Plasma proteome profiling of a mouse model of breast cancer identifies a set of up-regulated proteins in common with human breast cancer cells

We have applied an in-depth quantitative proteomic approach, combining isotopic labeling extensive intact protein separation and mass spectrometry, for high confidence identification of protein changes in plasmas from a mouse model of breast cancer. We hypothesized that a wide spectrum of proteins may be up-regulated in plasma with tumor development and that comparisons with proteins expressed in human breast cancer cell lines may identify a subset of up-regulated proteins in common with proteins expressed in breast cancer cell lines that may represent candidate biomarkers for breast cancer. Plasma from PyMT transgenic tumor-bearing mice and matched controls were obtained at two time points during tumor growth. A total of 133 proteins were found to be increased by 1.5-fold or greater at one or both time points. A comparison of this set of proteins with published findings from proteomic analysis of human breast cancer cell lines yielded 49 proteins with increased levels in mouse plasma that were identified in breast cancer cell lines. Pathway analysis comparing the subset of up-regulated proteins known to be expressed in breast cancer cell lines with other up-regulated proteins indicated a cancer related function for the former and a host-response function for the latter. We conclude that integration of proteomic findings from mouse models of breast cancer and from human breast cancer cell lines may help identify a subset of proteins released by breast cancer cells into the circulation and that occur at increased levels in breast cancer.     

Identification of tumor-associated plasma biomarkers using proteomic techniques: from mouse to human

In an effort to identify tumor-associated proteins from plasma of tumor-bearing mice that may be used as diagnostic biomarkers, we developed a strategy that combines a tumor xenotransplantation model in nude mice with comparative proteomic technology. Five human cancer cell lines (SC-M1, HONE-1, CC-M1, OECM1, GBM 8401) derived from stomach, nasopharyngeal, colon, oral and brain cancers were subcutaneously inoculated into nude mice and compared to control nude mice injected with phosphate-buffered saline. One month later, plasma from mice inoculated with cancer cells was collected for proteomic analysis using two-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS). Comparison of plasma 2-DE maps from tumor-bearing mice with those produced from control mice revealed the overexpression of several mouse acute phase proteins (APPs) such as haptoglobin. Another APP, serum amyloid A (SAA), was found only in mice bearing tumors induced by the stomach cancer cell line SC-M1, which has not previously been demonstrated in xenotransplatation experiment. Furthermore, by using immunohistochemistry, SAA and haptoglobin were found to originate from the mouse hosts and not from the human cancer cell line donors. The protein alterations were further confirmed on patients with stomach cancers where up-regulated levels of SAA were also observed. These results indicate that APPs may be used as nonspecific tumor-associated serum markers. SAA in particular may serve as a potential marker for detecting stomach cancer. Taken together, the combination of the xenotransplatation model in nude mice and proteomics analysis provided a valuable impact for clinical applications in cancer diagnostics. In addition, our findings demonstrate that a panel of APPs might serve as screening biomarkers for early cancer detection.     

High throughput quantitative analysis of serum proteins using glycopeptide capture and liquid chromatography mass spectrometry

It is expected that the composition of the serum proteome can provide valuable information about the state of the human body in health and disease and that this information can be extracted via quantitative proteomic measurements. Suitable proteomic techniques need to be sensitive, reproducible, and robust to detect potential biomarkers below the level of highly expressed proteins, generate data sets that are comparable between experiments and laboratories, and have high throughput to support statistical studies. Here we report a method for high throughput quantitative analysis of serum proteins. It consists of the selective isolation of peptides that are N-linked glycosylated in the intact protein, the analysis of these now deglycosylated peptides by liquid chromatography electrospray ionization mass spectrometry, and the comparative analysis of the resulting patterns. By focusing selectively on a few formerly N-linked glycopeptides per serum protein, the complexity of the analyte sample is significantly reduced and the sensitivity and throughput of serum proteome analysis are increased compared with the analysis of total tryptic peptides from unfractionated samples. We provide data that document the performance of the method and show that sera from untreated normal mice and genetically identical mice with carcinogen-induced skin cancer can be unambiguously discriminated using unsupervised clustering of the resulting peptide patterns. We further identify, by tandem mass spectrometry, some of the peptides that were consistently elevated in cancer mice compared with their control littermates.     

