Lectin chromatography/mass spectrometry discovery workflow identifies putative biomarkers of aggressive breast cancers

Magnetic Bead-Based Workflow for Sensitive and Streamlined Cell Surface Proteomics

Cell surface proteins represent an important class of molecules for therapeutic targeting and cellular phenotyping. However, their enrichment and detection via mass spectrometry-based proteomics remains challenging due to low abundance, post-translational modifications, hydrophobic regions, and processing requirements. To improve their identification, we optimized a Cell-Surface Capture (CSC) workflow that incorporates magnetic bead-based processing. Using this approach, we evaluated labeling conditions (biotin tags and catalysts), enrichment specificity (streptavidin beads), missed cleavages (lysis buffers), nonenzymatic deamidation (digestion and deglycosylation buffers), and data acquisition methods (DDA, DIA, and TMT). Our findings support the use of alkoxyamine-PEG4-biotin plus 5-methoxy-anthranilic acid, SDS/urea-based lysis buffers, single-pot solid-phased-enhanced sample-preparation (SP3), and streptavidin magnetic beads for maximal surfaceome coverage. Notably, with semiautomated processing, sample handling was simplified and between ∼600 and 900 cell surface N-glycoproteins were identified from only 25-200 μg of HeLa protein. CSC also revealed significant differences between in vitro monolayer cultures and in vivo tumor xenografts of murine CT26 colon adenocarcinoma samples that may aid in target identification for drug development. Overall, the improved efficiency of the magnetic-based CSC workflow identified both previously reported and novel N-glycosites with less material and high reproducibility that should help advance the field of surfaceomics by providing insight in cellular phenotypes not previously documented.

Conditional ablation of heparan sulfate expression in stromal fibroblasts promotes tumor growth in vivo

Heparan sulfate (HS) is a glycocalyx component present in the extracellular matrix and cell-surface HS proteoglycans (HSPGs). Although HSPGs are known to play functional roles in multiple aspects of tumor development and progression, the effect of HS expression in the tumor stroma on tumor growth in vivo remains unclear. We conditionally deleted Ext1, which encodes a glycosyltransferase essential for the biosynthesis of HS chains, using S100a4-Cre (S100a4-Cre; Ext1f/f) to investigate the role of HS in cancer-associated fibroblasts, which is the main component of the tumor microenvironment. Subcutaneous transplantation experiments with murine MC38 colon cancer and Pan02 pancreatic cancer cells demonstrated substantially larger subcutaneous tumors in S100a4-Cre; Ext1f/f mice. Additionally, the number of myofibroblasts observed in MC38 and Pan02 subcutaneous tumors of S100a4-Cre; Ext1f/f mice decreased. Furthermore, the number of intratumoral macrophages decreased in MC38 subcutaneous tumors in S100a4-Cre; Ext1f/f mice. Finally, the expression of matrix metalloproteinase-7 (MMP-7) markedly increased in Pan02 subcutaneous tumors in S100a4-Cre; Ext1f/f mice, suggesting that it may contribute to rapid growth. Therefore, our study demonstrates that the tumor microenvironment with HS-reduced fibroblasts provides a favorable environment for tumor growth by affecting the function and properties of cancer-associated fibroblasts, macrophages, and cancer cells.

Recent advances in the use of legume lectins for the diagnosis and treatment of breast cancer

Poor lifestyle choices and genetic predisposition are factors that increase the number of cancer cases, one example being breast cancer, the third most diagnosed type of malignancy. Currently, there is a demand for the development of new strategies to ensure early detection and treatment options that could contribute to the complete remission of breast tumors, which could lead to increased overall survival rates. In this context, the glycans observed at the surface of cancer cells are presented as efficient tumor cell markers. These carbohydrate structures can be recognized by lectins which can act as decoders of the glycocode. The application of plant lectins as tools for diagnosis/treatment of breast cancer encompasses the detection and sorting of glycans found in healthy and malignant cells. Here, we present an overview of the most recent studies in this field, demonstrating the potential of lectins as: mapping agents to detect differentially expressed glycans in breast cancer, as histochemistry/cytochemistry analysis agents, in lectin arrays, immobilized in chromatographic matrices, in drug delivery, and as biosensing agents. In addition, we describe lectins that present antiproliferative effects by themselves and/or in conjunction with other drugs in a synergistic effect.

ProteoSushi: A Software Tool to Biologically Annotate and Quantify Modification-Specific, Peptide-Centric Proteomics Data Sets

Large-scale proteomic profiling of protein post-translational modifications has provided important insights into the regulation of cell signaling and disease. These modification-specific proteomics workflows nearly universally enrich modified peptides prior to mass spectrometry analysis, but protein-centric proteomic software tools have many limitations evaluating and interpreting these peptide-centric data sets. We, therefore, developed ProteoSushi, a software tool tailored to analysis of each modified site in peptide-centric proteomic data sets that is compatible with any post-translational modification or chemical label. ProteoSushi uses a unique approach to assign identified peptides to shared proteins and genes, minimizing redundancy by prioritizing shared assignments based on UniProt annotation score and optional user-supplied protein/gene lists. ProteoSushi simplifies quantitation by summing or averaging intensities for each modified site, merging overlapping peptide charge states, missed cleavages, spectral matches, and variable modifications into a single value. ProteoSushi also annotates each PTM site with the most up-to-date biological information available from UniProt, such as functional roles or known modifications, the protein domain in which the site resides, the protein's subcellular location and function, and more. ProteoSushi has a graphical user interface for ease of use. ProteoSushi's flexibility and combination of analysis features streamlines peptide-centric data processing and knowledge mining of large modification-specific proteomics data sets.

Clinical Assay for the Early Detection of Colorectal Cancer Using Mass Spectrometric Wheat Germ Agglutinin Multiple Reaction Monitoring

Simple Summary

Colorectal cancer (CRC) is currently the third leading cause of cancer death worldwide. Early diagnosis of CRC is important for increasing the opportunity for treatment and receiving a good prognosis. The aim of our study was to develop a detection method that combined wheat germ agglutinin (WGA) chromatography with mass spectrometry (MS) for early detection of CRC. Further, machine learning algorithms and logistic regression were applied to combine multiple biomarkers we discovered. We validated in a population of 286 plasma samples the diagnostic performance of peptides corresponding to WGA-captured protein and its combination, which received a sensitivity of 84.5% and a specificity of 97.5% in the diagnoses of CRC. Proteomic biomarkers combined with algorithms can provide a powerful tool for discriminating patients with CRC and health controls (HCs). Measurements of WGA-captured PF4, ITIH4, and APOE with MS are then useful for early detection of CRC. Additionally, our study revealed the potential of applying lectin chromatography with MS for disease diagnosis.

