Quantitative analysis of aberrant protein glycosylation in liver cancer plasma by AAL-enrichment and MRM mass spectrometry

High-throughput N-glycoproteomics with fast liquid chromatographic separation

N-glycosylation is a common protein post translation modification, which has tremendous structure diversity and wide yet delicate regulation of protein structures and functions. Mass spectrometry-based N-glycoproteomics has become a state-of-the-art pipeline for both qualitative and quantitative characterization of N-glycosylation at the intact N-glycopeptide level, providing comprehensive information of peptide backbones, N-glycosites, monosaccharide compositions, sequence and linkage structures. For high-throughput analysis of large-cohort clinic samples, fast and high-performance separation is indispensable. Here we report our development of 1-h liquid chromatography gradient N-glycoproteomics method and accordingly optimized MS parameters. In the benchmark analysis of cancer and paracancerous tissue of hepatocellular carcinoma, 5,218 intact N-glycopeptides were identified, where 422 site- and structure-specific differential N-glycosylation on 145 N-glycoproteins was observed. The method, representing substantial increase of throughput, can be adopted for fast and efficient analysis of N-glycoproteomes at large scale.

Serum Glycoprotein Markers in Nonalcoholic Steatohepatitis and Hepatocellular Carcinoma

Fatty liver disease progresses through stages of fat accumulation and inflammation to nonalcoholic steatohepatitis (NASH), fibrosis and cirrhosis, and eventually hepatocellular carcinoma (HCC). Currently available diagnostic tools for HCC lack sensitivity and specificity. In this study, we investigated the use of circulating serum glycoproteins to identify a panel of potential prognostic markers that may be indicative of progression from the healthy state to NASH and further to HCC. Serum samples were processed and analyzed using a novel high-throughput glycoproteomics platform. Our initial dataset contained healthy, NASH, and HCC serum samples. We analyzed 413 glycopeptides, representing 57 abundant serum proteins, and compared among the three phenotypes. We studied the normalized abundance of common glycoforms and found 40 glycopeptides with statistically significant differences in abundances in NASH and HCC compared to controls. Summary level relative abundances of core-fucosylated, sialylated, and branched glycans containing glycopeptides were higher in NASH and HCC as compared to controls. We replicated some of our findings in an independent set of samples of individuals with benign liver conditions and HCC. Our results may be of value in the management of liver diseases. Data generated in this work can be downloaded from MassIVE (https://massive.ucsd.edu) with identifier MSV000088809.

[Recent advances in functionalized magnetic nanomaterials for glycoprotein and glycopeptide enrichment]

蛋白质糖基化作为最重要的翻译后修饰之一,在生物体诸如细胞信号转导、蛋白质翻译调控、免疫应答等诸多生命过程中发挥重要作用。此外,蛋白质的异常糖基化还与肿瘤等疾病的发生发展密切相关,这为以糖蛋白为目标的疾病生物标志物的发现提供了可能。尽管质谱已经成为糖蛋白质组学的重要分析工具,但糖肽的低丰度和低电离效率使得其直接质谱分析仍面临挑战。在糖蛋白质组学研究中,从复杂的生物样品中富集糖蛋白和糖肽是重要的环节。磁性固相萃取(MSPE)是一种操作简单、成本低和萃取效率高的样品预处理方法。在磁性固相萃取中,磁性吸附剂是影响萃取效果的关键,将功能化磁性纳米材料作为吸附剂进行糖蛋白质组学研究已经得到广泛应用。该文综述了糖分子、离子液体、凝集素、硼酸亲和配体、金属有机框架、共价有机骨架等功能化磁性纳米材料的制备及其在糖蛋白及糖肽富集中的应用。上述功能化磁性纳米材料具有高比表面积、大量作用位点等特点,其富集机理包括亲水相互作用色谱、凝集素亲和作用色谱、硼酸化学法和肼化学法等,主要应用于血清、血浆、细胞、组织、唾液等样品的糖蛋白和糖肽的富集。该文引用了近十年来发表的约90篇源于科学引文索引(SCI)与中文核心期刊的相关论文,并于文末对磁性纳米材料在糖蛋白和糖肽富集领域的发展趋势进行了展望。

ZIC-cHILIC Functionalized Magnetic Nanoparticle for Rapid and Sensitive Glycopeptide Enrichment from <1 µL Serum

