The prevalence and nature of glycan alterations on specific proteins in pancreatic cancer patients revealed using antibody-lectin sandwich arrays

Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data

Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

Relative Quantification and Higher-Order Modeling of the Plasma Glycan Cancer Burden Ratio in Ovarian Cancer Case-Control Samples

An early-stage, population-wide biomarker for ovarian cancer (OVC) is essential to reverse its high mortality rate. Aberrant glycosylation by OVC has been reported, but studies have yet to identify an N-glycan with sufficiently high specificity. We curated a human biorepository of 82 case-control plasma samples, with 27%, 12%, 46%, and 15% falling across stages I-IV, respectively. For relative quantitation, glycans were analyzed by the individuality normalization when labeling with glycan hydrazide tags (INLIGHT) strategy for enhanced electrospray ionization, MS/MS analysis. Sixty-three glycan cancer burden ratios (GBRs), defined as the log10 ratio of the case-control extracted ion chromatogram abundances, were calculated above the limit of detection. The final GBR models, built using stepwise forward regression, included three significant terms: OVC stage, normalized mean GBR, and tag chemical purity; glycan class, fucosylation, or sialylation were not significant variables. After Bonferroni correction, seven N-glycans were identified as significant (p < 0.05), and after false discovery rate correction, an additional four glycans were determined to be significant (p < 0.05), with one borderline (p = 0.05). For all N-glycans, the vectors of the effects from stages II-IV were sequentially reversed, suggesting potential biological changes in OVC morphology or in host response.

Mammalian protein glycosylation--structure versus function

Carbohydrates fulfil many common as well as extremely important functions in nature. They show a variety of molecular displays--e.g., free mono-, oligo-, and polysaccharides, glycolipids, proteoglycans, glycoproteins, etc.--with particular roles and localizations in living organisms. Structure-specific peculiarities are so many and diverse that it becomes virtually impossible to cover them all from an analytical perspective. Hence this manuscript, focused on mammalian glycosylation, rather than a complete list of analytical descriptors or recognized functions for carbohydrate structures, comprehensively reviews three central issues in current glycoscience, namely (i) structural analysis of glycoprotein glycans, covering both classical and novel approaches for teasing out the structural puzzle as well as potential pitfalls of these processes; (ii) an overview of functions attributed to carbohydrates, covering from monosaccharide to complex, well-defined epitopes and full glycans, including post-glycosylational modifications, and (iii) recent technical advances allowing structural identification of glycoprotein glycans with simultaneous assignation of biological functions.

Cancer serum biomarkers based on aberrant post-translational modifications of glycoproteins: Clinical value and discovery strategies

Due to the increase in life expectancy in the last decades, as well as changes in lifestyle, cancer has become one of the most common diseases both in developed and developing countries. Early detection remains the most promising approach to improve long-term survival of cancer patients and this may be achieved by efficient screening of biomarkers in biological fluids. Great efforts have been made to identify specific alterations during oncogenesis. Changes at the cellular glycosylation profiles are among such alterations. The "glycosylation machinery" of cells is affected by malignant transformation due to the altered expression of glycogens, leading to changes in glycan biosynthesis and diversity. Alterations in the post-translational modifications of proteins that occur in cancer result in the expression of antigenically distinct glycoproteins. Therefore, these aberrant and cancer-specific glycoproteins and the autoantibodies that are produced in response to their presence constitute targets for cancer biomarkers' search. Different strategies have been implemented for the discovery of cancer glycobiomarkers and are herein reviewed, along with their potentialities and limitations. Practical issues related with serum analysis are also addressed, as well as the challenges that this area faces in the near future.

Lectin Microarray-Based Sero-Biomarker Verification Targeting Aberrant O-Linked Glycosylation on Mucin 1

Glycoform of mucin 1 (MUC1) in cancerous cells changes markedly with cell differentiation, and thus, qualitative detection and verification of the MUC1 glycosylation changes have potential diagnostic value. We have developed an ultrasensitive method to detect the changes in cholangiocarcinoma (CC), which produces MUC1, and applied it in the diagnostics development. The focused glycan analysis using 43-lectin-immobilized microarray could obtain the glycan profiles of sialylated MUC1 in 5 μL of sera. The high-throughput analysis detected disease-specific alterations of glycosylation, and the statistical analysis confirmed that use of Wisteria floribunda agglutinin (WFA) alone produced a diagnostic score sufficient for discriminating 33 CC cases from 40 hepatolithiasis patients and 48 normal controls (p < 0.0001). The CC-related glycosylation change was verified by the lectin-antibody sandwich ELISA with WFA in two cohorts: (1) 78 Opisthorchis viverrini infected patients without CC and 78 with CC, (2) 33 CC patients and 40 hepatolithiasis patients (the same cohort used for the above lectin microarray). The WFA positivity distinguished patients with CC (opisthorchiasis: p < 0.0001, odds ratio = 1.047; hepatolithiasis: p = 0.0002, odds ratio = 1.018). Sensitive detection of qualitative alterations of sialylated MUC1 glycosylation is indispensable for the development of our glycodiagnostic test for CC.

Upregulation of glycans containing 3' fucose in a subset of pancreatic cancers uncovered using fusion-tagged lectins

The fucose post-translational modification is frequently increased in pancreatic cancer, thus forming the basis for promising biomarkers, but a subset of pancreatic cancer patients does not elevate the known fucose-containing biomarkers. We hypothesized that such patients elevate glycan motifs with fucose in linkages and contexts different from the known fucose-containing biomarkers. We used a database of glycan array data to identify the lectins CCL2 to detect glycan motifs with fucose in a 3' linkage; CGL2 for motifs with fucose in a 2' linkage; and RSL for fucose in all linkages. We used several practical methods to test the lectins and determine the optimal mode of detection, and we then tested whether the lectins detected glycans in pancreatic cancer patients who did not elevate the sialyl-Lewis A glycan, which is upregulated in ∼75% of pancreatic adenocarcinomas. Patients who did not upregulate sialyl-Lewis A, which contains fucose in a 4' linkage, tended to upregulate fucose in a 3' linkage, as detected by CCL2, but they did not upregulate total fucose or fucose in a 2' linkage. CCL2 binding was high in cancerous epithelia from pancreatic tumors, including areas negative for sialyl-Lewis A and a related motif containing 3' fucose, sialyl-Lewis X. Thus, glycans containing 3' fucose may complement sialyl-Lewis A to contribute to improved detection of pancreatic cancer. Furthermore, the use of panels of recombinant lectins may uncover details about glycosylation that could be important for characterizing and detecting cancer.

Glycan motif profiling reveals plasma sialyl-lewis x elevations in pancreatic cancers that are negative for sialyl-lewis A

The sialyl-Lewis A (sLeA) glycan forms the basis of the CA19-9 assay and is the current best biomarker for pancreatic cancer, but because it is not elevated in ∼25% of pancreatic cancers, it is not useful for early diagnosis. We hypothesized that sLeA-low tumors secrete glycans that are related to sLeA but not detectable by CA19-9 antibodies. We used a method called motif profiling to predict that a structural isomer of sLeA called sialyl-Lewis X (sLeX) is elevated in the plasma of some sLeA-low cancers. We corroborated this prediction in a set of 48 plasma samples and in a blinded set of 200 samples. An antibody sandwich assay formed by the capture and detection of sLeX was elevated in 13 of 69 cancers that were not elevated in sLeA, and a novel hybrid assay of sLeA capture and sLeX detected 24 of 69 sLeA-low cancers. A two-marker panel based on combined sLeA and sLeX detection differentiated 109 pancreatic cancers from 91 benign pancreatic diseases with 79% accuracy (74% sensitivity and 78% specificity), significantly better than sLeA alone, which yielded 68% accuracy (65% sensitivity and 71% specificity). Furthermore, sLeX staining was evident in tumors that do not elevate plasma sLeA, including those with poorly differentiated ductal adenocarcinoma. Thus, glycan-based biomarkers could characterize distinct subgroups of patients. In addition, the combined use of sLeA and sLeX, or related glycans, could lead to a biomarker panel that is useful in the clinical diagnosis of pancreatic cancer. Précis: This paper shows that a structural isomer of the current best biomarker for pancreatic cancer, CA19-9, is elevated in the plasma of patients who are low in CA19-9, potentially enabling more comprehensive detection and classification of pancreatic cancers.