Abstract

Colorectal cancer (CRC) is currently the third leading cause of cancer-related mortality in the world. U.S. Food and Drug Administration-approved circulating tumor markers, including carcinoembryonic antigen, carbohydrate antigen (CA) 19-9 and CA125 were used as prognostic biomarkers of CRC that attributed to low sensitivity in diagnosis of CRC. Therefore, our purpose is to develop a novel strategy for novel clinical biomarkers for early CRC diagnosis. We used mass spectrometry (MS) methods such as nanoLC-MS/MS, targeted LC-MS/MS, and stable isotope-labeled multiple reaction monitoring (MRM) MS coupled to test machine learning algorithms and logistic regression to analyze plasma samples from patients with early-stage CRC, late-stage CRC, and healthy controls (HCs). On the basis of our methods, 356 peptides were identified, 6 differential expressed peptides were verified, and finally three peptides corresponding wheat germ agglutinin (WGA)-captured proteins were semi-quantitated in 286 plasma samples (80 HCs and 206 CRCs). The novel peptide biomarkers combination of PF4^54–62, ITIH4^429–438, and APOE^198–207 achieved sensitivity 84.5%, specificity 97.5% and an AUC of 0.96 in CRC diagnosis. In conclusion, our study demonstrated that WGA-captured plasma PF4^54–62, ITIH4^429–438, and APOE^198–207 levels in combination may serve as highly effective early diagnostic biomarkers for patients with CRC.

Comprehensive Transcriptomic Analysis Identifies ST8SIA1 as a Survival-Related Sialyltransferase Gene in Breast Cancer

Hypersialylation caused by the overexpression of sialyltransferases (STs) is a common feature in cancer that is associated with several characteristics of tumorigenesis. Thus, identifying cancer-associated STs is critical for cancer therapy. However, ST screening has been frequently conducted in cell line models. In this study, we conducted a comprehensive analysis of STs in the clinical database and identified the STs related with the survival of breast cancer patients. RNA sequencing (RNA-Seq) data of 496 patients were obtained from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA). Of the eight mapped STs, ST3GAL5, and ST8SIA1 met the acceptable area under the curve (AUC) criteria for overall survival (OS). Using Kaplan–Meier methods, we determined that high expression of ST8SIA1 was associated with poor 10-year OS in all patients, triple-negative breast cancer (TNBC), and non-TNBC patients, and poor disease-free survival (DFS) rates particularly in TNBC. ST8SIA1 also had superior AUC values in terms of OS/DFS. High ST8SIA1 levels showed a higher risk for poor OS in different groups of patients and a higher risk for poor DFS particularly in TNBC. In summary, we conducted a comprehensive analysis of STs from the clinical database and identified ST8SIA1 as a crucial survival-related ST, which might be a potential therapeutic target for breast cancer and TNBC patients.

Use of Lectin-based Affinity Techniques in Breast Cancer Glycoproteomics: A Review

Changes in glycoprotein content, altered glycosylations, and aberrant glycan structures are increasingly recognized as cancer hallmarks. Because breast cancer is one of the most common causes of cancer deaths in the world, it is highly urgent to find other reliable biomarkers for its initial diagnosis and to learn as much as possible about this disease. In this Review, the applications of lectins to a screening of potential breast cancer biomarkers published during recent years are overviewed. These data provide a deeper insight into the use of modern strategies, technologies, and scientific knowledge in glycoproteomic breast cancer research. Particular attention is concentrated on the use of lectin-based affinity techniques, applied independently or most frequently in combination with mass spectrometry, as an effective tool for the targeting, separation, and reliable identification of glycoprotein molecules. Individual procedures and lectins used in published glycoproteomic studies of breast-cancer-related glycoproteins are discussed. The summarized approaches have the potential for use in diagnostic and predictive applications. Finally, the use of lectins is briefly discussed from the view of their future applications in the analysis of glycoproteins in cancer.

The Diverse Contributions of Fucose Linkages in Cancer

Fucosylation is a post-translational modification of glycans, proteins, and lipids that is responsible for many biological processes. Fucose conjugation via α(1,2), α(1,3), α(1,4), α(1,6), and O'- linkages to glycans, and variations in fucosylation linkages, has important implications for cancer biology. This review focuses on the roles that fucosylation plays in cancer, specifically through modulation of cell surface proteins and signaling pathways. How L-fucose and serum fucosylation patterns might be used for future clinical diagnostic, prognostic, and therapeutic approaches will be discussed.

Oncolytic Vaccinia Virus Expressing Aphrocallistes vastus Lectin as a Cancer Therapeutic Agent

Lectins display a variety of biological functions including insecticidal, antimicrobial, as well as antitumor activities. In this report, a gene encoding Aphrocallistes vastus lectin (AVL), a C-type lectin, was inserted into an oncolytic vaccinia virus vector (oncoVV) to form a recombinant virus oncoVV-AVL, which showed significant in vitro antiproliferative activity in a variety of cancer cell lines. Further investigations revealed that oncoVV-AVL replicated faster than oncoVV significantly in cancer cells. Intracellular signaling elements including NF-κB2, NIK, as well as ERK were determined to be altered by oncoVV-AVL. Virus replication upregulated by AVL was completely dependent on ERK activity. Furthermore, in vivo studies showed that oncoVV-AVL elicited significant antitumor effect in colorectal cancer and liver cancer mouse models. Our study might provide insights into a novel way of the utilization of marine lectin AVL in oncolytic viral therapies.