Due to their unique glycan composition and linkage, protein glycosylation plays significant roles in cellular function and is associated with various diseases. For comprehensive characterization of their extreme structural complexity occurring in >50% of human proteins, time-consuming multi-step enrichment of glycopeptides is required. Here we report zwitterionic n-dodecylphosphocholine-functionalized magnetic nanoparticles (ZIC-cHILIC@MNPs) as a highly efficient affinity nanoprobe for large-scale enrichment of glycopeptides. We demonstrate that ZIC-cHILIC@MNPs possess excellent affinity, with 80-91% specificity for glycopeptide enrichment, especially for sialylated glycopeptide (90%) from biofluid specimens. This strategy provides rapidity (~10 min) and high sensitivity (<1 μL serum) for the whole enrichment process in patient serum, likely due to the rapid separation using magnetic nanoparticles, fast reaction, and high performance of the affinity nanoprobe at nanoscale. Using this strategy, we achieved personalized profiles of patients with hepatitis B virus (HBV, n = 3) and hepatocellular carcinoma (HCC, n = 3) at the depth of >3000 glycopeptides, especially for the large-scale identification of under-explored sialylated glycopeptides. The glycoproteomics atlas also revealed the differential pattern of sialylated glycopeptides between HBV and HCC groups. The ZIC-cHILIC@MNPs could be a generic tool for advancing the glycoproteome analysis, and contribute to the screening of glycoprotein biomarkers.

Analysis of Serum Paraoxonase 1 Using Mass Spectrometry and Lectin Immunoassay in Patients With Alpha-Fetoprotein Negative Hepatocellular Carcinoma

The diagnosis of AFP (alpha-fetoprotein)-negative HCC (hepatocellular carcinoma) mostly relies on imaging and pathological examinations, and it lacks valuable and practical markers. Protein N-glycosylation is a crucial post-translation modifying process related to many biological functions in an organism. Alteration of N-glycosylation correlates with inflammatory diseases and infectious diseases including hepatocellular carcinoma. Here, serum N-linked intact glycopeptides with molecular weight (MW) of 40–55 kDa were analyzed in a discovery set (n = 40) including AFP-negative HCC and liver cirrhosis (LC) patients using label-free quantification methodology. Quantitative lens culinaris agglutin (LCA) ELISA was further used to confirm the difference of glycosylation on serum PON1 in liver diseases (n = 56). Then, the alteration of site-specific intact N-glycopeptides of PON1 was comprehensively assessed by using Immunoprecipitation (IP) and mass spectrometry based ¹⁶O/¹⁸O C-terminal labeling quantification method to distinguish AFP-negative HCC from LC patients in a validation set (n = 64). Totally 195 glycopeptides were identified using a dedicated search engine pGlyco. Among them, glycopeptides from APOH, HPT/HPTR, and PON1 were significantly changed in AFP-negative HCC as compared to LC. In addition, the reactivity of PON1 with LCA in HCC patients with negative AFP was significantly elevated than that in cirrhosis patients. The two glycopeptides HAN²⁵³WTLTPLK (H5N4S2) and (H5N4S1) corresponding to PON1 were significantly increased in AFP-negative HCC patients, as compared with LC patients. Variations in PON1 glycosylation may be associated with AFP-negative HCC and might be helpful to serve as potential glycomic-based biomarkers to distinguish AFP-negative HCC from cirrhosis.

Quantitative Analysis of α-1-Antitrypsin Glycosylation Isoforms in HCC Patients Using LC-HCD-PRM-MS

The change in glycosylation of serum proteins is often associated with the development of various diseases and thus can be used for diagnosis. In this study, a liquid chromatography-tandem mass spectrometry-based method is used for accurate structural analysis and quantification of site-specific glycoforms of serum α-1-antitrypsin (A1AT) in early-stage HCC and cirrhosis patients. Serum protein A1AT was purified from patient sera by immunoprecipitation with anti-A1AT antibody conjugated agarose beads, and the isolated A1AT protein was digested and analyzed by LC-MS/MS. Two tandem mass spectrometry strategies are integrated in this study: a nontargeted stepped HCD strategy for structural analysis of A1AT glycopeptides and a targeted parallel reaction monitoring (PRM) strategy for quantification of site-specific glycoforms of A1AT in HCC and cirrhosis patient sera. Accordingly, pGlyco2.0 software was used for glycopeptide identification, and Skyline software was used for glycoform quantification using the Y1 ion (peptide+GlcNAc) in MS/MS spectra. Ten site-specific glycopeptides of A1AT were identified with stepped HCD-MS/MS in patient samples, 7 of which were further quantified using HCD-PRM-MS among patient samples. We found that our strategy was able to distinguish isomers of glycopeptides where several isomers showed distinctly different patterns between cirrhosis and HCC patients. We also found that the ratio of different charge states (2+/3+) of one glycopeptide of A1AT can significantly discriminate early-stage HCC from cirrhosis with the area under the receiver operating characteristic curve AUC of 0.9. Further analysis showed that the difference may be related to the sialic acid/galactose linkage of the glycan motif.

