Mass spectrometry-based N-glycoproteomics for cancer biomarker discovery

Effective enrichment of glycated proteome using ultrasmall gold nanoclusters functionalized with boronic acid

Glycated proteins play a crucial role in various biological pathways and the pathogenesis of human diseases. A comprehensive analysis of glycated proteins is essential for understanding their biological significance. However, their low abundance and heterogeneity in complex biological samples necessitate an enrichment procedure prior to their detection. Current enrichment strategies primarily rely on the boronic acid (BA) affinity method combined with functional nanoparticles; however, the effectiveness of these approaches is often suboptimal. In this study, a novel nanocluster (NC)-based enrichment material was synthesized for the first time, characterized as Au22SG18 functionalized with 24 BA groups, in which SG is glutathione. The functionalized BA established a reversible covalent bond with the cis-dihydroxy group through pH adjustment, enabling selective enrichment of glycated peptides. After the optimization of the enrichment protocol, we demonstrated highly sensitive and selective enrichment of standard glycopeptides using the NC-based enrichment material, exhibiting excellent reusability. Efficient enrichment was also demonstrated for the glycated proteome from human serum. These results highlight the potential of the atomically well-defined ultrasmall Au NCs as a powerful tool for high-throughput analysis of glycated peptides.

Proteogenomic data and resources for pan-cancer analysis

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

High-resolution mass spectrometry for glycoproteomics

Tweetable abstract Bottom-up glycoproteomics combined with top-down strategy allows direct analysis of glycoform-mapped glycosylation and its glycans by high-resolution mass spectrometry.

Methods to improve quantitative glycoprotein coverage from bottom-up LC-MS data

Advances in mass spectrometry instrumentation, methods development, and bioinformatics have greatly improved the ease and accuracy of site-specific, quantitative glycoproteomics analysis. Data-dependent acquisition is the most popular method for identification and quantification of glycopeptides; however, complete coverage of glycosylation site glycoforms remains elusive with this method. Targeted acquisition methods improve the precision and accuracy of quantification, but at the cost of throughput and discoverability. Data-independent acquisition (DIA) holds great promise for more complete and highly quantitative site-specific glycoproteomics analysis, while maintaining the ability to discover novel glycopeptides without prior knowledge. We review additional features that can be used to increase selectivity and coverage to the DIA workflow: retention time modeling, which would simplify the interpretation of complex tandem mass spectra, and ion mobility separation, which would maximize the sampling of all precursors at a giving chromatographic retention time. The instrumentation and bioinformatics to incorporate these features into glycoproteomics analysis exist. These improvements in quantitative, site-specific analysis will enable researchers to assess glycosylation similarity in related biological systems, answering new questions about the interplay between glycosylation state and biological function.

Elevated N-Glycosylation Contributes to the Cisplatin Resistance of Non-Small Cell Lung Cancer Cells Revealed by Membrane Proteomic and Glycoproteomic Analysis

Chemoresistance is the major restriction on the clinical use of cisplatin. Aberrant changes in protein glycosylation are closely associated with drug resistance. Comprehensive study on the role of protein glycosylation in the development of cisplatin resistance would contribute to precise elucidation of the complicated mechanism of resistance. However, comprehensive characterization of glycosylated proteins remains a big challenge. In this work, we integrated proteomic and N-glycoproteomic workflow to comprehensively characterize the cisplatin resistance-related membrane proteins. Using this method, we found that proteins implicated in cell adhesion, migration, response to drug, and signal transduction were significantly altered in both protein abundance and glycosylation level during the development of cisplatin resistance in the non-small cell lung cancer cell line. Accordingly, the ability of cell migration and invasion was markedly increased in cisplatin-resistant cells, hence intensifying their malignancy. In contrast, the intracellular cisplatin accumulation was significantly reduced in the resistant cells concomitant with the down-regulation of drug uptake channel protein, LRRC8A, and over-expression of drug efflux pump proteins, MRP1 and MRP4. Moreover, the global glycosylation was elevated in the cisplatin-resistant cells. Consequently, inhibition of N-glycosylation reduced cell resistance to cisplatin, whereas promoting the high-mannose or sialylated type of glycosylation enhanced the resistance, suggesting that critical glycosylation type contributes to cisplatin resistance. These results demonstrate the high efficiency of the integrated proteomic and N-glycoproteomic workflow in discovering drug resistance-related targets, and provide new insights into the mechanism of cisplatin resistance.