The detection and discovery of glycan motifs in biological samples using lectins and antibodies: new methods and opportunities

Recent research has uncovered unexpected ways that glycans contribute to biology, as well as new strategies for combatting disease using approaches involving glycans. To make full use of glycans for clinical applications, we need more detailed information on the location, nature, and dynamics of glycan expression in vivo. Such studies require the use of specimens acquired directly from patients. Effective studies of clinical specimens require low-volume assays, high precision measurements, and the ability to process many samples. Assays using affinity reagents-lectins and glycan-binding antibodies-can meet these requirements, but further developments are needed to make the methods routine and effective. Recent advances in the use of glycan-binding proteins involve improved determination of specificity using glycan arrays; the availability of databases for mining and analyzing glycan array data; lectin engineering methods; and the ability to quantitatively interpret lectin measurements. Here, we describe many of the challenges and opportunities involved in the application of these new approaches to the study of biological samples. The new tools hold promise for developing methods to improve the outcomes of patients afflicted with diseases characterized by aberrant glycan expression.

Glycosylation characteristics of colorectal cancer

Glycans on proteins and lipids are known to alter with malignant transformation. The study of these may contribute to the discovery of biomarkers and treatment targets as well as understanding of cancer biology. We here describe the change of glycosylation specifically defining colorectal cancer with view on N-glycans, O-glycans, and glycosphingolipid glycans in colorectal cancer cells and tissues as well as patient sera. Glycan alterations observed in colon cancer include increased β1,6-branching and correlating higher abundance of (poly-)N-acetyllactosamine extensions of N-glycans as well as an increase in (truncated) high-mannose type glycans, while bisected structures decrease. Colorectal cancer-associated O-glycan changes are predominated by reduced expression of core 3 and 4 glycans, whereas higher levels of core 1 glycans, (sialyl) T-antigen, (sialyl) Tn-antigen, and a generally higher density of O-glycans are observed. Specific changes for glycosphingolipid glycans are lower abundances of disialylated structures as well as globo-type glycosphingolipid glycans with exception of Gb3. In general, alterations affecting all discussed glycan types are increased sialylation, fucosylation as well as (sialyl) Lewis-type antigens and type-2 chain glycans. As a consequence, interactions with glycan-binding proteins can be affected and the biological function and cellular consequences of the altered glycosylation with regard to tumorigenesis, metastasis, modulation of immunity, and resistance to antitumor therapy will be discussed. Finally, analytical approaches aiding in the field of glycomics will be reviewed with focus on binding assays and mass spectrometry.

Bile proteome in health and disease

The study of bile proteins could improve the understanding of physiological processes involved in the regulation of the hepato-biliary system. Researchers have tried for years to investigate the bile proteome but, until recently, only a few tens of proteins were known. The advent of proteomics, availing of large-scale analytical devices paired with potent bioinformatic resources, lately allowed the identification of thousands of proteins in bile. Nevertheless, the knowledge of their role in the hepato-biliary system still represents almost a "blank page in the book of physiology." In this review, we first guide the reader through the historical phases of the analysis of bile protein content, emphasizing the recent progresses achieved through the use of proteomic techniques. Thereafter, we deeply explore the involvement of bile proteins in health and disease, with a particular focus on the discovery of biomarkers for biliary tract malignancies.

Detection of distinct glycosylation patterns on human γ-glutamyl transpeptidase 1 using antibody-lectin sandwich array (ALSA) technology

Background

γ-Glutamyl transpeptidase 1 (GGT1) is an N-glycosylated membrane protein that catabolizes extracellular glutathione and other γ-glutamyl-containing substrates. In a variety of disease states, including tumor formation, the enzyme is shed from the surface of the cell and can be detected in serum. The structures of the N-glycans on human GGT1 (hGGT1) have been shown to be tissue-specific. Tumor-specific changes in the glycans have also been observed, suggesting that the N-glycans on hGGT1 would be an important biomarker for detecting tumors and monitoring their progression during treatment. However, the large quantities of purified protein required to fully characterize the carbohydrate content poses a significant challenge for biomarker development. Herein, we investigated a new antibody-lectin sandwich array (ALSA) platform to determine whether this microanalytical technique could be applied to the characterization of N-glycan content of hGGT1 in complex biological samples.

Results

Our data show that hGGT1 can be isolated from detergent extracted membrane proteins by binding to the ALSA platform. Probing hGGT1 with lectins enables characterization of the N-glycans. We probed hGGT1 from normal human liver tissue, normal human kidney tissue, and hGGT1 expressed in the yeast Pichia pastoris. The lectin binding patterns obtained with the ALSA platform are consistent with the hGGT1 N-glycan composition obtained from previous large-scale hGGT1 N-glycan characterizations from these sources. We also validate the implementation of the Microcystis aeruginosa lectin, microvirin, in this platform and provide refined evidence for its efficacy in specifically recognizing high-mannose-type N-glycans, a class of carbohydrate modification that is distinctive of hGGT1 expressed by many tumors.

Conclusion

Using this microanalytical approach, we provide proof-of-concept for the implementation of ALSA in conducting high-throughput studies aimed at investigating disease-related changes in the glycosylation patterns on hGGT1 with the goal of enhancing clinical diagnoses and targeted treatment regimens.

Electronic supplementary material

The online version of this article (doi:10.1186/s12896-014-0101-0) contains supplementary material, which is available to authorized users.

Profiling of concanavalin A-binding glycoproteins in human hepatic stellate cells activated with transforming growth factor-β1

Glycoproteins play important roles in maintaining normal cell functions depending on their glycosylations. Our previous study indicated that the abundance of glycoproteins recognized by concanavalin A (ConA) was increased in human hepatic stellate cells (HSCs) following activation by transforming growth factor-β1 (TGF-β1); however, little is known about the ConA-binding glycoproteins (CBGs) of HSCs. In this study, we employed a targeted glycoproteomics approach using lectin-magnetic particle conjugate-based liquid chromatography-tandem mass spectrometry to compare CBG profiles between LX-2 HSCs with and without activation by TGF-β1, with the aim of discovering novel CBGs and determining their possible roles in activated HSCs. A total of 54 and 77 proteins were identified in the quiescent and activated LX-2 cells, respectively. Of the proteins identified, 14.3% were glycoproteins and 73.3% were novel potential glycoproteins. Molecules involved in protein processing in the endoplasmic reticulum (e.g., calreticulin) and calcium signaling (e.g., 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase β-2 [PLCB2]) were specifically identified in activated LX-2 cells. Additionally, PLCB2 expression was upregulated in the cytoplasm of the activated LX-2 cells, as well as in the hepatocytes and sinusoidal cells of liver cirrhosis tissues. In conclusion, the results of this study may aid future investigations to find new molecular mechanisms involved in HSC activation and antifibrotic therapeutic targets.