Applications of multiple reaction monitoring targeted proteomics assays in human plasma

Introduction: Multiple (or selected) reaction monitoring-mass spectrometry (MRM/SRM) is a targeted proteomic method that can be used for relative and absolute quantification. Multiple reports exist supporting the potential of the approach in proteomic biomarker validation. Areas covered: To get an overview of the applications of MRM in protein quantification in plasma, a search in MedLine/PubMed was performed using the keywords: 'MRM/SRM plasma proteomic/proteomics/proteome'. The retrieved studies were further filtered to focus on disease biomarkers and the main results are summarized. Expert opinion: MRM is increasingly employed for the quantification of both well-established but also newly discovered putative biomarkers and occasionally their post-translationally modified forms in plasma. Fractionation is regularly required for the detection of low abundance proteins. Standardized procedures to facilitate assay establishment and marker quantification have been proposed and, in few cases, implemented. Nevertheless, in most cases, absolute quantification is not performed. To advance, multiple technical issues including the regular use of standard labeled peptides and appropriate quality controls to monitor assay performance should be considered. Additionally, clinical aspects involving careful study design to address biomarker clinical use should also be considered.

Glycoproteomic markers of hepatocellular carcinoma-mass spectrometry based approaches

Hepatocellular carcinoma (HCC) is the third most-common cause of cancer-related death worldwide. Most cases of HCC develop in patients that already have liver cirrhosis and have been recommended for surveillance for an early onset of HCC. Cirrhosis is the final common pathway for several etiologies of liver disease, including hepatitis B and C, alcohol, and increasingly non-alcoholic fatty liver disease. Only 20-30% of patients with HCC are eligible for curative therapy due primarily to inadequate early-detection strategies. Reliable, accurate biomarkers for HCC early detection provide the highest likelihood of curative therapy and survival; however, current early-detection methods that use abdominal ultrasound and serum alpha fetoprotein are inadequate due to poor adherence and limited sensitivity and specificity. There is an urgent need for convenient and highly accurate validated biomarkers for HCC early detection. The theme of this review is the development of new methods to discover glycoprotein-based markers for detection of HCC with mass spectrometry approaches. We outline the non-mass spectrometry based methods that have been used to discover HCC markers including immunoassays, capillary electrophoresis, 2-D gel electrophoresis, and lectin-FLISA assays. We describe the development and results of mass spectrometry-based assays for glycan screening based on either MALDI-MS or ESI analysis. These analyses might be based on the glycan content of serum or on glycan screening for target molecules from serum. We describe some of the specific markers that have been developed as a result, including for proteins such as Haptoglobin, Hemopexin, Kininogen, and others. We discuss the potential role for other technologies, including PGC chromatography and ion mobility, to separate isoforms of glycan markers. Analyses of glycopeptides based on new technologies and innovative softwares are described and also their potential role in discovery of markers of HCC. These technologies include new fragmentation methods such as EThcD and stepped HCD, which can identify large numbers of glycopeptide structures from serum. The key role of lectin extraction in various assays for intact glycopeptides or their truncated versions is also described, where various core-fucosylated and hyperfucosylated glycopeptides have been identified as potential markers of HCC. Finally, we describe the role of LC-MRMs or lectin-FLISA MRMs as a means to validate these glycoprotein markers from patient samples. These technological advancements in mass spectrometry have the potential to lead to novel biomarkers to improve the early detection of HCC.

