Identification of target proteins of N-acetylglucosaminyl transferase V in human colon cancer and implications of protein tyrosine phosphatase kappa in enhanced cancer cell migration

To gain a better understanding of the mechanism underlying colon cancer and to search for potential markers of colon cancer prognosis, a comparative proteomic analysis of colon cancer WiDr cells was conducted using 2-DE and lectin blot, followed by identification based on ESI-MS. Through these approaches 14 proteins were identified as candidate target proteins for N-acetylglucosaminyl transferase V (GnT-V) that would be expected to be implicated in the progression of colon cancer. We selected protein tyrosine phosphatase kappa (PTPkappa) as a model protein to validate this approach to the discovery of novel biomarkers in colon cancer. PTPkappa underwent an aberrant glycosylation in GnT-V-overexpressing WiDr cells, and the aberrantly glycosylated PTPkappa was vulnerable to proteolytic cleavage. The enhanced cleavage of PTPkappa in GnT-V-overexpressing cells was responsible for the mitigation of the homophilic binding capacity, resulting in an increase in cancer cell migration.     

Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer

Molecular biomarkers of early stage breast cancer may improve the sensitivity and specificity of diagnosis. Plasma biomarkers have additional value in that they can be monitored with minimal invasiveness. Plasma biomarker discovery by genome-wide proteomic methods is impeded by the wide dynamic range of protein abundance and the heterogeneity of protein expression in healthy and disease populations which requires the analysis of a large number of samples. We addressed these issues through the development of a novel protocol that couples a combinatorial peptide ligand library protein enrichment strategy with isobaric label-based 2D LC-MS/MS for the identification of candidate biomarkers in high throughput. Plasma was collected from patients with stage I breast cancer or benign breast lesions. Low abundance proteins were enriched using a bead-based combinatorial library of hexapeptides. This resulted in the identification of 397 proteins, 22% of which are novel plasma proteins. Twenty-three differentially expressed plasma proteins were identified, demonstrating the effectiveness of the described protocol and defining a set of candidate biomarkers to be validated in independent samples. This work can be used as the basis for the design of properly powered investigations of plasma protein expression for biomarker discovery in larger cohorts of patients with complex disease.     

Discovery of Colorectal Cancer Biomarker Candidates by Membrane Proteomic Analysis and Subsequent Verification using Selected Reaction Monitoring (SRM) and Tissue Microarray (TMA) Analysis