Pattern identification of lung cancer patients based on body constitution questionnaires (BCQ) and glycoproteomics for precision medicine

BACKGROUND

The patient's pattern identification has been used for personalized medicine in traditional Korean medicine (TKM) and aims for patient-specific therapy by Korean medical doctors. The pattern identification in this trial will be diagnosed from body constitution questionnaire (BCQ) with a more objective diagnosis of it but this method still needs a more concrete scientific basis. Glycoproteins are well-known to be associated with diseases (especially cancers) so glycoproteomics can be applied to differentiate pattern identification types of lung cancer patients. Thus, for the first time proteomics approach will be applied to the pattern identification by comparing BCQ assessment in order to establish a scientific basis with clinical proteomics for precision medicine.

METHODS

This observational trial will at first diagnose the pattern identification types of lung cancer patients with BCQ assessment and then elucidate their relationships with proteomics. Blood samples will be collected before surgery along with clinical information of participants. The patients' pattern identification in TKM will be diagnosed from BCQ assessment. Then, lung cancer patients will be divided and pooled into 3 lung cancer entire (LCE) groups according to their pattern identification types (Xu, Stasis, or Gentleness). Three lung cancer representative (LCR) groups will be selected and pooled from each LCE group by selecting those with the same control factors. The 3 LCE groups and the 3 LCR groups from lung cancer patients will be independently analyzed through the glycoproteomics approach based on the patients' pattern identification. Glycoproteins from the 6 groups will be identified through proteomics approach and then categorized for analysis.

DISCUSSION

This study intends to diagnose pattern identification of patients in TKM with BCQ assessment and proteomics approach. The identification of the glycoproteins in each group will lead to the scientific foundation of personalized medicine in TKM according to patients' pattern identification for lung cancer therapy. We intend to(1) diagnose the pattern identification types of lung cancer patients with BCQ under the framework of TKM;(2) evaluate BCQ assessment with glycoproteomics approach for precision medicine.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03384680. Registered 27 December 2017. Retrospectively registered.

Identification a novel clinical biomarker in early diagnosis of human non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is a malignant tumor with high morbidity and mortality. The clinical biomarkers currently used for the early diagnosis of lung cancer have poor sensitivity and specificity. Therefore, it is urgent to identify sensitive biomarkers for the early detection of NSCLC to improve the patient survival of patients. In our previously study, we identified glycoprotein alpha-1-antichymotrypsin (AACT) as an early biomarker of NSCLC. In this study, serum glycopeptides were enriched using the high-GlcNAc-specific binding lectin, AANL/AAL2, for further quantitative proteomics analysis using LC-MS/MS. A total of 55 differentially expressed proteins were identified by using demethylation labelling proteomics. Serum paraoxonase/arylesterase 1 (PON1) was selected for validation by western blotting and lectin-ELISA in samples from 120 enrolled patients. Our data showed that AANL-enriched PON1 has better diagnostic performance than total PON1 in early NSCLC, since it differed between early Stage I tumor samples and tumor-free samples (healthy and benign). Combining AANL-enriched PON1 with carcinoembryonic antigen (CEA) significantly improved the diagnostic specificity of CEA. Moreover, combined AANL-enriched PON1 and AANL-enriched AACT was significantly different between early NSCLC samples and tumor-free samples with an AUC of 0.940, 94.4% sensitivity, and 90.2% specificity. Our findings suggest that combined AANL-enriched PON1 and AANL-enriched AACT is a potential clinical biomarker for the early diagnosis of NSCLC.

Overview of Characterizing Cancer Glycans with Lectin-Based Analytical Methods

Glycosylation is a post-translational modification that is often altered in disease development and progression, including cancer. In cancerous patients, the abnormal expression of glycosylation enzymes leads to aberrant glycosylation, which has been linked to malignant tissues. Due to aberrant glycosylation, the presence of specific glycans can be used as biomarkers for identifying the type and stage of cancer. Glycan structures are heterogeneous, with different protein glycoforms having different functional activities. Lectins are an important tool in glycan analysis due to their specificity in binding to unique glycan linkages and monosaccharide units, which allows for the identification of unique glycan structural properties. In this review, we will discuss the use of lectins in microarrays and chromatography for characterizing glycan structures.

Recent advances in mass spectrometry-based glycoproteomics

Protein glycosylation plays fundamental roles in many biological processes as one of the most common, and the most complex, posttranslational modification. Alterations in glycosylation profile are now known to be associated with many diseases. As a result, the discovery and detailed characterization of glycoprotein disease biomarkers is a primary interest of biomedical research. Advances in mass spectrometry (MS)-based glycoproteomics and glycomics are increasingly enabling qualitative and quantitative approaches for site-specific structural analysis of protein glycosylation. While the complexity presented by glycan heterogeneity and the wide dynamic range of clinically relevant samples like plasma, serum, cerebrospinal fluid, and tissue make comprehensive analyses of the glycoproteome a challenging task, the ongoing efforts into the development of glycoprotein enrichment, enzymatic digestion, and separation strategies combined with novel quantitative MS methodologies have greatly improved analytical sensitivity, specificity, and throughput. This review summarizes current MS-based glycoproteomics approaches and highlights recent advances in its application to cancer biomarker and neurodegenerative disease research.

Identification of differentially expressed genes regulated by molecular signature in breast cancer-associated fibroblasts by bioinformatics analysis

OBJECTIVE

Breast cancer is a severe risk to public health and has adequately convoluted pathogenesis. Therefore, the description of key molecular markers and pathways is of much importance for clarifying the molecular mechanism of breast cancer-associated fibroblasts initiation and progression. Breast cancer-associated fibroblasts gene expression dataset was downloaded from Gene Expression Omnibus database.

METHODS

A total of nine samples, including three normal fibroblasts, three granulin-stimulated fibroblasts and three cancer-associated fibroblasts samples, were used to identify differentially expressed genes (DEGs) between normal fibroblasts, granulin-stimulated fibroblasts and cancer-associated fibroblasts samples. The gene ontology (GO) and pathway enrichment analysis was performed, and protein-protein interaction (PPI) network of the DEGs was constructed by NetworkAnalyst software.