Precise mapping of increased sialylation pattern and the expression of acute phase proteins accompanying murine tumor progression in BALB/c mouse by integrated sera proteomics and glycomics

Inbred BALB/c mouse implanted with murine tumors serves as an attractive model system for the studies of cancer biology in immuno-competent individuals. It is anticipated that tumor progression would induce notable pathophysiological consequences, some of which manifested as alteration in serum proteomic and glycomic profiles. Similar to sera derived from human cancer patients and immuno-compromised mice bearing human tumors, we show in this work that BALB/c mice of the same genetic background but bearing two distinct tumor origins both exhibited elevated expression levels of acute phase proteins including haptoglobin and serum amyloid P protein, in response to tumor progression. Such common traits are generally not informative nor qualifying as biomarkers. Additional mass spectrometry (MS)-based glycomic mapping nevertheless detected distinctive changes of sialylation pattern on the complex type N-glycans. MALDI MS/MS sequencing afforded a facile but definitive identification of an increase in internal Neu5Gcalpha2-6 sialylation on the GlcNAc of the Neu5Gc2-3Gal1-3GlcNAc terminal sequence as a common feature whereas a substitution of Neu5Gc by Neu5Ac was found to be induced by colonic but not breast tumor. A more pronounced change was similarly detected on N-glycans derived from ascitic fluids representing late tumor progression stages. We next demonstrated that such distinct change in glycotope expression can be localized to a particular protein carrier by LC-MS/MS analysis of glycopeptides. Serotransferrin was identified as one such abundant serum glycoprotein, which changed significantly not in protein expression level but in terminal glycosylation pattern.     

18O Labeling for a Quantitative Proteomic Analysis of Glycoproteins in Hepatocellular Carcinoma

Introduction

Quantitative proteomics using tandem mass spectrometry is an attractive approach for identification of potential cancer biomarkers. Fractionation of complex tissue samples into subproteomes prior to mass spectrometric analyses increases the likelihood of identifying cancer-specific proteins that might be present in low abundance. In this regard, glycosylated proteins are an interesting class of proteins that are already established as biomarkers for several cancers.

Materials and Methods

In this study, we carried out proteomic profiling of tumor and adjacent non-cancer liver tissues from hepatocellular carcinoma (HCC) patients. Glycoprotein enrichment from liver samples using lectin affinity chromatography and subsequent ¹⁸O/¹⁶O labeling of peptides allowed us to obtain relative abundance levels of lectin-bound proteins. As a complementary approach, we also examined the relative expression of proteins in HCC without glycoprotein enrichment. Lectin affinity enrichment was found to be advantageous to quantitate several interesting proteins, which were not detected in the whole proteome screening approach. We identified and quantitated over 200 proteins from the lectin-based approach. Interesting among these were fetuin, cysteine-rich protein 1, serpin peptidase inhibitor, leucine-rich alpha-2-glycoprotein 1, melanoma cell adhesion molecule, and heparan sulfate proteoglycan-2. Using lectin affinity followed by PNGase F digestion coupled to ¹⁸O labeling, we identified 34 glycosylation sites with consensus sequence N-X-T/S. Western blotting and immunohistochemical staining were carried out for several proteins to confirm mass spectrometry results.

Conclusion

This study indicates that quantitative proteomic profiling of tumor tissue versus non-cancerous tissue is a promising approach for the identification of potential biomarkers for HCC.     

Targeted identification of metastasis-associated cell-surface sialoglycoproteins in prostate cancer

Covalent attachment of carbohydrates to proteins is one of the most common post-translational modifications. At the cell surface, sugar moieties of glycoproteins contribute to molecular recognition events involved in cancer metastasis. We have combined glycan metabolic labeling with mass spectrometry analysis to identify and characterize metastasis-associated cell surface sialoglycoproteins. Our model system used syngeneic prostate cancer cell lines derived from PC3 (N2, nonmetastatic, and ML2, highly metastatic). The metabolic incorporation of AC(4)ManNAz and subsequent specific labeling of cell surface sialylation was confirmed by flow cytometry and confocal microscopy. Affinity isolation of the modified sialic-acid containing cell surface proteins via click chemistry was followed by SDS-PAGE separation and liquid chromatography-tandem MS analysis. We identified 324 proteins from N2 and 372 proteins of ML2. Using conservative annotation, 64 proteins (26%) from N2 and 72 proteins (29%) from ML2 were classified as extracellular or membrane-associated glycoproteins. A selective enrichment of sialoglycoproteins was confirmed. When compared with global proteomic analysis of the same cells, the proportion of identified glycoprotein and cell-surface proteins were on average threefold higher using the selective capture approach. Functional clustering of differentially expressed proteins by Ingenuity Pathway Analysis revealed that the vast majority of glycoproteins overexpressed in the metastatic ML2 subline were involved in cell motility, migration, and invasion. Our approach effectively targeted surface sialoglycoproteins and efficiently identified proteins that underlie the metastatic potential of the ML2 cells.     

A lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform for identification of multiple liver cancer biomarkers in human plasma

Aberrantly glycosylated proteins related to liver cancer progression were captured with specific lectin and identified from human plasma by multiple reaction monitoring (MRM) mass spectrometry as multiple biomarkers for hepatocellular carcinoma (HCC). The lectin fractionation for fucosylated protein glycoforms in human plasma was conducted with a fucose-specific aleuria aurantia lectin (AAL). Following tryptic digestion of the lectin-captured fraction, plasma samples from 30 control cases (including 10 healthy, 10 hepatitis B virus [HBV], and 10 cirrhosis cases) and 10 HCC cases were quantitatively analyzed by MRM to identify which glycoproteins are viable HCC biomarkers. A1AG1, AACT, A1AT, and CERU were found to be potent biomarkers to differentiate HCC plasma from control plasmas. The AUROC generated independently from these four biomarker candidates ranged from 0.73 to 0.92. However, the lectin-coupled MRM assay with multiple combinations of biomarker candidates is superior statistically to those generated from the individual candidates with AUROC more than 0.95, which can be an alternative to the immunoassay inevitably requiring tedious development of multiple antibodies against biomarker candidates to be verified. Eventually the lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform was found to be efficient to identify multiple biomarkers from human plasma according to cancer progression.     

Mass spectrometric identification of human prostate cancer-derived proteins in serum of xenograft-bearing mice

Lack of sensitivity and specificity of current tumor markers has intensified research efforts to find new biomarkers. The identification of potential tumor markers in human body fluids is hampered by large variability and complexity of both control and patient samples, laborious biochemical analyses, and the fact that the identified proteins are unlikely produced by the diseased cells but are due to secondary body defense mechanisms. In a new approach presented here, we eliminate these problems by performing proteomic analysis in a prostate cancer xenograft model in which human prostate cancer cells form a tumor in an immune-incompetent nude mouse. Using this concept, proteins present in mouse serum that can be identified as human will, by definition, originate from the human prostate cancer xenograft and might have potential diagnostic and prognostic value. Using one-dimensional gel electrophoresis, liquid chromatography, and mass spectrometry, we identified tumor-derived human nm23/nucleoside-diphosphate kinase (NME) in the serum of a nude mouse bearing the androgen-independent human prostate cancer xenograft PC339. NME is known to be involved in the metastatic potential of several tumor cells, including prostate cancer cells. Furthermore we identified six human enzymes involved in glycolysis (fructose-bisphosphate aldolase A, triose-phosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, alpha enolase, and lactate dehydrogenases A and B) in the serum of the tumor-bearing mice. The presence of human NME and glyceraldehyde-3-phosphate dehydrogenase in the serum of PC339-bearing mice was confirmed by Western blotting. Although the putative usefulness of these proteins in predicting prognosis of prostate cancer remains to be determined, the present data illustrate that our approach is a promising tool for the focused discovery of new prostate cancer biomarkers.     

Halobacterium salinarum NRC-1 PeptideAtlas: toward strategies for targeted proteomics and improved proteome coverage

The relatively small numbers of proteins and fewer possible post-translational modifications in microbes provide a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a PeptideAtlas (PA) covering 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636 000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has highlighted plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore, we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics.     