MUC16: molecular analysis and its functional implications in benign and malignant conditions

MUC16 is a high-molecular-weight glycoprotein that is expressed by the various epithelial cell surfaces of the human body to protect the cell layer from a myriad of insults. It is the largest mucin known to date, with an ∼22,152 aa sequence. Structurally, MUC16 is characterized into 3 distinct domains: the amino terminal, the tandem repeat, and the carboxyl terminal domain, with each domain having unique attributes. The extracellular portion of MUC16 is shed into the bloodstream and serves as a biomarker for diagnosing and monitoring patients with cancer; however, its functional role in cancer is yet to be elucidated. Several factors contribute to this challenge, which include the large protein size; the extensive glycosylation that the protein undergoes, which confers functional heterogeneity; lack of specific antibodies that detect the unique domains of MUC16; and the existence of splicing variants. Despite these limitations, MUC16 has been established as a molecule of significant application in cancer. Hence, in this review, we discuss the various aspects of MUC16, which include its discovery, structure, and biological significance both in benign and malignant conditions with an attempt to dissect its functional relevance

Discovery of specific metastasis-related N-glycan alterations in epithelial ovarian cancer based on quantitative glycomics

Generally, most of ovarian cancer cannot be detected until large scale and remote metastasis occurs, which is the major cause of high mortality in ovarian cancer. Therefore, it is urgent to discover metastasis-related biomarkers for the detection of ovarian cancer in its occult metastasis stage. Altered glycosylation is a universal feature of malignancy and certain types of glycan structures are well-known markers for tumor progressions. Thus, this study aimed to reveal specific changes of N-glycans in the secretome of the metastatic ovarian cancer. We employed a quantitative glycomics approach based on metabolic stable isotope labeling to compare the differential N-glycosylation of secretome between an ovarian cancer cell line SKOV3 and its high metastatic derivative SKOV3-ip. Intriguingly, among total 17 N-glycans identified, the N-glycans with bisecting GlcNAc were all significantly decreased in SKOV3-ip in comparison to SKOV3. This alteration in bisecting GlcNAc glycoforms as well as its corresponding association with ovarian cancer metastatic behavior was further validated at the glycotransferase level with multiple techniques including real-time PCR, western blotting, transwell assay, lectin blotting and immunohistochemistry analysis. This study illustrated metastasis-related N-glycan alterations in ovarian cancer secretome in vitro for the first time, which is a valuable source for biomarker discovery as well. Moreover, N-glycans with bisecting GlcNAc shed light on the detection of ovarian cancer in early peritoneal metastasis stage which may accordingly improve the prognosis of ovarian cancer patients.

Quantitative glycoproteomics analysis reveals changes in N-glycosylation level associated with pancreatic ductal adenocarcinoma

Glycosylation plays an important role in epithelial cancers, including pancreatic ductal adenocarcinoma. However, little is known about the glycoproteome of the human pancreas or its alterations associated with pancreatic tumorigenesis. Using quantitative glycoproteomics approach, we investigated protein N-glycosylation in pancreatic tumor tissue in comparison with normal pancreas and chronic pancreatitis tissue. The study lead to the discovery of a roster of glycoproteins with aberrant N-glycosylation level associated with pancreatic cancer, including mucin-5AC (MUC5AC), carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5), insulin-like growth factor binding protein (IGFBP3), and galectin-3-binding protein (LGALS3BP). Pathway analysis of cancer-associated aberrant glycoproteins revealed an emerging phenomenon that increased activity of N-glycosylation was implicated in several pancreatic cancer pathways, including TGF-β, TNF, NF-kappa-B, and TFEB-related lysosomal changes. In addition, the study provided evidence that specific N-glycosylation sites within certain individual proteins can have significantly altered glycosylation occupancy in pancreatic cancer, reflecting the complexity of the molecular mechanisms underlying cancer-associated glycosylation events.

High-Throughput Analysis of Plasma Hybrid Markers for Early Detection of Cancers

Biomarkers for the early detection of cancer in the general population have to perform with high sensitivity and specificity in order to prevent the costs associated with over-diagnosis. There are only a few current tissue or blood markers that are recommended for generalized cancer screening. Despite the recognition that combinations of multiple biomarkers will likely improve their utility, biomarker panels are usually limited to a single class of molecules. Tissues and body fluids including plasma and serum contain not only proteins, DNA and microRNAs that are differentially expressed in cancers but further cancer specific information might be gleaned by comparing different classes of biomolecules. For example, the level of a certain microRNA might be related to the level of a particular protein in a cancer specific manner. Proteins might have cancer-specific post-translational modifications (e.g., phosphorylation or glycosylation) or lead to the generation of autoantibodies. Most currently approved biomarkers are glycoproteins. Autoantibodies can be produced as a host's early surveillance response to cancer-specific proteins in pre-symptomatic and pre-diagnostic stages of cancer. Thus, measurement of the level of a protein, the level of its glycosylation or phosphorylation and whether autoantibodies are produced to it can yield multi-dimensional information on each protein. We consider specific proteins that show consistent cancer-specific changes in two or three of these measurements to be "hybrid markers". We hypothesize these markers will suffer less variation between different individuals since one component can act to "standardize" the other measurement. As a proof of principle, a 180 plasma sample set consisting of 120 cases (60 colon cancers and 60 adenomas) and 60 controls were analyzed using our high-density antibody array for changes in their protein, IgG-complex and sialyl-Lewis A (SLeA) modified proteins. At p < 0.05, expression changes in 1,070 proteins, 49 IgG-complexes (11 present in the protein list) and 488 Lewis X-modified proteins (57 on the protein list) were observed. The biomarkers significant on both lists are potential hybrid markers. Thus, plasma hybrid markers have the potential to create a new class of early detection markers of cancers.

Mapping PAM4 (clivatuzumab), a monoclonal antibody in clinical trials for early detection and therapy of pancreatic ductal adenocarcinoma, to MUC5AC mucin

BACKGROUND

PAM4, an antibody that has high specificity for pancreatic ductal adenocarcinoma (PDAC), compared to normal pancreas, benign lesions of the pancreas, and cancers originating from other tissues, is being investigated as a biomarker for early detection, as well as antibody-targeted imaging and therapy. Therefore, the identity of the antigen bound by this monoclonal antibody (MAb) can provide information leading to improved use of the antibody. Prior results suggested the antigen is a mucin-type glycoprotein rich in cysteine disulfide bridges that provide stable conformation for the PAM4-epitope.

METHODS

Indirect and sandwich enzyme immunoassays (EIA) were performed to compare and contrast the reactivity of PAM4 with several anti-mucin antibodies having known reactivity to specific mucin species (e.g., MUC1, MUC4, MUC5AC, etc.). Studies designed to block reactivity of PAM4 with its specific antigen also were performed.

RESULTS

We demonstrate that MAbs 2-11 M1 and 45 M1, each reactive with MUC5AC, are able to provide signal in a heterologous sandwich immunoassay where PAM4 is the capture antibody. Further, we identify MAbs 21 M1, 62 M1, and 463 M1, each reactive with MUC5AC, as inhibiting the reaction of PAM4 with its specific epitope. MAbs directed to MUC1, MUC3, MUC4, MUC16 and CEACAM6 are not reactive with PAM4-captured antigen, nor are they able to block the reaction of PAM4 with its antigen.

CONCLUSIONS

These data implicate MUC5AC as a specific mucin species to which PAM4 is reactive. Furthermore, this realization may allow for the improvement of the current PAM4 serum-based immunoassay for detection of early-stage PDAC by the application of anti-MUC5AC MAbs as probes in this sandwich EIA.