RESULTS

Totally, 190 DEGs were identified, including 66 up-regulated and 124 down-regulated genes. GO analysis results showed that up-regulated DEGs were significantly enriched in biological processes (BP), including cell-cell signalling and negative regulation of cell proliferation; molecular function (MF), including insulin-like growth factor II binding and insulin-like growth factor I binding; cellular component (CC), including insulin-like growth factor binding protein complex and integral component of plasma membrane; the down-regulated DEGs were significantly enriched in BP, including cell adhesion and extracellular matrix organization; MF, including N-acetylgalactosamine 4-sulfate 6-O-sulfotransferase activity and calcium ion binding; CC, including extracellular space and extracellular matrix. WIKIPATHWAYS analysis showed the up-regulated DEGs were enriched in myometrial relaxation and contraction pathways. WIKIPATHWAYS, REACTOME, PID_NCI and KEGG pathway analysis showed the down-regulated DEGs were enriched endochondral ossification, TGF beta signalling pathway, integrin cell surface interactions, beta1 integrin cell surface interactions, malaria and glycosaminoglycan biosynthesis-chondroitin sulfate/dermatan sulphate. The top 5 up-regulated hub genes, CDKN2A, MME, PBX1, IGFBP3, and TFAP2C and top 5 down-regulated hub genes VCAM1, KRT18, TGM2, ACTA2, and STAMBP were identified from the PPI network, and subnetworks revealed these genes were involved in significant pathways, including myometrial relaxation and contraction pathways, integrin cell surface interactions, beta1 integrin cell surface interaction. Besides, the target hsa-mirs for DEGs were identified. hsa-mir-759, hsa-mir-4446-5p, hsa-mir-219a-1-3p and hsa-mir-26a-5p were important miRNAs in this study.

CONCLUSIONS

We pinpoint important key genes and pathways closely related with breast cancer-associated fibroblasts initiation and progression by a series of bioinformatics analysis on DEGs. These screened genes and pathways provided for a more detailed molecular mechanism underlying breast cancer-associated fibroblasts occurrence and progression, holding promise for acting as molecular markers and probable therapeutic targets.

Ulva pertusa lectin 1 delivery through adenovirus vector affects multiple signaling pathways in cancer cells

Ulva pertusa lectin 1 (UPL1) is a N-acetyl-D-glucosamine (GlcNAc) binding lectin in marine green alga Ulva pertusa. Exogenous UPL1 colocalized with protein arginine methyltransferase 5 (PRMT5), methylosome protein 50 (MEP50), β-actin and β-tubulin, indicating the interaction of UPL1 with the methylosome and cytoskeleton. UPL1 delivery through adenovirus vector (Ad-UPL1) dramatically induced extracellularly regulated protein kinases 1/2 (ERK1/2) phosphorylation in liver cancer cell lines BEL-7404 and Huh7. Signaling pathways including p38 mitogen-activated protein kinase (MAPK), and Akt were also affected by Ad-UPL1 in a cell type dependent manner. MEK1/2 inhibitor U0126, as well as to a lesser extent p38 MAPK inhibitor SB203580 and phosphoinositide 3-kinase (PI3K) inhibitor LY294002, completely eliminated a higher molecular weight isoform of β-tubulin induced by Ad-UPL1, and significantly enhanced the cytotoxicity of Ad-UPL1 in Huh7 cells, suggesting that the inhibition of MEK1/2, p38 MAPK, and PI3K enhanced antiproliferative effect of Ad-UPL1 possibly through regulating the modification of β-tubulin. Ad-UPL1 completely inhibited the expression of autophagy-related factor Beclin1, but induced LC3-II expression in Huh7 cells. In addition, Ad-UPL1 significantly enhanced starvation induced survival suppression in Huh7 cells. Our data elucidated intracellular signaling pathways affected by exogenous UPL1, and may provide insights into a novel way of UPL1 delivery through adenovirus vectors combined with survival signaling inhibitors for cancer treatment.

Glycoproteins in Claudin-Low Breast Cancer Cell Lines Have a Unique Expression Profile

Claudin proteins are components of epithelial tight junctions; a subtype of breast cancer has been defined by the reduced expression of mRNA for claudins and other genes. Here, we characterize the expression of glycoproteins in breast cell lines for the claudin-low subtype using liquid chromatography/tandem mass spectrometry. Unsupervised clustering techniques reveal a group of claudin-low cell lines that is distinct from nonmalignant, basal, and luminal lines. The claudin-low cell lines express F11R, EPCAM, and other proteins at very low levels, whereas CD44 is expressed at a high level. Comparison of mRNA expression to glycoprotein expression shows modest correlation; the best agreement occurs when the mRNA expression level is lowest and little or no protein is detected. These findings from cell lines are compared to those for tumor samples by the Clinical Proteomic Tumor Analysis Consortium (CPTAC). The CPTAC samples contain a group low in CLDN3. The samples low in CLDN3 proteins share many differentially expressed glycoproteins with the claudin-low cell lines. In contrast to the situation for cell lines or patient samples classified as claudin-low by RNA expression, however, most of the tumor samples low in CLDN3 protein express the estrogen receptor or HER2. These tumor samples express CD44 protein at low rather than high levels. There is no correlation between CLDN3 gene expression and protein expression in these CPTAC samples; hence, the claudin-low subtype defined by gene expression is not the same group of tumors as that defined by low expression of CLDN3 protein.

Marine Lectins DlFBL and HddSBL Fused with Soluble Coxsackie-Adenovirus Receptor Facilitate Adenovirus Infection in Cancer Cells BUT Have Different Effects on Cell Survival

Cancer development and progression are usually associated with glycosylation change, providing prognostic and diagnostic biomarkers, as well as therapeutic targets, for various cancers. In this work, Dicentrarchus labrax fucose binding lectin (DlFBL) and Haliotis discus discus sialic acid binding lectin (HddSBL) were genetically fused with soluble coxsackie-adenovirus receptor (sCAR), and produced through a bacterial expression system. Results showed that recombinant sCAR-DlFBL not only facilitated adenovirus Ad-EGFP infection in K562/ADR and U87MG cells, but also enhanced the cytotoxicity of adenovirus harboring gene encoding Pinellia pedatisecta agglutinin (PPA) or DlFBL (Ad-PPA or Ad-DlFBL) on U87MG cells through inducing apoptosis. Recombinant sCAR-HddSBL facilitated Ad-EGFP infection, but dramatically counteracted the cytotoxicity of both Ad-PPA and Ad-DlFBL in U87MG cells. Further analysis revealed that sCAR-HddSBL, but not sCAR-DlFBL, significantly upregulated transcription factor E2F1 levels in U87MG cells, which might be responsible for the adverse effect of sCAR-HddSBL on Ad-PPA and Ad-DlFBL. Taken together, our data suggested that sCAR-DlFBL could be further developed to redirect therapeutic adenoviruses to infect cancer cells such as U87MG, and the sCAR-lectin fusion proteins for adenoviral retargeting should be carefully examined for possible survival signaling induced by lectins, such as HddSBL.

