochemical Immunosensor on Paper for High-Sensitivity Early Detection of Pancreatic Cancer

Due to the lack of specific early detection methods for pancreatic cancer, it usually goes undetected until it is advanced. By employing paper-based electrodes (PPE), herein we for the first time developed a disposable low-cost paper-based immunosensor for rapid early quantitative detection of pancreatic cancer with a new biomarker, pseudopodium-enriched atypical kinase one, SGK269 (PEAK1). The immunosensor was constructed by fabricating PPEs immobilized with the versatile nanomaterial graphene oxide for the incorporation of antibodies to form an immunosensing platform, without the need of complicated surface modification. After it was confirmed that the PPEs exhibited excellent electrochemical properties, a sandwich-type electrochemical immunosensor was subsequently constructed by employing graphene oxide layers immobilized with anti-PEAK1, and the antibody conjugated with gold nanoparticles (AuNPs-tagged-Anti PEAK1). Further, spectral and surface characteristic studies confirmed the formation of the immunosensing platform. The immunosensor for PEAK1 exhibited a wide linear range between 10 pg mL^-1 and 10⁶ pg mL^-1 with a low limit of detection (LOD) of 10 pg mL^-1. The obtained results point towards rapid, sensitive, and specific early diagnosis of pancreatic cancer at the point of care and other low-resource settings.

Biosensors for early diagnosis of pancreatic cancer: a review

Pancreatic cancer is characterized by extremely high mortality and poor prognosis and is projected to be the leading cause of cancer deaths by 2030. Due to the lack of early symptoms and appropriate methods to detect pancreatic carcinoma at an early stage as well as its aggressive progression, the disease is often quite advanced by the time a definite diagnosis is established. The 5-year relative survival rate for all stages is approximately 8%. Therefore, detection of pancreatic cancer at an early surgically resectable stage is the key to decrease mortality and to improve survival. The traditional methods for diagnosing pancreatic cancer involve an imaging test, such as ultrasound or magnetic resonance imaging, paired with a biopsy of the mass in question. These methods are often expensive, time consuming, and require trained professionals to use the instruments and analyze the imaging. To overcome these issues, biosensors have been proposed as a promising tool for the early diagnosis of pancreatic cancer. The present review critically discusses the latest developments in biosensors for the early diagnosis of pancreatic cancer. Protein and microRNA biomarkers of pancreatic cancer and corresponding biosensors for pancreatic cancer diagnosis have been reviewed, and all these cases demonstrate that the emerging biosensors are becoming an increasingly relevant alternative to traditional techniques. In addition, we discuss the existing problems in biosensors and future challenges.

Glycoproteins and glycoproteomics in pancreatic cancer

Aberrations in protein glycosylation and polysaccharides play a pivotal role in pancreatic tumorigenesis, influencing cancer progression, metastasis, immuno-response and chemoresistance. Abnormal expression in sugar moieties can impact the function of various glycoproteins, including mucins, surface receptors, adhesive proteins, proteoglycans, as well as their effectors and binding ligands, resulting in an increase in pancreatic cancer invasiveness and a cancer-favored microenvironment. Recent advance in glycoproteomics, glycomics and other chemical biology techniques have been employed to better understand the complex mechanism of glycosylation events and how they orchestrate molecular activities in genomics, proteomics and metabolomics implicated in pancreatic adenocarcinoma. A variety of strategies have been demonstrated targeting protein glycosylation and polysaccharides for diagnostic and therapeutic development.

The Asian Grocery Store-Based Cancer Education Program: Creating New Education Modules

Operating since 1994, the UCSD Moores Cancer Center's Asian Grocery Store-Based Cancer Education Program (the Program) is a proven and sustainable strategy for disseminating cancer and poison control information to Asian and Pacific Islander (API) communities. This paper describes the process taken to identify health topics that can be readily addressed within the Program's infrastructure and reports results of the pilot testing of the educational module that was developed by following that process. The development of each new module is guided by the Health Belief Model and the Tipping Point Model. The process starts with the selection of a health topic demonstrating pressing need and treatment options in the API community. Then, using the Pareto principle, reasonably modifiable risk factors are chosen to be addressed in the module. "Sticky messaging" for the modifiable risk factors is developed to package the health information as memorable and transmissible calls-to-action. Finally, grocery store outreaches were used to pilot test the new module to assess its effectiveness at facilitating health care information to API community members. By adhering to the steps described in this paper, the authors were able to: (1) select liver cancer as a pressing API health issue that could be positively impacted by the Program; (2) identify reasonably modifiable risk factors for the chosen health issue; (3) generate compelling call-to-action messages to decrease risk of exposure; and (4) demonstrate the cultural and linguistic alignment of the liver cancer control module. The development and testing of new health education modules follow a methodical process guided by scientific principles. Understanding and employing the elements of an existing evidence-based and sustainable health education program can increase the likelihood of success in addressing the health needs of the API community.