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the identification of useful biomarker candidates for various cancers. Data are available via ProteomeXchange with identifier PXD000851.Recent advances in proteomic technology have contributed to the identification of biomarkers for various diseases. Improvements in LC-MS technology have led to an increase in the number of proteins that have been identified. In addition, a stable isotopic labeling method using isobaric tag for relative and absolute quantitation (iTRAQ)¹ and stable isotope labeling by amino acids in cell culture has enabled the quantitative analysis of multiple samples (1, 2). Therefore, a large number of proteins have already been identified as biomarker candidates; however, only a few of these have been used in practical applications because most have not yet progressed to the validation stage, in which potential biomarker candidates are quantified on a large scale. The validation of biomarker candidates is generally accomplished using Western blotting and enzyme-linked immunosorbent assays (ELISA) if specific and well-characterized antibodies for these candidates are available. However, highly specific antibodies are not currently available for most novel biomarker candidate proteins, and it takes a significant amount of time and money to obtain these antibodies and optimize ELISA assay systems for many candidates; therefore, another validation assay system needs to be developed. Selected (or multiple) reaction monitoring (SRM or MRM) was previously shown to be a potentially effective method for the validation of biomarker candidates (3–5). The SRM/MRM assay can measure multiple targets at high sensitivity and throughput without antibodies; hence, it is useful for initial quantitative evaluations and the large-scale validation of biomarker candidates, which defines validation of hundreds of biomarker candidate proteins simultaneously.In addition to these technical improvements, the fractionation process also plays an important role in proteome analysis for biomarker discovery. This procedure very effectively analyzes the proteomes of specific cellular compartments or organelles in detail, which reduces sample complexity. The preparation of a membrane fraction was previously shown to be useful for identifying membrane proteins that are generally expressed at relatively low levels. Membrane proteins play critical roles in many biological functions, such as signal transduction, cell-cell interactions, and ion transport, account for ∼38% of all proteins encoded by the mammalian genome and more than one-third of biomarker candidates, and are also potential targets for drug therapy (6, 7). Therefore, membrane proteome analysis is important for biomarker discovery. However, difficulties have been associated with extracting and solubilizing membrane proteins and subsequent protease digestion. Many procedures have consequently been developed to improve the solubilization and digestion of membrane proteins (8–11), and a protocol using phase transfer surfactant (PTS) was shown to be suitable for membrane proteomics using LC-MS/MS (12, 13).The selection of a control group for comparisons is also important for identifying potential biomarkers. Tissue samples from cancer patients have been used in many studies to discover biomarker candidates by proteomic analysis. Previous studies, including our own, attempted to compare cancer tissues with matched normal tissue (14–17). However, marked differences have been reported in the histology, genetics, and proteomics of normal and cancer tissues, and many biomarker candidates have been identified, by making it difficult to narrow down more reliable candidates for further validation. Lazebnik recently emphasized that the features of malignant, but not benign tumors could be used as a hallmark of cancer (18), and also that premalignant lesions were more appropriate controls for cancer tissue than normal tissue for the identification of biomarker candidates involved in cancer progression. Moreover, comparisons of cancer with and without metastasis may also assist in the discovery of biomarker candidates involved in cancer metastasis. Therefore, the identification of biomarker candidates that can be used to diagnose and determine the prognosis of cancer should become more effective by comparing cancer tissues at different stages, including benign tumors.We performed a shotgun proteomic analysis of membrane fractions prepared from colorectal cancer tissue and benign polyps in the present study to identify biomarker candidates for the diagnosis and treatment of cancer. We identified a large number of biomarker candidate proteins associated with the progression of colon cancer by using membrane protein extraction with PTS followed by iTRAQ labeling. SRM/MRM confirmed the altered expression of these biomarker candidates, and these results were further verified using an independent set of tissue samples. A protein with uncharacterized function, C8orf55, was also validated with a tissue microarray that included various types of cancers.     

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.     

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

We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (n=5/subtype). The samples were fractionated using the lectins Aleuria aurantia (AAL) and Sambucus nigra agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically N-deglycosylated and analyzed by LC-MS/MS. In total, we identified 533 glycoproteins, ～90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype.     

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.     

NMR structural characterization of substrates bound to N-acetylglucosaminyltransferase V

N-Acetylglucosaminyltransferase V (GnT-V) is an enzyme involved in the biosynthesis of asparagine-linked oligosaccharides. It is responsible for the transfer of N-acetylglucosamine (GlcNAc) from the nucleotide sugar donor, uridine 5'-diphospho-N-acetylglucosamine (UDP-GlcNAc), to the 6 position of the alpha-1-6 linked Man residue in N-linked oligosaccharide core structures. GnT-V up-regulation has been linked to increased cancer invasiveness and metastasis and, appropriately, targeted for drug development. However, drug design is impeded by the lack of structural information on the protein and the way in which substrates are bound. Even though the catalytic domain of this type II membrane protein can be expressed in mammalian cell culture, obtaining structural information has proved challenging due to the size of the catalytic domain (95 kDa) and its required glycosylation. Here, we present an experimental approach to obtaining information on structural characteristics of the active site of GnT-V through the investigation of the bound conformation and relative placement of its ligands, UDP-GlcNAc and beta-D-GlcpNAc-(1-->2)-alpha-D-Manp-(1-->6)-beta-D-GlcpOOctyl. Nuclear magnetic resonance (NMR) spectroscopy experiments, inducing transferred nuclear Overhauser effect (trNOE) and saturation transfer difference (STD) experiments, were used to characterize the ligand conformation and ligand-protein contact surfaces. In addition, a novel paramagnetic relaxation enhancement experiment using a spin-labeled ligand analogue, 5'-diphospho-4-O-2,2,6,6-tetramethylpiperidine 1-oxyl (UDP-TEMPO), was used to characterize the relative orientation of the two bound ligands. The structural information obtained for the substrates in the active site of GnT-V can be useful in the design of inhibitors for GnT-V.     