GlycoPep MassList: software to generate massive inclusion lists for glycopeptide analyses

Protein glycosylation drives many biological processes and serves as markers for disease; therefore, the development of tools to study glycosylation is an essential and growing area of research. Mass spectrometry can be used to identify both the glycans of interest and the glycosylation sites to which those glycans are attached, when proteins are proteolytically digested and their glycopeptides are analyzed by a combination of high-resolution mass spectrometry (MS) and tandem mass spectrometry (MS/MS) methods. One major challenge in these experiments is collecting the requisite MS/MS data. The digested glycopeptides are often present in complex mixtures and in low abundance, and the most commonly used approach to collect MS/MS data on these species is data-dependent acquisition (DDA), where only the most intense precursor ions trigger MS/MS. DDA results in limited glycopeptide coverage. Semi-targeted data acquisition is an alternative experimental approach that can alleviate this difficulty. However, due to the massive heterogeneity of glycopeptides, it is not obvious how to expediently generate inclusion lists for these types of analyses. To solve this problem, we developed the software tool GlycoPep MassList, which can be used to generate inclusion lists for liquid chromatography tandem-mass spectrometry (LC-MS/MS) experiments. The utility of the software was tested by conducting comparisons between semi-targeted and untargeted data-dependent analysis experiments on a variety of proteins, including IgG, a protein whose glycosylation must be characterized during its production as a biotherapeutic. When the GlycoPep MassList software was used to generate inclusion lists for LC-MS/MS experiments, more unique glycopeptides were selected for fragmentation. Generally, ∼30 % more unique glycopeptides can be analyzed per protein, in the simplest cases, with low background. In cases where background ions from proteins or other interferents are high, usage of an inclusion list is even more advantageous. The software is freely publically accessible. Graphical abstract Software increases the number of glycopeptides that get selected for MS/MS analysis.

Identification of GlcNAcylated alpha-1-antichymotrypsin as an early biomarker in human non-small-cell lung cancer by quantitative proteomic analysis with two lectins

Background:

Non-small-cell lung cancer (NSCLC) is the main type of lung cancer with high mortality rates in worldwide. There is a need to identify better biomarkers to detect NSCLC at an early stage as this will improve therapeutic effect and patient survival rates.

Methods:

Two lectins (AAL/AAGL and AAL2/AANL), which specifically bind to tumour-related glycan antigens, were first used to enrich serum glycoproteins from the serum of early NSCLC patients, benign lung diseases subjects and healthy individuals. The samples were investigated by using iTRAQ labelling and LC-MS/MS.

Results:

A total of 53 differentially expressed proteins were identified by quantitative proteomics and four glycoproteins (AACT, AGP1, CFB and HPX) were selected for further verification by western blotting. Receiver operating characteristic analysis showed AACT was the best candidate for early NSCLC diagnosis of the four proteins, with 94.1% sensitivity in distinguishing early tumour Stage (IA+IB) from tumour-free samples (healthy and benign samples, HB). The GlcNAcylated AACT was further detected by lectin-based ELISA and has better advantage in clinical application than total AACT. The GlcNAcylated AACT can effectively differentiate Stage I from HB samples with an AUC of 0.908 and 90.9% sensitivity at a specificity of 86.2%. A combination of GlcNAcylated AACT and carcinoembryonic antigen (CEA) was able to effectively differing Stage I from HB samples (AUC=0.914), which significantly improve the specificity of CEA. The combination application also has the better clinical diagnostic efficacy in distinguishing cancer (NSCLC) from HB samples than CEA or GlcNAcylated AACT used alone, and yielded an AUC of 0.817 with 93.1% specificity.

Conclusions:

Our findings suggest that the GlcNAcylated AACT will be a promising clinical biomarker in diagnosis of early NSCLC.

Mass spectrometry-based analyses showing the effects of secretor and blood group status on salivary N-glycosylation

Background

The carbohydrate portions of salivary glycoproteins play important roles, including mediating bacterial and leukocyte adhesion. Salivary glycosylation is complex. Many of its glycoproteins present ABO and Lewis blood group determinants. An individual’s genetic complement and secretor status govern the expression of blood group antigens. We queried the extent to which salivary glycosylation varies according to blood group and secretor status. First, we screened submandibular/sublingual and parotid salivas collected as ductal secretions for reactivity with a panel of 16 lectins. We selected three lectins that reacted with the largest number of glycoproteins and one that recognized uncommon lactosamine-containing structures. Ductal salivas representing a secretor with complex blood group expression and a nonsecretor with a simple pattern were separated by SDS-PAGE. Gel slices were trypsin digested and the glycopeptides were individually separated on each of the four lectins. The bound fractions were de-N-glycosylated. LC–MS/MS identified the original glycosylation sites, the peptide sequences, and the parent proteins.

Results

The results revealed novel salivary N-glycosites and glycoproteins not previously reported. As compared to the secretor, nonsecretor saliva had higher levels of N-glycosylation albeit with simpler structures.

Conclusions

Together, the results suggested a molecular basis for inter-individual variations in salivary protein glycosylation with functional implications for oral health.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-015-9100-y) contains supplementary material, which is available to authorized users.