Pancreatitis-diabetes-pancreatic cancer: summary of an NIDDK-NCI workshop

A workshop sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and the National Cancer Institute (NCI) on "Pancreatitis-Diabetes-Pancreatic Cancer" focused on the risk factors of chronic pancreatitis (CP) and diabetes mellitus (DM) on the development of pancreatic ductal adenocarcinoma (PDAC). Sessions were held on (a) an overview of the problem of PDAC; (b) CP as a risk factor of PDAC; (c) DM as a risk factor of PDAC; (d) pancreatogenic, or type 3c, DM; (e) genomic associations of CP, DM, and PDAC; (f) surveillance of high-risk populations and early detection of PDAC; and (g) effects of DM treatment on PDAC. Recent data and current understandings of the mechanisms of CP- and DM-associated factors on PDAC development were discussed, and a detailed review of the possible risks of DM treatment on the development of PDAC was provided by representatives from academia, industry, and the Food and Drug Administration. The current status of possible biomarkers of PDAC and surveillance strategies for high-risk populations were discussed, and the gaps in knowledge and opportunities for further research were elucidated. A broad spectrum of expertise of the speakers and the discussants provided an unusually productive workshop, the highlights of which are summarized in the accompanying article.

Discovery of sialyl Lewis A and Lewis X modified protein cancer biomarkers using high density antibody arrays

We report on a high-dimensional method to globally profile glycoproteins that are modified with sialyl Lewis A or Lewis X glycans. Specifically, glycoproteins in serum or plasma are fractionated on a high-density antibody microarray (i.e., each are localized to their specific antibody spot) and are specifically detected via fluorescently labeled anti-sialyl Lewis A or anti-Lewis X antibodies with quantification in a microarray scanner. Non-glycosylated proteins or glycoproteins with other glycan motifs do not interfere with this assay. The whole process is very rapid and applicable for high-throughput screening without the need for purification of glycoproteins from the samples. Using these methods, sialyl Lewis A or Lewis X moieties were found to be expressed on many previously unreported secreted or membrane associated proteins. Furthermore, the combination of sialyl Lewis A or Lewis X content with protein level increased the ability of certain glycoproteins to distinguish 30 patients with stage III and IV colon cancer from 60 control samples. Thus, this highly sensitive method is capable of discovering novel specific glycan modifications on proteins, many of which will likely be useful for disease detection and monitoring.

BIOLOGICAL SIGNIFICANCE

In this paper, we show that we can detect cancer-specific glycan modifications on thousands of proteins using a high-density antibody array paired with a glycan specific antibody to probe the bound glycoproteins. To our knowledge, our array is by far the largest and densest that has ever been used for global profiling of specific glycan modification on proteins. Analysis of colon cancer patient plasma for sialyl Lewis A and Lewis X modifications revealed previously unknown protein carriers of these modifications and significant increases in these specific glycans on some proteins in people with cancer versus healthy controls, suggesting this method could be used to discover novel biomarkers.

Mucins in pancreatic cancer and its microenvironment

Pancreatic cancer remains a lethal malignancy with poor prognosis owing to therapeutic resistance, frequent recurrence and the absence of treatment strategies that specifically target the tumour and its supporting stroma. Deregulated cell-surface proteins drive neoplastic transformations and are envisioned to mediate crosstalk between the tumour and its microenvironment. Emerging studies have elaborated on the role of mucins in diverse biological functions, including enhanced tumorigenicity, invasiveness, metastasis and drug resistance through their characteristic O-linked and N-linked oligosaccharides (glycans), extended structures and unique domains. Multiple mucin domains differentially interact and regulate different components of the tumour microenvironment. This Review discusses: the expression pattern of various mucins in the pancreas under healthy, inflammatory, and cancerous conditions; the context-dependent attributes of mucins that differ under healthy and pathological conditions; the contribution of the tumour microenvironment in pancreatic cancer development and/or progression; diagnostic and/or prognostic efficacy of mucins; and mucin-based therapeutic strategies. Overall, this information should help to delineate the intricacies of pancreatic cancer by exploring the family of mucins, which, through various mechanisms in both tumour cells and the microenvironment, worsen disease outcome.

Using antibody arrays to measure protein abundance and glycosylation: considerations for optimal performance

Antibody arrays provide a valuable method for obtaining multiple protein measurements from small volumes of biological samples. Antibody arrays can be designed to target not only core protein abundances (relative or absolute abundances, depending on the availability of standards for calibration), but also posttranslational modifications, provided antibodies or other affinity reagents are available to detect them. Glycosylation is a common modification that has important and diverse functions in both normal and disease biology. Significant progress has been made in developing methods for measuring glycan levels on multiple specific proteins using antibody arrays and glycan-binding reagents. This unit describes practical approaches for developing, optimizing, and using antibody array assays to determine both protein abundance and glycosylation state. Low-volume arrays can be used to reduce sample consumption, and a new way to improve the binding strength of particular glycan-binding reagents through multimerization is discussed. These methods can be useful for a wide range of biological studies in which glycosylation may change and/or affect protein function.

Prediction of glycan motifs using quantitative analysis of multi-lectin binding: Motifs on MUC1 produced by cultured pancreatic cancer cells

PURPOSE

Lectins are valuable tools for detecting specific glycans in biological samples, but the interpretation of the measurements can be ambiguous due to the complexities of lectin specificities. Here, we present an approach to improve the accuracy of interpretation by converting lectin measurements into quantitative predictions of the presence of various glycan motifs.

EXPERIMENTAL DESIGN

The conversion relies on a database of analyzed glycan array data that provides information on the specificities of the lectins for each of the motifs. We tested the method using measurements of lectin binding to glycans on glycan arrays and then applied the method to predicting motifs on the protein mucin 1 (MUC1) expressed in eight different pancreatic cancer cell lines.

RESULTS

The combined measurements from several lectins were more accurate than individual measurements for predicting the presence or absence of motifs on arrayed glycans. The analysis of MUC1 revealed that each cell line expressed a unique pattern of glycoforms, and that the glycoforms significantly differed between MUC1 collected from conditioned media and MUC1 collected from cell lysates.

CONCLUSIONS AND CLINICAL RELEVANCE

This new method could provide more accurate analyses of glycans in biological sample and make the use of lectins more practical and effective for a broad range of researchers.

Specific glycoforms of MUC5AC and endorepellin accurately distinguish mucinous from nonmucinous pancreatic cysts

Specific protein glycoforms may be uniquely informative about the pathological state of a cyst and may serve as accurate biomarkers. Here we tested that hypothesis using antibody-lectin sandwich arrays in broad screens of protein glycoforms and in targeted studies of candidate markers. We profiled 16 different glycoforms of proteins captured by 72 different antibodies in cyst fluid from mucinous and nonmucinous cysts (n = 22), and we then tested a three-marker panel in 22 addition samples and 22 blinded samples. Glycan alterations were not widespread among the proteins and were mainly confined to MUC5AC and endorepellin. Specific glycoforms of these proteins, defined by reactivity with wheat germ agglutinin and a blood group H antibody, were significantly elevated in mucinous cysts, whereas the core protein levels were not significantly elevated. A three-marker panel based on these glycoforms distinguished mucinous from nonmucinous cysts with 93% accuracy (89% sensitivity, 100% specificity) in a prevalidation sample set (n = 44) and with 91% accuracy (87% sensitivity, 100% specificity) in independent, blinded samples (n = 22). Targeted lectin measurements and mass spectrometry analyses indicated that the higher wheat germ agglutinin and blood group H reactivity was due to oligosaccharides terminating in GlcNAc or N-acetyl-lactosamine with occasional α1,2-linked fucose. The results show that MUC5AC and endorepellin glycoforms may be highly specific and sensitive biomarkers for the differentiation of mucinous from nonmucinous pancreatic cysts.

The Marker State Space (MSS) method for classifying clinical samples

The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines “marker states” based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications.

