Glycoprotein biomarker panel for pancreatic cancer discovered by quantitative proteomics analysis

Circulating biomarkers for early diagnosis of pancreatic cancer: facts and hopes

Pancreatic cancer (PC) is characterized by extremely high mortality and poor prognosis, which are largely ascribed to difficulties in early diagnosis and limited therapeutics. Although there is a sufficient window for intervention before preneoplastic lesions progress to invasive disease, effective early detection of PC remains difficult using current biomarkers and imaging techniques. Biomarkers with satisfactory diagnostic efficacy and convenient analysis methods are urgently required. In this review, we summarized recent advances in the identification of biomarkers in circulation for early detection of PC. A number of novel circulating biomarkers, such as metabolites, cell-free DNA (cfDNA), noncoding RNA, and exosomes, that show promising diagnostic value have been discovered using advances in sequencing techniques and "omics" analyses. Panels comprising several biomarkers may also exhibit better diagnostic performance. In the future, we need more efficient circulating biomarkers for the identification of noninvasive precursor lesions and early disease. Collaborative large-scale studies are also required to show the clinical validity and applicability of potential biomarkers.

Validation of Biomarkers for Early Detection of Pancreatic Cancer: Summary of The Alliance of Pancreatic Cancer Consortia for Biomarkers for Early Detection Workshop

Pancreatic cancer is the third leading cause of cancer death in the United States, and the 5-year relative survival for patients diagnosed with pancreatic cancer is less than 10%. Early intervention is the key to a better survival outcome. Currently, there are no biomarkers that can reliably detect pancreatic cancer at an early stage or identify precursors that are destined to progress to malignancy. The National Cancer Institute in partnership with the Kenner Family Research Fund and the Pancreatic Cancer Action Network convened a Data Jamboree on Biomarkers workshop on December 5, 2016, to discuss and evaluate existing or newly developed biomarkers and imaging methods for early detection of pancreatic cancer. The primary goal of this workshop was to determine if there are any promising biomarkers for early detection of pancreatic cancer that are ready for clinical validation. The Alliance of Pancreatic Cancer Consortia for Biomarkers for Early Detection, formed under the auspices of this workshop, will provide the common platform and the resources necessary for validation. Although none of the biomarkers evaluated seemed ready for a large-scale biomarker validation trial, a number of them had sufficiently high sensitivity and specificity to warrant additional research, especially if combined with other biomarkers to form a panel.

Profiling of different pancreatic cancer cells used as models for metastatic behaviour shows large variation in their N-glycosylation

To characterise pancreatic cancer cells from different sources which are used as model systems to study the metastatic behaviour in pancreatic ductal adenocarcinoma (PDAC), we compared the N-glycan imprint of four PDAC cells which were previously shown to differ in their galectin-4 expression and metastatic potential in vivo. Next to the sister cell lines Pa-Tu-8988S and Pa-Tu-8988T, which were isolated from the same liver metastasis of a PDAC, this included two primary PDAC cell cultures, PDAC1 and PDAC2. Additionally, we extended the N-glycan profiling to a normal, immortalized pancreatic duct cell line. Our results revealed major differences in the N-glycosylation of the different PDAC cells as well as compared to the control cell line, suggesting changes of the N-glycosylation in PDAC. The N-glycan profiles of the PDAC cells, however, differed vastly as well and demonstrate the diversity of PDAC model systems, which ultimately affects the interpretation of functional studies. The results from this study form the basis for further biological evaluation of the role of protein glycosylation in PDAC and highlight that conclusions from one cell line cannot be generalised, but should be regarded in the context of the corresponding phenotype.

Highly Sensitive Detection of Protein Biomarkers with Organic Electrochemical Transistors

The analysis of protein biomarkers is of great importance in the diagnosis of diseases. Although many convenient and low-cost electrochemical approaches have been extensively investigated, they are not sensitive enough in the detection of protein biomarkers with low concentrations in physiological environments. Here, this study reports a novel organic-electrochemical-transistor-based biosensor that can successfully detect cancer protein biomarkers with ultrahigh sensitivity. The devices are operated by detecting electrochemical activity on gate electrodes, which is dependent on the concentrations of proteins labeled with catalytic nanoprobes. The protein sensors can specifically detect a cancer biomarker, human epidermal growth factor receptor 2, down to the concentration of 10^-14 g mL^-1 , which is several orders of magnitude lower than the detection limits of previously reported electrochemical approaches. Moreover, the devices can successfully differentiate breast cancer cells from normal cells at various concentrations. The ultrahigh sensitivity of the protein sensors is attributed to the inherent amplification function of the organic electrochemical transistors. This work paves a way for developing highly sensitive and low-cost biosensors for the detection of various protein biomarkers in clinical analysis in the future.

Selective and Cleavable Extraction of Sialo-glycoproteins by Disulfide-Linked Amino-oxy-Functionalized Fe3O4 Magnetic Nanoparticles

The low abundance of sialo-glycoprotein hampered the separation, enrichment, and analysis of sialo-glycoproteins, which are critical for studying their functions. Here, we designed cleavable amino-oxy functionalized magnetic materials and employed to fast and selective isolate sialo-glycoproteins. This includes the ligation of disulfide-linked amino-oxy-functionalized magnetic nanoparticles with periodate-treated glycoproteins or cells, followed by magnetic separation. A reductive reagent could release the sialo-glycoproteins with small molecular fragments on the terminal of glycan chains, and the sialo-glycoproteins were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis. On-bead digestion of the peptides were analyzed by tandem mass spectrometry. The results indicated that this method could selectively separate the majority of cell-surface sialo-glycoproteins.

Recent advances in proteomic profiling of pancreatic ductal adenocarcinoma and the road ahead

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers worldwide. However, there remain many unmet clinical needs, from diagnosis to treatment strategies. The inherent complexity of the molecular characteristics of PDAC has made it difficult to meet these challenges, rendering proteomic profiling of PDAC a critical area of research. Area covered: In this review, we present recent advances in mass spectrometry (MS) and its current application in proteomic studies on PDAC. In addition, we discuss future directions for research that can efficiently incorporate current MS-based technologies that address key issues of PDAC proteomics. Expert commentary: Compared with other cancer studies, little progress has been made in PDAC proteomics, perhaps attributed to the difficulty in performing in-depth and large-scale clinical studies on PDAC. However, recent advances in mass spectrometry can advance PDAC proteomics past the fundamental research stage.