Proteomics analysis of bodily fluids in pancreatic cancer

Proteomics study of pancreatic cancer using bodily fluids emphasizes biomarker discovery and clinical application, presenting unique prospect and challenges. Depending on the physiological nature of the bodily fluid and its proximity to pancreatic cancer, the proteomes of bodily fluids, such as pancreatic juice, pancreatic cyst fluid, blood, bile, and urine, can be substantially different in terms of protein constitution and the dynamic range of protein concentration. Thus, a comprehensive discovery and specific detection of cancer-associated proteins within these varied fluids is a complex task, requiring rigorous experiment design and a concerted approach. While major challenges still remain, fluid proteomics studies in pancreatic cancer to date have provided a wealth of information in revealing proteome alterations associated with pancreatic cancer in various bodily fluids.

Identification of prohibitin 1 as a potential prognostic biomarker in human pancreatic carcinoma using modified aqueous two-phase partition system combined with 2D-MALDI-TOF-TOF-MS/MS

Membrane proteins are an important source of potential targets for anticancer drugs or biomarkers for early diagnosis. In this study, we used a modified aqueous two-phase partition system combined with two-dimensional (2D) matrix-assisted laser desorption ionization (MALDI) time of flight (TOF) mass spectrometry (MS, 2D-MALDI-TOF-TOF-MS/MS) analysis to isolate and identify membrane proteins in PANC-1 pancreatic cancer cells. Using this method, we identified 55 proteins, of which 31 (56.4 %) were membrane proteins, which, according to gene ontology annotation, are associated with various cellular processes including cell signal transduction, differentiation, and apoptosis. Immunohistochemical analysis showed that the expression level of one of the identified mitochondria membrane proteins, prohibitin 1 (PHB1), is correlated with pancreatic carcinoma differentiation; PHB1 is expressed at a higher level in normal pancreatic tissue than in well-differentiated carcinoma tissue. Further studies showed that PHB1 plays a proapoptotic role in human pancreatic cancer cells, which suggests that PHB1 has antitumorigenic properties. In conclusion, we have provided a modified method for isolating and identifying membrane proteins and demonstrated that PHB1 may be a promising biomarker for early diagnosis and therapy of pancreatic (and potentially other) cancers.

Evaluation of circulating ADH and MIC-1 as diagnostic markers in Egyptian patients with pancreatic cancer

BACKGROUND

Despite the incidence rate of pancreatic cancer (PC) is uncommon in developing countries, it is considered as one of the most lethal disease. Improving patients' survival requires diagnosis of the disease at early stage. Therefore, it is imperative to identify more specific and sensitive marker(s) to be used for early detection of PC.

OBJECTIVES

Our aim is to evaluate the potential role of circulating ADH and MIC-1 to be used as diagnostic markers in Egyptian patients and assess their value either alone or combined with CA19-9 in early detection of PC.

METHODS

Alcohol dehydrogenase (ADH), macrophage inhibitory cytokine (MIC-1) and CA19-9 were measured by ELISA in serum procured from PC patients (n = 50) versus normal subjects (n = 20).

RESULTS

Our results demonstrate that the circulating levels of ADH, MIC-1 and CA19-9 in blood of PC were significantly higher than in healthy controls (HCs) (p < 0.001). The highest marker sensitivity observed at early stage was MIC-1 (90%) and specificity was ADH (83%). The level of all three markers was elevated significantly in early stage of PC in comparison to HCs. The addition of ADH and MIC-1 to CA19-9 significantly improved the efficacy of diagnosis (p = 0.023).

CONCLUSION

Our data demonstrate that not only the combination of ADH and MIC-1 to CA19-9 can be used in early detection of PC but also can improve the overall quality of diagnosis of this lethal disease.