Using lectins in biomarker research: addressing the limitations of sensitivity and availability

Carbohydrates have fundamental roles throughout biology, yet they have not been as well studied as proteins and nucleic acids, in part due to limitations in the experimental tools. Improved methods for studying glycans could spur significant advances in the understanding and application of glycobiology. The use of affinity reagents, such as lectins and glycan-binding antibodies, is a valuable complement to methods involving mass spectrometry and chromatography. This article addresses two limitations that have prevented the broader experimental use of glycan-binding proteins: sensitivity and availability. The sensitivity limitation stems from the poor affinity that many glycan-binding proteins have as isolated analytical reagents. To address this problem, I propose making use of multivalent interactions between lectins and glycans, mimicking those frequently found in the biological setting. Recent experiments show that a practical technique for producing lectin multimers can significantly improve detection sensitivity. The second limitation, availability, is the difficulty of finding and obtaining glycan-binding proteins that recognize less common or arbitrarily defined glycan structures. To address this problem, I propose translating the wealth of existing glycan array data into a quantitative, searchable database of the specificities of glycan-binding proteins. Such a resource would allow us to more easily identify proteins with defined specificities and perform detailed comparisons between reagents. Solutions to these two limitations could lead to the more effective use of, and a broader range of, glycan-binding reagents.

Glycoproteomics-based cancer marker discovery adopting dual enrichment with Wisteria floribunda agglutinin for high specific glyco-diagnosis of cholangiocarcinoma

Cholangiocarcinoma (CC) is a lethal malignancy because it exhibits asymptomatic growth infiltrating the surrounding structures and therefore is usually detected at an advanced stage. The mainstay of treatment for CC is complete resection with negative surgical margins. Therefore, its diagnosis at a relatively early stage is demanded for performing relevant surgical resection. Since the definitive CC diagnosis depends on invasive methods such as biliary cytology and biopsy, a noninvasive assay with high diagnostic accuracy is keenly required. We therefore developed a CC marker with high specificity by the Wisteria floribunda agglutinin (WFA)-assisted glycoproteomics approach. WFA-positive glycoproteins were enriched by the direct dissection of the WFA-stained CC tissue region and following WFA-agarose column chromatography. Subsequent analysis by mass spectrometry identified 71 proteins as candidate markers. Screening of these candidates by gene expression profiling and immunohistochemistry resulted in the selection of L1 cell adhesion molecule (L1CAM) as the most specific CC marker. We confirmed the importance of WFA-positivity for L1CAM using both bile and serum of CC and benign bile duct disease patients. Specifically, WFA-positive L1CAM was enriched from serum by the WFA-assisted affinity capturing, with which CC was efficiently distinguished from benign. In the primary verification study using bile from CC patients (n=29) and that of benign bile duct disease (n=29), WFA-positive L1CAM distinguished CC with high specificity (sensitivity=0.66, specificity=0.93, overall accuracy=0.79, area under the receiver operating curve [AUC]=0.82). The combined use of the WFA-positive L1CAM assay with the high sensitive assay detecting WFA-positive sialylated mucin 1 sufficiently improved the diagnostic accuracy of CC (overall accuracy=0.84, AUC=0.93). This combination will possibly be a precise procedure for CC diagnosis compared with conventional diagnostic techniques.

BIOLOGICAL SIGNIFICANCE

In this study, we constructed the system for verification of the candidate molecules that exhibit disease specific glyco-alterations and discovered a useful CC marker by the glycoproteomics-assisted strategy for biomarker discovery. Based on the strategy, we previously found that WFA is the best probe to detect CC-specific glycosylation and WFA-positive sialyl MUC1 as a possible biomarker candidate. While the diagnostic specificity of WFA-positive sialyl MUC1 was not superb, we proposed a new biomarker candidate WFA-positive L1CAM with high specificity in bile and serum to complement the previous one. We proved that the novel combination assay of WFA-L1CAM and WFA-sialyl MUC1 selected based on our strategy has the possibility to become a reliable serological test. This study represents application of our strategy, which can be extrapolated to discovery of marker candidates for other diseases.

Nanoengineered glycan sensors enabling native glycoprofiling for medicinal applications: towards profiling glycoproteins without labeling or liberation steps

Nanoengineered glycan sensors may help realize the long-held goal of accurate and rapid glycoprotein profiling without labeling or glycan liberation steps. Current methods of profiling oligosaccharides displayed on protein surfaces, such as liquid chromatography, mass spectrometry, capillary electrophoresis, and microarray methods, are limited by sample pretreatment and quantitative accuracy. Microarrayed platforms can be improved with methods that better estimate kinetic parameters rather than simply reporting relative binding information. These quantitative glycan sensors are enabled by an emerging class of nanoengineered materials that differ in their mode of signal transduction from traditional methods. Platforms that respond to mass changes include a quartz crystal microbalance and cantilever sensors. Electronic response can be detected from electrochemical, field effect transistor, and pore impedance sensors. Optical methods include fluorescent frontal affinity chromatography, surface plasmon resonance methods, and fluorescent carbon nanotubes. After a very brief primer on glycobiology and its connection to medicine, these emerging systems are critically reviewed for their potential use as core sensors in future glycoprofiling tools.

Aberrant expression of mucin core proteins and o-linked glycans associated with progression of pancreatic cancer

PURPOSE

Mucin expression is a common feature of most adenocarcinomas and features prominently in current attempts to improve diagnosis and therapy for pancreatic cancer and other adenocarcinomas. We investigated the expression of a number of mucin core proteins and associated O-linked glycans expressed in pancreatic adenocarcinoma-sialyl Tn (STn), Tn, T antigen, sialyl Lewis A (CA19-9), sialyl Lewis C (SLeC), Lewis X (LeX), and sialyl LeX (SLeX)-during the progression of pancreatic cancer from early stages to metastatic disease.

EXPERIMENTAL DESIGN

Immunohistochemical analyses of mucin and associated glycan expression on primary tumor and liver metastatic tumor samples were conducted with matched sets of tissues from 40 autopsy patients diagnosed with pancreatic adenocarcinoma, 14 surgically resected tissue samples, and 8 normal pancreata.

RESULTS

There were significant changes in mucin expression patterns throughout disease progression. MUC1 and MUC4 were differentially glycosylated as the disease progressed from early pancreatic intraepithelial neoplasias to metastatic disease. De novo expression of several mucins correlated with increased metastasis indicating a potentially more invasive phenotype, and we show the expression of MUC6 in acinar cells undergoing acinar to ductal metaplasia. A "cancer field-effect" that included changes in mucin protein expression and glycosylation in the adjacent normal pancreas was also seen.

CONCLUSIONS

There are significant alterations in mucin expression and posttranslational processing during progression of pancreatic cancer from early lesions to metastasis. The results are presented in the context of how mucins influence the biology of tumor cells and their microenvironment during progression of pancreatic cancer.

The sweet and sour of serological glycoprotein tumor biomarker quantification

Aberrant and dysregulated protein glycosylation is a well-established event in the process of oncogenesis and cancer progression. Years of study on the glycobiology of cancer have been focused on the development of clinically viable diagnostic applications of this knowledge. However, for a number of reasons, there has been only sparse and varied success. The causes of this range from technical to biological issues that arise when studying protein glycosylation and attempting to apply it to practical applications. This review focuses on the pitfalls, advances, and future directions to be taken in the development of clinically applicable quantitative assays using glycan moieties from serum-based proteins as analytes. Topics covered include the development and progress of applications of lectins, mass spectrometry, and other technologies towards this purpose. Slowly but surely, novel applications of established and development of new technologies will eventually provide us with the tools to reach the ultimate goal of quantification of the full scope of heterogeneity associated with the glycosylation of biomarker candidate glycoproteins in a clinically applicable fashion.