LC-MS/MS isomeric profiling of permethylated N-glycans derived from serum haptoglobin of hepatocellular carcinoma (HCC) and cirrhotic patients

Early stage detection and cancer treatment demand the identification of reliable biomarkers. Over the past decades, efforts have been devoted to assess the variation of glycosylation level as well as the glycan structures of proteins in blood or serum, associated with the development and/or progression of several cancers, including liver. Herein, an LC-MS/MS-based analysis was conducted to define the glycosylation patterns of haptoglobin glycoprotein derived from sera collected from cirrhotic and hepatocellular carcinoma (HCC) patients. The haptoglobin samples were extracted from serum using an antibody-immobilized column prior to the release of N-glycans. A comparison of non-isomeric and isomeric permethylated glycan forms was achieved using C18 and porous graphitic carbon (PGC) columns, respectively. In the case of C18-LC-MS/MS analysis, 25 glycan structures were identified of which 10 sialylated structures were found to be statistically significant between the two cohorts. Also, 8 out of 34 glycan structures identified by PGC-LC-MS/MS were found to be statistically significant, suggesting that isomeric distributions of a particular glycan composition were different in abundances between the two cohorts. The glycan isoform patterns distinguished early stage HCC from cirrhotic patients. Both retention times and tandem mass spectra were utilized to determine the specific isomeric glycan structures. All of the glycan isomers, which were statistically significant, were either branch fucosylated or composed of α-2,6 linked sialic acid moieties. The result of this study demonstrates the potential importance of isomeric separation for defining disease prompted aberrant glycan changes. The levels of several glycan isoforms effectively distinguished early stage HCC from cirrhosis.

Deep-Dive Targeted Quantification for Ultrasensitive Analysis of Proteins in Nondepleted Human Blood Plasma/Serum and Tissues

Mass spectrometry-based targeted proteomics (e.g., selected reaction monitoring, SRM) is emerging as an attractive alternative to immunoassays for protein quantification. Recently we have made significant progress in SRM sensitivity for enabling quantification of low nanograms per milliliter to sub-naograms per milliliter level proteins in nondepleted human blood plasma/serum without affinity enrichment. However, precise quantification of extremely low abundance proteins (e.g., ≤ 100 pg/mL in blood plasma/serum) using targeted proteomics approaches still remains challenging, especially for these samples without available antibodies for enrichment. To address this need, we have developed an antibody-independent deep-dive SRM (DD-SRM) approach that capitalizes on multidimensional high-resolution reversed-phase liquid chromatography (LC) separation for target peptide separation and enrichment combined with precise selection of target peptide fractions of interest, significantly improving SRM sensitivity by ∼5 orders of magnitude when compared to conventional LC-SRM. Application of DD-SRM to human serum and tissue provides precise quantification of endogenous proteins at the ∼10 pg/mL level in nondepleted serum and at <10 copies per cell level in tissue. Thus, DD-SRM holds great promise for precisely measuring extremely low abundance proteins or protein modifications, especially when high-quality antibodies are not available.

Comparative proteomic profiling of the serum differentiates pancreatic cancer from chronic pancreatitis

Finland ranks sixth among the countries having highest incidence rate of pancreatic cancer with mortality roughly equaling incidence. The average age of diagnosis for pancreatic cancer is 69 years in Nordic males, whereas the average age of diagnosis of chronic pancreatitis is 40–50 years, however, many cases overlap in age. By radiology, the evaluation of a pancreatic mass, that is, the differential diagnosis between chronic pancreatitis and pancreatic cancer is often difficult. Preoperative needle biopsies are difficult to obtain and are demanding to interpret. New blood based biomarkers are needed. The accuracy of the only established biomarker for pancreatic cancer, CA 19‐9 is rather poor in differentiating between benign and malignant mass of the pancreas. In this study, we have performed mass spectrometry analysis (High Definition MS^E) of serum samples from patients with chronic pancreatitis (13) and pancreatic cancer (22). We have quantified 291 proteins and performed detailed statistical analysis such as principal component analysis, orthogonal partial least square discriminant analysis and receiver operating curve analysis. The proteomic signature of chronic pancreatitis versus pancreatic cancer samples was able to separate the two groups by multiple statistical techniques. Some of the enriched pathways in the proteomic dataset were LXR/RXR activation, complement and coagulation systems and inflammatory response. We propose that multiple high‐confidence biomarker candidates in our pilot study including Inter‐alpha‐trypsin inhibitor heavy chain H2 (Area under the curve, AUC: 0.947), protein AMBP (AUC: 0.951) and prothrombin (AUC: 0.917), which should be further evaluated in larger patient series as potential new biomarkers for differential diagnosis.

Key biological processes driving metastatic spread of pancreatic cancer as identified by multi-omics studies

Pancreatic ductal adenocarcinoma (PDAC) is an extremely aggressive malignancy, characterized by a high metastatic burden, already at the time of diagnosis. The metastatic potential of PDAC is one of the main reasons for the poor outcome next to lack of significant improvement in effective treatments in the last decade. Key mutated driver genes, such as activating KRAS mutations, are concordantly expressed in primary and metastatic tumors. However, the biology behind the metastatic potential of PDAC is not fully understood. Recently, large-scale omic approaches have revealed new mechanisms by which PDAC cells gain their metastatic potency. In particular, genomic studies have shown that multiple heterogeneous subclones reside in the primary tumor with different metastatic potential. The development of metastases may be correlated to a more mesenchymal transcriptomic subtype. However, for cancer cells to survive in a distant organ, metastatic sites need to be modulated into pre-metastatic niches. Proteomic studies identified the influence of exosomes on the Kuppfer cells in the liver, which could function to prepare this tissue for metastatic colonization. Phosphoproteomics adds an extra layer to the established omic techniques by unravelling key functional signaling. Future studies integrating results from these large-scale omic approaches will hopefully improve PDAC prognosis through identification of new therapeutic targets and patient selection tools. In this article, we will review the current knowledge on the biology of PDAC metastasis unravelled by large scale multi-omic approaches.