Proteomics and its applications in breast cancer

Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies.

Detection of Aberrant Glycosylation of Serum Haptoglobin for Gastric Cancer Diagnosis Using a Middle-Up-Down Glycoproteome Platform

Gastric cancer is a frequently occurring cancer and is the leading cause of cancer-related deaths. Recent studies have shown that aberrant glycosylation of serum haptoglobin is closely related to gastric cancer and has enormous potential for use in diagnosis. However, there is no platform with high reliability and high reproducibility to comprehensively analyze haptoglobin glycosylation covering microheterogeneity to macroheterogeneity for clinical applications. In this study, we developed a middle-up-down glycoproteome platform for fast and accurate monitoring of haptoglobin glycosylation. This platform utilizes an online purification of LC for sample desalting, and an in silico haptoglobin glycopeptide library constructed by combining peptides and N-glycans to readily identify glycopeptides. In addition, site-specific glycosylation with glycan heterogeneity can be obtained through only a single MS analysis. Haptoglobin glycosylation in clinical samples consisting of healthy controls (n = 47) and gastric cancer patients (n = 43) was extensively investigated using three groups of tryptic glycopeptides: GP1 (including Asn184), GP2 (including Asn207 and Asn211), and GP3 (including Asn241). A total of 23 individual glycopeptides were determined as potential biomarkers (p < 0.00001). In addition, to improve diagnostic efficacy, we derived representative group biomarkers with high AUC values (0.929 to 0.977) through logistic regression analysis for each GP group. It has been found that glycosylation of haptoglobin is highly associated with gastric cancer, especially the glycosite Asn241. Our assay not only allows to quickly and easily obtain information on glycosylation heterogeneity of a target glycoprotein but also makes it an efficient tool for biomarker discovery and clinical diagnosis.

Global and site-specific analysis of protein glycosylation in complex biological systems with Mass Spectrometry

Protein glycosylation is ubiquitous in biological systems and plays essential roles in many cellular events. Global and site-specific analysis of glycoproteins in complex biological samples can advance our understanding of glycoprotein functions and cellular activities. However, it is extraordinarily challenging because of the low abundance of many glycoproteins and the heterogeneity of glycan structures. The emergence of mass spectrometry (MS)-based proteomics has provided us an excellent opportunity to comprehensively study proteins and their modifications, including glycosylation. In this review, we first summarize major methods for glycopeptide/glycoprotein enrichment, followed by the chemical and enzymatic methods to generate a mass tag for glycosylation site identification. We next discuss the systematic and quantitative analysis of glycoprotein dynamics. Reversible protein glycosylation is dynamic, and systematic study of glycoprotein dynamics helps us gain insight into glycoprotein functions. The last part of this review focuses on the applications of MS-based proteomics to study glycoproteins in different biological systems, including yeasts, plants, mice, human cells, and clinical samples. Intact glycopeptide analysis is also included in this section. Because of the importance of glycoproteins in complex biological systems, the field of glycoproteomics will continue to grow in the next decade. Innovative and effective MS-based methods will exponentially advance glycoscience, and enable us to identify glycoproteins as effective biomarkers for disease detection and drug targets for disease treatment. © 2019 Wiley Periodicals, Inc. Mass Spec Rev 9999: XX-XX, 2019.

Current and future biomarkers for risk-stratification and treatment personalisation in multiple myeloma

Multiple myeloma, an incurable malignancy of the plasma cells in the bone marrow, has a complex pathogenesis due to clonal heterogeneity. Over the years, many clinical trials and researches have led to the development of effective myeloma treatments, resulting in survival prolongation. Molecular prognostic markers for risk-stratification to predict survival, and predictive markers for treatment response are being extensively explored. This review discusses the current risk-adaptive strategies based on genetic and molecular risk signatures that are in practice to predict survival and describes the future prognostic and predictive biomarkers across the fields of genomics, proteomics, and glycomics in myeloma. Gene expression profiling and next generation sequencing are coming to the forefront of risk-stratification and therapeutic-response prediction. Similarly, proteomic and glycomic-based platforms are gaining momentum in biomarker discovery to predict drug resistance and disease progression.