Multiplexed Targeted Mass Spectrometry-Based Assays for the Quantification of N-Linked Glycosite-Containing Peptides in Serum

Protein glycosylation is one of the most common protein modifications, and the quantitative analysis of glycoproteins has the potential to reveal biological functions and their association with disease. However, the high throughput accurate quantification of glycoproteins is technically challenging due to the scarcity of robust assays to detect and quantify glycoproteins. Here we describe the development of multiplexed targeted MS assays to quantify N-linked glycosite-containing peptides in serum using parallel reaction monitoring (PRM). Each assay was characterized by its performance metrics and criteria established by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (NCI CPTAC) to facilitate the widespread adoption of the assays in studies designed to confidently detect changes in the relative abundance of these analytes. An in-house developed software program, MRMPlus, was used to compute assay performance parameters including specificity, precision, and repeatability. We show that 43 selected N-linked glycosite-containing peptides identified in prostate cancer tissue studies carried out in our group were detected in the sera of prostate cancer patients within the quantitative range of the developed PRM assays. A total of 41 of these formerly N-linked glycosite-containing peptides (corresponding to 37 proteins) were reproducibly quantified based on their relative peak area ratios in human serum during PRM assay development, with 4 proteins showing differential significance in serum from nonaggressive (NAG) vs aggressive (AG) prostate cancer patient serum (n = 50, NAG vs AG). The data demonstrate that the assays can be used for the high throughput and reproducible quantification of a panel of formerly N-linked glycosite-containing peptides. The developed assays can also be used for the quantification of formerly N-linked glycosite-containing peptides in human serum irrespective of disease state.

Carbohydrates on Proteins: Site-Specific Glycosylation Analysis by Mass Spectrometry

Glycosylation on proteins adds complexity and versatility to these biologically vital macromolecules. To unveil the structure-function relationship of glycoproteins, glycopeptide-centric analysis using mass spectrometry (MS) has become a method of choice because the glycan is preserved on the glycosylation site and site-specific glycosylation profiles of proteins can be readily determined. However, glycopeptide analysis is still challenging given that glycopeptides are usually low in abundance and relatively difficult to detect and the resulting data require expertise to analyze. Viewing the urgent need to address these challenges, emerging methods and techniques are being developed with the goal of analyzing glycopeptides in a sensitive, comprehensive, and high-throughput manner. In this review, we discuss recent advances in glycoprotein and glycopeptide analysis, with topics covering sample preparation, analytical separation, MS and tandem MS techniques, as well as data interpretation and automation.

A peptide N-terminal protection strategy for comprehensive glycoproteome analysis using hydrazide chemistry based method

Enrichment of glycopeptides by hydrazide chemistry (HC) is a popular method for glycoproteomics analysis. However, possible side reactions of peptide backbones during the glycan oxidation in this method have not been comprehensively studied. Here, we developed a proteomics approach to locate such side reactions and found several types of the side reactions that could seriously compromise the performance of glycoproteomics analysis. Particularly, the HC method failed to identify N-terminal Ser/Thr glycopeptides because the oxidation of vicinal amino alcohol on these peptides generates aldehyde groups and after they are covalently coupled to HC beads, these peptides cannot be released by PNGase F for identification. To overcome this drawback, we apply a peptide N-terminal protection strategy in which primary amine groups on peptides are chemically blocked via dimethyl labeling, thus the vicinal amino alcohols on peptide N-termini are eliminated. Our results showed that this strategy successfully prevented the oxidation of peptide N-termini and significantly improved the coverage of glycoproteome.

Glycoproteomic comparison of clinical triple-negative and luminal breast tumors

Triple-negative (TN) breast cancer accounts for ∼ 15% of breast cancers and is characterized by a high likelihood of relapse and a lack of targeted therapies. In contrast, luminal-type tumors that express the estrogen and progesterone receptors (ER+/PR+) and lack expression of human epidermal growth factor receptor 2 (Her2-) are treated with targeted hormonal therapy and carry a better prognosis. To identify potential targets for the development of future therapeutics aimed specifically at TN breast cancers, we have used a hydrazide-based glycoproteomic workflow to compare protein expression in clinical tumors from nine TN (Her2-/ER-/PR-) and nine luminal (Her2-/ER+/PR+) patients. Using a label-free LC-MS based approach, we identified and quantified 2264 proteins. Of these, 90 proteins were more highly expressed and 86 proteins were underexpressed in the TN tumors relative to the luminal tumors. The expression level of four of these potential targets was verified in the original set of tumors by Western blot and correlated well with our mass-spectrometry-based quantification. Furthermore, 30% of the proteins differentially expressed between luminal and TN tumors were validated in a larger cohort of 406 TN and 469 luminal tumors through corresponding differences in their mRNA expression in publically available microarray data. A group of 29 of these differentially expressed proteins was shown to correctly classify 88% of TN and luminal tumors using microarray data of their associated mRNA levels. Interestingly, even within a group of TN breast cancer patients, the expression levels of these same mRNAs were able to significantly predict patient survival, suggesting that these proteins play a role in the aggressiveness seen in TN tumors. This study provides a comprehensive list of potential targets for the development of diagnostic and therapeutic agents specifically aimed at treating TN breast cancer and demonstrates the utility of using publicly available microarray data to further prioritize potential targets.

Overcoming challenges and opening new opportunities in glycoproteomics

Glycoproteomics has emerged as a prime area of interest within the field of proteomics because glycoproteins have been shown to function as biomarkers for disease and as promising therapeutic targets. A significant challenge in the study of glycoproteins is the fact that they are expressed in relatively low abundance in cells. In response, various enrichment methods have been developed to improve the detection of glycoproteins. One such method involves their capture via oxidation of their glycan chains and covalent attachment with hydrazide resins which, when catalyzed by PNGase F, release N-linked glycans and convert the glycosite Asn to Asp; this conversion is identifiable with LC/ESI-MS/MS as a corresponding increase of 0.984 Da in molecular weight. The present study builds on this body of work, providing evidence of three additional strategies that improve glycoprotein identification: (1) use of a high resolution mass spectrometer—the Q Exactive MS—which delivers 2–3 times more glycoprotein identifications than a low resolution MS; (2) optimization of instrument settings and database search parameters to reduce misidentification of N-linked glycopeptides to ~1 percent; and (3) labeling glycopeptides with ¹⁸O during PNGase F treatment to locate N-linked glycosites within peptides containing multiple N-linked sequons.