FGF7/FGFR2 signal promotes invasion and migration in human gastric cancer through upregulation of thrombospondin-1

Fibroblast growth factor 7 (FGF7) is a mesenchyme-specific heparin-binding growth factor that binds FGF receptor 2 (FGFR2) to regulate numerous cellular and physiological processes. FGF7/FGFR2 signal is associated with gastric cancer progression. In the present study, we investigated the molecular mechanism by which FGF7/FGFR2 promotes invasion and migration in human gastric cancer. We first demonstrated that increased FGFR2 expression in human gastric cancer tissues was significantly associated with tumor depth and clinical stage in human gastric cancer tissues. Thrombospondin 1 (THBS1) is an extracellular glycoprotein that plays multiple roles in cell-matrix and cell-cell interactions. Increased expression of THBS1 significantly correlated with tumor differentiation. FGFR2 and THBS1 expression were both increased in cancer tissues as compared with adjacent normal tissues and their expression was positively correlated. In vitro, FGF7 stimulation of cell invasion and migration was partially suppressed by the FGFR2 knockdown. In addition, FGF7/FGFR2 upregulated THBS1, and cell invasion and migration were decreased by knockdown of THBS1. Furthermore, the PI3K/Akt/mTOR signaling pathway was predominantly responsible for FGF7/FGFR2-induced THBS1 upregulation. Taken together, our data suggest that FGF7/FGFR2/THBS1 is associated with the regulation of invasion and migration in human gastric cancer.

Sparse Proteomics Analysis - a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data

BACKGROUND

High-throughput proteomics techniques, such as mass spectrometry (MS)-based approaches, produce very high-dimensional data-sets. In a clinical setting one is often interested in how mass spectra differ between patients of different classes, for example spectra from healthy patients vs. spectra from patients having a particular disease. Machine learning algorithms are needed to (a) identify these discriminating features and (b) classify unknown spectra based on this feature set. Since the acquired data is usually noisy, the algorithms should be robust against noise and outliers, while the identified feature set should be as small as possible.

RESULTS

We present a new algorithm, Sparse Proteomics Analysis (SPA), based on the theory of compressed sensing that allows us to identify a minimal discriminating set of features from mass spectrometry data-sets. We show (1) how our method performs on artificial and real-world data-sets, (2) that its performance is competitive with standard (and widely used) algorithms for analyzing proteomics data, and (3) that it is robust against random and systematic noise. We further demonstrate the applicability of our algorithm to two previously published clinical data-sets.

A protein corona-enabled blood test for early cancer detection

Pancreatic cancer is a very aggressive malignancy that is often diagnosed in the advanced stages, with the implication that long-term survivors are extremely rare. Thus, developing new methods for the early detection of pancreatic cancer is an urgent task for current research. To date, nanotechnology offers unprecedented opportunities for cancer therapeutics and diagnosis. The aim of this study is the development of a new pancreatic cancer diagnostic technology based on the exploitation of the nano-bio-interactions between nanoparticles and blood samples. In this study, blood samples from 20 pancreatic cancer patients and 5 patients without malignancy were allowed to interact with designed lipid nanoparticles, leading to the formation of a hard "protein corona" at the nanoparticle surface. After isolation, the protein patterns were characterized by sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS PAGE). We found that the protein corona of pancreatic cancer patients was much more enriched than that of healthy individuals. Statistical analysis of SDS-PAGE results allowed us to discriminate between healthy and pancreatic cancer patients with a total discriminate correctness rate of 88%.

Glycans and glycoproteins as specific biomarkers for cancer

Protein glycosylation and other post-translational modifications are involved in potentially all aspects of human growth and development. Defective glycosylation has adverse effects on human physiological conditions and accompanies many chronic and infectious diseases. Altered glycosylation can occur at the onset and/or during tumor progression. Identifying these changes at early disease stages may aid in making decisions regarding treatments, as early intervention can greatly enhance survival. This review highlights some of the efforts being made to identify N- and O-glycosylation profile shifts in cancer using mass spectrometry. The analysis of single or panels of potential glycoprotein cancer markers are covered. Other emerging technologies such as global glycan release and site-specific glycosylation analysis and quantitation are also discussed. Graphical Abstract Steps involved in the biomarker discovery.

Proteomic strategies in the search for novel pancreatic cancer biomarkers and drug targets: recent advances and clinical impact

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers; despite a low incidence rate it is the fourth leading cause of cancer-related death in the world. Improvement of the diagnosis, prognosis and treatment remains the main focus of pancreatic cancer research. Rapid developments in proteomic technologies has improved our understanding of the pancreatic cancer proteome. Here, the authors summarise the recent proteomic strategies undertaken in the search for: novel biomarkers for early diagnosis, pancreatic cancer-specific proteins which may be used for novel targeted therapies and proteins which may be useful for monitoring disease progression post-therapy. Recent advances and findings discussed here provide great promise of having a significant clinical impact and improving the outcome of patients with this malignancy.

The Promises of Quantitative Proteomics in Precision Medicine

Precision medicine approach has a potential to ensure optimum efficacy and safety of drugs at individual patient level. Physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models could play a significant role in precision medicine by predicting interindividual variability in drug disposition and response. In order to develop robust PBPK/PD models, it is imperative that the critical physiological parameters affecting drug disposition and response and their variability are precisely characterized. Currently used PBPK/PD modeling software, for example, Simcyp and Gastroplus, encompass information such as organ volumes, blood flows to organs, body fat composition, glomerular filtration rate, etc. However, the information on the interindividual variability of the majority of the proteins associated with PK and PD, for example, drug metabolizing enzymes, transporters, and receptors, are not fully incorporated into these PBPK modeling platforms. Such information is significant because the population factors such as age, genotype, disease, and gender can affect abundance or activity of these proteins. To fill this critical knowledge gap, mass spectrometry-based quantitative proteomics has emerged as an important technique to characterize interindividual variability in the protein abundance of drug metabolizing enzymes, transporters, and receptors. Integration of these quantitative proteomics data into in silico PBPK/PD modeling tools will be crucial toward precision medicine.

