The sTRA Plasma Biomarker: Blinded Validation of Improved Accuracy Over CA19-9 in Pancreatic Cancer Diagnosis.

PURPOSE: The CA19-9 biomarker is elevated in a substantial group of patients with pancreatic ductal adenocarcinoma (PDAC), but not enough to be reliable for the detection or diagnosis of the disease. We hypothesized that a glycan called sTRA (sialylated tumor-related antigen) is a biomarker for PDAC that improves upon CA19-9. EXPERIMENTAL DESIGN: We examined sTRA and CA19-9 expression and secretion in panels of cell lines, patient-derived xenografts, and primary tumors. We developed candidate biomarkers from sTRA and CA19-9 in a training set of 147 plasma samples and used the panels to make case-control calls, based on predetermined thresholds, in a 50-sample validation set and a blinded, 147-sample test set. RESULTS: The sTRA glycan was produced and secreted by pancreatic tumors and models that did not produce and secrete CA19-9. Two biomarker panels improved upon CA19-9 in the training set, one optimized for specificity, which included CA19-9 and 2 versions of the sTRA assay, and another optimized for sensitivity, which included 2 sTRA assays. Both panels achieved statistical improvement (P < 0.001) over CA19-9 in the validation set, and the specificity-optimized panel achieved statistical improvement (P < 0.001) in the blinded set: 95% specificity and 54% sensitivity (75% accuracy), compared with 97%/30% (65% accuracy). Unblinding produced further improvements and revealed independent, complementary contributions from each marker. CONCLUSIONS: sTRA is a validated serological biomarker of PDAC that yields improved performance over CA19-9. The new panels may enable surveillance for PDAC among people with elevated risk, or improved differential diagnosis among patients with suspected pancreatic cancer.

The CA19-9 and Sialyl-TRA Antigens Define Separate Subpopulations of Pancreatic Cancer Cells.

Molecular markers to detect subtypes of cancer cells could facilitate more effective treatment. We recently identified a carbohydrate antigen, named sTRA, that is as accurate a serological biomarker of pancreatic cancer as the cancer antigen CA19-9. We hypothesized that the cancer cells producing sTRA are a different subpopulation than those producing CA19-9. The sTRA glycan was significantly elevated in tumor tissue relative to adjacent pancreatic tissue in 3 separate tissue microarrays covering 38 patients. The morphologies of the cancer cells varied in association with glycan expression. Cells with dual staining of both markers tended to be in well-to-moderately differentiated glands with nuclear polarization, but exclusive sTRA staining was present in small clusters of cells with poor differentiation and large vacuoles, or in small and ill-defined glands. Patients with higher dual-staining of CA19-9 and sTRA had statistically longer time-to-progression after surgery. Patients with short time-to-progression (<2 years) had either low levels of the dual-stained cells or high levels of single-stained cells, and such patterns differentiated short from long time-to-progression with 90% (27/30) sensitivity and 80% (12/15) specificity. The sTRA and CA19-9 glycans define separate subpopulations of cancer cells and could together have value for classifying subtypes of pancreatic adenocarcinoma.

A Gastric Glycoform of MUC5AC Is a Biomarker of Mucinous Cysts of the Pancreas.