Chemical methods for glycoprotein discovery

An important frontier in glycoproteomics is the discovery of proteins with post-translational glycan modifications. The first step in glycoprotein identification is the isolation of glycosylated proteins from the remainder of the proteome. New enzymatic and metabolic methods are being used to chemically tag proteins to enable their isolation. Once isolated, glycoproteins can be identified by mass spectrometry. Additional information can be obtained by using either enzymatic or chemoselective reactions to incorporate isotope labels at specific sites of glycosylation. Isotopic labeling facilitates mass spectrometry-based confirmation of glycoprotein identity, identification of glycosylation sites, and quantification of the extent of modification. By combining chemical tagging for isolation and isotope labeling for mass spectrometry analysis, researchers are developing highly effective strategies for glycoproteomics. These techniques are enabling cancer biologists to identify biomarkers whose glycosylation state correlates with disease states, and developmental biologists to characterize stage-specific changes in glycoprotein expression. Next-generation methods will make functional analyses of the glycoproteome possible, including the discovery of glycoprotein interaction partners and the identification of enzymes responsible for synthesis of particular glycan structures.     

Analysis of low-abundance, low-molecular-weight serum proteins using mass spectrometry.

To detect diseases early in the general population, new diagnostic approaches are needed that have adequate sensitivity and specificity. Recent studies have used mass spectrometry to identify a serum proteomic pattern for breast and ovarian cancer. Serum contains 60-80 mg/mL protein, but 57-71% of this is serum albumin, and 8-26% are gamma-globulins. These large proteins must be depleted before smaller, less-abundant proteins can be detected using mass spectrometry, but because serum albumin is known to act as a carrier for smaller proteins, removal of these molecules using columns or filtration may result in the loss of molecules of interest. The objective of this study was to develop a reproducible method to deplete serum samples of high-abundance proteins in order to analyze the less-abundant proteins present in serum. We used organic solvents to precipitate the large proteins out of solution. We also predicted that this would cause many smaller proteins to dissociate from their carrier molecules, allowing for detection of a larger number of peptides and small proteins. These treated samples were analyzed using capillary liquid chromatography coupled with electrospray ionization mass spectrometry. Analysis demonstrated reproducible results. Acetonitrile treatment clearly released many carrier-bound molecular species and was superior to ultrafiltration alone for serum proteomic analysis.     

Profiling of the tetraspanin web of human colon cancer cells

Tetraspanins are integral membrane proteins involved in a variety of physiological and pathological processes. In cancer, clinical and experimental studies have reported a link between tetraspanin expression levels and metastasis. Tetraspanins play a role as organizers of multimolecular complexes in the plasma membrane. Indeed each tetraspanin associates specifically with one or a few other membrane proteins forming primary complexes. Thus, tetraspanin-tetraspanin associations lead to a molecular network of interactions, the "tetraspanin web." We performed a proteomic characterization of the tetraspanin web using a model of human colon cancer consisting of three cell lines derived from the primary tumor and two metastases (hepatic and peritoneal) from the same patient. The tetraspanin complexes were isolated after immunoaffinity purification using monoclonal antibodies directed against the tetraspanin CD9, and the associated proteins were separated by SDS-PAGE and identified by mass spectrometry using LC-MS/MS. This allowed the identification of 32 proteins including adhesion molecules (integrins, proteins with Ig domains, CD44, and epithelial cell adhesion molecule) (EpCAM), membrane proteases (ADAM10, TADG-15, and CD26/dipeptidyl peptidase IV), and signaling proteins (heterotrimeric G proteins). Importantly some components were differentially detected in the tetraspanin web of the three cell lines: the laminin receptor Lutheran/B-cell adhesion molecule (Lu/B-CAM) was expressed only on the primary tumor cells, whereas CD26/dipeptidyl peptidase IV and tetraspanin Co-029 were observed only on metastatic cells. Concerning Co-029, immunohistofluorescence showed a high expression of Co-029 on epithelial cells in normal colon and a lower expression in tumors, whereas heterogeneity in terms of expression level was observed on metastasis. Finally we demonstrated that epithelial cell adhesion molecule and CD9 form a new primary complex in the tetraspanin web.     