Analysis of serum Haptoglobin using glycoproteomics and lectin immunoassay in liver diseases in Hepatitis B virus infection

BACKGROUND

Hepatocellular carcinoma (HCC) due to Hepatitis B viral (HBV) infection is a major cause in Asia-Pacific countries. Its early detection is of paramount importance using a marker having both sensitivity and specificity. The present study promises diagnostic and prognostic markers by the identification of site-specific glycoforms on Haptoglobin (Hp) using LC-MS/MS and lectin ELISA in liver diseased conditions in HBV infection.

METHODS

Three groups of patients: chronic, liver cirrhosis and HCC with HBV infection along with controls were enrolled. Hp was purified using affinity column chromatography and, peptide sequence, N-glycosylation site, glycan composition and glycoforms were identified using mass spectrometry. Quantitative lectin ELISA was used to measure levels of fucosylation on Hp in liver diseases due to HBV.

RESULTS

Hp levels were significantly lower in HCC when compared with Non-HCC cases (p < .05). Fucosylated glycoforms were significantly increased at site Asn184, Asn207 and Asn211 in liver diseased stages versus controls. A significant association was observed between the Fuc-Hp/Hp Elisa index and, advanced liver disease stages and controls using lectin Elisa (p < .001).

CONCLUSION

Quantitation of fucosylation levels on Hp protein using Lectin ELISA may be useful glycobiomarker either alone or in combination (AFP + DCP + FucHp; AUC = 0.94) in HBV HCC diagnosis in clinical practice.

Diagnostic Significance of Serum IgG Galactosylation in CA19-9-Negative Pancreatic Carcinoma Patients

Background: Although Carbohydrate antigen 19-9 (CA19-9) is considered clinically useful and informative for pancreatic carcinoma (PC), false positive results, and false negative results have restricted its clinical use. Especially missed or delayed diagnosis of PC patients with negative CA19-9 value limited the utility. To improve prognosis of PC patients, the discovery of reliable biomarkers to assist CA19-9 is desired. Serum IgG galactosylation based on our previous report was altered in PC patients comparing to healthy controls. The objective of this study was to explore the diagnostic significance of IgG galactosylation in assisting CA19-9 for PC in a comprehensive way.

Methods: Serum IgG galactosylation profiles were analyzed by MALDI-MS in cohort 1 (n = 252) and cohort 2 in which all CA19-9 levels were negative (n = 133). In each cohort, not only healthy controls and PC patients but also benign pancreatic disease (BPD) patients were enrolled. Peaks were acquired by the software of MALDI-MS sample acquisition, followed by being processed and analyzed by the software of Progenesis MALDI. IgG Gal-ratio, which was calculated from the relative intensity of peaks G0, G1, and G2 according to the formula (G0/(G1+G2×2)), was employed as an index for indicating the distribution of IgG galactosylation.

Results: The Gal-ratio was elevated in PC comparing with that in non-cancer group (healthy controls and BPD). The area under the receiver operating characteristic curve (AUC) of IgG Gal-ratio was higher than that of CA19-9 (0.912 vs. 0.814). The performance was further improved when Gal-ratio and CA19-9 were combined (AUC: 0.928). Meanwhile, Gal-ratio also had great diagnostic value with a sensitivity of 92.31% (AUC: 0.883) in detection of PC at early stage. Notably, IgG Gal-ratio has great sensitivity (90.63%) and specificity (76.81%) in CA19-9-negative PC patients.

Conclusions: IgG Gal-ratio had a great performance in detection of PC and could be used to assist CA19-9 in improving diagnosis performance through early stage detection, differentiation from BPD, and PC diagnosis with CA19-9-negative level.

Two-Dimensional MoS2-Based Zwitterionic Hydrophilic Interaction Liquid Chromatography Material for the Specific Enrichment of Glycopeptides

