Yunli Hu

Identifying cancer biomarkers by mass spectrometry-based glycomics

Correlations between aberrant glycosylation and cancer have been established for decades. The major advances in mass spectrometry (MS) and separation science have rapidly advanced detailed characterization of the changes associated with cancer development and progression. Over the past 10 years, many reports have described MS‐based glycomic methods directed toward comparing the glycomic profiles of different human specimens collected from disease‐free individuals and patients with cancers. Glycomic profiling of glycoproteins isolated from human specimens originating from disease‐free individuals and patients with cancers have also been performed. Profiling of native, labeled, and permethylated glycans has been acquired using MALDI‐MS and LC‐MS. This review focuses on describing, discussing, and evaluating the different glycomic methods employed to characterize and quantify glycomic changes associated with cancers of different organs, including breast, colon, esophagus, liver, ovarian, pancreas, and prostate.

Quantitative Glycomics Strategies

The correlations between protein glycosylation and many biological processes and diseases are increasing the demand for quantitative glycomics strategies enabling sensitive monitoring of changes in the abundance and structure of glycans. This is currently attained through multiple strategies employing several analytical techniques such as capillary electrophoresis, liquid chromatography, and mass spectrometry. The detection and quantification of glycans often involve labeling with ionic and/or hydrophobic reagents. This step is needed in order to enhance detection in spectroscopic and mass spectrometric measurements. Recently, labeling with stable isotopic reagents has also been presented as a very viable strategy enabling relative quantitation. The different strategies available for reliable and sensitive quantitative glycomics are herein described and discussed.

Enhanced sensitivity of LC-MS analysis of permethylated N-glycans through online purification†

Aberrant glycosylation of proteins and lipids has been implicated in many human diseases, thus prompting the need for reliable analytical methods that permit dependable quantification of glycans originating from biological specimens. MS of permethylated glycans is currently employed to monitor disease‐related aberrant glycosylation of proteins and lipids. However, enhancing the sensitivity of this type of analysis is still needed. Here, analysis of permethylated glycans at enhanced sensitivity is attained through miniaturized solid‐phase permethylation and online solid‐phase purification. Solid‐phase permethylation method was miniaturized by reducing the amount of sodium hydroxide beads (one‐third the original amount) packed in microspin columns. The efficiency of glycan permethylation was not adversely affected by this reduction. Online solid‐phase purification of permethylated N‐glycans derived from model glycoproteins, such as fetuin, α‐1 acid glycoprotein and ribonuclease B, offered more sensitive and reproducible results than offline liquid–liquid and solid‐phase extractions. Online solid‐phase purification method described here permitted a 75% increase in signal intensities of permethylated glycans relative to offline purification methods. This is mainly due to the minimized sample handling associated with an online cleaning procedure. The efficiency and utility of online solid‐phase purification was also demonstrated here for N‐glycans derived from human blood serum. Online solid‐phase purification permitted the detection of 73 N‐glycan structures, while only 63 glycan structures were detected in the case of samples purified through liquid–liquid extraction. The intensities of the 63 structures that were detected in both cases were 75% higher for samples that were purified through the online method.

Comparing MALDI-MS, RP-LC-MALDI-MS and RP-LC-ESI-MS glycomic profiles of permethylated N-glycans derived from model glycoproteins and human blood serum.