A procedure for the analysis of site-specific and structure-specific fucosylation in alpha-1-antitrypsin

A MS-based methodology has been developed for analysis of core-fucosylated versus antennary-fucosylated glycosites in glycoproteins. This procedure is applied to the glycoprotein alpha-1-antitrypsin (A1AT), which contains both core- and antennary-fucosylated glycosites. The workflow involves digestion of intact glycoproteins into glycopeptides, followed by double digestion with sialidase and galactosidase. The resulting glycopeptides with truncated glycans were separated using an off-line HILIC (hydrophilic interaction liquid chromatography) separation where multiple fractions were collected at various time intervals. The glycopeptides in each fraction were treated with PNGase F and then divided into halves. One half of the sample was applied for peptide identification while the other half was processed for glycan analysis by derivatizing with a meladrazine reagent followed by MS analysis. This procedure provided site-specific identification of glycosylation sites and the ability to distinguish core fucosylation and antennary fucosylation via a double digestion and a mass profile scan. Both core and antennary fucosylation are shown to be present on various glycosites in A1AT.

Dysbindin as a novel biomarker for pancreatic ductal adenocarcinoma identified by proteomic profiling

Pancreatic adenocarcinoma (PDAC) is known to have a poor prognosis partly because of lack of effective biomarkers. In the test set, we investigated dysbindin (DTNBP1) as a potential biomarker for PDAC by comparing preoperative and postoperative serum mass spectrometry (MS) proteomic profilings. Of the included 50 PDAC patients, 42 (positivity of 84.0%) detected a lower MS peak in postoperative serums than preoperative ones which was then identified as dysbindin. In the verification set, receiver operating characteristics (ROC) were used to assess diagnostic efficiency. 550 participants were included in the verification set [250 with PDAC, 80 with benign biliary obstruction (BBO), 70 with chronic pancreatitis (CP) and 150 healthy donors (HD)]. Dysbindin was increased in PDAC patient sera than in all controls. ROC curves revealed the optimum diagnostic cutoff for dysbindin was 699.16 pg/ml [area under curve (AUC) 0.849 (95% CI 0.812-0.885), sensitivity 81.9% and specificity 84.7%]. Raised concentration of dysbindin in sera could differentiate PDAC from BBO, CP and HD. Moreover, dysbindin maintained its diagnostic accuracy for PDAC patients who were CA19-9 negative [AUC 0.875 (95% CI 0.804-0.945), sensitivity 83.0%, specificity 89.0%] and for patients with benign biliary obstruction [AUC 0.849 (95% CI 0.803-0.894), sensitivity 82.3%, specificity 84.0%].Our discovery of dysbindin may complement measurement of CA19-9 in the diagnosis of PDAC and help to discriminate PDAC from other pancreatic diseases or begin biliary obstruction.

Integration of Breast Cancer Secretomes with Clinical Data Elucidates Potential Serum Markers for Disease Detection, Diagnosis, and Prognosis

Cancer cells secrete factors that influence adjacent cell behavior and can lead to enhanced proliferation and metastasis. To better understand the role of these factors in oncogenesis and disease progression, estrogen and progesterone receptor positive MCF-7 cells, triple negative breast cancer MDA-MB-231, DT22, and DT28 cells, and MCF-10A non-transformed mammary epithelial cells were grown in 3D cultures. A special emphasis was placed on triple negative breast cancer since these tumors are highly aggressive and no targeted treatments are currently available. The breast cancer cells secreted factors of variable potency that stimulated proliferation of the relatively quiescent MCF-10A cells. The conditioned medium from each cell line was subjected to mass spectrometry analysis and a variety of secreted proteins were identified including glycolytic enzymes, proteases, protease inhibitors, extracellular matrix proteins, and insulin-like growth factor binding proteins. An investigation of the secretome from each cell line yielded clues about strategies used for breast cancer proliferation and metastasis. Some of the proteins we identified may be useful in the development of a serum-based test for breast cancer detection, diagnosis, prognosis, and monitoring.

Decreased Serum Thrombospondin-1 Levels in Pancreatic Cancer Patients Up to 24 Months Prior to Clinical Diagnosis: Association with Diabetes Mellitus

PURPOSE

Identification of serum biomarkers enabling earlier diagnosis of pancreatic ductal adenocarcinoma (PDAC) could improve outcome. Serum protein profiles in patients with preclinical disease and at diagnosis were investigated.

EXPERIMENTAL DESIGN

Serum from cases up to 4 years prior to PDAC diagnosis and controls (UKCTOCS,n= 174) were studied, alongside samples from patients diagnosed with PDAC, chronic pancreatitis, benign biliary disease, type 2 diabetes mellitus, and healthy subjects (n= 298). Isobaric tags for relative and absolute quantification (iTRAQ) enabled comparisons of pooled serum from a test set (n= 150). Validation was undertaken using multiple reaction monitoring (MRM) and/or Western blotting in all 472 human samples and samples from a KPC mouse model.

RESULTS

iTRAQ identified thrombospondin-1 (TSP-1) as reduced preclinically and in diagnosed samples. MRM confirmed significant reduction in levels of TSP-1 up to 24 months prior to diagnosis. A combination of TSP-1 and CA19-9 gave an AUC of 0.86, significantly outperforming both markers alone (0.69 and 0.77, respectively;P< 0.01). TSP-1 was also decreased in PDAC patients compared with healthy controls (P< 0.05) and patients with benign biliary obstruction (P< 0.01). Low levels of TSP-1 correlated with poorer survival, preclinically (P< 0.05) and at clinical diagnosis (P< 0.02). In PDAC patients, reduced TSP-1 levels were more frequently observed in those with confirmed diabetes mellitus (P< 0.01). Significantly lower levels were also observed in PDAC patients with diabetes compared with individuals with type 2 diabetes mellitus (P= 0.01).

CONCLUSIONS

Circulating TSP-1 levels decrease up to 24 months prior to diagnosis of PDAC and significantly enhance the diagnostic performance of CA19-9. The influence of diabetes mellitus on biomarker behavior should be considered in future studies.