Phosphatidylinositol 3,4,5-trisphosphate activity probes for the labeling and proteomic characterization of protein binding partners

Phosphatidylinositol polyphosphate lipids, such as phosphatidylinositol 3,4,5-trisphosphate [PI(3,4,5)P?], regulate critical biological processes, many of which are aberrant in disease. These lipids often act as site-specific ligands in interactions that enforce membrane association of protein binding partners. Herein, we describe the development of bifunctional activity probes corresponding to the headgroup of PI(3,4,5)P? that are effective for identifying and characterizing protein binding partners from complex samples, namely cancer cell extracts. These probes contain both a photoaffinity tag for covalent labeling of target proteins and a secondary handle for subsequent detection or manipulation of labeled proteins. Probes bearing different secondary tags were exploited, either by direct attachment of a fluorescent dye for optical detection or by using an alkyne that can be derivatized after protein labeling via click chemistry. First, we describe the design and modular synthetic strategy used to generate multiple probes with different reporter tags of use for characterizing probe-labeled proteins. Next, we report initial labeling studies using purified protein, the PH domain of Akt, in which probes were found to label this target, as judged by in-gel detection. Furthermore, protein labeling was abrogated by controls including competition with an unlabeled PI(3,4,5)P? headgroup analogue as well as through protein denaturation, indicating specific labeling. In addition, probes featuring linkers of different lengths between the PI(3,4,5)P? headgroup and photoaffinity tag led to variations in protein labeling, indicating that a shorter linker was more effective in this case. Finally, proteomic labeling studies were performed using cell extracts; labeled proteins were observed by in-gel detection and characterized using postlabeling with biotin, affinity chromatography, and identification via tandem mass spectrometry. These studies yielded a total of 265 proteins, including both known and novel candidate PI(3,4,5)P?-binding proteins.     

Identification and validation of SRC and phospho-SRC family proteins in circulating mononuclear cells as novel biomarkers for pancreatic cancer

There is an urgent need to develop novel markers of pancreatic cancer to facilitate early diagnosis. Pancreatic carcinoma is characterized by marked stroma formation with a high number of infiltrating tumor-associated macrophages (TAMs) that originate from circulating mononuclear cells (MNCs). We hypothesized that differential analysis of protein expression and phosphorylation in circulating MNCs from healthy nude mice and nude mice bearing orthotopic human pancreatic cancer would identify a surrogate marker of pancreatic cancer. These differences were analyzed by two-dimensional gel electrophoresis followed by Western blot analysis using antibody against phosphorylated tyrosine proteins (pY). Protein and phosphorylated protein spots of interest were identified by mass spectrometry and validated by Western blot analysis as candidate markers for pancreatic cancer. We found that the expression and phosphorylation of Src family proteins were significantly higher in circulating MNCs from mice bearing pancreatic cancer than in circulating MNCs from healthy mice. TAMs in mice with pancreatic tumors also had higher Src family protein expression and phosphorylation than resident macrophages in the pancreas of healthy mice. The expression and phosphorylation of Src family proteins were correlated with tumor weight; however, increased Src expression and phosphorylation also occurred in MNCs from mice with chronic pancreatitis. This is the first report to explore novel pancreatic tumor markers in circulating MNCs. Although the specificity of the marker for pancreatic cancer was low, it could be used to monitor the disease or to select high-risk patients with chronic pancreatitis.     

Monitoring of gene expression by functional proteomics: response of human lung fibroblast cells to stimulation by endothelin-1.

Proteomic methods have been used to monitor changes in protein synthesis in the first 4 h following stimulation of human lung fibroblasts with endothelin-1. Using pulsed [(35)S]methionine labeling, about 70 proteins with altered protein synthesis could be detected, and the 35 proteins showing the largest changes were identified by mass spectrometry. The observed proteins included unexpected proteins such as Sox5, two isoforms of Rab14, Rab3A, translationally controlled tumor protein, and one protein of previously unknown function. There was a wide range of different kinetic behavior, and groups of functionally linked proteins such as Rab14, nucleophosmin,and cyclin-dependent kinase inhibitor 1B could be detected from similar kinetics. We propose that the functional proteomic methods are competitive with and have some advantages compared to expression profiling methods for monitoring gene expression.     

Integrated Proteomic Analysis of Human Cancer Cells and Plasma from Tumor Bearing Mice for Ovarian Cancer Biomarker Discovery

Background

The complexity of the human plasma proteome represents a substantial challenge for biomarker discovery. Proteomic analysis of genetically engineered mouse models of cancer and isolated cancer cells and cell lines provide alternative methods for identification of potential cancer markers that would be detectable in human blood using sensitive assays. The goal of this work is to evaluate the utility of an integrative strategy using these two approaches for biomarker discovery.

