A recently developed matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) method to spatially profile the location and distribution of multiple N-linked glycan species in ...frozen tissues has been extended and improved for the direct analysis of glycans in clinically derived formalin-fixed paraffin-embedded (FFPE) tissues. Formalin-fixed tissues from normal mouse kidney, human pancreatic and prostate cancers, and a human hepatocellular carcinoma tissue microarray were processed by antigen retrieval followed by on-tissue digestion with peptide N-glycosidase F. The released N-glycans were detected by MALDI-IMS analysis, and the structural composition of a subset of glycans could be verified directly by on-tissue collision-induced fragmentation. Other structural assignments were confirmed by off-tissue permethylation analysis combined with multiple database comparisons. Imaging of mouse kidney tissue sections demonstrates specific tissue distributions of major cellular N-linked glycoforms in the cortex and medulla. Differential tissue distribution of N-linked glycoforms was also observed in the other tissue types. The efficacy of using MALDI-IMS glycan profiling to distinguish tumor from non-tumor tissues in a tumor microarray format is also demonstrated. This MALDI-IMS workflow has the potential to be applied to any FFPE tissue block or tissue microarray to enable higher throughput analysis of the global changes in N-glycosylation associated with cancers.
Lectins and glycan-binding antibodies are powerful tools in biological research, provided detailed information is available about their glycan-binding specificities. Glycan-arrays, in combination ...with bioinformatics tools to mine the data, offer the ability to obtain such information. This review focuses on the bioinformatics tools and resources that are available for the analysis of glycan-array data. The tools are enabling new insights into protein-glycan interactions and enhancing the value of glycan-binding proteins in research.
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Highlights
•Lectins and glycan-binding antibodies are valuable as probe of glycans.•Advanced bioinformatics tools enable the mining of glycan-array data.•New insights into protein-glycan interactions have value in biological research.
Proteins that bind carbohydrate structures can serve as tools to quantify or localize specific glycans in biological specimens. Such proteins, including lectins and glycan-binding antibodies, are particularly valuable if accurate information is available about the glycans that a protein binds. Glycan arrays have been transformational for uncovering rich information about the nuances and complexities of glycan-binding specificity. A challenge, however, has been the analysis of the data. Because protein-glycan interactions are so complex, simplistic modes of analyzing the data and describing glycan-binding specificities have proven inadequate in many cases. This review surveys the methods for handling high-content data on protein-glycan interactions. We contrast the approaches that have been demonstrated and provide an overview of the resources that are available. We also give an outlook on the promising experimental technologies for generating new insights into protein-glycan interactions, as well as a perspective on the limitations that currently face the field.
Antibody arrays have valuable applications in cancer research. Many different antibody array technologies have been developed, each with particular advantages, disadvantages, and optimal ...applications. The methods have been demonstrated on various sample types, such as serum, plasma, and other bodily fluids; cell culture supernatants; tissue culture lysates; and resected tumor specimens. The applications to cancer research have included profiling proteins to identify candidate biomarkers, characterizing signaling pathways, and the measurement of changes in modification or expression level of cancer-related proteins. Further innovations in the methods and experimental strategies are broadening the scope of the applications and the type of information that can be gathered. These alternate formats and uses of antibody arrays include arrays to measure whole cells, arrays to measure enzyme activities, reverse phase arrays, and bead-based arrays. This article reviews the various types of antibody array methods and their applications to cancer research.
Antibody microarrays have great potential for significant value in biological research. Cancer research in particular could benefit from the unique experimental capabilities of this technology. This ...article examines the current state of antibody microarray technological developments and assay formats, along with a review of the demonstrated applications to cancer research. Work is ongoing in the refinement of various aspects of the protocols and the development of robust methods for routine use. Antibody microarray experimental formats can be broadly categorized into two classes: (1) direct labeling experiments, and (2) dual antibody sandwich assays. In the direct labeling method, the covalent labeling of all proteins in a complex mixture provides a means for detecting bound proteins after incubation on an antibody microarray. If proteins are labeled with a tag, such as biotin, the signal from bound proteins can be amplified. In the sandwich assay, proteins captured on an antibody microarray are detected by a cocktail of detection antibodies, each antibody matched to one of the spotted antibodies. Each format has distinct advantages and disadvantages. Several applications of antibody arrays to cancer research have been reported, including the analysis of proteins in blood serum, resected frozen tumors, cell lines, and on membranes of blood cells. These demonstrations clearly show the utility of antibody microarrays for cancer research and signal the imminent expansion of this platform to many areas of biological research.