Pinellia pedatisecta agglutinin-based lectin blot analysis distinguishes between glycosylation patterns in various cancer cell lines

The analysis of altered glycosylation patterns may provide biomarkers for various types of cancer. The present study developed a Pinellia pedatisecta agglutinin (PPA)-based lectin blot analysis technique, which was used to analyze the glycosylation patterns in various types of cancer cells. Results showed that a typical band located between 47 and 85 kDa was obtained in the HL60 leukemia cells, whereas three typical bands located between 20 and 47 kDa were observed in the Kasumi-1 leukemia cells. For the PLC, BEL-7404, Huh7 and H1299 solid tumor cell lines, different band patterns were detected, with bands typically located between 55 and 100 kDa. The findings of the present study show that PPA-based lectin blot analysis is capable of distinguishing between glycosylation patterns in leukemia and solid tumor cell lines. The glycofiles detected using PPA-based lectin blot analysis may provide a ‘glycosylation fingerprint’ for a variety of cancer cells, which may be valuable for cancer prognosis and diagnosis.

A universal chemical enrichment method for mapping the yeast N-glycoproteome by mass spectrometry (MS)

Glycosylation is one of the most common and important protein modifications in biological systems. Many glycoproteins naturally occur at low abundances, which makes comprehensive analysis extremely difficult. Additionally, glycans are highly heterogeneous, which further complicates analysis in complex samples. Lectin enrichment has been commonly used, but each lectin is inherently specific to one or several carbohydrates, and thus no single or collection of lectin(s) can bind to all glycans. Here we have employed a boronic acid-based chemical method to universally enrich glycopeptides. The reaction between boronic acids and sugars has been extensively investigated, and it is well known that the interaction between boronic acid and diols is one of the strongest reversible covalent bond interactions in an aqueous environment. This strong covalent interaction provides a great opportunity to catch glycopeptides and glycoproteins by boronic acid, whereas the reversible property allows their release without side effects. More importantly, the boronic acid-diol recognition is universal, which provides great capability and potential for comprehensively mapping glycosylation sites in complex biological samples. By combining boronic acid enrichment with PNGase F treatment in heavy-oxygen water and MS, we have identified 816 N-glycosylation sites in 332 yeast proteins, among which 675 sites were well-localized with greater than 99% confidence. The results demonstrated that the boronic acid-based chemical method can effectively enrich glycopeptides for comprehensive analysis of protein glycosylation. A general trend seen within the large data set was that there were fewer glycosylation sites toward the C termini of proteins. Of the 332 glycoproteins identified in yeast, 194 were membrane proteins. Many proteins get glycosylated in the high-mannose N-glycan biosynthetic and GPI anchor biosynthetic pathways. Compared with lectin enrichment, the current method is more cost-efficient, generic, and effective. This method can be extensively applied to different complex samples for the comprehensive analysis of protein glycosylation.

CD123 targeting oncolytic adenoviruses suppress acute myeloid leukemia cell proliferation in vitro and in vivo

We report here a novel strategy to redirect oncolytic adenoviruses to CD123 by carry a soluble coxsackie-adenovirus receptor (sCAR)-IL3 expression cassette in the viral genome to form Ad.IL3, which sustainably infected acute myeloid leukemia (AML) cells through CD123. Ad.IL3 was further engineered to harbor gene encoding manganese superoxide dismutase (MnSOD) or mannose-binding plant lectin Pinellia pedatisecta agglutinin (PPA), forming Ad.IL3-MnSOD and Ad.IL3-PPA. As compared with Ad.IL3 or Ad.sp-E1A control, Ad.IL3-MnSOD and Ad.IL3-PPA significantly suppressed in vitro proliferation of HL60 and KG-1 cells. Elevated apoptosis was detected in HL60 and KG-1 cells treated with either Ad.IL3-MnSOD or Ad.IL3-PPA. The caspase-9–caspase-7 pathway was determined to be activated by Ad.IL3-MnSOD as well as by Ad.IL3-PPA in HL60 cells. In an HL60/Luc xenograft nonobese diabetic/severe-combined immunodeficiency mice model, Ad.IL3-MnSOD and Ad.IL3-PPA suppressed cancer cell growth as compared with Ad.IL3. A significant difference of cancer cell burden was detected between Ad.IL3 and Ad.IL3-PPA groups at day 9 after treatment. Furthermore, Ad.IL3-MnSOD significantly prolonged mouse survival as compared with Ad.sp-E1A. These findings demonstrated that Ad.IL3-gene could serve as a novel agent for AML therapy. Harboring sCAR-ligand expression cassette in the viral genome may provide a universal method to redirect oncolytic adenoviruses to various membrane receptors on cancer cells resisting serotype 5 adenovirus infection.

Phosphoprotein secretome of tumor cells as a source of candidates for breast cancer biomarkers in plasma

Breast cancer is a heterogeneous disease whose molecular diversity is not well reflected in clinical and pathological markers used for prognosis and treatment selection. As tumor cells secrete proteins into the extracellular environment, some of these proteins reach circulation and could become suitable biomarkers for improving diagnosis or monitoring response to treatment. As many signaling pathways and interaction networks are altered in cancerous tissues by protein phosphorylation, changes in the secretory phosphoproteome of cancer tissues could reflect both disease progression and subtype. To test this hypothesis, we compared the phosphopeptide-enriched fractions obtained from proteins secreted into conditioned media (CM) derived from five luminal and five basal type breast cancer cell lines using label-free quantitative mass spectrometry. Altogether over 5000 phosphosites derived from 1756 phosphoproteins were identified, several of which have the potential to qualify as phosphopeptide plasma biomarker candidates for the more aggressive basal and also the luminal-type breast cancers. The analysis of phosphopeptides from breast cancer patient plasma and controls allowed us to construct a discovery list of phosphosites under rigorous collection conditions, and second to qualify discovery candidates generated from the CM studies. Indeed, a set of basal-specific phosphorylation CM site candidates derived from IBP3, CD44, OPN, FSTL3, LAMB1, and STC2, and luminal-specific candidates derived from CYTC and IBP5 were selected and, based on their presence in plasma, quantified across all cell line CM samples using Skyline MS1 intensity data. Together, this approach allowed us to assemble a set of novel cancer subtype specific phosphopeptide candidates for subsequent biomarker verification and clinical validation.