Molecular indicators to specify the risk posed by a pancreatic cyst would benefit patients. Previously we showed that most cancer-precursor cysts, termed mucinous cysts, produce abnormal glycoforms of the proteins MUC5AC and endorepellin. Here we sought to validate the glycoforms as a biomarker of mucinous cysts and to specify the oligosaccharide linkages that characterize MUC5AC. We hypothesized that mucinous cysts secrete MUC5AC displaying terminal N-acetylglucosamine (GlcNAc) in either alpha or beta linkage. We used antibody-lectin sandwich assays to detect glycoforms of MUC5AC and endorepellin in cyst fluid samples from three independent cohorts of 49, 32, and 66 patients, and we used monoclonal antibodies to test for terminal, alpha-linked GlcNAc and the enzyme that produces it. A biomarker panel comprising the previously-identified glycoforms of MUC5AC and endorepellin gave 96%, 96%, and 87% accuracy for identifying mucinous cysts in the three cohorts with an average sensitivity of 92% and an average specificity of 94%. Glycan analysis showed that MUC5AC produced by a subset of mucinous cysts displays terminal alpha-GlcNAc, a motif expressed in stomach glands. The alpha-linked glycoform of MUC5AC was unique to intraductal papillary mucinous neoplasms (IPMN), whereas terminal beta-linked GlcNAc was increased in both IPMNs and mucinous cystic neoplasms (MCN). The enzyme that synthesizes alpha-GlcNAc, A4GNT, was expressed in the epithelia of mucinous cysts that expressed alpha-GlcNAc, especially in regions with high-grade dysplasia. Thus IPMNs secrete a gastric glycoform of MUC5AC that displays terminal alpha-GlcNAc, and the combined alpha-GlcNAc and beta-GlcNAc glycoforms form an accurate biomarker of mucinous cysts.

Combining a GSI and BCL-2 inhibitor to overcome melanoma's resistance to current treatments.

Major limitations of current melanoma treatments are for instances of relapse and the lack of therapeutic options for BRAF wild-type patients who do not respond to immunotherapy. Many studies therefore focus on killing resistant subpopulations, such as Melanoma Initiating Cells (MICs) to prevent relapse. Here we examined whether combining a GSI (γ-Secretase Inhibitor) with ABT-737 (a small molecule BCL-2/BCL-XL/BCL-W inhibitor) can kill both the non-MICs (bulk of melanoma) and MICs. To address the limitations of melanoma therapies, we included multiple tumor samples of patients relapsed from current treatments, with a diverse genetic background (with or without the common BRAF, NRAS or NF1 mutations) in these studies. Excitingly, the combination treatment reduced cell viability and induced apoptosis of the non-MICs; disrupted primary spheres, decreased the ALDH+ cells, and inhibited the self-renewability of the MICs in multiple melanoma cell lines and relapsed patient samples. Using a low-cell-number mouse xenograft model, we demonstrated that the combination significantly reduced the tumor initiating ability of MIC-enriched cultures from relapsed patient samples. Mechanistic studies also indicate that cell death is NOXA-dependent. In summary, this combination may be a promising strategy to address treatment relapse and for triple wild-type patients who do not respond to immunotherapy.

Characterizing Protein Glycosylation through On-Chip Glycan Modification and Probing.

Glycans are critical to protein biology and are useful as disease biomarkers. Many studies of glycans rely on clinical specimens, but the low amount of sample available for some specimens limits the experimental options. Here we present a method to obtain information about protein glycosylation using a minimal amount of protein. We treat proteins that were captured or directly spotted in small microarrays (2.2 mm × 2.2 mm) with exoglycosidases to successively expose underlying features, and then we probe the native or exposed features using a panel of lectins or glycan-binding reagents. We developed an algorithm to interpret the data and provide predictions about the glycan motifs that are present in the sample. We demonstrated the efficacy of the method to characterize differences between glycoproteins in their sialic acid linkages and N-linked glycan branching, and we validated the assignments by comparing results from mass spectrometry and chromatography. The amount of protein used on-chip was about 11 ng. The method also proved effective for analyzing the glycosylation of a cancer biomarker in human plasma, MUC5AC, using only 20 µL of the plasma. A glycan on MUC5AC that is associated with cancer had mostly 2,3-linked sialic acid, whereas other glycans on MUC5AC had a 2,6 linkage of sialic acid. The on-chip glycan modification and probing (on-chip GMAP) method provides a platform for analyzing protein glycosylation in clinical specimens and could complement the existing toolkit for studying glycosylation in disease.

Glycans related to the CA19-9 antigen are elevated in distinct subsets of pancreatic cancers and improve diagnostic accuracy over CA19-9.