Improved Pancreatic Adenocarcinoma Diagnosis in Jaundiced and Non-Jaundiced Pancreatic Adenocarcinoma Patients through the Combination of Routine Clinical Markers Associated to Pancreatic Adenocarcinoma Pathophysiology

BACKGROUND

There is still no reliable biomarker for the diagnosis of pancreatic adenocarcinoma. Carbohydrate antigen 19-9 (CA 19-9) is a tumor marker only recommended for pancreatic adenocarcinoma follow-up. One of the clinical problems lies in distinguishing between this cancer and other benign pancreatic diseases such as chronic pancreatitis. In this study we will assess the value of panels of serum molecules related to pancreatic cancer physiopathology to determine whether alone or in combination could help to discriminate between these two pathologies.

METHODS

CA 19-9, carcinoembryonic antigen (CEA), C-reactive protein, albumin, insulin growth factor-1 (IGF-1) and IGF binding protein-3 were measured using routine clinical analyzers in a cohort of 47 pancreatic adenocarcinoma, 20 chronic pancreatitis and 15 healthy controls.

RESULTS

The combination of CA 19-9, IGF-1 and albumin resulted in a combined area under the curve (AUC) of 0.959 with 93.6% sensitivity and 95% specificity, much higher than CA 19-9 alone. An algorithm was defined to classify the patients as chronic pancreatitis or pancreatic cancer with the above specificity and sensitivity. In an independent validation group of 20 pancreatic adenocarcinoma and 13 chronic pancreatitis patients, the combination of the four molecules classified correctly all pancreatic adenocarcinoma and 12 out of 13 chronic pancreatitis patients.

CONCLUSIONS

Although this panel of markers should be validated in larger cohorts, the high sensitivity and specificity values and the convenience to measure these parameters in clinical laboratories shows great promise for improving pancreatic adenocarcinoma diagnosis.

Contributions of immunoaffinity chromatography to deep proteome profiling of human biofluids

Human biofluids, especially blood plasma or serum, hold great potential as the sources of candidate biomarkers for various diseases; however, the enormous dynamic range of protein concentrations in biofluids represents a significant analytical challenge for detecting promising low-abundance proteins. Over the last decade, various immunoaffinity chromatographic methods have been developed and routinely applied for separating low-abundance proteins from the high- and moderate-abundance proteins, thus enabling much more effective detection of low-abundance proteins. Herein, we review the advances of immunoaffinity separation methods and their contributions to the proteomic applications in human biofluids. The limitations and future perspectives of immunoaffinity separation methods are also discussed.

Translational Research and Plasma Proteomic in Cancer

Proteomics is a recent field of research in molecular biology that can help in the fight against cancer through the search for biomarkers that can detect this disease in the early stages of its development. Proteomic is a speedily growing technology, also thanks to the development of even more sensitive and fast mass spectrometry analysis. Although this technique is the most widespread for the discovery of new cancer biomarkers, it still suffers of a poor sensitivity and insufficient reproducibility, essentially due to the tumor heterogeneity. Common technical shortcomings include limitations in the sensitivity of detecting low abundant biomarkers and possible systematic biases in the observed data. Current research attempts are trying to develop high-resolution proteomic instrumentation for high-throughput monitoring of protein changes that occur in cancer. In this review, we describe the basic features of the proteomic tools which have proven to be useful in cancer research, showing their advantages and disadvantages. The application of these proteomic tools could provide early biomarkers detection in various cancer types and could improve the understanding the mechanisms of tumor growth and dissemination.

Solvent interaction analysis as a proteomic approach to structure-based biomarker discovery and clinical diagnostics

Proteins have several measurable features in biological fluids that may change under pathological conditions. The current disease biomarker discovery is mostly based on protein concentration in the sample as the measurable feature. Changes in protein structures, such as post-translational modifications and in protein-partner interactions are known to accompany pathological processes. Changes in glycosylation profiles are well-established for many plasma proteins in various types of cancer and other diseases. The solvent interaction analysis method is based on protein partitioning in aqueous two-phase systems and is highly sensitive to changes in protein structure and protein-protein- and protein-partner interactions while independent of the protein concentration in the biological sample. It provides quantitative index: partition coefficient representing changes in protein structure and interactions with partners. The fundamentals of the method are presented with multiple examples of applications of the method to discover and monitor structural protein biomarkers as disease-specific diagnostic indicators.

Biomarker Development for Intraductal Papillary Mucinous Neoplasms Using Multiple Reaction Monitoring Mass Spectrometry

Intraductal papillary mucinous neoplasm (IPMN) is a common precursor of pancreatic cancer (PC). Much clinical attention has been directed toward IPMNs due to the increase in the prevalence of PC. The diagnosis of IPMN depends primarily on a radiological examination, but the diagnostic accuracy of this tool is not satisfactory, necessitating the development of accurate diagnostic biomarkers for IPMN to prevent PC. Recently, high-throughput targeted proteomic quantification methods have accelerated the discovery of biomarkers, rendering them powerful platforms for the evolution of IPMN diagnostic biomarkers. In this study, a robust multiple reaction monitoring (MRM) pipeline was applied to discovery and verify IPMN biomarker candidates in a large cohort of plasma samples. Through highly reproducible MRM assays and a stringent statistical analysis, 11 proteins were selected as IPMN marker candidates with high confidence in 184 plasma samples, comprising a training (n = 84) and test set (n = 100). To improve the discriminatory power, we constructed a six-protein panel by combining marker candidates. The multimarker panel had high discriminatory power in distinguishing between IPMN and controls, including other benign diseases. Consequently, the diagnostic accuracy of IPMN can be improved dramatically with this novel plasma-based panel in combination with a radiological examination.