Mass spectrometry (MS)-based glycoproteomics research requires highly efficient sample preparation to eliminate interference from non-glycopeptides and to improve the efficiency of glycopeptide detection. In this work, a novel MoS₂/Au-NP (gold nanoparticle)-L-cysteine nanocomposite was prepared for glycopeptide enrichment. The two-dimensional (2D) structured MoS₂ nanosheets served as a matrix that could provide a large surface area for immobilizing hydrophilic groups (such as L-cysteine) with low steric hindrance between the materials and the glycopeptides. As a result, the novel nanomaterial possessed an excellent ability to capture glycopeptides. Compared to commercial zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) materials, the novel nanomaterials exhibited excellent enrichment performance with ultrahigh selectivity and sensitivity (approximately 10 fmol), high binding capacity (120 mg g^-1), high enrichment recovery (more than 93%), satisfying batch-to-batch reproducibility, and good universality for glycopeptide enrichment. In addition, its outstanding specificity and efficiency for glycopeptide enrichment was confirmed by the detection of glycopeptides from an human serum immunoglobulin G (IgG) tryptic digest in quantities as low as a 1:1250 molar ratio of IgG tryptic digest to bovine serum albumin tryptic digest. The novel nanocomposites were further used for the analysis of complex samples, and 1920 glycopeptide backbones from 775 glycoproteins were identified in three replicate analyses of 50 μg of proteins extracted from HeLa cell exosomes. The resulting highly informative mass spectra indicated that this multifunctional nanomaterial-based enrichment method could be used as a promising tool for the in-depth and comprehensive characterization of glycoproteomes in MS-based glycoproteomics.

Quantitative N-glycoproteomics reveals altered glycosylation levels of various plasma proteins in bloodstream infected patients

Bloodstream infections are associated with high morbidity and mortality with rates varying from 10-25% and higher. Appropriate and timely onset of antibiotic therapy influences the prognosis of these patients. It requires the diagnostic accuracy which is not afforded by current gold standards such as blood culture. Moreover, the time from blood sampling to blood culture results is a key determinant of reducing mortality. No established biomarkers exist which can differentiate bloodstream infections from other systemic inflammatory conditions. This calls for studies on biomarkers potential of molecular profiling of plasma as it is affected most by the molecular changes accompanying bloodstream infections. N-glycosylation is a post-translational modification which is very sensitive to changes in physiology. Here we have performed targeted quantitative N-glycoproteomics from plasma samples of patients with confirmed positive blood culture together with age and sex matched febrile controls with negative blood culture reports. Three hundred and sixty eight potential N-glycopeptides were quantified by mass spectrometry and 149 were further selected for identification. Twenty four N-glycopeptides were identified with high confidence together with elucidation of the peptide sequence, N-glycosylation site, glycan composition and proposed glycan structures. Principal component analysis, orthogonal projections to latent structures-discriminant analysis (S-Plot) and self-organizing maps clustering among other statistical methods were employed to analyze the data. These methods gave us clear separation of the two patient classes. We propose high-confidence N-glycopeptides which have the power to separate the bloodstream infections from blood culture negative febrile patients and shed light on host response during bacteremia. Data are available via ProteomeXchange with identifier PXD009048.

Evaluation of ion mobility for the separation of glycoconjugate isomers due to different types of sialic acid linkage, at the intact glycoprotein, glycopeptide and glycan level

The study of protein glycosylation can be regarded as an intricate but very important task, making glycomics one of the most challenging and interesting, albeit under-researched, type of "omics" science. Complexity escalates remarkably when considering that carbohydrates can form severely branched structures with many different constituents, which often leads to the formation of multiple isomers. In this regard, ion mobility (IM) spectrometry has recently demonstrated its power for the separation of isomeric compounds. In the present work, the potential of traveling wave IM (TWIMS) for the separation of isomeric glycoconjugates was evaluated, using mouse transferrin (mTf) as model glycoprotein. Particularly, we aim to assess the performance of this platform for the separation of isomeric glycoconjugates due to the type of sialic acid linkage, at the intact glycoprotein, glycopeptide and glycan level. Straightforward separation of isomers was achieved with the analysis of released glycans, as opposed to the glycopeptides which showed a more complex pattern. Finally, the developed methodology was applied to serum samples of mice, to investigate its robustness when analyzing real complex samples.