BACKGROUND AND AIMS: The CA19-9 antigen is the current best biomarker for pancreatic cancer, but it is not elevated in about 25% of pancreatic cancer patients at a cutoff that gives a 25% false-positive rate. We hypothesized that antigens related to the CA19-9 antigen, which is a glycan called sialyl-Lewis A (sLeA), are elevated in distinct subsets of pancreatic cancers. METHODS: We profiled the levels of multiple glycans and mucin glycoforms in plasma from 200 subjects with either pancreatic cancer or benign pancreatic disease, and we validated selected findings in additional cohorts of 116 and 100 subjects, the latter run blinded and including cancers that exclusively were early-stage. RESULTS: We found significant elevations in two glycans: an isomer of sLeA called sialyl-Lewis X, present both in sulfated and non-sulfated forms; and the sialylated form of a marker for pluripotent stem cells, type 1 N-acetyl-lactosamine. The glycans performed as well as sLeA as individual markers and were elevated in distinct groups of patients, resulting in a 3-marker panel that significantly improved upon any individual biomarker. The panel gave 85% sensitivity and 90% specificity in the combined discovery and validation cohorts, relative to 54% sensitivity and 86% specificity for sLeA; and it gave 80% sensitivity and 84% specificity in the independent test cohort, as opposed to 66% sensitivity and 72% specificity for sLeA. CONCLUSIONS: Glycans related to sLeA are elevated in distinct subsets of pancreatic cancers and yield improved diagnostic accuracy over CA19-9.

Definitive Characterization of CA 19-9 in Resectable Pancreatic Cancer Using a Reference Set of Serum and Plasma Specimens.

The validation of candidate biomarkers often is hampered by the lack of a reliable means of assessing and comparing performance. We present here a reference set of serum and plasma samples to facilitate the validation of biomarkers for resectable pancreatic cancer. The reference set includes a large cohort of stage I-II pancreatic cancer patients, recruited from 5 different institutions, and relevant control groups. We characterized the performance of the current best serological biomarker for pancreatic cancer, CA 19-9, using plasma samples from the reference set to provide a benchmark for future biomarker studies and to further our knowledge of CA 19-9 in early-stage pancreatic cancer and the control groups. CA 19-9 distinguished pancreatic cancers from the healthy and chronic pancreatitis groups with an average sensitivity and specificity of 70-74%, similar to previous studies using all stages of pancreatic cancer. Chronic pancreatitis patients did not show CA 19-9 elevations, but patients with benign biliary obstruction had elevations nearly as high as the cancer patients. We gained additional information about the biomarker by comparing two distinct assays. The two CA 9-9 assays agreed well in overall performance but diverged in measurements of individual samples, potentially due to subtle differences in antibody specificity as revealed by glycan array analysis. Thus, the reference set promises be a valuable resource for biomarker validation and comparison, and the CA 19-9 data presented here will be useful for benchmarking and for exploring relationships to CA 19-9.

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.

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.

Array-based immunoassays with rolling-circle amplification detection.

This chapter describes methods for the use of antibody microarrays with rolling-circle amplification (RCA). The methods are divided into three sections. The first section covers antibody preparation and microarray production, the second describes the method for using biological samples on antibody microarrays, and the third describes the method for RCA use on antibody microarrays. RCA can be used on antibody microarrays to increase the signal from each antibody spot and lower the detection limits of the assays. We also describe a practical method for running multiple, low-volume microarrays on a single microscope slide. These methods should be useful for researchers interested in rapidly developing and optimizing custom immunoassays for the analysis of low-abundance analytes using low sample volumes.

Characterization of glycoproteins in pancreatic cyst fluid using a high-performance multiple lectin affinity chromatography platform.