Modulation of glycan detection on specific glycoproteins by lectin multimerization

Improved methods for studying glycans could spur significant advances in the understanding and application of glycobiology. The use of affinity reagents such as lectins and glycan-binding antibodies is a valuable complement to methods involving mass spectrometry and chromatography. Many lectins, however, are not useful as analytic tools due to low affinity in vitro. As an approach to increasing lectin avidity to targeted glycans, we tested the use of lectin multimerization. Several biotinylated lectins were linked together through streptavidin interactions. The binding of certain lectins for purified glycoproteins and glycoproteins captured directly out of biological solutions was increased using multimerization, resulting in the detection of lower concentrations of glycoprotein than possible using monomeric detection. The analysis of glycoproteins in plasma samples showed that the level of binding enhancement through multimerization was not equivalent across patient samples. Wheat germ agglutinin (WGA) reactive glycans on fibronectin and thrombospondin-5 were preferentially bound by multimers in pancreatic cancer patient samples relative to control samples, suggesting a cancer-associated change in glycan density that could be detected only through lectin multimerization. This strategy could lead to the more sensitive and informative detection of glycans in biological samples and a broader spectrum of lectins that are useful as analytical reagents.

Diverse monoclonal antibodies against the CA 19-9 antigen show variation in binding specificity with consequences for clinical interpretation

The CA 19-9 antigen is currently the best individual marker for the detection of pancreatic cancer. In order to optimize the CA 19-9 assay and to develop approaches to further improve cancer detection, it is important to understand the specificity differences between CA 19-9 antibodies and the consequential affect on biomarker performance. Antibody arrays enabled multiplexed comparisons between five different CA 19-9 antibodies used in the analysis of plasma samples from pancreatic cancer patients and controls. Major differences were observed between antibodies in their detection of particular patient samples. Glycan array analysis revealed that certain antibodies were highly specific for the canonical CA 19-9 epitope, sialyl-Lewis A, while others bound sialyl-Lewis A in addition to a related structure called sialyl-Lewis C and modification with Nue5Gc. In a much larger patient cohort, we confirmed the binding of sialyl-Lewis C glycan by one of the antibodies and showed that the broader specificity led to the detection of an increased number of cancer patients without increasing detection of pancreatitis patient samples. This work demonstrates that variation between antibody specificity for cancer-associated glycans can have significant implications for biomarker performance and highlights the value of characterizing and detecting the range of glycan structures that are elevated in cancer.

Vertebrate protein glycosylation: diversity, synthesis and function

Protein glycosylation is a ubiquitous post-translational modification found in all domains of life. Despite their significant complexity in animal systems, glycan structures have crucial biological and physiological roles, from contributions in protein folding and quality control to involvement in a large number of biological recognition events. As a result, they impart an additional level of 'information content' to underlying polypeptide structures. Improvements in analytical methodologies for dissecting glycan structural diversity, along with recent developments in biochemical and genetic approaches for studying glycan biosynthesis and catabolism, have provided a greater understanding of the biological contributions of these complex structures in vertebrates.

Application of proteomics to cancer early detection

Strategies to achieve personalized medicine and improve public health encompass assessment of an individual's risk for disease, early detection, and molecular classification of disease resulting in an informed choice of the most appropriate treatment instituted at an early stage of disease development. An unmet need in this field for which proteomics is well suited to make a major contribution is the development of blood-based tests for early cancer detection. This is illustrated in proteomic studies of epithelial cancer that encompass analysis of specimens collected both at the time of diagnosis and specimens collected before onset of symptoms that are particularly suited for the identification of early detection markers. This overarching effort benefits from the availability of plasmas from subject cohorts and of engineered mouse models that are sampled at early stages of tumor development. Integration of findings from plasma with tumor tissue and cancer cell proteomic and genomic data allows elucidation of signatures in plasma for altered signaling pathways. The discovery and further development of early detection markers take advantage of the availability of in-depth quantitative proteomics methods and bioinformatics resources for data mining.

Alteration of protein glycosylation in human hepatic stellate cells activated with transforming growth factor-β1

Although aberrant glycosylation of human glycoproteins is related to liver fibrosis that results from chronic damage to the liver in conjunction with the activation of hepatic stellate cells (HSCs), little is known about the precision alteration of protein glycosylation referred to the activation of HSCs by transforming growth factor-β1 (TGF-β1). The human HSCs, LX-2 were activated by TGF-β1. The lectin microarrays were used to probe the alteration of protein glycosylation in the activated HSCs compared with the quiescent HSCs. Lectin histochemistry was used to further validate the lectin binding profiles and assess the distribution of glycosidic residues in cells. As a result, 14 lectins (e. g. AAL, PHA-E, ECA and ConA) showed increased signal while 7 lectins (e. g. UEA-I and GNA) showed decreased signal in the activated LX-2 compared with the quiescent LX-2. Meanwhile, AAL, PHA-E and ECA staining showed moderate binding to the cytoplasma membrane in the quiescent LX-2, and the binding intensified in the same regions of the activated LX-2. In conclusion, the precision alteration of protein glycosylation related to the activation of the HSCs may provide useful information to find new molecular mechanism of HSC activation and antifibrotic therapeutic strategies.

Chemically-blocked antibody microarray for multiplexed high-throughput profiling of specific protein glycosylation in complex samples

In this study, we describe an effective protocol for use in a multiplexed high-throughput antibody microarray with glycan binding protein detection that allows for the glycosylation profiling of specific proteins. Glycosylation of proteins is the most prevalent post-translational modification found on proteins, and leads diversified modifications of the physical, chemical, and biological properties of proteins. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases. However, current methods to study protein glycosylation typically are too complicated or expensive for use in most normal laboratory or clinical settings and a more practical method to study protein glycosylation is needed. The new protocol described in this study makes use of a chemically blocked antibody microarray with glycan-binding protein (GBP) detection and significantly reduces the time, cost, and lab equipment requirements needed to study protein glycosylation. In this method, multiple immobilized glycoprotein-specific antibodies are printed directly onto the microarray slides and the N-glycans on the antibodies are blocked. The blocked, immobilized glycoprotein-specific antibodies are able to capture and isolate glycoproteins from a complex sample that is applied directly onto the microarray slides. Glycan detection then can be performed by the application of biotinylated lectins and other GBPs to the microarray slide, while binding levels can be determined using Dylight 549-Streptavidin. Through the use of an antibody panel and probing with multiple biotinylated lectins, this method allows for an effective glycosylation profile of the different proteins found in a given human or animal sample to be developed.

Mucin 16 (cancer antigen 125) expression in human tissues and cell lines and correlation with clinical outcome in adenocarcinomas of the pancreas, esophagus, stomach, and colon

Mucin 16 (cancer antigen 125) is a cell surface glycoprotein that plays a role in promoting cancer cell growth in ovarian cancer. The aims of this study were to examine mucin 16 expression in a large number of digestive tract adenocarcinomas and precursors and to determine whether mucin 16 up-regulation is correlated with patient outcome. Tissue microarrays were constructed using surgical resection tissues and included pancreatic (115 normal, 29 precursors, 200 pancreatic ductal adenocarcinomas), esophageal (86 normal, 104 precursors, 95 esophageal adenocarcinomas, 35 lymph node metastases), gastric (211 normal, 8 precursors, 119 gastric adenocarcinomas, 62 lymph node metastases), and colorectal (34 normal, 17 precursors, 39 colorectal adenocarcinomas) tissues. Mucin 16 was detected in 81.5%, 69.9%, 41.2%, and 64.1% of the pancreatic ductal adenocarcinomas, esophageal adenocarcinomas, gastric adenocarcinomas, and colorectal adenocarcinomas, respectively. Mucin 16 was seen in a subset of the precursors. On multivariate analysis, moderate/diffuse mucin 16 in pancreatic ductal adenocarcinomas was strongly associated with poor survival (P < .001), independent of other prognosis predictors. A similar trend was observed for esophageal adenocarcinomas (P = .160) and gastric adenocarcinomas (P = .080). Focal mucin 16 in colorectal adenocarcinomas was significantly correlated (P = .044) with a better patient outcome, when compared with mucin 16-negative cases. Using Western blot analysis, we found mucin 16 expression in 3 of 6 pancreatic ductal adenocarcinoma and 1 of 2 esophageal adenocarcinoma cell lines. We conclude that most of the digestive tract adenocarcinomas and a subset of their precursors express mucin 16. Mucin 16 expression is an independent predictor of poor outcome in pancreatic ductal adenocarcinomas and potentially in esophageal adenocarcinomas and gastric adenocarcinomas. We propose that mucin 16 may function as a prognostic marker and therapeutic target in the future.