Diagnostic value of S100P for pancreatic cancer: a meta-analysis

Pancreatic cancer (PC) is a fatal disease with a high mortality and poor prognosis. PC is the fourth leading cause of cancer death in America, and 80 % of PCs are diagnosed at an unresectable stage. Effective early detection assays are crucial since a successful operation at early stage is the best strategy for this disease. S100 calcium-binding protein P (S100P) has been reported as a predictive diagnostic index for PC and involves in the development of PC. However, the diagnostic accuracy of S100P in detecting PC has never been systematically assessed. The aim of the present study was to evaluate the diagnostic performance of S100P for PC. All relevant original articles about S100P in the diagnosis of PC published up to December 2013 were retrieved. The methodological quality of each study was assessed by QUADAS. The overall diagnostic sensitivity, specificity, diagnostic odds ratio (DOR), with 95 % confidence interval (CI), and area under the receiver operating characteristic curve (AUC) were pooled to evaluate the diagnostic value of S100P for PC using the Meta-DiSc1.4 statistical software. Eight studies met our criteria in the present meta-analysis. The pooled sensitivity, specificity, and DOR calculated by the bivariate random effects model were 0.87 (95 % CI 0.83-0.90), 0.88 (95 % CI 0.82-0.93), and 38.32 (95 % CI 11.22-130.87), respectively. The summary receiver operating characteristic (SROC) curve was located near the desirable left corner and the AUC was 0.9272. The current evidence suggests that S100P plays an important role in the diagnosis of PC with a high sensitivity and specificity. S100P may be regarded as a promising diagnostic marker to PC screening.

Proteomic identification of potential prognostic biomarkers in resectable pancreatic ductal adenocarcinoma

Pancreatic cancer is a devastating disease with a mortality rate almost identical with its incidence. In this context, the investigation of the pancreatic cancer proteome has gained considerable attention because profiles of proteins may be able to identify disease states and progression more accurately. Therefore, our objective was to investigate the changes in the proteome of patients suffering from pancreatic ductal adenocarcinoma (PDAC) by a comprehensive quantitative approach. Comparative proteomic profiling by label-free LC-MS/MS analysis of nine matched pairs of tumor and nontumor pancreas samples was used to identify differences in protein levels characteristic for PDAC. In this analysis, 488 proteins were quantified by at least two peptides of which 99 proteins displayed altered levels in PDAC (p < 0.01, fold change >1.3). Screening of data revealed a number of molecules that had already been related to PDAC such as galectin-1 (LEG1), major vault protein, adenylyl cyclase-associated protein 1 (CAP1), but also a potential new prognostic biomarker prolargin (PRELP). The Kaplan-Meier survival analysis revealed a significant correlation of protein abundance of PRELP with postoperative survival of patients with PDAC. For selected proteins the findings were verified by targeted proteomics (SRM), validated by immunohistochemistry and Western blotting and their value as candidate biomarkers is discussed.

Advances in the proteomic discovery of novel therapeutic targets in cancer

Proteomic approaches are continuing to make headways in cancer research by helping to elucidate complex signaling networks that underlie tumorigenesis and disease progression. This review describes recent advances made in the proteomic discovery of drug targets for therapeutic development. A variety of technical and methodological advances are overviewed with a critical assessment of challenges and potentials. A number of potential drug targets, such as baculoviral inhibitor of apoptosis protein repeat-containing protein 6, macrophage inhibitory cytokine 1, phosphoglycerate mutase 1, prohibitin 1, fascin, and pyruvate kinase isozyme 2 were identified in the proteomic analysis of drug-resistant cancer cells, drug action, and differential disease state tissues. Future directions for proteomics-based target identification and validation to be more translation efficient are also discussed.

Integrated genomic, transcriptomic, and RNA-interference analysis of genes in somatic copy number gains in pancreatic ductal adenocarcinoma

OBJECTIVES

This study used an integrated analysis of copy number, gene expression, and RNA interference screens for identification of putative driver genes harbored in somatic copy number gains in pancreatic ductal adenocarcinoma (PDAC).

METHODS

Somatic copy number gain data on 60 PDAC genomes were extracted from public data sets to identify genomic loci that are recurrently gained. Array-based data from a panel of 29 human PDAC cell lines were used to quantify associations between copy number and gene expression for the set of genes found in somatic copy number gains. The most highly correlated genes were assessed in a compendium of pooled short hairpin RNA screens on 27 of the same human PDAC cell lines.

RESULTS

A catalog of 710 protein-coding and 46 RNA genes mapping to 20 recurrently gained genomic loci were identified. The gene set was further refined through stringent integration of copy number, gene expression, and RNA interference screening data to uncover 34 candidate driver genes.

CONCLUSIONS

Among the candidate genes from the integrative analysis, ECT2 was found to have significantly higher essentiality in specific PDAC cell lines with genomic gains at the 3q26.3 locus, which harbors this gene, suggesting that ECT2 may play an oncogenic role in the PDAC neoplastic process.