BIOLOGICAL SIGNIFICANCE

Ion mobility mass spectrometry is a promising analytical technique for the separation of glycoconjugate isomers due to type of sialic acid linkage. The impact of such a small modification in the glycan structure is more evident in smaller analytes, reason why the analysis of free glycans was easier compared to the intact protein or the glycopeptides. The established methodology could be regarded as starting point in the separation of highly decorated glycoconjugates. This is an important topic nowadays, as differences in the abundance of some glycan isomers could be the key for the early diagnosis, control or differentiation of certain diseases, such as inflammation or cancer.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

Glycosaminoglycans and glycolipids as potential biomarkers in lung cancer

In this report, we used liquid chromatography-mass spectrometry and Western blotting to analyze the content and structure of glycosaminoglycans, glycolipids and selected proteins to compare differences between patient-matched normal and cancerous lung tissues obtained from lung cancer patients. The cancer tissue samples contained over twice as much chondroitin sulfate (CS)/dermatan sulfate (DS) as did the normal tissue samples, while the amount of heparan sulfate (HS) and hyaluronan (HA) in normal and cancer tissues were not significantly different. In HS, several minor disaccharide components, including NS6S, NS2S and 2S were significantly lower in cancer tissues, while the levels of major disaccharides, TriS, NS and 0S disaccharides were not significantly different in normal and cancer tissues. In regards to CS/DS, the level of 4S disaccharide (the major component of CS-type A and DS) decreased and the level of 6S disaccharide (the major component of CS- type C) increased in cancer tissues. We also compared the content and structure of GAGs in lung tissues from smoking and non-smoking patients. Analysis of the glycolipids showed all lipids present in these lung tissues, with the exception of sphingomyelin were higher in cancer tissues than in normal tissues. Western analysis showed that syndecan 1 and 2 proteoglycans displayed much higher expression in cancer tissue/biopsy samples. This investigation begins to provide an understanding of patho-physiological roles on glycosaminoglycans and glycolipids and might be useful in identifying potential biomarkers in lung cancer.

Algorithms and design strategies towards automated glycoproteomics analysis

Glycoproteomics involves the study of glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics and bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:475-498, 2017.

An engineered high affinity Fbs1 carbohydrate binding protein for selective capture of N-glycans and N-glycopeptides

A method for selective and comprehensive enrichment of N-linked glycopeptides was developed to facilitate detection of micro-heterogeneity of N-glycosylation. The method takes advantage of the inherent properties of Fbs1, which functions within the ubiquitin-mediated degradation system to recognize the common core pentasaccharide motif (Man3GlcNAc2) of N-linked glycoproteins. We show that Fbs1 is able to bind diverse types of N-linked glycomolecules; however, wild-type Fbs1 preferentially binds high-mannose-containing glycans. We identified Fbs1 variants through mutagenesis and plasmid display selection, which possess higher affinity and improved recovery of complex N-glycomolecules. In particular, we demonstrate that the Fbs1 GYR variant may be employed for substantially unbiased enrichment of N-linked glycopeptides from human serum. Most importantly, this highly efficient N-glycopeptide enrichment method enables the simultaneous determination of N-glycan composition and N-glycosites with a deeper coverage (compared to lectin enrichment) and improves large-scale N-glycoproteomics studies due to greatly reduced sample complexity.

Protein glycosylation is an essential post-translational modification which analysis is complicated by the diversity of glycan composition and heterogeneity at individual attachment sites. Here the authors describe a method to selectively enrich N-linked glycopeptides to facilitate the detection of micro-heterogeneity in N-glycosylation.

Glycans and glycoproteins as specific biomarkers for cancer

Protein glycosylation and other post-translational modifications are involved in potentially all aspects of human growth and development. Defective glycosylation has adverse effects on human physiological conditions and accompanies many chronic and infectious diseases. Altered glycosylation can occur at the onset and/or during tumor progression. Identifying these changes at early disease stages may aid in making decisions regarding treatments, as early intervention can greatly enhance survival. This review highlights some of the efforts being made to identify N- and O-glycosylation profile shifts in cancer using mass spectrometry. The analysis of single or panels of potential glycoprotein cancer markers are covered. Other emerging technologies such as global glycan release and site-specific glycosylation analysis and quantitation are also discussed. Graphical Abstract Steps involved in the biomarker discovery.

Three-Dimensionally Functionalized Reverse Phase Glycoprotein Array for Cancer Biomarker Discovery and Validation

Glycoproteins have vast structural diversity that plays an important role in many biological processes and have great potential as disease biomarkers. Here, we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase glycoprotein array (polyGPA), to capture and profile glycoproteomes specifically, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture preoxidized glycans on glycoproteins from complex protein samples such as biofluids. The captured glycoproteins were subsequently detected using the same validated antibodies as in RPPA. We demonstrated the outstanding specificity, sensitivity, and quantitative capabilities of polyGPA by capturing and detecting purified as well as endogenous α-1-acid glycoprotein (AGP) in human plasma. We further applied quantitative N-glycoproteomics and the strategy to validate a panel of glycoproteins identified as potential biomarkers for bladder cancer by analyzing urine glycoproteins from bladder cancer patients or matched healthy individuals.

Integrated and Quantitative Proteomics of Human Tumors

Quantitative proteomics represents a powerful approach for the comprehensive analysis of proteins expressed under defined conditions. These properties have been used to investigate the proteome of disease states, including cancer. It has become a major subject of studies to apply proteomics for biomarker and therapeutic target identification. In the last decades, technical advances in mass spectrometry have increased the capacity of protein identification and quantification. Moreover, the analysis of posttranslational modification (PTM), especially phosphorylation, has allowed large-scale identification of biological mechanisms. Even so, increasing evidence indicates that global protein quantification is often insufficient for the explanation of biology and has shown to pose challenges in identifying new and robust biomarkers. As a consequence, to improve the accuracy of the discoveries made using proteomics in human tumors, it is necessary to combine (i) robust and reproducible methods for sample preparation allowing statistical comparison, (ii) PTM analyses in addition to global proteomics for additional levels of knowledge, and (iii) use of bioinformatics for decrypting protein list. Herein, we present technical specificities for samples preparation involving isobaric tag labeling, TiO₂-based phosphopeptides enrichment and hydrazyde-based glycopeptides purification as well as the key points for the quantitative analysis and interpretation of the protein lists. The method is based on our experience with tumors analysis derived from hepatocellular carcinoma, chondrosarcoma, human embryonic intervertebral disk, and chordoma experiments.

Recent advances in mass spectrometry-based proteomics of gastric cancer

The last decade has witnessed remarkable technological advances in mass spectrometry-based proteomics. The development of proteomics techniques has enabled the reliable analysis of complex proteomes, leading to the identification and quantification of thousands of proteins in gastric cancer cells, tissues, and sera. This quantitative information has been used to profile the anomalies in gastric cancer and provide insights into the pathogenic mechanism of the disease. In this review, we mainly focus on the advances in mass spectrometry and quantitative proteomics that were achieved in the last five years and how these up-and-coming technologies are employed to track biochemical changes in gastric cancer cells. We conclude by presenting a perspective on quantitative proteomics and its future applications in the clinic and translational gastric cancer research.

Classification of congenital disorders of glycosylation based on analysis of transferrin glycopeptides by capillary liquid chromatography-mass spectrometry

In this work, we describe a multivariate data analysis approach for data exploration and classification of the complex and large data sets generated to study the alteration of human transferrin (Tf) N-glycopeptides in patients with congenital disorders of glycosylation (CDG). Tf from healthy individuals and two types of CDG patients (CDG-I and CDG-II) is purified by immunoextraction from serum samples before trypsin digestion and separation by capillary liquid chromatography mass spectrometry (CapLC-MS). Following a targeted data analysis approach, partial least squares discriminant analysis (PLS-DA) is applied to the relative abundance of Tf glycopeptide glycoforms obtained after integration of the extracted ion chromatograms of the different samples. The performance of PLS-DA for classification of the different samples and for providing a novel insight into Tf glycopeptide glycoforms alteration in CDGs is demonstrated. Only six out of fourteen of the detected glycoforms are enough for an accurate classification. This small glycoform set may be considered a sensitive and specific novel biomarker panel for CDGs.

Site-specific characterization of N-linked glycosylation in human urinary glycoproteins and endogenous glycopeptides

Glycosylation is a very important post-translational modification involved in various cellular processes, such as cell adhesion, signal transduction and immune response. Urine is a rich source of glycoproteins and attractive biological fluid for biomarker discovery, owing to its availability, ease of collection, and correlation with pathophysiology of diseases. Although the urinary proteomics have been explored previously, the urinary glycoproteome characterization remains challenging requiring the development and optimization of analytical and bioinformatics methods for protein glycoprofiling. This study describes the high confident identification of 472 unique N-glycosylation sites covering 256 urinary glycoproteins. Besides, 202 unique N-glycosylation sites were identified in low molecular weight endogenous glycopeptides, which belong to 90 glycoproteins. Global site-specific characterization of the N-linked glycan heterogeneity was achieved by intact glycopeptide analysis, revealing 303 unique glycopeptides most of them displaying complex/hybrid glycans composed by sialic acid and fucose. These datasets consist in a valuable resource of glycoproteins and N-glycosylation sites found in healthy human urine that can be further explored in different disorders, in which the N-linked glycosylation may be aberrant.

Glycosylation status of serum immunoglobulin G in patients with prostate diseases

Occurrences of high values in patients with benign prostate disease and low values in patients with highly suspicious cancer have diminished the trustworthiness of prostate‐specific antigen as an early diagnostic marker of prostate cancer. In the search for other complimentary markers, we focused on serum IgG from patients with prostate diseases as well as normal subjects. IgG purified from the sera of normal control subjects and patients with prostate diseases, was digested with peptide N‐glycanase. Released glycans were quantified using MALDI‐time of flight mass spectrometry. We report that N‐linked (N‐acetylhexosamine)₂(deoxyhexose)(mannose)₃(N‐acetylglucosamine)₂ was significantly increased in the IgG heavy chains of patients with prostate cancer compared with that of either benign prostatic disease patients or healthy subjects, whereas (hexose)(N‐acetylhexosamine)₂(deoxyhexose)(mannose)₃ (N‐acetylglucosamine)₂ was more abundant in the heavy chains of healthy subjects and benign prostatic disease patients. Thus, an absence of the terminal hexose of N‐linked glycans has been closely connected to the progression of prostate cancer. Furthermore, surface plasmon resonance analyses have revealed that IgG from patients with prostate cancer has a decreased binding for Sambucus nigra lectin, compared with that from the benign prostatic disease patients or from normal subjects, suggesting lower levels of (N‐acetylneuraminic acid)(α2‐6)galactose/N‐acetylgalactosamine groups in the N‐linked glycans of patient IgG. Meanwhile, wheat germ agglutinin binding to IgG of the cancer group was significantly larger than that for the benign prostatic disease group but smaller than that for normal subjects. Our study indicates that the glycosylation changes in IgG can become useful diagnostic parameters for prostate cancer.

Translational Research and Plasma Proteomic in Cancer

Proteomics is a recent field of research in molecular biology that can help in the fight against cancer through the search for biomarkers that can detect this disease in the early stages of its development. Proteomic is a speedily growing technology, also thanks to the development of even more sensitive and fast mass spectrometry analysis. Although this technique is the most widespread for the discovery of new cancer biomarkers, it still suffers of a poor sensitivity and insufficient reproducibility, essentially due to the tumor heterogeneity. Common technical shortcomings include limitations in the sensitivity of detecting low abundant biomarkers and possible systematic biases in the observed data. Current research attempts are trying to develop high-resolution proteomic instrumentation for high-throughput monitoring of protein changes that occur in cancer. In this review, we describe the basic features of the proteomic tools which have proven to be useful in cancer research, showing their advantages and disadvantages. The application of these proteomic tools could provide early biomarkers detection in various cancer types and could improve the understanding the mechanisms of tumor growth and dissemination.

Only one health, and so many omics

The development of new approaches based on wide profiling methods in studying biological and medical systems is bringing large amounts of data on a daily basis. The causes of complex diseases have been directed to the genome examination bringing formidable knowledge. We can study genome, but also proteome, exome, transcriptome, epigenome, metabolome, and newcomers too such as microbiome, connectome and exposome. The title of this editorial is paraphrasing the famous saying of Victor Schlichter from Buenos Aires children hospital in Argentina who said "How unfair! Only one health, and so many diseases". Today there is indeed a whole lot of omics. We think that we are lucky to have all the omics possible, but we also wanted to stress the importance of future holistic approach in integrating the knowledge omics has rewarded us.

Current strategies and findings in clinically relevant post-translational modification-specific proteomics

Mass spectrometry-based proteomics has considerably extended our knowledge about the occurrence and dynamics of protein post-translational modifications (PTMs). So far, quantitative proteomics has been mainly used to study PTM regulation in cell culture models, providing new insights into the role of aberrant PTM patterns in human disease. However, continuous technological and methodical developments have paved the way for an increasing number of PTM-specific proteomic studies using clinical samples, often limited in sample amount. Thus, quantitative proteomics holds a great potential to discover, validate and accurately quantify biomarkers in body fluids and primary tissues. A major effort will be to improve the complete integration of robust but sensitive proteomics technology to clinical environments. Here, we discuss PTMs that are relevant for clinical research, with a focus on phosphorylation, glycosylation and proteolytic cleavage; furthermore, we give an overview on the current developments and novel findings in mass spectrometry-based PTM research.

Dose-dependent effect of 2-deoxy-D-glucose on glycoprotein mannosylation in cancer cells

High glucose consumption due to Warburg effect is one of the metabolic hallmarks of cancer. Consequently, glucose antimetabolites, such as 2-deoxy-glucose (2DG), can induce substantial growth inhibition of cancer cells. However, the inhibition of metabolic pathways is not the sole effect of 2DG on cancer cells. As mannose-mimetic molecule, 2DG is believed to interfere with normal glycosylation of proteins in cells. Here, we address how 2DG influences protein glycosylation in cancer cells and discuss possible implications of the consequences of this influence. In detail, six colorectal cancer cell lines were examined for alterations of protein glycosylation by measuring monosaccharide incorporation into cellular glycoproteins and cell surface glycosylation by lectin FACS. A significant increase in mannose incorporation was observed on treatment with 2DG (1 mM for 48 h), which was also reflected by an increased binding of the mannose-binding lectin Concanavalin A in FACS analysis. This phenomenon, which could be reversed by external addition of mannose, was not caused by 2DG-mediated mannosidase inhibition, as shown by pulse-chase experiments, arguing in favor of the hypothesis that 2DG directly influenced the incorporation of mannose. Increased mannose content was generally observed in cellular glycoproteins, including glycoproteins isolated from the plasma membrane fraction. Our results indicate that 2DG at low doses, which have only a limited metabolism-related effect on glycosylation, induces a strong increase in mannose incorporation into cellular glycoproteins. On the other hand, higher 2DG concentrations (10 and 20 mM) led to a significant decrease of absolute mannose incorporation accompanied by a dramatically reduced protein synthesis rate. 2DG-induced alterations of glycosylation may represent a novel mechanism potentially explaining the varied effects of 2DG on cancer cells. Moreover, 2DG treatment may open a path toward novel diagnostic and cancer therapeutic approaches, which specifically target altered glycoantigen structures induced by 2DG.

High mobility group box-1 and its clinical value in breast cancer

BACKGROUND

High mobility group box-1 (HMGB1) is a factor regulating malignant tumorigenesis, proliferation, and metastasis, and is associated with poor clinical pathology in various human cancers. We investigated the differential concentrations of HMGB1 in tissues and sera, and their clinical value for diagnosis in patients with breast cancer, benign breast disease, and healthy individuals.

METHODS

HMGB1 levels in tumor tissues, adjacent normal tissues, and benign breast disease tissues was detected via immunohistochemistry. Serum HMGB1 was measured using an enzyme-linked immunosorbent assay in 56 patients with breast cancer, 25 patients with benign breast disease, and 30 healthy control subjects. The clinicopathological features of the patients were compared. Tissues were evaluated histopathologically by pathologists.

RESULTS

HMGB1 levels in the tissues and sera of patients with breast cancer were significantly higher than those in patients with benign breast disease or normal individuals. The 56 cancer patients were classified as having high tissue HMGB1 levels (n=41) or low tissue HMGB1 levels (n=15), but the corresponsive serum HMGB1 in these two groups was not significantly different. HMGB1 levels in breast cancer tissues significantly correlated with differentiation grade, lymphatic metastasis, and tumor-node-metastasis stage, but not patient age, tumor size, or HER-2/neu expression; no association between serum HMGB1 levels and these clinicopathological parameters was found. The sensitivity and specificity of tissue HMGB1 levels for the diagnosis of breast cancer were 73.21% and 84.00%, respectively, while positive and negative predictive values were 91.11% and 58.33%.

CONCLUSION

HMGB1 might be involved in the development and progression of breast cancer and could be a supportive diagnostic marker for breast cancer. Serum HMGB1 could be a useful serological biomarker for diagnosis and screening of breast cancer.

Highly specific enrichment of N-glycoproteome through a nonreductive amination reaction using Fe3O4@SiO2-aniline nanoparticles

To highly efficient extract theN-glycoproteome, a novel solid-phase extraction method based on a nonreductive amination reaction was developed.