Methodology/Principal Findings

We investigated a strategy that combined quantitative plasma proteomics of an ovarian cancer mouse model with analysis of proteins secreted or shed by human ovarian cancer cells. Of 106 plasma proteins identified with increased levels in tumor bearing mice, 58 were also secreted or shed from ovarian cancer cells. The remainder consisted primarily of host-response proteins. Of 25 proteins identified in the study that were assayed, 8 mostly secreted proteins common to mouse plasma and human cancer cells were significantly upregulated in a set of plasmas from ovarian cancer patients. Five of the eight proteins were confirmed to be upregulated in a second independent set of ovarian cancer plasmas, including in early stage disease.

Conclusions/Significance

Integrated proteomic analysis of cancer mouse models and human cancer cell populations provides an effective approach to identify potential circulating protein biomarkers.     

Comparative serum glycoproteomics using lectin selected sialic acid glycoproteins with mass spectrometric analysis: application to pancreatic cancer serum

A strategy is developed in this study for identifying sialylated glycoprotein markers in human cancer serum. This method consists of three steps: lectin affinity selection, a liquid separation and characterization of the glycoprotein markers using mass spectrometry. In this work, we use three different lectins (Wheat Germ Agglutinin, (WGA) Elderberry lectin,(SNA), Maackia amurensis lectin, (MAL)) to extract sialylated glycoproteins from normal and cancer serum. Twelve highly abundant proteins are depleted from the serum using an IgY-12 antibody column. The use of the different lectin columns allows one to monitor the distribution of alpha(2,3) and alpha(2,6) linkage type sialylation in cancer serum vs that in normal samples. Extracted glycoproteins are fractionated using NPS-RP-HPLC followed by SDS-PAGE. Target glycoproteins are characterized further using mass spectrometry to elucidate the carbohydrate structure and glycosylation site. We applied this approach to the analysis of sialylated glycoproteins in pancreatic cancer serum. Approximately 130 sialylated glycoproteins are identified using microLC-MS/MS. Sialylated plasma protease C1 inhibitor is identified to be down-regulated in cancer serum. Changes in glycosylation sites in cancer serum are also observed by glycopeptide mapping using microLC-ESI-TOF-MS where the N83 glycosylation of alpha1-antitrypsin is down regulated. In addition, the glycan structures of the altered proteins are assigned using MALDI-QIT-MS. This strategy offers the ability to quantitatively analyze changes in glycoprotein abundance and detect the extent of glycosylation alteration as well as the carbohydrate structure that correlate with cancer.     

Comparative profiling of serum glycoproteome by sequential purification of glycoproteins and 2-nitrobenzensulfenyl (NBS) stable isotope labeling: a new approach for the novel biomarker discovery for cancer

The recent progress in various proteomic technologies allows us to screen serum biomarker including carbohydrate antigens. However, only a limited number of proteins could be detected by current conventional methods such as shotgun proteomics, primarily because of the enormous concentration distribution of serum proteins and peptides. To circumvent this difficulty and isolate potential cancer-specific biomarkers for diagnosis and treatment, we established a new screening system consisting of the sequential steps of (1) immunodepletion of 6 high-abundance proteins, (2) targeted enrichment of glycoproteins by lectin column chromatography, and (3) the quantitative proteome analysis using 12C6- or 13C6-NBS (2-nitrobenzenesulfenyl) stable isotope labeling followed by MALDI-QIT-TOF mass spectrometric analysis. Through this systematic analysis for five serum samples derived from patients with lung adenocarcinoma, we identified as candidate biomarkers 34 serum glycoproteins that revealed significant difference in alpha1,6-fucosylation level between lung cancer and healthy control, clearly demonstrating that the carbohydrate-focused proteomics could allow for the detection of serum components with cancer-specific features. In addition, we developed a more simplified and practical technique, mass spectrometry-based glycan structure analysis and lectin blotting, in order to validate glycan structure of candidate biomarkers that could be applicable in clinical use. Our new glycoproteomic strategy will provide highly sensitive and quantitative profiling of specific glycan structures on multiple proteins, which should be useful for serum biomarker discovery.