Tissue proteomics in pancreatic cancer study: discovery, emerging technologies, and challenges

Pancreatic cancer is a highly lethal disease that is difficult to diagnose and treat. The advances in proteomics technology, especially quantitative proteomics, have stimulated a great interest in applying this technology for pancreatic cancer study. A variety of tissue proteomics approaches have been applied to investigate pancreatic cancer and the associated diseases. These studies were carried out with various goals, aiming to better understand the molecular mechanisms underlying pancreatic tumorigenesis, to improve therapeutic treatment and to identify cancer associated protein signatures, signaling events as well as interactions between cancer cells and tumor microenvironment. Here, we provide an overview on the tissue proteomics studies of pancreatic cancer reported in the past few years in light of discovery and technology development.

Strategies for discovering novel pancreatic cancer biomarkers

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related deaths in both men and women in Canada and the United States and has the most dismal survival rates among any solid malignancy. Most patients are diagnosed with pancreatic cancer once the disease has progressed into an advanced or metastatic stage, making the only curative approach of resection surgery impossible. The persistent delayed or missed diagnosis of pancreatic cancer can be attributed to the absence of early symptoms and the lack of efficient non-invasive screening or diagnostic tests in clinical practice. Given that earlier diagnosis is critical for ameliorating patients' survival rates, there is an urgent need for biomarkers with enough sensitivity and specificity to help diagnose pancreatic cancer early. Serological biomarkers provide a minimally invasive and efficient way of detecting pancreatic cancer, however, there is currently no marker with sufficient diagnostic sensitivity and specificity to identify early cancer patients. This review focuses on the classical tumor markers for PDAC as well as emerging markers. In addition, we will discuss an integrative proteomic approach used in our lab to identify a panel of biomarkers that have the potential to allow the early detection of PDAC.This article is part of a Special Issue entitled: From protein structures to clinical applications.

Novel prognostic protein markers of resectable pancreatic cancer identified by coupled shotgun and targeted proteomics using formalin-fixed paraffin-embedded tissues

Pancreatic cancer is among the most lethal malignancies worldwide. We aimed to identify novel prognostic markers by applying mass spectrometry (MS)-based proteomic analysis to formalin-fixed paraffin-embedded (FFPE) tissues. Resectable, node positive pancreatic ductal adenocarcinoma (PDAC) with poor (n = 4) and better (n = 4) outcomes, based on survival duration, with essentially the same clinicopathological backgrounds, and noncancerous pancreatic ducts (n = 5) were analyzed. Cancerous and noncancerous cells collected from FFPE tissue sections by laser microdissection (LMD) were processed for liquid chromatography (LC)-tandem MS (MS/MS). Candidate proteins were identified by semiquantitative comparison and then analyzed quantitatively using selected reaction monitoring (SRM)-based MS. To confirm the associations between candidate proteins and outcomes, we immunohistochemically analyzed a cohort of 87 cases. In result, totally 1,229 proteins were identified and 170 were selected as candidate proteins for SRM-based targeted proteomics. Fourteen proteins overexpressed in cancerous as compared to noncancerous tissue showed different expressions in the poor and better outcome groups. Among these proteins, we found that three novel proteins ECH1, OLFM4 and STML2 were overexpressed in poor group than in better group, and that one known protein GTR1 was expressed reciprocally. Kaplan-Meier analysis showed high expressions of all four proteins to correlate with significantly worse overall survival (p < 0.05). In conclusion, we identified four proteins as candidates of prognostic marker of PDAC. The combination of shotgun proteomics verified by SRM and validated by immunohistochemistry resulted in the prognostic marker discovery that will contribute the understanding of PDAC biology and therapeutic development.

The molecular and cellular heterogeneity of pancreatic ductal adenocarcinoma

Current standard therapies for pancreatic ductal adenocarcinoma have failed to attenuate the aggressiveness of this disease or confer notable improvements in survival. Previous molecular research into pancreatic cancers, along with advances in sequencing technologies, have identified many altered genes in patients with pancreatic cancer and revealed the marked genetic heterogeneity of individual tumors. Thus, the lack of success of conventional empiric therapy can be partly attributed to the underlying heterogeneity of pancreatic tumors. The genetic alterations that have been detected in pancreatic cancer range from simple mutations at the level of base pairs to complex chromosomal structural changes and rearrangements. The identification of molecular changes that are unique to an individual patient's tumors, and the subsequent development of strategies to target the tumors in a personalized approach to therapeutics, is a necessary advance to improve therapy for patients with this disease.