N-linked glycan structures and their expressions change in the blood sera of ovarian cancer patients

Glycosylated proteins play important roles in a broad spectrum of biochemical and biological processes, and prior reports have suggested that changes in protein glycosylation occur during cancer initiation and progression. Ovarian cancer (OC) is a fatal malignancy, most commonly diagnosed after the development of metastases. Therefore, early detection of OC is key to improving survival. To this end, specific changes of the serum glycome have been proposed as possible biomarkers for different types of cancers. In this study, we extend this concept to OC. To characterize differences in total N-glycan levels, serum samples provided by 20 healthy control women were compared to those acquired from patients diagnosed with late-stage recurrent OC who were enrolled in an experimental treatment trial prior to receiving therapy (N=19) and one month later, prior to the second treatment cycle (N=11). Additionally, analyses of the N-glycans associated with IgG and characterization of the relative abundance levels of core vs outer-arm fucosylation were also performed. The N-linked glycomic profiles revealed increased abundances of tri- and tetra-branched structures with varying degrees of sialylation and fucosylation and an apparent decrease in the levels of "bisecting" glycans in OC samples compared to controls. Increased levels of a-galactosylation structures were observed on N-linked glycans derived from IgG, which were independent of the presence of fucose residues. Elevated levels of outer-arm fucosylation were also identified in the OC samples. These results allowed the control samples to be distinguished from the baseline ovarian cancer patients prior to receiving the experimental treatment. In some cases, the pre-treatment samples could be distinguished from the post-experimental treatment samples, as many of those patients showed a further progression of the disease.

Comparison of surgical and endoscopic sample collection for pancreatic cyst fluid biomarker identification

Significant efforts are underway to develop new biomarkers from pancreatic cyst fluid. Previous research has made use of cyst fluid collected from surgically removed cysts, but the clinical implementation of biomarkers would use cyst fluid collected by endoscopic ultrasound-guided, fine-needle aspiration (EUS-FNA). The purpose of this study was to investigate the clinical applicability of cyst fluid research obtained using surgical specimens. Matched pairs of operating-room collected (OR) and EUS-FNA samples from 12 patients were evaluated for the levels of three previously described biomarkers, CA 19-9, CEA, and glycan levels detected by wheat germ agglutinin on MUC5AC (MUC5AC-WGA). CA 19-9 and MUC5AC-WGA correlated well between the sample types, although CEA was more variable between the sample types for certain patients. The variability was not due to the time delay between EUS-FNA and OR collection or differences in total protein concentrations but may be caused by contamination of the cyst fluid with blood proteins. The classification of each patient based on thresholds for each marker was perfectly consistent between sample types for CA 19-9 and MUC5AC-WGA and mostly consistent for CEA. Therefore, results obtained using OR-collected pancreatic cyst fluid samples should reliably transfer to the clinical setting using EUS-FNA samples.

Glycomic and proteomic profiling of pancreatic cyst fluids identifies hyperfucosylated lactosamines on the N-linked glycans of overexpressed glycoproteins

Pancreatic cancer is now the fourth leading cause of cancer deaths in the United States, and it is associated with an alarmingly low 5-year survival rate of 5%. However, a patient's prognosis is considerably improved when the malignant lesions are identified at an early stage of the disease and removed by surgical resection. Unfortunately, the absence of a practical screening strategy and clinical diagnostic test for identifying premalignant lesions within the pancreas often prevents early detection of pancreatic cancer. To aid in the development of a molecular screening system for early detection of the disease, we have performed glycomic and glycoproteomic profiling experiments on 21 pancreatic cyst fluid samples, including fluids from mucinous cystic neoplasms and intraductal papillary mucinous neoplasms, two types of mucinous cysts that are considered high risk to undergo malignant transformation. A total of 80 asparagine-linked (N-linked) glycans, including high mannose and complex structures, were identified. Of special interest was a series of complex N-linked glycans containing two to six fucose residues, located predominantly as substituents on β-lactosamine extensions. Following the observation of these "hyperfucosylated" glycans, bottom-up proteomics experiments utilizing a label-free quantitative approach were applied to the investigation of two sets of tryptically digested proteins derived from the cyst fluids: 1) all soluble proteins in the raw samples and 2) a subproteome of the soluble cyst fluid proteins that were selectively enriched for fucosylation through the use of surface-immobilized Aleuria aurantia lectin. A comparative analysis of these two proteomic data sets identified glycoproteins that were significantly enriched by lectin affinity. Several candidate glycoproteins that appear hyperfucosylated were identified, including triacylglycerol lipase and pancreatic α-amylase, which were 20- and 22-fold more abundant, respectively, following A. aurantia lectin enrichment.

High-throughput studies of protein glycoforms using antibody-lectin sandwich arrays

The antibody-lectin sandwich arrays (ALSA) is a powerful new tool for glycoproteomics research. ALSA enables precise measurements of the glycosylation states of multiple proteins captured directly from biological samples. The platform can be used in a high-throughput mode with low sample consumption, making it well suited to biomarker research exploring glycan alterations on specific proteins. This article provides detailed descriptions of the use of ALSA, with a particular focus on biomarker research. The preparation and selection of antibodies and lectins, the preparation and use of the arrays and samples, and special considerations for using the platform for biomarker research are covered.

Enhanced discrimination of malignant from benign pancreatic disease by measuring the CA 19-9 antigen on specific protein carriers

The CA 19-9 assay detects a carbohydrate antigen on multiple protein carriers, some of which may be preferential carriers of the antigen in cancer. We tested the hypothesis that the measurement of the CA 19-9 antigen on individual proteins could improve performance over the standard CA 19-9 assay. We used antibody arrays to measure the levels of the CA 19-9 antigen on multiple proteins in serum or plasma samples from patients with pancreatic adenocarcinoma or pancreatitis. Sample sets from three different institutions were examined, comprising 531 individual samples. The measurement of the CA 19-9 antigen on any individual protein did not improve upon the performance of the standard CA 19-9 assay (82% sensitivity at 75% specificity for early-stage cancer), owing to diversity among patients in their CA 19-9 protein carriers. However, a subset of cancer patients with no elevation in the standard CA 19-9 assay showed elevations of the CA 19-9 antigen specifically on the proteins MUC5AC or MUC16 in all sample sets. By combining measurements of the standard CA 19-9 assay with detection of CA 19-9 on MUC5AC and MUC16, the sensitivity of cancer detection was improved relative to CA 19-9 alone in each sample set, achieving 67–80% sensitivity at 98% specificity. This finding demonstrates the value of measuring glycans on specific proteins for improving biomarker performance. Diagnostic tests with improved sensitivity for detecting pancreatic cancer could have important applications for improving the treatment and management of patients suffering from this disease.