Mass-Selected Site-Specific Core-Fucosylation of Serum Proteins in Hepatocellular Carcinoma

A mass spectrometry-based methodology has been developed to screen for changes in site-specific core-fucosylation (CF) of serum proteins in early stage HCC with different etiologies. The methods involve depletion of high-abundance proteins, trypsin digestion of medium-to-low-abundance proteins into peptides, iTRAQ labeling, and Lens culinaris Agglutinin (LCA) enrichment of CF peptides, followed by endoglycosidase F3 digestion before mass spectrometry analysis. 1300 CF peptides from 613 CF proteins were identified from patients sera, where 20 CF peptides were differentially expressed in alcohol (ALC)-related HCC samples compared with ALC-related cirrhosis samples and 26 CF peptides changed in hepatitis C virus (HCV)-related HCC samples compared with HCV-related cirrhosis samples. Among these, we found three CF peptides from fibronectin upregulated in ALC-related HCC samples compared with ALC-related cirrhosis samples with an AUC (area under the curve) value of 0.89 at site 1007 with a specificity of 85.7% at a sensitivity of 92.9% (generated with 10-fold cross-validation). When combined with the AFP index, the AUC value reached to 0.92 with a specificity of 92.9% at a sensitivity of 100%, significantly improved compared to that with AFP alone (LR test p < 0.001). In HCV-related samples, the CF level of cadherin-5 at site 61 showed the best AUC value of 0.75 but was not as promising as that of fibronectin site 1007 for ALC-related samples. The CF peptides of fibronectin may serve as potential biomarkers for early stage HCC screening in ALC-related cirrhosis patients.

Original insights on thrombospondin-1-related antireceptor strategies in cancer

Thrombospondin-1 (TSP-1) is a large matricellular glycoprotein known to be overexpressed within tumor stroma in several cancer types. While mainly considered as an endogenous angiogenesis inhibitor, TSP-1 exhibits multifaceted functionalities in a tumor context depending both on TSP-1 concentration as well as differential receptor expression by cancer cells and on tumor-associated stromal cells. Besides, the complex modular structure of TSP-1 along with the wide variety of its soluble ligands and membrane receptors considerably increases the complexity of therapeutically targeting interactions involving TSP-1 ligation of cell-surface receptors. Despite the pleiotropic nature of TSP-1, many different antireceptor strategies have been developed giving promising results in preclinical models. However, transition to clinical trials often led to nuanced outcomes mainly due to frequent severe adverse effects. In this review, we will first expose the intricate and even sometimes opposite effects of TSP-1-related signaling on tumor progression by paying particular attention to modulation of angiogenesis and tumor immunity. Then, we will provide an overview of current developments and prospects by focusing particularly on the cell-surface molecules CD47 and CD36 that function as TSP-1 receptors; including antibody-based approaches, therapeutic gene modulation and the use of peptidomimetics. Finally, we will discuss original approaches specifically targeting TSP-1 domains, as well as innovative combination strategies with a view to producing an overall anticancer response.

A quantitative proteomics analysis of MCF7 breast cancer stem and progenitor cell populations

Accumulating evidence has demonstrated that breast cancers are initiated and develop from a small population of stem-like cells termed cancer stem cells (CSCs). These cells are hypothesized to mediate tumor metastasis and contribute to therapeutic resistance. However, the molecular regulatory networks responsible for maintaining CSCs in an undifferentiated state have yet to be elucidated. In this study, we used CSC markers to isolate pure breast CSCs fractions (ALDH+ and CD44+CD24- cell populations) and the mature luminal cells (CD49f-EpCAM+) from the MCF7 cell line. Proteomic analysis was performed on these samples and a total of 3304 proteins were identified. A label-free quantitative method was applied to analyze differentially expressed proteins. Using the criteria of greater than twofold changes and p value <0.05, 305, 322 and 98 proteins were identified as significantly different in three pairwise comparisons of ALDH+ versus CD44+CD24-, ALDH+ versus CD49f-EpCAM+ and CD44+CD24- versus CD49f-EpCAM+, respectively. Pathway analysis of differentially expressed proteins by Ingenuity Pathway Analysis (IPA) revealed potential molecular regulatory networks that may regulate CSCs. Selected differential proteins were validated by Western blot assay and immunohistochemical staining. The use of proteomics analysis may increase our understanding of the underlying molecular mechanisms of breast CSCs. This may be of importance in the future development of anti-CSC therapeutics.

Mass spectrometric analysis of the cell surface N-glycoproteome by combining metabolic labeling and click chemistry

Cell surface N-glycoproteins play extraordinarily important roles in cell-cell communication, cell-matrix interactions, and cellular response to environmental cues. Global analysis is exceptionally challenging because many N-glycoproteins are present at low abundances and effective separation is difficult to achieve. Here, we have developed a novel strategy integrating metabolic labeling, copper-free click chemistry, and mass spectrometry (MS)-based proteomics methods to analyze cell surface N-glycoproteins comprehensively and site-specifically. A sugar analog containing an azido group, N-azidoacetylgalactosamine, was fed to cells to label glycoproteins. Glycoproteins with the functional group on the cell surface were then bound to dibenzocyclooctyne-sulfo-biotin via copper-free click chemistry under physiological conditions. After protein extraction and digestion, glycopeptides with the biotin tag were enriched by NeutrAvidin conjugated beads. Enriched glycopeptides were deglycosylated with peptide-N-glycosidase F in heavy-oxygen water, and in the process of glycan removal, asparagine was converted to aspartic acid and tagged with 18O for MS analysis. With this strategy, 144 unique N-glycopeptides containing 152 N-glycosylation sites were identified in 110 proteins in HEK293T cells. As expected, 95% of identified glycoproteins were membrane proteins, which were highly enriched. Many sites were located on important receptors, transporters, and cluster of differentiation proteins. The experimental results demonstrated that the current method is very effective for the comprehensive and site-specific identification of the cell surface N-glycoproteome and can be extensively applied to other cell surface protein studies.