Proteomics portrait of archival lesions of chronic pancreatitis

Chronic pancreatitis is a chronic inflammatory disorder of the pancreas. The etiology is multi-fold, but all lead to progressive scarring and loss of pancreatic function. Early diagnosis is difficult; and the understanding of the molecular events that underlie this progressive disease is limited. In this study, we investigated differential proteins associated with mild and severe chronic pancreatitis in comparison with normal pancreas and pancreatic cancer. Paraffin-embedded formalin-fixed tissues from five well-characterized specimens each of normal pancreas (NL), mild chronic pancreatitis (MCP), severe chronic pancreatitis (SCP) and pancreatic ductal adenocarcinoma (PDAC) were subjected to proteomic analysis using a “label-free” comparative approach. Our results show that the numbers of differential proteins increase substantially with the disease severity, from mild to severe chronic pancreatitis, while the number of dysregulated proteins is highest in pancreatic adenocarcinoma. Important functional groups and biological processes associated with chronic pancreatitis and cancer include acinar cell secretory proteins, pancreatic fibrosis/stellate cell activation, glycoproteins, and inflammatory proteins. Three differential proteins were selected for verification by immunohistochemistry, including collagen 14A1, lumican and versican. Further canonical pathway analysis revealed that acute phase response signal, prothrombin activation pathway, and pancreatic fibrosis/pancreatic stellate cell activation pathway were the most significant pathways involved in chronic pancreatitis, while pathways relating to metabolism were the most significant pathways in pancreatic adenocarcinoma. Our study reveals a group of differentially expressed proteins and the related pathways that may shed light on the pathogenesis of chronic pancreatitis and the common molecular events associated with chronic pancreatitis and pancreatic adenocarcinoma.

The application of a three-step proteome analysis for identification of new biomarkers of pancreatic cancer

We searched for novel tumor markers of pancreatic cancer by three-step serum proteome analysis. Twelve serum abundant proteins were depleted using immunoaffinity columns followed by fractionation by reverse-phase high-performance liquid chromatography. Proteins in each fraction were separated by two-dimensional gel electrophoresis. Then the gel was stained by Coomassie Brilliant Blue. Protein spots in which the expression levels were significantly different between cancer and normal control were identified by LC-MS/MS. One hundred and two spots were upregulated, and 84 spots were downregulated in serum samples obtained from patients with pancreatic cancers, and 58 proteins were identified by mass spectrometry. These candidate proteins were validated using western blot analysis and enzyme-linked immunosorbent assay (ELISA). As a result of these validation process, we could confirm that the serum levels of apolipoprotein A-IV, vitamin D-binding protein, plasma retinol-binding protein 4, and tetranectin were significantly decreased in patients with pancreatic cancer.

Serum biomarker panels for the detection of pancreatic cancer

PURPOSE

Serum-biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations.

EXPERIMENTAL DESIGN

Eighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), benign pancreatic conditions (n = 144), and healthy control individuals (n = 227). Samples from each group were split randomly into training and blinded validation sets prior to analysis. A Metropolis algorithm with Monte Carlo simulation (MMC) was used to identify discriminatory biomarker panels in the training set. Identified panels were evaluated in the validation set and in patients diagnosed with colon (n = 33), lung (n = 62), and breast (n = 108) cancers.

RESULTS

Several robust profiles of protein alterations were present in sera of PDAC patients compared to the Healthy and Benign groups. In the training set (n = 160 PDAC, 74 Benign, 107 Healthy), the panel of CA 19-9, ICAM-1, and OPG discriminated PDAC patients from Healthy controls with a sensitivity/specificity (SN/SP) of 88/90%, while the panel of CA 19-9, CEA, and TIMP-1 discriminated PDAC patients from Benign subjects with an SN/SP of 76/90%. In an independent validation set (n = 173 PDAC, 70 Benign, 120 Healthy), the panel of CA 19-9, ICAM-1 and OPG demonstrated an SN/SP of 78/94% while the panel of CA19-9, CEA, and TIMP-1 demonstrated an SN/SP of 71/89%. The CA19-9, ICAM-1, OPG panel is selective for PDAC and does not recognize breast (SP = 100%), lung (SP = 97%), or colon (SP = 97%) cancer.

CONCLUSIONS

The PDAC-specific biomarker panels identified in this investigation warrant additional clinical validation to determine their role in screening targeted high-risk populations.