HST-MRM-MS: A Novel High-Sample-Throughput Multiple Reaction Monitoring Mass Spectrometric Method for Multiplex Absolute Quantitation of Hepatocellular Carcinoma Serum Biomarker

Absolute quantification of clinical biomarkers by mass spectrometry (MS) has been challenged due to low sample-throughput of current multiple reaction monitoring (MRM) methods. For this problem to be overcome, in this work, a novel high-sample-throughput multiple reaction monitoring mass spectrometric (HST-MRM-MS) quantification approach is developed to achieve simultaneous quantification of 24 samples. Briefly, triplex dimethyl reagents (L, M, and H) and eight-plex iTRAQ reagents were used to label the N- and C-termini of the Lys C-digested peptides, respectively. The triplex dimethyl labeling produces three coelute peaks in MRM traces, and the iTRAQ labeling produces eight peaks in MS2, resulting in 24 (3×8) channels in a single experiment. HST-MRM-MS has shown good accuracy ( R² > 0.98 for absolute quantification), reproducibility (RSD < 15%), and linearity (2-3 orders of magnitude). Moreover, the novel method has been successfully applied in quantifying serum biomarkers in hepatocellular carcinoma (HCC)-related serum samples. In conclusion, HST-MRM-MS is an accurate, high-sample-throughput, and broadly applicable MS-based absolute quantification method.

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.

A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

Reverse lectin ELISA for detecting fucosylated forms of α1-acid glycoprotein associated with hepatocellular carcinoma

Altered fucosylation of glycoproteins is associated with development of hepatocellular carcinoma (HCC). Lectins have been commonly used to assay changes in fucosylation of plasma glycoproteins. In the present study a recombinantly engineered form of the fucose binding lectin Aleuria aurantia (AAL) consisting of a single binding site for fucose (S2), was used to construct a reverse lectin ELISA method. Microtiter plates coated with the S2 lectin were used to capture glycoproteins from plasma samples followed by antibody detection of S2-bound fucosylated α1-acid glycoprotein (S2-bound AGP). The method was used to compare the level of S2-bound AGP in serum samples from a small cohort of patients with hepatitis, cirrhosis or HCC. Using the reverse S2 lectin ELISA it was shown that the levels of S2-bound AGP was significantly higher in HCC patients compared to non-cancer patients and that there was also a significant elevation of S2-bound AGP in HCC patients compared to cirrhosis patients. There was no correlation between the level of S2-bound AGP and total AGP concentration. The performance of S2-bound AGP in differentiating HCC from cirrhosis samples or hepatitis samples were compared to other markers. A combination of S2-bound AGP, α-fetoprotein and AGP concentration showed performances giving area under receiver operating curves of 0.87 and 0.95 respectively.

Analysis of fucosylation in liver-secreted N-glycoproteins from human hepatocellular carcinoma plasma using liquid chromatography with tandem mass spectrometry

Fucosylation of N-glycoproteins has been implicated in various diseases, such as hepatocellular carcinoma (HCC). However, few studies have performed site-specific analysis of fucosylation in liver-secreted proteins. In this study, we characterized the fucosylation patterns of liver-secreted proteins in HCC plasma using a workflow to identify site-specific N-glycoproteins, where characteristic B- and/or Y-ion series with and without fucose in collision-induced dissociation were used in tandem mass spectrometry. In total, 71 fucosylated N-glycopeptides from 13 major liver-secreted proteins in human plasma were globally identified by LC-MS/MS. Additionally, 37 fucosylated N-glycopeptides were newly identified from nine liver-secreted proteins, including alpha-1-antichymotrypsin, alpha-1-antitrypsin, alpha-2-HS-glycoprotein, ceruloplasmin, alpha-1-acid glycoprotein 1/2, alpha-2-macroglobulin, serotransferrin, and beta-2-glycoprotein 1. Of the fucosylated N-glycopeptides, bi- and tri-antennary glycoforms were the most common ones identified in liver-secreted proteins from HCC plasma. Therefore, we suggest that this analytical method is effective for characterizing fucosylation in liver-secreted proteins. Graphical abstract A global map of fucosylated and non-fucosylated glycopeptides from 13 liver-secreted glycoproteins in hepatocellular carcinoma plasma.