A multiplex lectin-channel monitoring method for human serum glycoproteins by quantitative mass spectrometry

A mass profiling method and multiple reaction monitoring (MRM)-based quantitative approach were used to analyze multiple lectin-captured fractions of human serum using different lectins such as aleuria aurantia lectin (AAL), phytohemagglutinin-L(4) (L-PHA), concanavalin A (Con A), and Datura stramonium agglutinin (DSA) to quantitatively monitor protein glycosylation diversity. Each fraction, prepared by multiple lectin-fractionation and tryptic digestion, was analyzed by 1-D LC-MS/MS. Semi-quantitative profiling showed that the list of glycoproteins identified from each lectin-captured fraction is significantly different according to the used lectin. Thus, it was confirmed that the multiplex lectin-channel monitoring (LCM) using multiple lectins is useful for investigating protein glycosylation diversity in a proteome sample. Based on the semi-quantitative mass profiling, target proteins showing lectin-specificity among each lectin-captured fraction were selected and analyzed by the MRM-based method in triplicate using each lectin-captured fraction (average CV 7.9%). The MRM-based analysis for each lectin-captured fraction was similar to those obtained by the profiling experiments. The abundance of each target protein measured varied dramatically, based on the lectin-specificity. The multiplex LCM approach using MRM-based analyses is useful for quantitatively monitoring target protein glycoforms selectively fractionated by multiple lectins. Thus through multiplex LCM rather than single, we could inquire minutely into protein glycosylation states.

Characterization of the monoclonal antibody against classical swine fever virus glycoprotein E(rns) and its application to an indirect sandwich ELISA

Classical swine fever virus (CSFV) E(rns) is an envelope glycoprotein possessing RNase activity. The E(rns)-based enzyme-linked immunosorbent assay (ELISA) has been considered a discriminating diagnostic test for differentiating infected from vaccinated animals. The purpose of this study was to produce a specific monoclonal antibody (MAb) to E(rns) for further developing an indirect sandwich ELISA. The MAb CW813 was shown to specifically recognize both the monomer and dimer forms of Pichia pastoris yeast-expressed E(rns) (yE(rns)). The antigenic site recognized by MAb CW813 was mapped to the region of amino acid residues 101-160 of E(rns) where it was neither a neutralizing epitope nor essential to RNase activity. Furthermore, MAb CW813 was utilized as a capture antibody to develop a yE(rns)-based indirect sandwich ELISA for detecting swine antibody to E(rns). The assay demonstrated a high sensitivity and specificity that may provide an alternative method for developing a diagnostic kit with easy manipulation and low cost.

The fine specificity of mannose-binding and galactose-binding lectins revealed using outlier motif analysis of glycan array data

Glycan-binding proteins are commonly used as analytical reagents to detect the levels of specific glycan structures in biological samples. A detailed knowledge of the specificities of glycan-binding proteins is required for properly interpreting their binding data. A powerful technology for characterizing glycan-binding specificity is the glycan array. However, the interpretation of glycan-array data can be difficult due to the complex fine specificities of certain glycan-binding proteins. We developed a systematic approach, called outlier-motif analysis, for extracting fine-specificity information from glycan-array data, and we applied the method to the study of four commonly used lectins: two mannose binders (concanavalin A and Lens culinaris) and two galactose binders (Bauhinia purpurea and peanut agglutinin). The study confirmed the known, primary specificity of each lectin and also revealed new insights into their binding preferences. Lens culinaris's main specificity may be non-terminal, α-linked mannose with a single linkage at its 2' carbon, which is more restricted than previous definitions. We found broader specificity for bauhinea purpurea (BPL) than previously reported, showing that BPL can bind terminal N-acetylgalactosamine (GalNAc) and penultimate β-linked galactose under certain limitations. Peanut agglutinin may bind terminal Galβ1,3Gal, a glycolipid motif, in addition to terminal Galβ1,3GalNAc, a common O-linked glycoprotein motif. These results could be used to more accurately interpret data obtained using these well-studied lectins. Furthermore, this study demonstrates a systematic and general approach for extracting fine-specificity information from glycan-array data.

Identification of blood-protein carriers of the CA 19-9 antigen and characterization of prevalence in pancreatic diseases

The current best serum marker for pancreatic cancer, CA 19-9, detects a carbohydrate antigen on multiple protein carriers. Better knowledge of the protein carriers of the CA 19-9 antigen in various disease states may lead to improved diagnostic tests. To identify proteins that carry the CA 19-9 antigen, we immunoprecipitated the CA 19-9 antigen from pooled sera and identified the associated proteins using MS. Among the high-confidence identifications, we confirmed the presence of the CA 19-9 antigen on Apolipoprotein B-100 by antibody arrays and Western blot and on kininogen, ARVCF, and Apolipoprotein E by antibody arrays. We characterized the frequency and levels of the CA 19-9 antigen on the four proteins across various patient groups (pancreatic cancer, pancreatitis, and healthy controls) using antibody arrays. Nearly, 10-25% of the subjects showed elevations of the antigen on each protein, but the elevations were not associated with disease state or total CA 19-9 levels. These results contribute to our knowledge of the carrier proteins of an important functional glycan and the rate at which the glycan is displayed. This work also demonstrates a strategy for using the complementary methods of MS and antibody microarrays to identify protein carriers of glycans and assess the diagnostic value of measuring glycans on individual proteins.

Aberrant glycosylation associated with enzymes as cancer biomarkers

BACKGROUND

One of the new roles for enzymes in personalized medicine builds on a rational approach to cancer biomarker discovery using enzyme-associated aberrant glycosylation. A hallmark of cancer, aberrant glycosylation is associated with differential expressions of enzymes such as glycosyltransferase and glycosidases. The aberrant expressions of the enzymes in turn cause cancer cells to produce glycoproteins with specific cancer-associated aberrations in glycan structures.

CONTENT

In this review we provide examples of cancer biomarker discovery using aberrant glycosylation in three areas. First, changes in glycosylation machinery such as glycosyltransferases/glycosidases could be used as cancer biomarkers. Second, most of the clinically useful cancer biomarkers are glycoproteins. Discovery of specific cancer-associated aberrations in glycan structures of these existing biomarkers could improve their cancer specificity, such as the discovery of AFP-L3, fucosylated glycoforms of AFP. Third, cancer-associated aberrations in glycan structures provide a compelling rationale for discovering new biomarkers using glycomic and glycoproteomic technologies.

SUMMARY

As a hallmark of cancer, aberrant glycosylation allows for the rational design of biomarker discovery efforts. But more important, we need to translate these biomarkers from discovery to clinical diagnostics using good strategies, such as the lessons learned from translating the biomarkers discovered using proteomic technologies to OVA 1, the first FDA-cleared In Vitro Diagnostic Multivariate Index Assay (IVDMIA). These lessons, providing important guidance in current efforts in biomarker discovery and translation, are applicable to the discovery of aberrant glycosylation associated with enzymes as cancer biomarkers as well.

Markers of pancreatic cancer: working toward early detection

Because early detection of pancreatic cancer is the best way to cure this disease, investigators continue to try to identify accurate markers of early pancreatic cancer. Because early-stage pancreatic cancer is generally asymptomatic, the only reliable way to detect it is by targeting individuals at increased risk for pancreatic screening.

New technologies for glycomic analysis: toward a systematic understanding of the glycome

Carbohydrates are the most difficult class of biological molecules to study by high-throughput methods owing to the chemical similarities between the constituent monosaccharide building blocks, template-less biosynthesis, and the lack of clearly identifiable consensus sequences for the glycan modification of cohorts of glycoproteins. These molecules are crucial for a wide variety of cellular processes ranging from cell-cell communication to immunity, and they are altered in disease states such as cancer and inflammation. Thus, there has been a dedicated effort to develop glycan analysis into a high-throughput analytical field termed glycomics. Herein we highlight major advances in applying separation, mass spectrometry, and microarray methods to the fields of glycomics and glycoproteomics. These new analytical techniques are rapidly advancing our understanding of the importance of glycosylation in biology and disease.