The early detection of pancreatic ductal adenocarcinoma (PDAC) is a complex clinical obstacle yet is key to improving the overall likelihood of patient survival. Current and prospective carbohydrate ...biomarkers carbohydrate antigen 19-9 (CA19-9) and sialylated tumor-related antigen (sTRA) are sufficient for surveilling disease progression yet are not approved for delineating PDAC from other abdominal cancers and noncancerous pancreatic pathologies. To further understand these glycan epitopes, an imaging mass spectrometry (IMS) approach was used to assess the N-glycome of the human pancreas and pancreatic cancer in a cohort of patients with PDAC represented by tissue microarrays and whole-tissue sections. Orthogonally, these same tissues were characterized by multiround immunofluorescence that defined expression of CA19-9 and sTRA as well as other lectins toward carbohydrate epitopes with the potential to improve PDAC diagnosis. These analyses revealed distinct differences not only in N-glycan spatial localization across both healthy and diseased tissues but importantly between different biomarker-categorized tissue samples. Unique sulfated biantennary N-glycans were detected specifically in normal pancreatic islets. N-glycans from CA19-9–expressing tissues tended to be biantennary, triantennary, and tetra-antennary structures with both core and terminal fucose residues and bisecting GlcNAc. These N-glycans were detected in less abundance in sTRA-expressing tumor tissues, which favored triantennary and tetra-antennary structures with polylactosamine extensions. Increased sialylation of N-glycans was detected in all tumor tissues. A candidate new biomarker derived from IMS was further explored by fluorescence staining with selected lectins on the same tissues. The lectins confirmed the expression of the epitopes in cancer cells and revealed different tumor-associated staining patterns between glycans with bisecting GlcNAc and those with terminal GlcNAc. Thus, the combination of lectin-immunohistochemistry and lectin-IMS techniques produces more complete information for tumor classification than the individual analyses alone. These findings potentiate the development of early assessment technologies to rapidly and specifically identify PDAC in the clinic that may directly impact patient outcomes.
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•N-glycan structures localize to distinct regions in normal and PDAC tumor tissue.•N-glycan composition differs between biomarker-stratified PDAC subtypes.•Modeling with N-glycan IMS and biomarker data improves tumor/normal discrimination.•Multiplexed IMS and lectin staining potentiates new PDAC classification strategies.
N-glycosylation is an attractive target for PDAC biomarker discovery because of its well-understood roles in oncogenesis, cancer maintenance, and metastasis. Using MALDI-IMS, we observed distinct histopathology localized differences in N-glycosylation distributions between healthy and cancerous tissues. We combined the tumor-to-normal ratio of N-glycan changes determined from IMS with biomarker IHC data into modeling which improved PDAC identification over models utilizing either data set individually. This multiplexed approach potentiates the development of cross-disciplinary biomarker panels for pancreatic cancer detection.
Antibody arrays are valuable for the parallel analysis of multiple proteins in small sample volumes. The earliest and most widely used application of antibody arrays has been to measure multiple ...protein abundances, using sandwich assays and label-based assays, for biomarker discovery and biological studies. Modifications to these assays have led to studies profiling specific protein post-translational modifications. Additional novel uses include profiling enzyme activities and protein cell-surface expression. Finally, array-based antibody platforms are being used to assist the development and characterization of antibodies. Continued progress in the technology will surely lead to extensions of these applications and the development of new ways of using the methods.
Outcomes following tumor resection vary dramatically among patients with pancreatic ductal adenocarcinoma (PDAC). A challenge in defining predictive biomarkers is to discern within the complex tumor ...tissue the specific subpopulations and relationships that drive recurrence. Multiplexed immunofluorescence is valuable for such studies when supplied with markers of relevant subpopulations and analysis methods to sort out the intra-tumor relationships that are informative of tumor behavior. We hypothesized that the glycan biomarkers CA19-9 and STRA, which detect separate subpopulations of cancer cells, define intra-tumoral features associated with recurrence.
We probed this question using automated signal thresholding and spatial cluster analysis applied to the immunofluorescence images of the STRA and CA19-9 glycan biomarkers in whole-block sections of PDAC tumors collected from curative resections.
The tumors (N = 22) displayed extreme diversity between them in the amounts of the glycans and in the levels of spatial clustering, but neither the amounts nor the clusters of the individual and combined glycans associated with recurrence. The combined glycans, however, marked divergent types of spatial clusters, alternatively only STRA, only CA19-9, or both. The co-occurrence of more than one cluster type within a tumor associated significantly with disease recurrence, in contrast to the independent occurrence of each type of cluster. In addition, intra-tumoral regions with heterogeneity in biomarker clusters spatially aligned with pathology-confirmed cancer cells, whereas regions with homogeneous biomarker clusters aligned with various non-cancer cells.
Thus, the STRA and CA19-9 glycans are markers of distinct and co-occurring subpopulations of cancer cells that in combination are associated with recurrence. Furthermore, automated signal thresholding and spatial clustering provides a tool for quantifying intra-tumoral subpopulations that are informative of outcome.
There is a substantial list of pre‐analytical variables that can alter the analysis of blood‐derived samples. We have undertaken studies on some of these issues including choice of sample type, ...stability during storage, use of protease inhibitors, and clinical standardization. As there is a wide range of sample variables and a broad spectrum of analytical techniques in the HUPO PPP effort, it is not possible to define a single list of pre‐analytical standards for samples or their processing. We present here a compendium of observations, drawing on actual results and sound clinical theories and practices. Based on our data, we find that (1) platelet‐depleted plasma is preferable to serum for certain peptidomic studies; (2) samples should be aliquoted and stored preferably in liquid nitrogen; (3) the addition of protease inhibitors is recommended, but should be incorporated early and used judiciously, as some form non specific protein adducts and others interfere with peptide studies. Further, (4) the diligent tracking of pre‐analytical variables and (5) the use of reference materials for quality control and quality assurance, are recommended. These findings help provide guidance on sample handling issues, with the overall suggestion being to be conscious of all possible pre‐analytical variables as a prerequisite of any proteomic study.
A new platform for N-glycoprotein analysis from serum that combines matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) workflows with antibody slide arrays is ...described. Antibody panel based (APB) N-glycan imaging allows for the specific capture of N-glycoproteins by antibodies on glass slides and N-glycan analysis in a protein-specific and multiplexed manner. Development of this technique has focused on characterizing two abundant and well-studied human serum glycoproteins, alpha-1-antitrypsin and immunoglobulin G. Using purified standard solutions and 1 μL samples of human serum, both glycoproteins can be immunocaptured and followed by enzymatic release of N-glycans. N-Glycans are detected with a MALDI FT-ICR mass spectrometer in a concentration-dependent manner while maintaining specificity of capture. Importantly, the N-glycans detected via slide-based antibody capture were identical to that of direct analysis of the spotted standards. As a proof of concept, this workflow was applied to patient serum samples from individuals with liver cirrhosis to accurately detect a characteristic increase in an IgG N-glycan. This novel approach to protein-specific N-glycan analysis from an antibody panel can be further expanded to include any glycoprotein for which a validated antibody exists. Additionally, this platform can be adapted for analysis of any biofluid or biological sample that can be analyzed by antibody arrays.
We have developed and tested a method for printing protein microarrays and using these microarrays in a comparative fluorescence assay to measure the abundance of many specific proteins in complex ...solutions. A robotic device was used to print hundreds of specific antibody or antigen solutions in an array on the surface of derivatized microscope slides. Two complex protein samples, one serving as a standard for comparative quantitation, the other representing an experimental sample in which the protein quantities were to be measured, were labeled by covalent attachment of spectrally resolvable fluorescent dyes.
Specific antibody-antigen interactions localized specific components of the complex mixtures to defined cognate spots in the array, where the relative intensity of the fluorescent signal representing the experimental sample and the reference standard provided a measure of each protein's abundance in the experimental sample. To test the specificity, sensitivity and accuracy of this assay, we analyzed the performance of 115 antibody/antigen pairs. 50% of the arrayed antigens and 20% of the arrayed antibodies provided specific and accurate measurements of their cognate ligands at or below concentrations of 0.34 microg/ml and 1.6 microg/ml, respectively. Some of the antibody/antigen pairs allowed detection of the cognate ligands at absolute concentrations below 1 ng/ml, and partial concentrations of 1 part in 106, sensitivities sufficient for measurement of many clinically important proteins in patient blood samples.
These results suggest that protein microarrays can provide a practical means to characterize patterns of variation in hundreds of thousands of different proteins in clinical or research applications.
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