Targeted proteomics of solid cancers: from quantification of known biomarkers towards reading the digital proteome maps

The concept of personalized medicine includes novel protein biomarkers that are expected to improve the early detection, diagnosis and therapy monitoring of malignant diseases. Tissues, biofluids, cell lines and xenograft models are the common sources of biomarker candidates that require verification of clinical value in independent patient cohorts. Targeted proteomics - based on selected reaction monitoring, or data extraction from data-independent acquisition based digital maps - now represents a promising mass spectrometry alternative to immunochemical methods. To date, it has been successfully used in a high number of studies answering clinical questions on solid malignancies: breast, colorectal, prostate, ovarian, endometrial, pancreatic, hepatocellular, lung, bladder and others. It plays an important role in functional proteomic experiments that include studying the role of post-translational modifications in cancer progression. This review summarizes verified biomarker candidates successfully quantified by targeted proteomics in this field and directs the readers who plan to design their own hypothesis-driven experiments to appropriate sources of methods and knowledge.

A panel of regulated proteins in serum from patients with cervical intraepithelial neoplasia and cervical cancer

We developed a discovery-validation mass-spectrometry-based pipeline to identify a set of proteins that are regulated in serum of patients with cervical intraepithelial neoplasia (CIN) and squamous cell cervical cancer using iTRAQ, label-free shotgun, and targeted mass-spectrometric quantification. In the discovery stage we used a "pooling" strategy for the comparative analysis of immunodepleted serum and revealed 15 up- and 26 down-regulated proteins in patients with early- (CES) and late-stage (CLS) cervical cancer. The analysis of nondepleted serum samples from patients with CIN, CES, an CLS and healthy controls showed significant changes in abundance of alpha-1-acid glycoprotein 1, alpha-1-antitrypsin, serotransferrin, haptoglobin, alpha-2-HS-glycoprotein, and vitamin D-binding protein. We validated our findings using a fast UHPLC/MRM method in an independent set of serum samples from patients with cervical cancer or CIN and healthy controls as well as serum samples from patients with ovarian cancer (more than 400 samples in total). The panel of six proteins showed 67% sensitivity and 88% specificity for discrimination of patients with CIN from healthy controls, a stage of the disease where current protein-based biomarkers, for example, squamous cell carcinoma antigen (SCCA), fail to show any discrimination. Additionally, combining the six-protein panel with SCCA improves the discrimination of patients with CES and CLS from healthy controls.

Isotope-coded carbamidomethylation for quantification of N-glycoproteins with online microbore hollow fiber enzyme reactor-nanoflow liquid chromatography-tandem mass spectrometry

This paper introduces a simple, inexpensive, and robust quantitative proteomic method for quantifying N-linked glycoproteins based on isotope-coded carbamidomethylation (iCCM) incorporated into an online microbore hollow fiber enzyme reactor and nanoflow liquid chromatography-tandem mass spectrometry (mHFER-nLC-MS/MS). The iCCM quantitation uses carbamidomethylation (CM; a routine protection of thiol groups before proteolysis) of the Cys residue of proteins with iodoacetamide (IAA) or its isotope (IAA-(13)C2,D2: 4 Da difference). CM-/iCCM-labeled proteome samples are mixed for proteolysis; then, online enrichment of N-glycopeptides using lectin affinity is carried out in an mHFER before nLC-MS/MS for quantification using multiple reaction monitoring (MRM). Initial evaluation of the iCCM method varying the mixing ratio of CM-/iCCM-labeled bovine serum albumin (BSA) standards yielded successful quantification of 18 peptides with less than 2% variation in the calculated ratio of light/heavy-labeled peptides. The iCCM quantitation with mHFER-nLC-MS/MS was evaluated with three standard glycoproteins (α-1-acid glycoproteins, fetuin and transferrin) and then applied to serum glycoproteins from liver cancer patients and controls, resulting in successful quantification of 73 N-glycopeptides (from 49 N-glycoproteins), among which 19 N-glycopeptides from 14 N-glycoproteins showed more than a 2.5-fold aberrant change in liver cancer patients' sera compared with the pooled control. Although iCCM quantitation with mHFER-nLC-MS/MS applies only to glycopeptides with Cys residue, the method can offer several advantages over other labeling methods when applied to targeted glycoproteins: The iCCM method does not require an additional labeling reaction under special conditions nor complicated procedures to purify labeled products using additional columns. Isotope labeling at the protein level can minimize potential uncertainty originating from unequal efficiencies in protein digestion in separate vials and retrieval of each labeled peptide when labeling takes place at the peptide level. In addition, the labeling reagents for the iCCM method are readily obtained at a reasonable cost, which can make protein quantification easily accessible.