A multiplexed bead assay for profiling glycosylation patterns on serum protein biomarkers of pancreatic cancer

A multiplexed bead-based immunoassay was developed to simultaneously profile glycosylation patterns of serum proteins to investigate their usefulness as biomarkers for pancreatic cancer. The multiplex assay utilized protein-specific capture antibodies chemically coupled individually to beads labeled with specific amounts of fluorescent dye. Captured proteins were detected based on the extent and specific type of glycosylation as determined by successive binding of fluorescent lectin probes. Advantages to this technique include the fact that antibodies coupled to the beads had minimal nonspecific binding to the lectins ConA/SNA, avoiding the step of chemically blocking the antibody glycans and the bead assays were performed in a 96-well filter plate enabling high-throughput screening applications with improved reproducibility. The assay was tested with ConA and SNA lectins to examine the glycosylation patterns of α-1-β glycoprotein (A1BG) and serum amyloid p (SAP) component for use as potential biomarkers for the detection of pancreatic cancer based on the results from prior biomarker studies. The results showed that the SNA response on the captured A1BG protein could distinguish chronic pancreatitis samples from pancreatic cancer with a p-value of 0.035 and for the SAP protein with SNA, a p-value of 0.026 was found between the signal of normal controls and the pancreatic cancer samples. For the ConA response, a decline in the signal for both proteins in the serum samples was found to distinguish pancreatic cancer from normal controls and renal cell carnoma samples (A1BG, p<0.05; and SAP, p<0.0001).

Protein alterations associated with pancreatic cancer and chronic pancreatitis found in human plasma using global quantitative proteomics profiling

Pancreatic cancer is a lethal disease that is difficult to diagnose at early stages when curable treatments are effective. Biomarkers that can improve current pancreatic cancer detection would have great value in improving patient management and survival rate. A large scale quantitative proteomics study was performed to search for the plasma protein alterations associated with pancreatic cancer. The enormous complexity of the plasma proteome and the vast dynamic range of protein concentration therein present major challenges for quantitative global profiling of plasma. To address these challenges, multidimensional fractionation at both protein and peptide levels was applied to enhance the depth of proteomics analysis. Employing stringent criteria, more than 1300 proteins total were identified in plasma across 8-orders of magnitude in protein concentration. Differential proteins associated with pancreatic cancer were identified, and their relationship with the proteome of pancreatic tissue and pancreatic juice from our previous studies was discussed. A subgroup of differentially expressed proteins was selected for biomarker testing using an independent cohort of plasma and serum samples from well-diagnosed patients with pancreatic cancer, chronic pancreatitis, and nonpancreatic disease controls. Using ELISA methodology, the performance of each of these protein candidates was benchmarked against CA19-9, the current gold standard for a pancreatic cancer blood test. A composite marker of TIMP1 and ICAM1 demonstrate significantly better performance than CA19-9 in distinguishing pancreatic cancer from the nonpancreatic disease controls and chronic pancreatitis controls. In addition, protein AZGP1 was identified as a biomarker candidate for chronic pancreatitis. The discovery and technical challenges associated with plasma-based quantitative proteomics are discussed and may benefit the development of plasma proteomics technology in general. The protein candidates identified in this study provide a biomarker candidate pool for future investigations.

Proteomics in pancreatic cancer research

In this review, we give an overview of the actual role of proteomic technologies in the study of pancreatic cancers (PCs). We describe PC proteomics on the basis of sample origins, i.e. tissues, body fluids, and PC cell lines. As regards PC tissues, we report the identification of a number of candidate biomarkers of precursor lesions that may allow early diagnosis of this neoplasia. Moreover, we describe cytoskeletal and hypoxia-regulated proteins that confirm the involvement of cytoskeleton modifications and metabolism adaptations in carcinogenesis. We also discuss the most important biomarkers identified by proteomic analysis involved in local invasion and distant metastasis, and in the cross-talk between pancreatic tumor and the surrounding stroma. Furthermore, we report novel candidate biomarkers identified in serum, plasma, and pancreatic juice of cancer patients compared with cancer-free controls. Proteomic alterations in PC cell line models as compared to normal controls and studies on cell lines treated with drugs or new agents to understand their mechanism of pharmacological action or the onset of drug resistance are also presented. Finally, we discuss the recent improvements obtained in classical 2-DE and high-throughput proteomic strategies able to allow the overcoming of relevant proteomic drawbacks.

Database resources for proteomics-based analysis of cancer

Biological/bioinformatics databases are essential for medical and biological studies. They integrate and organize biologically related information in a structured format and provide researchers with easy access to a variety of relevant data. This review presents an overview of publicly available databases relevant to proteomics studies in cancer research. They include gene/protein expression databases, gene mutation and single nucleotide polymorphisms databases, tumor antigen databases, protein-protein interaction, and biological pathway databases. Automated information retrieval from these databases enables efficient large-scale proteomics data analysis.

Reduced plasma level of CXC chemokine ligand 7 in patients with pancreatic cancer

BACKGROUND

Early detection is essential to improve the outcome of patients with pancreatic cancer. A noninvasive and cost-effective diagnostic test using plasma/serum biomarkers would facilitate the detection of pancreatic cancer at the early stage.

METHODS

Using a novel combination of hollow fiber membrane-based low-molecular-weight protein enrichment and LC-MS-based quantitative shotgun proteomics, we compared the plasma proteome between 24 patients with pancreatic cancer and 21 healthy controls (training cohort). An identified biomarker candidate was then subjected to a large blinded independent validation (n = 237, validation cohort) using a high-density reverse-phase protein microarray.

RESULTS

Among a total of 53,009 MS peaks, we identified a peptide derived from CXC chemokine ligand 7 (CXCL7) that was significantly reduced in pancreatic cancer patients, showing an area under curve (AUC) value of 0.84 and a P value of 0.00005 (Mann-Whitney U test). Reduction of the CXCL7 protein was consistently observed in pancreatic cancer patients including those with stage I and II disease in the validation cohort (P < 0.0001). The plasma level of CXCL7 was independent from that of CA19-9 (Pearson's r = 0.289), and combination with CXCL7 significantly improved the AUC value of CA19-9 to 0.961 (P = 0.002).

CONCLUSIONS

We identified a significant decrease of the plasma CXCL7 level in patients with pancreatic cancer, and combination of CA19-9 with CXCL7 improved the discriminatory power of the former for pancreatic cancer.

IMPACT

The present findings may provide a new diagnostic option for pancreatic cancer and facilitate early detection of the disease.

Discovery of putative pancreatic cancer biomarkers using subcellular proteomics

Pancreatic cancer (PC) is a highly aggressive disease that frequently remains undetected until it has progressed to an advanced, systemic stage. Successful treatment of PC is hindered by the lack of early detection. The application of proteomic analysis to PC combined with subcellular fractionation has introduced new possibilities in the field of biomarker discovery. We utilized matched pairs of pancreas tumor and non-tumor pancreas from patients undergoing tumor resection. The tissues were treated to obtain cellular protein fractions corresponding to cytosol, membrane, nucleus and cytoskeleton. The fractions were then separated by molecular weight and digested with trypsin, followed by liquid chromatography and tandem mass spectrometry. The spectra obtained were searched using Sequest engine and combined into a single analysis file to obtain a semi-quantitative number, spectral count, using Scaffold software. We identified 2393 unique proteins in non-tumor and cancer pancreas. Utilizing PLGEM statistical analysis we determined 104 proteins were significantly changed in cancer. From these, we further validated four secreted proteins that are up-regulated in cancer and have potential for development as minimally-invasive diagnostic markers. We conclude that subcellular fractionation followed by gel electrophoresis and tandem mass spectrometry is a powerful strategy for identification of differentially expressed proteins in pancreatic cancer.

[Risk factors and early diagnosis of pancreatic cancer]

Pancreatic cancer (PC) is usually incurable. Identifying people at risk for developing PC may improve the prognosis of this entity. The main risk factors for PC are Peutz-Jeghers syndrome, hereditary pancreatitis and a history family of PC. Other factors, such as advanced age and smoking, should also be taken into account. PC screening is only useful in very high risk individuals. Tools that allow tumors to be identified in the early stages are required in order to apply appropriate curative treatments. In this scenario, only endoscopic ultrasound with cytological analysis of suspicious pancreatic lesions has proved to be useful.

Comparison of different tissue sampling methods for protein extraction from formalin-fixed and paraffin-embedded tissue specimens

AIMS

Protein extracts from formalin-fixed and paraffin-embedded (FFPE) tissue for proteomic analysis has recently gained attention. In this study, we explored the possibility to standardize tissue sampling from paraffin blocks and compared the protein extracts with those obtained from fresh frozen material.

MATERIALS AND METHODS

Fresh frozen and FFPE material was obtained from five patients with pancreatic ductal adenocarcinoma either by cutting sections with a microtome or by stamping a cylinder with tissue micro-array technology. All samples were weighed, forwarded to protein extraction and analyzed by polyacrylamide gel electrophoresis and Western blotting. Immunohistochemistry allocated proteins in tissue sections.

RESULTS

Sampling of tissue was highly reproducible, as assessed by sample weight. While protein concentrations were significantly higher in fresh frozen material compared to FFPE material, equal amounts of protein were extracted from FFPE using either paraffin sections or core cylinders in SDS-PAGE, all three procedures showed comparable protein patterns. In Western blotting, annexin I had the same molecular weight independent of the sample source and sampling procedure.

CONCLUSIONS

The sampling of FFPE specimens for protein extraction and analysis can be standardized, uncovering equal amounts of tissue and protein. In addition, the proteins extracted from FFPE tissue seem to be the same compared with those extracted from fresh frozen tissue.