Currently, pancreatic cancer is the fourth cause of cancer death. In 2013, it is estimated that ∼38 460 people will die of pancreatic cancer. Early detection of malignant cyst (pancreatic cancer precursor) is necessary to help prevent late diagnosis of the tumor. In this study, we characterized glycoproteins and nonglycoproteins on pooled mucinous (n = 10) and nonmucinous (n = 10) pancreatic cyst fluid to identify "proteins of interest" to differentiate between mucinous cyst from nonmucinous cyst and investigate these proteins as potential biomarker targets. An automated multilectin affinity chromatography (M-LAC) platform was utilized for glycoprotein enrichment followed by nano-LC-MS/MS analysis. Spectral count quantitation allowed for the identification of proteins with significant differential levels in mucinous cysts from nonmucinous cysts of which one protein (periostin) was confirmed via immunoblotting. To exhaustively evaluate differentially expressed proteins, we used a number of proteomic tools including gene ontology classification, pathway and network analysis, Novoseek data mining, and chromosome gene mapping. Utilization of complementary proteomic tools revealed that several of the proteins such as mucin 6 (MUC6), bile salt-activated lipase (CEL), and pyruvate kinase lysozyme M1/M2 with significant differential expression have strong association with pancreatic cancer. Furthermore, chromosome gene mapping demonstrated coexpressions and colocalization of some proteins of interest including 14-3-3 protein epsilon (YWHAE), pigment epithelium derived factor (SERPINF1), and oncogene p53.

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.

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.

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.

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.

MicroRNA-26a is strongly downregulated in melanoma and induces cell death through repression of silencer of death domains (SODD).

Melanoma is an aggressive cancer that metastasizes rapidly and is refractory to conventional chemotherapies. Identifying microRNAs (miRNAs) that are responsible for this pathogenesis is therefore a promising means of developing new therapies. We identified miR-26a through microarray and quantitative reverse-transcription-PCR (qRT-PCR) experiments as an miRNA that is strongly downregulated in melanoma cell lines as compared with primary melanocytes. Treatment of cell lines with miR-26a mimic caused significant and rapid cell death compared with a negative control in most melanoma cell lines tested. In surveying targets of miR-26a, we found that protein levels of SMAD1 (mothers against decapentaplegic homolog 1) and BAG-4/SODD were strongly decreased in sensitive cells treated with miR-26a mimic as compared with the control. The luciferase reporter assays further demonstrated that miR-26a can repress gene expression through the binding site in the 3' untranslated region (3'UTR) of SODD (silencer of death domains). Knockdown of these proteins with small interfering RNA (siRNA) showed that SODD has an important role in protecting melanoma cells from apoptosis in most cell lines sensitive to miR-26a, whereas SMAD1 may have a minor role. Furthermore, transfecting cells with a miR-26a inhibitor increased SODD expression. Our findings indicate that miR-26a replacement is a potential therapeutic strategy for metastatic melanoma, and that SODD, in particular, is a potentially useful therapeutic target.

ABT-737 synergizes with Bortezomib to kill melanoma cells.

The BH3 mimetic ABT-737 is a potent inhibitor of the anti-apoptotic proteins Bcl-2, Bcl-X(L), and Bcl-w. The Bcl-2 family modulates sensitivity to anticancer drugs in many cancers, including melanomas. In this study, we examined whether ABT-737 is effective in killing melanoma cells either alone or in combination with a proteasome inhibitor already in clinical use (Bortezomib) in vitro and in vivo, and further evaluated the mechanisms of action. Results showed that ABT-737 alone induced modest cytotoxicity in melanoma cells, but only at higher doses. Knock-down of the anti-apoptotic proteins Bcl-2, Bcl-X(L), or Mcl-1 with siRNAs demonstrated that Mcl-1 is the critical mediator of melanoma's resistance to ABT-737 treatment. However, ABT-737 displayed strong synergistic lethality when combined with Bortezomib. Immunoblot analyses demonstrated that Bortezomib increased expression of Noxa, a pro-apoptotic Bcl-2 member that antagonizes Mcl-1. Additionally, siRNA-mediated inhibition of Noxa expression protected melanoma cells from cytotoxicity induced by the combination treatment. These results demonstrate that Bortezomib synergizes with ABT-737 by neutralizing Mcl-1's function via increased levels of Noxa. In a xenograft mouse model, although drug doses were limited due to toxicity, ABT-737 or Bortezomib slowed melanoma tumor growth compared to the control, and the drug combination significantly decreased growth compared to either drug alone. These data imply that less toxic drugs fulfilling a function similar to Bortezomib to neutralize Mcl-1 are promising candidates for combination with ABT-737 for treating melanomas.

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.

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.