From SELDI-TOF MS to protein identification by on-chip elution

SELDI-TOF MS has been demonstrated as a powerful tool for biomarker discovery. However, a major disadvantage of SELDI-TOF MS is the lack of direct identification of the discriminatory peaks discovered. We describe a novel experimental identification strategy where peptides/proteins captured to a weak cation exchange ProteinArray surface (CM10) are eluted, and thereafter identified by utilizing a sensitive LC-MS/MS (i.e. LTQ Orbitrap). A mixture of four known proteins was used to test the novel experimental approach described, and all four proteins were successfully identified. Additionally, a biomarker candidate previously discovered in plasma of Atlantic cod (Gadus morhua) by SELDI-TOF MS was identified. Thus, this study indicated that a combination of on-chip elution and a highly sensitive LC-MS/MS system can be an alternative approach to identify biomarker candidates discovered by use of SELDI-TOF MS.     

A targeted proteomics-based pipeline for verification of biomarkers in plasma

High-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.     

Control of metastasis by Asn-linked, beta1-6 branched oligosaccharides in mouse mammary cancer cells

Studies in cell lines and malignant human tissues have shown that increased cell-surface Asn-linked beta1-6(GlcNAcbeta1-6Man) branching is associated with increased tumorigenic and metastatic properties. In this study, three mouse mammary cancer cell lines were transfected with an expression vector containing the mouse cDNA for N-acetylglucosaminyltransferase V (GlcNAcT-V EC 2.4.1.155), the glycosyltransferase responsible for initiating beta1-6 branching on Asn-linked carbohydrates. The cell lines were screened for increased cytotoxicity to L-PHA, a lectin specific for beta1-6 branching structures. Cell lines exhibiting increased L-PHA cytotoxicity expressed increased levels of beta1-6 branching structures. Northern blots detected the presence of GlcNAcT-V transcribed from the expression vector in the L-PHA sensitive cell lines. After injection into the tail veins of mice, transfected cell lines with increased beta1-6 branching on the cell surface formed elevated levels of lung tumors relative to control transfected cell lines (P < 0.002). Western blots of membrane proteins from GlcNAcT-V transfected and control cells probed with the lectins DSA and WGA did not show an increase in polyN-acetyllactosamine and sialic acid content in the transfected cell lines. These results demonstrate that a specific increase in beta1-6 branching due to an elevation in GlcNAcT-V expression increases metastatic potential.     