Large-scale identification of core-fucosylated glycopeptide sites in pancreatic cancer serum using mass spectrometry

Glycosylation has significant effects on protein function and cell metastasis, which are important in cancer progression. It is of great interest to identify site-specific glycosylation in search of potential cancer biomarkers. However, the abundance of glycopeptides is low compared to that of nonglycopeptides after trypsin digestion of serum samples, and the mass spectrometric signals of glycopeptides are often masked by coeluting nonglycopeptides due to low ionization efficiency. Selective enrichment of glycopeptides from complex serum samples is essential for mass spectrometry (MS)-based analysis. Herein, a strategy has been optimized using LCA enrichment to improve the identification of core-fucosylation (CF) sites in serum of pancreatic cancer patients. The optimized strategy was then applied to analyze CF glycopeptide sites in 13 sets of serum samples from pancreatic cancer, chronic pancreatitis, healthy controls, and a standard reference. In total, 630 core-fucosylation sites were identified from 322 CF proteins in pancreatic cancer patient serum using an Orbitrap Elite mass spectrometer. Further data analysis revealed that 8 CF peptides exhibited a significant difference between pancreatic cancer and other controls, which may be potential diagnostic biomarkers for pancreatic cancer.

Biomarkers for early diagnosis of pancreatic cancer

Pancreatic ductal adenocarcinoma is an aggressive malignancy with a 5-year survival rate of approximately 5%. The lack of established strategies for early detection contributes to this poor prognosis. Although several novel candidate biomarkers have been proposed for earlier diagnosis, none have been adopted into routine clinical use. In this review, the authors examine the challenges associated with finding new pancreatic cancer diagnostic biomarkers and explore why translation of biomarker research for patient benefit has thus far failed. The authors also review recent progress and highlight advances in the understanding of the biology of pancreatic cancer that may lead to improvements in biomarker detection and implementation.

Integrated transcriptomic and proteomic analysis of the global response of Synechococcus to high light stress

Sufficient light is essential for the growth and physiological functions of photosynthetic organisms, but prolonged exposure to high light (HL) stress can cause cellular damage and ultimately result in the death of these organisms. Synechococcus sp. PCC 7002 (hereafter Synechococcus 7002) is a unicellular cyanobacterium with exceptional tolerance to HL intensities. However, the molecular mechanisms involved in HL response by Synechococcus 7002 are not well understood. Here, an integrated RNA sequencing transcriptomic and quantitative proteomic analysis was performed to investigate the cellular response to HL in Synechococcus 7002. A total of 526 transcripts and 233 proteins were identified to be differentially regulated under HL stress. Data analysis revealed major changes in mRNAs and proteins involved in the photosynthesis pathways, resistance to light-induced damage, DNA replication and repair, and energy metabolism. A set of differentially expressed mRNAs and proteins were validated by quantitative RT-PCR and Western blot, respectively. Twelve genes differentially regulated under HL stress were selected for knockout generation and growth analysis of these mutants led to the identification of key genes involved in the response of HL in Synechococcus 7002. Taken altogether, this study established a model for global response mechanisms to HL in Synechococcus 7002 and may be valuable for further studies addressing HL resistance in photosynthetic organisms.

Potential for proteomic approaches in determining efficacy biomarkers following administration of fish oils rich in omega-3 fatty acids: application in pancreatic cancers

Pancreatic cancer is a disease with a significantly poor prognosis. Despite modern advances in other medical, surgical, and oncologic therapy, the outcome from pancreatic cancer has improved little over the last 40 years. To improve the management of this difficult disease, trials investigating the use of dietary and parenteral fish oils rich in omega-3 (ω-3) fatty acids, exhibiting proven anti-inflammatory and anticarcinogenic properties, have revealed favorable results in pancreatic cancers. Proteomics is the large-scale study of proteins that attempts to characterize the complete set of proteins encoded by the genome of an organism and that, with the use of sensitive mass spectrometric-based techniques, has allowed high-throughput analysis of the proteome to aid identification of putative biomarkers pertinent to given disease states. These biomarkers provide useful insight into potentially discovering new markers for early detection or elucidating the efficacy of treatment on pancreatic cancers. Here, our review identifies potential proteomic-based biomarkers in pancreatic cancer relating to apoptosis, cell proliferation, angiogenesis, and metabolic regulation in clinical studies. We also reviewed proteomic biomarkers from the administration of ω-3 fatty acids that act on similar anticarcinogenic pathways as above and reflect that proteomic studies on the effect of ω-3 fatty acids in pancreatic cancer will yield favorable results.

Introducing biomarker panel in esophageal, gastric, and colon cancers; a proteomic approach

Cancer research is an attractive field in molecular biology and medicine. By applying large-scale tools such as advanced genomics and proteomics, cancer diagnosis and treatment have been improved greatly. Cancers of esophagus, gastric, and colon accounted for major health problem globally. Biomarker panel could bring out the accuracy for cancer evaluation tests as it can suggest a group of candidate molecules specified to particular malignancy in a way that distinguishing malignant tumors from benign, differentiating from other diseases, and identifying each stages with high specificity and sensitivity. In this review, a systematic search of unique protein markers reported by several proteomic literatures are classified in their specific cancer type group as novel panels for feasible accurate malignancy diagnosis and treatment. About thousands of introduced proteins were studied; however, a small number of them belonged to a specific kind of malignancy. In conclusion, despite the fact that combinatorial biomarkers appear to be hopeful, more evaluation of them is crucial to achieve the suitable biomarker panel for clinical application. This effort needs more investigations and researches for finding a specific and sensitive panel.

Exploring the glycoproteomics landscape with advanced MS technologies

The advance of glycoproteomic technologies has offered unique insights into the importance of glycosylation in determining the functional roles of a protein within a cell. Biologically active glycoproteins include the categories of enzymes, hormones, proteins involved in cell proliferation, cell membrane proteins involved in cell-cell recognition, and communication events or secreted proteins, just to name a few. The recent progress in analytical instrumentation, methodologies, and computational approaches has enabled a detailed exploration of glycan structure, connectivity, and heterogeneity, underscoring the staggering complexity of the glycome repertoire in a cell. A variety of approaches involving the use of spectroscopy, MS, separation, microfluidic, and microarray technologies have been used alone or in combination to tackle the glycoproteome challenge, the research results of these efforts being captured in an overwhelming number of annual publications. This work is aimed at reviewing the major developments and accomplishments in the field of glycoproteomics, with focus on the most recent advancements (2012-2014) that involve the use of capillary separations and MS detection.