The exostosin family: proteins with many functions

Heparan sulfates are complex sulfated molecules found in abundance at cell surfaces and in the extracellular matrix. They bind to and influence the activity of a variety of molecules like growth factors, proteases and morphogens and are thus involved in various cell-cell and cell-matrix interactions. The mammalian EXT proteins have glycosyltransferase activities relevant for HS chain polymerization, however their exact role in this process is still confusing. In this review, we summarize current knowledge about the biochemical activities and some proposed functions of the members of the EXT protein family and their roles in human disease.

Pinellia pedatisecta agglutinin targets drug resistant K562/ADR leukemia cells through binding with sarcolemmal membrane associated protein and enhancing macrophage phagocytosis

Pinelliapedatisecta agglutinin (PPA) has previously been used in labeling fractions of myeloid leukemia cells in our laboratory. We report here that a bacterial expressed recombinant PPA domain b tagged with soluble coxsackie and adenovirus receptor (sCAR-PPAb) preferentially recognized drug resistant cancer cells K562/ADR and H460/5Fu, as compared to their parental cell lines. Pretreatment of K562/ADR cells with sCAR-PPAb significantly enhanced phagocytosis of K562/ADR by macrophages in vivo. Meanwhile, in a K562/ADR xenograft model, intratumoral injection of sCAR-PPAb induced macrophage infiltration and phagocytosis. Furthermore, immunoprecipitation, mass spectrometry and Western blot identified the membrane target of PPA on K562/ADR as sarcolemmal membrane associated protein (SLMAP). An antibody against SLMAP significantly promoted the phagocytosis of K562/ADR by macrophages in vitro. These findings suggest that PPA not only could be developed into a novel agent that can detect drug resistant cancer cells and predict chemotherapy outcome, but also it has potential value in immunotherapy against drug resistant cancer cells through inducing the tumoricidal activity of macrophages.

Systemic alteration of cell-surface and secreted glycoprotein expression in malignant breast cancer cell lines

Breast cancer cell lines express fewer transmembrane and secreted glycoproteins than nonmalignant ones. The objective of these experiments was to characterize the changes in the expression of several hundred glycoproteins quantitatively. Secreted and cell-surface glycoproteins were isolated using a glycoprotein capture protocol and then identified by tandem mass spectrometry. Glycoproteins expressed by a group of cell lines originating from malignant tumors of the breast were compared with those expressed by a nonmalignant set. The average number of spectral counts (proportional to relative protein abundance) and the total number of glycopeptides in the malignant samples were reduced to about two-thirds of the level in the nonmalignant samples. Most glycoproteins were expressed at a different level in the malignant samples, with nearly as many increasing as decreasing. The glycoproteins with reduced expression accounted for a larger change in spectral counts, and hence for the net loss of spectral counts in the malignant lines. Similar results were found when the glycoproteins were studied via identified glycosylation sites only, or through identified sites together with non-glycopeptides. The overall reduction is largely due to the loss of integrins, laminins and other proteins that form or interact with the basement membrane.

Sweet-Heart - an integrated suite of enabling computational tools for automated MS2/MS3 sequencing and identification of glycopeptides

High efficiency identification of intact glycopeptides from a shotgun glycoproteomic LC-MS(2) dataset remains problematic. The prevalent mode of identifying the de-N-glycosylated peptides is littered with false positives and addresses only the issue of site occupancy. Here, we present Sweet-Heart, a computational tool set developed to tackle the heart of the problems in MS(2) sequencing of glycopeptide. It accepts low resolution and low accuracy ion trap MS(2) data, filters for glycopeptides, couples knowledge-based de novo interpretation of glycosylation-dependent fragmentation pattern with protein database search, and uses machine-learning algorithm to score the computed glyco and peptide combinations. Higher ranking candidates are then compiled into a list of MS(2)/MS(3) entries to drive subsequent rounds of targeted MS(3) sequencing of putative peptide backbone, allowing its validation by database search in a fully automated fashion. With additional fishing out of all related glycoforms and final data integration, the platform proves to be sufficiently sensitive and selective, conducive to novel glycosylation discovery, and robust enough to discriminate, among others, N-glycolyl neuraminic acid/fucose from N-acetyl neuraminic acid/hexose. A critical appraisal of its computing performance shows that Sweet-Heart allows high sensitivity comprehensive mapping of site-specific glycosylation for isolated glycoproteins and facilitates analysis of glycoproteomic data.

BIOLOGICAL SIGNIFICANCE

The biological relevance of protein site-specific glycosylation cannot be meaningfully addressed without first defining its pattern by direct analysis of glycopeptides. Sweet-Heart is a novel suite of computational tools allowing for automated analysis of mass spectrometry-based glycopeptide sequencing data. It is developed to accept ion trap MS2/MS3 data and uses a machine learning algorithm to score and rank the candidate peptide core and glycosyl substituent combinations. By eliminating the need for manual, labor-intensive, and subjective data interpretation, it facilitates high throughput shotgun glycoproteomic data analysis and is conducive to identification of unanticipated glycosylation, as demonstrated here with a recombinant EGFR.

Quantification of the N-glycosylated secretome by super-SILAC during breast cancer progression and in human blood samples

Cells secrete a large number of proteins to communicate with their surroundings. Furthermore, plasma membrane proteins and intracellular proteins can be released into the extracellular space by regulated or non-regulated processes. Here, we profiled the supernatant of 11 cell lines that are representative of different stages of breast cancer development by specifically capturing N-glycosylated peptides using the N-glyco FASP technology. For accurate quantification we developed a super-SILAC mix from several labeled breast cancer cell lines and used it as an internal standard for all samples. In total, 1398 unique N-glycosylation sites were identified and quantified. Enriching for N-glycosylated peptides focused the analysis on classically secreted and membrane proteins. N-glycosylated secretome profiles correctly clustered the different cell lines to their respective cancer stage, suggesting that biologically relevant differences were detected. Five different profiles of glycoprotein dynamics during cancer development were detected, and they contained several proteins with known roles in breast cancer. We then used the super-SILAC mix in plasma, which led to the quantification of a large number of the previously identified N-glycopeptides in this important body fluid. The combination of quantifying the secretome of cancer cell lines and of human plasma with a super-SILAC approach appears to be a promising new approach for finding markers of disease.