Serum peptidome profiling revealed platelet factor 4 as a potential discriminating Peptide associated with pancreatic cancer

PURPOSE

Mass spectrometry-based serum peptidome profiling is a promising tool to identify novel disease-associated biomarkers, but is limited by preanalytic factors and the intricacies of complex data processing. Therefore, we investigated whether standardized sample protocols and new bioinformatic tools combined with external data validation improve the validity of peptidome profiling for the discovery of pancreatic cancer-associated serum markers.

EXPERIMENTAL DESIGN

For the discovery study, two sets of sera from patients with pancreatic cancer (n = 40) and healthy controls (n = 40) were obtained from two different clinical centers. For external data validation, we collected an independent set of samples from patients (n = 20) and healthy controls (n = 20). Magnetic beads with different surface functionalities were used for peptidome fractionation followed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). Data evaluation was carried out by comparing two different bioinformatic strategies. Following proteome database search, the matching candidate peptide was verified by MALDI-TOF MS after specific antibody-based immunoaffinity chromatography and independently confirmed by an ELISA assay.

RESULTS

Two significant peaks (m/z 3884; 5959) achieved a sensitivity of 86.3% and a specificity of 97.6% for the discrimination of patients and healthy controls in the external validation set. Adding peak m/z 3884 to conventional clinical tumor markers (CA 19-9 and CEA) improved sensitivity and specificity, as shown by receiver operator characteristics curve analysis (AUROC(combined) = 1.00). Mass spectrometry-based m/z 3884 peak identification and following immunologic quantitation revealed platelet factor 4 as the corresponding peptide.

CONCLUSIONS

MALDI-TOF MS-based serum peptidome profiling allowed the discovery and validation of platelet factor 4 as a new discriminating marker in pancreatic cancer.

Correlations between p53 gene mutations and histologic characteristics of pancreatic ductal carcinoma

OBJECTIVE

With the aim of improving early detection of pancreatic carcinoma, we attempted to make correlations among positive immunohistochemical detection of p53 expression, mutations in the p53 gene, and detailed histologic features of pancreatic carcinoma.

METHODS

Seven cases of invasive pancreatic ductal carcinoma demonstrating p53 overexpression were analyzed. Serial 4- and 20-microm sections from paraffin blocks were used for immunodetection of p53 protein and microdissection, respectively. We used direct sequencing of polymerase chain reaction at 101 p53-positive and 10 p53-negative sites to sequence exons 5 to 8 of p53 and then analyzed these results in concert with detailed histologic features.

RESULTS

Regardless of the degree of p53 overexpression, we detected p53 point mutations in all p53-positive lesions, including 22 noninvasive sites, 17 invasive areas, and 1 lymph node metastasis. No significant correlations were measured between specific p53 mutations and histologic features. Within individual tumors, the same p53 mutation was generally, but not always, detected in different areas in invasive and noninvasive lesions.

CONCLUSIONS

Our results demonstrate that p53 mutation is an early genetic event affecting a diversity of molecular pathways in pancreatic carcinogenesis and indicates a possibility of early diagnosis of pancreatic carcinoma by detecting a few p53-positive cells obtained from the pancreatic fluid.

Proteomic analyses of pancreatic cyst fluids

OBJECTIVES

There are currently no diagnostic indicators that are consistently reliable, obtainable, and conclusive for diagnosing and risk-stratifying pancreatic cysts. Proteomic analyses were performed to explore pancreatic cyst fluids to yield effective diagnostic biomarkers.

METHODS

We have prospectively recruited 20 research participants and prepared their pancreatic cyst fluids specifically for proteomic analyses. Proteomic approaches applied were as follows: (1) matrix-assisted laser-desorption-ionization time-of-flight mass spectrometry peptidomics with LC/MS/MS (HPLC-tandem mass spectrometry) protein identification; (2) 2-dimensional gel electrophoresis; (3) GeLC/MS/MS (tryptic digestion of proteins fractionated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and identified by LC/MS/MS).

RESULTS

Sequencing of more than 350 free peptides showed that exopeptidase activities rendered peptidomics of cyst fluids unreliable; protein nicking by proteases in the cyst fluids produced hundreds of protein spots from the major proteins, making 2-dimensional gel proteomics unmanageable; GeLC/MS/MS revealed a panel of potential biomarker proteins that correlated with carcinoembryonic antigen (CEA).

CONCLUSIONS

Two homologs of amylase, solubilized molecules of 4 mucins, 4 solubilized CEA-related cell adhesion molecules (CEACAMs), and 4 S100 homologs may be candidate biomarkers to facilitate future pancreatic cyst diagnosis and risk-stratification. This approach required less than 40 microL of cyst fluid per sample, offering the possibility to analyze cysts smaller than 1 cm in diameter.