A pilot study to develop a diagnostic test for pancreatic ductal adenocarcinoma based on differential expression of select miRNA in plasma and bile

OBJECTIVES

Accurate peripheral markers for the diagnosis of pancreatic ductal adenocarcinoma (PDAC) are lacking. We measured the differential expression of select microRNAs (miRNAs) in plasma and bile among patients with PDAC, chronic pancreatitis (CP), and controls.

METHODS

We identified patients (n=215) with treatment-naive PDAC (n=77), CP with bile/pancreatic duct pathology (n=67), and controls (n=71) who had been prospectively enrolled in a Pancreatobiliary Biorepository at the time of endoscopic retrograde cholangiopancreatography or endoscopic ultrasound. Controls were patients with choledocholithiasis but normal pancreata. The sample was separated into training (n=95) and validation (n=120) cohorts to establish and then test the performance of PDAC Signature Panels in diagnosing PDAC. The training cohort (n=95) included age-matched patients with PDAC, CP, and controls. Panels were derived from the differential expression of 10 candidate miRNAs in plasma or bile. We selected miRNAs having excellent accuracy for inclusion in regression models.

RESULTS

Using the training cohort, we confirmed the differential expression of 9/10 miRNAs in plasma (miR-10b, -30c, -106b, -132, -155, -181a, -181b, -196a, and -212) and 7/10 in bile (excluding miR-21, -132, and -181b). Of these, five (miR-10b, -155, -106b, -30c, and -212) had excellent accuracy for distinguishing PDAC. In the training and validation cohorts, the sensitivity/specificity for a PDAC Panel derived from plasma was 95/100% and 100/100%, respectively; in bile, these were 96/100% and 100/100%.

CONCLUSIONS

Increased expression of miRNA-10b, -155, and -106b in plasma appears highly accurate in diagnosing PDAC. Additional studies are needed to confirm this Panel and explore its value as a prognostic test.

Quantitative analysis of single amino acid variant peptides associated with pancreatic cancer in serum by an isobaric labeling quantitative method

Single amino acid variations are highly associated with many human diseases. The direct detection of peptides containing single amino acid variants (SAAVs) derived from nonsynonymous single nucleotide polymorphisms (SNPs) in serum can provide unique opportunities for SAAV associated biomarker discovery. In the present study, an isobaric labeling quantitative strategy was applied to identify and quantify variant peptides in serum samples of pancreatic cancer patients and other benign controls. The largest number of SAAV peptides to date in serum including 96 unique variant peptides were quantified in this quantitative analysis, of which five variant peptides showed a statistically significant difference between pancreatic cancer and other controls (p-value < 0.05). Significant differences in the variant peptide SDNCEDTPEAGYFAVAVVK from serotransferrin were detected between pancreatic cancer and controls, which was further validated by selected reaction monitoring (SRM) analysis. The novel biomarker panel obtained by combining α-1-antichymotrypsin (AACT), Thrombospondin-1 (THBS1) and this variant peptide showed an excellent diagnostic performance in discriminating pancreatic cancer from healthy controls (AUC = 0.98) and chronic pancreatitis (AUC = 0.90). These results suggest that large-scale analysis of SAAV peptides in serum may provide a new direction for biomarker discovery research.

Diagnostic approach to pancreatic cysts

PURPOSE OF REVIEW

Diagnosis of pancreatic cysts remains challenging due to limitations of currently available radiologic and endoscopic tools. The diagnostic approach should focus on identifying mucinous and malignant cysts. Mucinous cysts require further differentiation to allow appropriate management.

RECENT FINDINGS

Although the overall rate of malignant pancreatic cysts is low, it remains higher than the general population. MRI with magnetic resonance cholangiopancreatography is the preferred imaging modality for pancreatic cysts. Attempts to improve diagnostic yield of endoscopic ultrasound-guided fine needle aspiration include performing cyst wall cytology and DNA analysis. The 2012 international consensus guidelines for mucinous cystic neoplasm and intraductal papillary mucinous neoplasm are superior to the original 2006 guidelines, although issues include the relatively poor ability to diagnose malignant cysts leading to unnecessary surgeries and the de-emphasis of cyst size. Cyst size remains an important predictor of malignancy. Translational research involving genomics, microRNA, proteomics, and metabolomics holds promise for improved biomarkers. Endoscopic innovations may safely aid in cyst diagnosis.

SUMMARY

Incremental improvements in pancreatic cyst diagnosis have occurred with new biomarkers and endoscopic tools requiring validation in large-scale studies.

Immunoproteomic profiling of Saccharomyces cerevisiae systemic infection in a murine model

Saccharomyces cerevisiae is considered a safe microorganism widely used as a dietary supplement. However, in the latest decades several cases of S. cerevisiae infections have been reported. Recent studies in a murine model of systemic infection have also revealed the virulence of some S. cerevisiae dietary strains. Here we use an immunoproteomic approach based on protein separation by 2D-PAGE followed by Western-blotting to compare the serological response against a virulent dietary and a non-virulent laboratory strains leading to the identification of highly different patterns of antigenic proteins. Thirty-six proteins that elicit a serological response in mice have been identified. Most of them are involved in stress responses and metabolic pathways. Their selectivity as putative biomarkers for S. cerevisiae infections was assessed by testing sera from S. cerevisiae-infected mice against Candida albicans and C. glabrata proteins. Some chaperones and metabolic proteins showed cross-reactivity. We also compare the S. cerevisiae immunodetected proteins with previously described C. albicans antigens. The results point to the stress-related proteins Ahp1, Yhb1 and Oye2, as well as the glutamine synthetase Gln1 and the oxysosterol binding protein Kes1 as putative candidates for being evaluated as biomarkers for diagnostic assays of S. cerevisiae infections.

BIOLOGICAL SIGNIFICANCE

S. cerevisiae can cause opportunistic infections, and therefore, a precise diagnosis of fungal infections is necessary. This immunoproteomic analysis of sera from a model murine infection with a virulent dietary S. cerevisiae strain has been shown to be a source of candidate proteins for being evaluated as biomarkers to develop assays for diagnosis of S. cerevisiae infections. To our knowledge, this is the first study devoted to the identification of S. cerevisiae immunogenic proteins and the results allowed the proposal of five antigens to be further investigated.