The glycomic profiling of purified glycoproteins and biological specimen is routinely achieved through different analytical methods, but mainly through MS and LC‐MS. The enhanced ionization efficiency and improved tandem MS interpretation of permethylated glycans have prompted the popularity of this approach. This study focuses on comparing the glycomic profiling of permethylated N‐glycans derived from model glycoproteins and human blood serum using MALDI‐MS as well as RP‐LC‐MALDI‐MS and RP‐LC‐ESI‐MS. In the case of model glycoproteins, the glycomic profiles acquired using the three methods were very comparable. However, this was not completely true in the case of glycans derived from blood serum. RP‐LC‐ESI‐MS analysis of reduced and permethylated N‐glycans derived from 250 nl of blood serum allowed the confident detection of 73 glycans (the structures of which were confirmed by mass accuracy and tandem MS), while 53 and 43 structures were identified in the case of RP‐LC‐MALDI‐MS and MALDI‐MS analyses of the same sample, respectively. RP‐LC‐ESI‐MS analysis facilitates automated and sensitive tandem MS acquisitions. The glycan structures that were detected only in the RP‐LC‐ESI‐MS analysis were glycans existing at low abundances. This is suggesting the higher detection sensitivity of RP‐LC‐ESI‐MS analysis, originating from both reduced competitive ionization and saturation of detectors, facilitated by the chromatographic separation. The latter also permitted the separation of several structural isomers; however, isomeric separations pertaining to linkages were not detected.

Defining putative glycan cancer biomarkers by MS

For decades, the association between aberrant glycosylation and many types of cancers has been shown. However, defining the changes of glycan structures has not been demonstrated until recently. This has been facilitated by the major advances in MS and separation science, which allows the detailed characterization of glycan changes associated with cancer. MS glycomics methods have been successfully employed to compare the glycomic profiles of different human specimens collected from disease-free individuals and patients with cancer. Additionally, comparing the glycomic profiles of glycoproteins purified from specimen collected from disease-free individuals and patients with cancer has also been performed. These types of glycan analyses employing MS or LC-MS allow the characterization of native, labeled and permethylated glycans. This review discusses the different glycomic and glycoproteomic methods employed for defining glycans as cancer biomarkers of different organs, including breast, colon, esophagus, liver, lung, ovarian, pancreas and prostate.

Ion mobility-mass spectrometry analysis of serum N-linked glycans from esophageal adenocarcinoma phenotypes.

Three disease phenotypes, Barretts esophagus (BE), high-grade dysplasia (HGD), esophageal adenocarcinoma (EAC), and a set of normal control (NC) serum samples are examined using a combination of ion mobility spectrometry (IMS), mass spectrometry (MS), and principal component analysis (PCA) techniques. Samples from a total of 136 individuals were examined, including 7 characterized as BE, 12 as HGD, 56 as EAC, and 61 as NC. In typical data sets, it was possible to assign ∼20 to 30 glycan ions based on MS measurements. Ion mobility distributions for these ions show multiple features. In some cases, such as the [S1H5N4+3Na]3+ and [S1F1H5N4+3Na]3+ glycan ions, the ratio of intensities of high-mobility features to low-mobility features vary significantly for different groups. The degree to which such variations in mobility profiles can be used to distinguish phenotypes is evaluated for 11 N-linked glycan ions. An outlier analysis on each sample class followed by an unsupervised PCA using a genetic algorithm for pattern recognition reveals that EAC samples are separated from NC samples based on 46 features originating from the 11-glycan composite IMS distribution.

LC-MS profiling of N-Glycans derived from human serum samples for biomarker discovery in hepatocellular carcinoma.

Defining clinically relevant biomarkers for early stage hepatocellular carcinoma (HCC) in a high-risk population of cirrhotic patients has potentially far-reaching implications for disease management and patient health. Changes in glycan levels have been associated with the onset of numerous diseases including cancer. In the present study, we used liquid chromatography coupled with electrospray ionization mass spectrometry (LC–ESI-MS) to analyze N-glycans in sera from 183 participants recruited in Egypt and the U.S. and identified candidate biomarkers that distinguish HCC cases from cirrhotic controls. N-Glycans were released from serum proteins and permethylated prior to the LC–ESI-MS analysis. Through two complementary LC–ESI-MS quantitation approaches, global profiling and targeted quantitation, we identified 11 N-glycans with statistically significant differences between HCC cases and cirrhotic controls. These glycans can further be categorized into four structurally related clusters, matching closely with the implications of important glycosyltransferases in cancer progression and metastasis. The results of this study illustrate the power of the integrative approach combining complementary LC–ESI-MS based quantitation approaches to investigate changes in N-glycan levels between HCC cases and patients with liver cirrhosis.

Automated annotation and quantification of glycans using liquid chromatography–mass spectrometry

UNLABELLED As a common post-translational modification, protein glycosylation plays an important role in many biological processes, and it is known to be associated with human diseases. Mass spectrometry (MS)-based glycomic profiling techniques have been developed to measure the abundances of glycans in complex biological samples and applied to the discovery of putative glycan biomarkers. To automate the annotation of glycomic profiles in the liquid chromatography-MS (LC-MS) data, we present here a user-friendly software tool, MultiGlycan, implemented in C# on Windows systems. We tested MultiGlycan by using several glycomic profiling datasets acquired using LC-MS under different preparations and show that MultiGlycan executes fast and generates robust and reliable results. AVAILABILITY MultiGlycan can be freely downloaded at http://darwin.informatics.indiana.edu/MultiGlycan/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Glycomic Profiling of Tissue Sections by LC-MS

Because routine preparation of glycan samples involves multiple reaction and cleaning steps at which sample loss occurs, glycan analysis is typically performed using large tissue samples. This type of analysis yields no detailed molecular spatial information and requires special care to maintain proper storage and shipping conditions. We describe here a new glycan sample preparation protocol using minimized sample preparation steps and optimized procedures. Tissue sections and spotted samples first undergo on-surface enzymatic digestion to release N-glycans. The released glycans are then reduced and permethylated prior to online purification and LC-electrospray ionization (ESI)-MS analysis. The efficiency of this protocol was initially evaluated using model glycoproteins and human blood serum (HBS) spotted on glass or Teflon slides. The new protocol permitted the detection of permethylated N-glycans derived from 10 ng RNase B. On the other hand, 66 N-glycans were identified when injecting the equivalent of permethylated glycans derived from a 0.1-μL aliquot of HBS. On-tissue enzymatic digestion of nude mouse brain tissue permitted the detection of 43 N-glycans. The relative peak areas of these 43 glycans were comparable to those from a C57BL/6 mouse reported by the Consortium for Functional Glycomics (CFG). However, the sample size analyzed in the protocol described here was substantially smaller than for the routine method (submicrogram vs mg). The on-tissue N-glycan profiling method permits high sensitivity and reproducibility and can be widely applied to assess the spatial distribution of glycans associated with tissue sections, and may be correlated with immunoflourescence imaging when adjacent tissue sections are analyzed.

Quantitative LC–MS/MS Glycomic Analysis of Biological Samples Using AminoxyTMT

Protein glycosylation plays an important role in various biological processes, such as modification of protein function, regulation of protein-protein interactions, and control of turnover rates of proteins. Moreover, glycans have been considered as potential biomarkers for many mammalian diseases and development of aberrant glycosylation profiles is an important indicator of the pathology of a disease or cancer. Hence, quantitation is an important aspect of a comprehensive glycomics study. Although numerous MS-based quantitation strategies have been developed in the past several decades, some issues affecting sensitivity and accuracy of quantitation still exist, and the development of more effective quantitation strategies is still required. Aminoxy tandem mass tag (aminoxyTMT) reagents are recently commercialized isobaric tags which enable relative quantitation of up to six different glycan samples simultaneously. In this study, liquid chromatography and mass spectrometry conditions have been optimized to achieve reliable LC-MS/MS quantitative glycomic analysis using aminoxyTMT reagents. Samples were resuspended in 0.2 M sodium chloride solution to promote the formation of sodium adduct precursor ions, which leads to higher MS/MS reporter ion yields. This method was first evaluated with glycans from model glycoproteins and pooled human blood serum samples. The observed variation of reporter ion ratios was generally less than 10% relative to the theoretical ratio. Even for the highly complex minor N-glycans, the variation was still below 15%. This strategy was further applied to the glycomic profiling of N-glycans released from blood serum samples of patients with different esophageal diseases. Our results demonstrate the benefits of utilizing aminoxyTMT reagents for reliable quantitation of biological glycomic samples.