Remodeling of sugar chain structures of human interferon-gamma

Natural human interferon (IFN)-gamma has mainly biantennary complex-type sugar chains and scarcely has multiantennary structures. We attempted to remodel the sugar chain structures using IFN-gamma as a model glycoprotein. To obtain the branching glycoforms of IFN-gamma, we introduced the genes for GnT-IV (UDP-N-acetylglucosamine:alpha-1,3-D-mannoside beta-1, 4-N-acetylglucosaminyltransferase) and/or GnT-V (UDP-N-acetylglucosamine:alpha-1,6-D-mannoside beta-1, 6-N-acetylglucosaminyltransferase) into Chinese hamster ovary (CHO) cells producing human IFN-gamma. The parental CHO cells produced IFN-gamma with biantennary sugar chains mainly. When the GnT-IV activity was increased, triantennary sugar chains with a branch produced by GnT-IV increased up to 66.9% of the total sugar chains. When the GnT-V activity was increased, triantennary sugar chains with a corresponding branch increased up to 55.7% of the total sugar chains. When the GnT-IV and -V activities were increased at a time, tetraantennary sugar chains increased up to 56.2% of the total sugar chains. The proportion of these multiantennary sugar chains corresponded to the intracellular activities of GnT-IV and -V. What is more, lectin blot and flow cytometric analysis indicated that the multi-branch structure of the sugar chains was increased not only on IFN-gamma, one of the secretory glycoproteins, but also on almost CHO cellular proteins by introducing either or both of the GnT genes. The results suggest that the branching structure of sugar chains of glycoproteins could be controlled by cellular GnT-IV and GnT-V activities. This technology can produce glycoforms out of natural occurrence, which should enlarge the potency of glycoprotein therapeutics.     

N-acetylglucosaminyltransferase-V requires a specific noncatalytic luminal domain for its activity toward glycoprotein substrates

N-acetylglucosaminyltransferase-V (GnT-V or MGAT5) catalyzes the formation of an N-glycan β1,6-GlcNAc branch on selective target proteins in the Golgi apparatus and is involved in cancer malignancy and autoimmune disease etiology. Several three-dimensional structures of GnT-V were recently solved, and the recognition mechanism of the oligosaccharide substrate was clarified. However, it is still unclear how GnT-V selectively acts on glycoprotein substrates. In this study, we focused on an uncharacterized domain at the N-terminal side of the luminal region (N domain) of GnT-V, which was previously identified in a crystal structure, and aimed to reveal its role in GnT-V action. Using lectin blotting and fluorescence assisted cell sorting analysis, we found that a GnT-VΔN mutant lacking the N domain showed impaired biosynthetic activity in cells, indicating that the N domain is required for efficient glycosylation. To clarify this mechanism, we measured the in vitro activity of purified GnT-VΔN toward various kinds of substrates (oligosaccharide, glycohexapeptide, and glycoprotein) using HPLC and a UDP-Glo assay. Surprisingly, GnT-VΔN showed substantially reduced activity toward the glycoprotein substrates, whereas it almost fully maintained its activity toward the oligosaccharides and the glycopeptide substrates. Finally, docking models of GnT-V with substrate glycoproteins suggested that the N domain could interact with the substrate polypeptide directly. Our findings suggest that the N domain of GnT-V plays a critical role in the recognition of glycoprotein substrates, providing new insights into the mechanism of substrate-selective biosynthesis of N-glycans.     

Elevated expression of N-acetylglucosaminyltransferase V in first trimester human placenta

In early pregnancy, placental trophoblast cells rapidly grow and invade into maternal uterine tissue. N-Acetylglucosaminyltransferase V (GnT-V) and its product, beta1-6-GlcNAc branching glycan, are known to correlate with tumor invasion and metastasis. Since the placentation process resembles invasion of cancer cells, we examined the expression of beta1-6-GlcNAc branching glycan and GnT-V in human placenta. Placentas derived from the first trimester contained a larger amount of beta1-6-GlcNAc branching glycan, detected by leukoagglutinating phytohemagglutinin lectin blotting, than those at term. Immunohistochemical study revealed that beta1-6-GlcNAc branching glycans and GnT-V protein were localized in the trophoblast layer. Both protein expression and the enzyme activity of GnT-V in first trimester placentas were higher than those at term. These results suggest that GnT-V would contribute to placentation in the early phase of pregnancy, possibly regulating the process of invasion of trophoblast cells.     

Proteomic Helicobacter pylori biomarkers discriminating between duodenal ulcer and gastric cancer

Protein patterns of 129 Helicobacter pylori strains isolated from Korean and Colombian patients suffering from duodenal ulcer or gastric cancer were analyzed by the high-throughput methodology SELDI-TOF-MS. Eighteen statistically significant candidate biomarkers discriminating between the two clinical outcomes were selected by using the Mann–Whitney test. Three biomarker proteins were purified and identified as a neutrophil-activating protein NapA (HU HPAG1_0821), a RNA-binding protein (HPAG1_0813), and a DNA-binding histone-like protein HU, respectively (jhp0228). These novel biomarkers can be used for development of diagnostic assays predicting the evolution to gastric cancer in H. pylori-infected patients.     

Identification of novel tumor antigens with patient-derived immune-selected antibodies

The identification of tumor antigens capable of eliciting an immune response in vivo may be an effective method to identify therapeutic cancer targets. We have developed a method to identify such antigens using frozen tumor-draining lymph node samples from breast cancer patients. Immune responses in tumor-draining lymph nodes were identified by immunostaining lymph node sections for B-cell markers (CD20&CD23) and Ki67 which revealed cell proliferation in germinal center zones. Antigen-dependent somatic hypermutation (SH) and clonal expansion (CE) were present in heavy chain variable (VH) domain cDNA clones obtained from these germinal centers, but not from Ki67 negative germinal centers. Recombinant VH single-domain antibodies were used to screen tumor proteins and affinity select potential tumor antigens. Neuroplastin (NPTN) was identified as a candidate breast tumor antigen using proteomic identification of affinity selected tumor proteins with a recombinant VH single chain antibody. NPTN was found to be highly expressed in approximately 20% of invasive breast carcinomas and 50% of breast carcinomas with distal metastasis using a breast cancer tissue array. Additionally, NPTN over-expression in a breast cancer cell line resulted in a significant increase in tumor growth and angiogenesis in vivo which was related to increased VEGF production in the transfected cells. These results validate NPTN as a tumor-associated antigen which could promote breast tumor growth and metastasis if aberrantly expressed. These studies also demonstrate that humoral immune responses in tumor-draining lymph nodes can provide antibody reagents useful in identifying tumor antigens with applications for biomarker screening, diagnostics and therapeutic interventions.     

Computational Prediction of Human Salivary Proteins from Blood Circulation and Application to Diagnostic Biomarker Identification

Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer.     

Structure-based design of UDP-GlcNAc analogs as candidate GnT-V inhibitors

Background: N-Glycan branching regulates various functions of glycoproteins. N-Acetylglucosaminyltransferase V (GnT-V) is a GlcNAc transferase that acts on N-glycans and the GnT-V-producing branch is highly related to cancer progression. This indicates that specific GnT-V inhibitors may be drug candidates for cancer treatment. To design novel GnT-V inhibitors, we focused on the unique and weak recognition of the donor substrate UDP-GlcNAc by GnT-V. On the basis of the catalytic pocket structure, we hypothesized that UDP-GlcNAc analogs with increasing hydrophobicity may be GnT-V inhibitors.Methods: We chemically synthesized 10 UDP-GlcNAc analogs in which one or two phosphate groups were replaced with hydrophobic groups. To test these compounds, we set up an HPLC-based enzyme assay system for all N-glycan-branching GlcNAc transferases in which GnT-I–V activity was measured using purified truncated enzymes. Using this system, we assessed the inhibitory effects of the synthesized compounds on GnT-V and their specificity.Results: Several UDP-GlcNAc analogs inhibited GnT-V activity, although the inhibition potency was modest. Compared with other GnTs, these compounds showed a preference for GnT-V, which suggested that GnT-V was relatively tolerant of hydrophobicity in the donor substrate. Docking models of the inhibitory compounds with GnT-V suggested the mechanisms of how these compounds interacted with GnT-V and inhibited its action.Conclusions: Chemical modification of the donor substrate may be a promising strategy to develop selective inhibitors of GnT-V.General significance: Our findings provide new insights into the design of GnT inhibitors and how GnTs recognize the donor substrate.