Differential proteomic approach for identification and verification of aberrantly glycosylated proteins in adenocarcinoma lung cancer (ADLC) plasmas by lectin-capturing and targeted mass spectrometry

To investigate quantitative differences in aberrant glycosylation of target glycoproteins between noncancerous group and patient group with adenocarcinoma lung cancer (ADLC), differential proteomic approach was developed by cooperatively using comparative lectin-capturing, targeted mass spectrometry (MRM MS), and antibody/lectin sandwich ELISA. Plasma samples comparatively prepared from 3 ADLC patients and 3 controls, with and without lectin-fractionation using fucose-specific Aleuria aurantia lectin (AAL), were trypsin-digested and analyzed for target glycoproteins, alpha-1-acid glycoprotein (AGP) and ceruloplasmin (CP), by MRM MS. From the MRM MS data the abundance levels of AAL-captured glycoforms of both targets were significantly higher in ADLC cases compared to controls, although the levels in total protein abundance were comparable between ADLC and control groups. This difference between ADLC and control groups in the fucosylated glycoform levels was originated mainly from aberrant fucosylation on the targets in ADLC plasmas rather than change in total protein abundance of the targets, and also confirmed by sandwich ELISA. AGP and CP were further verified to be biomarker candidates by MRM-based analysis of AAL-captured plasmas (30 ADLC cases, 30 controls), with AUROC 0.758 and 0.847 respectively. This differential proteomic approach can be useful for identifying and verifying biomarker candidate involved in aberrant protein glycosylation.

BIOLOGICAL SIGNIFICANCE

The present paper introduces an efficient differential proteomic method to investigate quantitative differences in aberrant protein glycosylation of serological glycoproteins between noncancerous group and lung cancer patient group. This differential proteomic approach consisting of the targeted MRM MS of comparatively lectin-captured plasma fractions and the antibody/lectin sandwich ELISA-based assay was evaluated to be useful for identification of aberrantly fucosylated glycoproteins AGP and CP in lung cancer plasmas. In addition, we have demonstrated that the MRM MS-based differential proteomic approach is also useful for high-throughput verification of the aberrantly fucosylated glycoproteins AGP and CP using the large number of individual plasmas. Therefore, the present MRM MS-based differential proteomic strategy with lectin-capturing can be a powerful tool for high-throughput verification of aberrantly glycosylated biomarker candidates, identified preliminary by mass profiling experiments in proteomic fields but requiring further validation using a large number of cohorts.

Glycoproteomic and glycomic databases

Protein glycosylation serves critical roles in the cellular and biological processes of many organisms. Aberrant glycosylation has been associated with many illnesses such as hereditary and chronic diseases like cancer, cardiovascular diseases, neurological disorders, and immunological disorders. Emerging mass spectrometry (MS) technologies that enable the high-throughput identification of glycoproteins and glycans have accelerated the analysis and made possible the creation of dynamic and expanding databases. Although glycosylation-related databases have been established by many laboratories and institutions, they are not yet widely known in the community. Our study reviews 15 different publicly available databases and identifies their key elements so that users can identify the most applicable platform for their analytical needs. These databases include biological information on the experimentally identified glycans and glycopeptides from various cells and organisms such as human, rat, mouse, fly and zebrafish. The features of these databases - 7 for glycoproteomic data, 6 for glycomic data, and 2 for glycan binding proteins are summarized including the enrichment techniques that are used for glycoproteome and glycan identification. Furthermore databases such as Unipep, GlycoFly, GlycoFish recently established by our group are introduced. The unique features of each database, such as the analytical methods used and bioinformatical tools available are summarized. This information will be a valuable resource for the glycobiology community as it presents the analytical methods and glycosylation related databases together in one compendium. It will also represent a step towards the desired long term goal of integrating the different databases of glycosylation in order to characterize and categorize glycoproteins and glycans better for biomedical research.

Mass spectrometry-based analysis of glycoproteins and its clinical applications in cancer biomarker discovery

Glycosylation is one of the most important posttranslational modifications of proteins and plays essential roles in various biological processes. Aberration in the glycan moieties of glycoproteins is associated with many diseases. It is especially critical to develop the rapid and sensitive methods for analysis of aberrant glycoproteins associated with diseases. Mass spectrometry (MS) has become a powerful tool for glycoprotein analysis. Especially, tandem mass spectrometry can provide highly informative fragments for structural identification of glycoproteins. This review provides an overview of the development of MS technologies and their applications in identification of abnormal glycoproteins and glycans in human serum to screen cancer biomarkers in recent years.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers.