Defining the human kidney N-glycome in normal and cancer tissues using MALDI imaging mass spectrometry

Non-targeted isomer-sensitive N-glycome analysis reveals new layers of organ-specific diversity in mice

N-glycosylation is one of the most common protein modifications in eukaryotes, with immense importance at the molecular, cellular, and organismal level. Accurate and reliable N-glycan analysis is essential to obtain a systems-wide understanding of fundamental biological processes. Due to the structural complexity of glycans, their analysis is still highly challenging. Here we make publicly available a consistent N-glycome dataset of 20 different mouse tissues and demonstrate a multimodal data analysis workflow that allows for unprecedented depth and coverage of N-glycome features. This highly scalable, LC-MS/MS data-driven method integrates the automated identification of N-glycan spectra, the application of non-targeted N-glycome profiling strategies and the isomer-sensitive analysis of glycan structures. Our delineation of critical sub-structural determinants and glycan isomers across the mouse N-glycome uncovered tissue-specific glycosylation patterns, the expression of non-canonical N-glycan structures and highlights multiple layers of N-glycome complexity that derive from organ-specific regulations of glycobiological pathways.

wMKL: multi-omics data integration enables novel cancer subtype identification via weight-boosted multi-kernel learning

BACKGROUND

Cancer is a heterogeneous disease driven by complex molecular alterations. Cancer subtypes determined from multi-omics data can provide novel insight into personalised precision treatment. It is recognised that incorporating prior weight knowledge into multi-omics data integration can improve disease subtyping.

METHODS

We develop a weighted method, termed weight-boosted Multi-Kernel Learning (wMKL) which incorporates heterogeneous data types as well as flexible weight functions, to boost subtype identification. Given a series of weight functions, we propose an omnibus combination strategy to integrate different weight-related P-values to improve subtyping precision.

RESULTS

wMKL models each data type with multiple kernel choices, thus alleviating the sensitivity and robustness issue due to selecting kernel parameters. Furthermore, wMKL integrates different data types by learning weights of different kernels derived from each data type, recognising the heterogeneous contribution of different data types to the final subtyping performance. The proposed wMKL outperforms existing weighted and non-weighted methods. The utility and advantage of wMKL are illustrated through extensive simulations and applications to two TCGA datasets. Novel subtypes are identified followed by extensive downstream bioinformatics analysis to understand the molecular mechanisms differentiating different subtypes.

CONCLUSIONS

The proposed wMKL method provides a novel strategy for disease subtyping. The wMKL is freely available at https://github.com/biostatcao/wMKL .

A Machine Learning-Driven Comparison of Ion Images Obtained by MALDI and MALDI-2 Mass Spectrometry Imaging

Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) enables label-free imaging of biomolecules in biological tissues. However, many species remain undetected due to their poor ionization efficiencies. MALDI-2 (laser-induced post-ionization) is the most widely used post-ionization method for improving analyte ionization efficiencies. Mass spectra acquired using MALDI-2 constitute a combination of ions generated by both MALDI and MALDI-2 processes. Until now, no studies have focused on a detailed comparison between the ion images (as opposed to the generated m/z values) produced by MALDI and MALDI-2 for mass spectrometry imaging (MSI) experiments. Herein, we investigated the ion images produced by both MALDI and MALDI-2 on the same tissue section using correlation analysis (to explore similarities in ion images for ions common to both MALDI and MALDI-2) and a deep learning approach. For the latter, we used an analytical workflow based on the Xception convolutional neural network, which was originally trained for human-like natural image classification but which we adapted to elucidate similarities and differences in ion images obtained using the two MSI techniques. Correlation analysis demonstrated that common ions yielded similar spatial distributions with low-correlation species explained by either poor signal intensity in MALDI or the generation of additional unresolved signals using MALDI-2. Using the Xception-based method, we identified many regions in the t-SNE space of spatially similar ion images containing MALDI and MALDI-2-related signals. More notably, the method revealed distinct regions containing only MALDI-2 ion images with unique spatial distributions that were not observed using MALDI. These data explicitly demonstrate the ability of MALDI-2 to reveal molecular features and patterns as well as histological regions of interest that are not visible when using conventional MALDI.

Advances in mass spectrometry imaging for spatial cancer metabolomics

Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.

Recent Developments and Application of Mass Spectrometry Imaging in N-Glycosylation Studies: An Overview

Among the most typical posttranslational modifications is glycosylation, which often involves the covalent binding of an oligosaccharide (glycan) to either an asparagine (N-linked) or a serine/threonine (O-linked) residue. Studies imply that the N-glycan portion of a glycoprotein could serve as a particular disease biomarker rather than the protein itself because N-linked glycans have been widely recognized to evolve with the advancement of tumors and other diseases. N-glycans found on protein asparagine sites have been especially significant. Since N-glycans play clearly defined functions in the folding of proteins, cellular transport, and transmission of signals, modifications to them have been linked to several illnesses. However, because these N-glycans' production is not template driven, they have a substantial morphological range, rendering it difficult to distinguish the species that are most relevant to biology and medicine using standard techniques. Mass spectrometry (MS) techniques have emerged as effective analytical tools for investigating the role of glycosylation in health and illness. This is due to developments in MS equipment, data collection, and sample handling techniques. By recording the spatial dimension of a glycan's distribution in situ, mass spectrometry imaging (MSI) builds atop existing methods while offering added knowledge concerning the structure and functionality of biomolecules. In this review article, we address the current development of glycan MSI, starting with the most used tissue imaging techniques and ionization sources before proceeding on to a discussion on applications and concluding with implications for clinical research.

An N-glycome tissue atlas of 15 human normal and cancer tissue types determined by MALDI-imaging mass spectrometry

N-glycosylation is an abundant post-translational modification of most cell-surface proteins. N-glycans play a crucial role in cellular functions like protein folding, protein localization, cell-cell signaling, and immune detection. As different tissue types display different N-glycan profiles, changes in N-glycan compositions occur in tissue-specific ways with development of disease, like cancer. However, no comparative atlas resource exists for documenting N-glycome alterations across various human tissue types, particularly comparing normal and cancerous tissues. In order to study a broad range of human tissue N-glycomes, N-glycan targeted MALDI imaging mass spectrometry was applied to custom formalin-fixed paraffin-embedded tissue microarrays. These encompassed fifteen human tissue types including bladder, breast, cervix, colon, esophagus, gastric, kidney, liver, lung, pancreas, prostate, sarcoma, skin, thyroid, and uterus. Each array contained both normal and tumor cores from the same pathology block, selected by a pathologist, allowing more in-depth comparisons of the N-glycome differences between tumor and normal and across tissue types. Using established MALDI-IMS workflows and existing N-glycan databases, the N-glycans present in each tissue core were spatially profiled and peak intensity data compiled for comparative analyses. Further structural information was determined for core fucosylation using endoglycosidase F3, and differentiation of sialic acid linkages through stabilization chemistry. Glycan structural differences across the tissue types were compared for oligomannose levels, branching complexity, presence of bisecting N-acetylglucosamine, fucosylation, and sialylation. Collectively, our research identified the N-glycans that were significantly increased and/or decreased in relative abundance in cancer for each tissue type. This study offers valuable information on a wide scale for both normal and cancerous tissues, serving as a reference for future studies and potential diagnostic applications of MALDI-IMS.

Next-generation pathology practices with mass spectrometry imaging

Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology-related research. In this review, we summarize common MSI techniques, including matrix-assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next-generation pathology practices.

Low-melting point agarose as embedding medium for MALDI mass spectrometry imaging and laser-capture microdissection-based proteomics

The combination of MALDI mass spectrometry imaging, laser-capture microdissection, and quantitative proteomics allows the identification and characterization of molecularly distinct tissue compartments. Such workflows are typically performed using consecutive tissue sections, and so reliable sectioning and mounting of high-quality tissue sections is a prerequisite of such investigations. Embedding media facilitate the sectioning process but can introduce contaminants which may adversely affect either the mass spectrometry imaging or proteomics analyses. Seven low-temperature embedding media were tested in terms of embedding temperature and cutting performance. The two media that provided the best results (5% gelatin and 2% low-melting point agarose) were compared with non-embedded tissue by both MALDI mass spectrometry imaging of lipids and laser-capture microdissection followed by bottom-up proteomics. Two out of the seven tested media (5% gelatin and 2% low-melting point agarose) provided the best performances on terms of mechanical properties. These media allowed for low-temperature embedding and for the collection of high-quality consecutive sections. Comparisons with non-embedded tissues revealed that both embedding media had no discernable effect on proteomics analysis; 5% gelatin showed a light ion suppression effect in the MALDI mass spectrometry imaging experiments, 2% agarose performed similarly to the non-embedded tissue. 2% low-melting point agarose is proposed for tissue embedding in experiments involving MALDI mass spectrometry imaging of lipids and laser-capture microdissection, proteomics of consecutive tissue sections.

Prognostic significance of serum fucosylated pro-haptoglobin in advanced renal cell carcinoma patients treated with immune checkpoint inhibitors

With the widespread use of immune checkpoint inhibitors (ICIs), identifying predictive biomarkers is critical. Recently, serum fucosylated haptoglobin (Fuc-Hp) was thought to play an important role in tumour immunity in several types of cancer. Therefore, evaluating serum Fuc-Hp in the peripheral blood can potentially identify non-invasive predictive biomarkers for the clinical efficacy of ICIs. In this study, 31 patients with advanced renal cell carcinoma (RCC) treated with nivolumab were enrolled and defined as responders or non-responders according to RECIST criteria. Serum samples were collected before and 1 month after treatment initiation, and an ELISA assay was performed using Aleuria Aurantia Lectin (AAL) and 10-7G monoclonal antibodies that recognise Fuc-mature Hp (Fuc-mHp) and Fuc-pro Hp (Fuc-pHp), respectively. We first measured AAL-haptoglobin (Fuc-mHp) and total haptoglobin levels before nivolumab and found that neither value could predict the clinical response. Notably, serum 10-7G levels were significantly lower in the responder group (p = 0.035). We also confirmed the use of serum 10-7G levels for predicting progressive disease after nivolumab (area under the curve, 0.816). Accordingly, low 10-7G levels were significantly correlated with better progression-free survival (p = 0.041). In conclusion, serum Fuc-pHp analysis may identify patients with advanced RCC who benefit from ICIs.

Analysis of Immunogenic Galactose-α-1,3-galactose-Containing N-Glycans in Beef, Mutton, and Pork Tenderloin by Combining Matrix-Assisted Laser Desorption/Ionization-Mass Spectroscopy and Capillary Electrophoresis Hyphenated with Mass Spectrometry via Electrospray Ionization

Severe allergic reactions to certain types of meat following tick bites have been reported in geographic regions which are endemic with ticks. This immune response is directed to a carbohydrate antigen (galactose-α-1,3-galactose or α-Gal), which is present in glycoproteins of mammalian meats. At the moment, asparagine-linked complex carbohydrates (N-glycans) with α-Gal motifs in meat glycoproteins and in which cell types or tissue morphologies these α-Gal moieties are present in mammalian meats are still unclear. In this study, we analyzed α-Gal-containing N-glycans in beef, mutton, and pork tenderloin and provided for the first time the spatial distribution of these types of N-glycans in various meat samples. Terminal α-Gal-modified N-glycans were found to be highly abundant in all analyzed samples (55, 45, and 36% of N-glycome in beef, mutton, and pork, respectively). Visualizations of the N-glycans with α-Gal modification revealed that this motif was mainly present in the fibroconnective tissue. To conclude, this study contributes to a better understanding of the glycosylation biology of meat samples and provides guidance for processed meat products, in which only meat fibers are required as an ingredient (i.e., sausages or canned meat).

Applications and continued evolution of glycan imaging mass spectrometry

Glycosylation is an important posttranslational modifier of proteins and lipid conjugates critical for the stability and function of these macromolecules. Particularly important are N-linked glycans attached to asparagine residues in proteins. N-glycans have well-defined roles in protein folding, cellular trafficking and signal transduction, and alterations to them are implicated in a variety of diseases. However, the non-template driven biosynthesis of these N-glycans leads to significant structural diversity, making it challenging to identify the most biologically and clinically relevant species using conventional analyses. Advances in mass spectrometry instrumentation and data acquisition, as well as in enzymatic and chemical sample preparation strategies, have positioned mass spectrometry approaches as powerful analytical tools for the characterization of glycosylation in health and disease. Imaging mass spectrometry expands upon these strategies by capturing the spatial component of a glycan's distribution in-situ, lending additional insight into the organization and function of these molecules. Herein we review the ongoing evolution of glycan imaging mass spectrometry beginning with widely adopted tissue imaging approaches and expanding to other matrices and sample types with potential research and clinical implications. Adaptations of these techniques, along with their applications to various states of disease, are discussed. Collectively, glycan imaging mass spectrometry analyses broaden our understanding of the biological and clinical relevance of N-glycosylation to human disease.

Rewiring of the N-Glycome with prostate cancer progression and therapy resistance

An understanding of the molecular features associated with prostate cancer progression (PCa) and resistance to hormonal therapy is crucial for the identification of new targets that can be utilized to treat advanced disease and prolong patient survival. The glycome, which encompasses all sugar polymers (glycans) synthesized by cells, has remained relatively unexplored in the context of advanced PCa despite the fact that glycans have great potential value as biomarkers and therapeutic targets due to their high density on the cell surface. Using imaging mass spectrometry (IMS), we profiled the N-linked glycans in tumor tissue derived from 131 patients representing the major disease states of PCa to identify glycosylation changes associated with loss of tumor cell differentiation, disease remission, therapy resistance and disease recurrence, as well as neuroendocrine (NE) differentiation which is a major mechanism for therapy failure. Our results indicate significant changes to the glycosylation patterns in various stages of PCa, notably a decrease in tri- and tetraantennary glycans correlating with disease remission, a subsequent increase in these structures with the transition to therapy-resistant PCa, and downregulation of complex N-glycans correlating with NE differentiation. Furthermore, both nonglucosylated and monoglucosylated mannose 9 demonstrate aberrant upregulation in therapy-resistant PCa which may be useful therapeutic targets as these structures are not normally presented in healthy tissue. Our findings characterize changes to the tumor glycome that occur with hormonal therapy and the development of castration-resistant PCa (CRPC), identifying several glycan markers and signatures which may be useful for diagnostic or therapeutic purposes.

In Situ Imaging of O-Linked β-N-Acetylglucosamine Using On-Tissue Hydrolysis and MALDI Mass Spectrometry

Post-translational O-glycosylation of proteins via the addition of N-acetylglucosamine (O-GlcNAc) is a regulator of many aspects of cellular physiology. Processes driven by perturbed dynamics of O-GlcNAcylation modification have been implicated in cancer development. Variability in O-GlcNAcylation is emerging as a metabolic biomarker of many cancers. Here, we evaluate the use of MALDI-mass spectrometry imaging (MSI) to visualize the location of O-GlcNAcylated proteins in tissue sections by mapping GlcNAc that has been released by the enzymatic hydrolysis of glycoproteins using an O-GlcNAc hydrolase. We use this strategy to monitor O-GlcNAc within hepatic VX2 tumor tissue. We show that increased O-GlcNAc is found within both viable tumor and tumor margin regions, implicating GlcNAc in tumor progression.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2019-2020

This review is the tenth update of the original article published in 1999 on the application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry to the analysis of carbohydrates and glycoconjugates and brings coverage of the literature to the end of 2020. Also included are papers that describe methods appropriate to analysis by MALDI, such as sample preparation techniques, even though the ionization method is not MALDI. The review is basically divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of arrays. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other areas such as medicine, industrial processes and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. The reported work shows increasing use of incorporation of new techniques such as ion mobility and the enormous impact that MALDI imaging is having. MALDI, although invented nearly 40 years ago is still an ideal technique for carbohydrate analysis and advancements in the technique and range of applications show little sign of diminishing.

A roadmap for translational cancer glycoimmunology at single cell resolution

Cancer cells can evade immune responses by exploiting inhibitory immune checkpoints. Immune checkpoint inhibitor (ICI) therapies based on anti-CTLA-4 and anti-PD-1/PD-L1 antibodies have been extensively explored over the recent years to unleash otherwise compromised anti-cancer immune responses. However, it is also well established that immune suppression is a multifactorial process involving an intricate crosstalk between cancer cells and the immune systems. The cancer glycome is emerging as a relevant source of immune checkpoints governing immunosuppressive behaviour in immune cells, paving an avenue for novel immunotherapeutic options. This review addresses the current state-of-the-art concerning the role played by glycans controlling innate and adaptive immune responses, while shedding light on available experimental models for glycoimmunology. We also emphasize the tremendous progress observed in the development of humanized models for immunology, the paramount contribution of advances in high-throughput single-cell analysis in this context, and the importance of including predictive machine learning algorithms in translational research. This may constitute an important roadmap for glycoimmunology, supporting careful adoption of models foreseeing clinical translation of fundamental glycobiology knowledge towards next generation immunotherapies.

High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry

Tissue microarrays (TMAs) are commonly used for the rapid analysis of large numbers of tissue samples, often in morphological assessments but increasingly in spectroscopic analysis, where specific molecular markers are targeted via immunostaining. Here we report the use of an automated high-throughput system based on desorption electrospray ionization (DESI) mass spectrometry (MS) for the rapid generation and online analysis of high-density (6144 samples/array) TMAs, at rates better than 1 sample/second. Direct open-air analysis of tissue samples (hundreds of nanograms) not subjected to prior preparation, plus the ability to provide molecular characterization by tandem mass spectrometry (MS/MS), make this experiment versatile and applicable to both targeted and untargeted analysis in a label-free manner. These capabilities are demonstrated in a proof-of-concept study of frozen brain tissue biopsies where we showcase (i) a targeted MS/MS application aimed at identification of isocitrate dehydrogenase mutation in glioma samples and (ii) an untargeted MS tissue type classification using lipid profiles and correlation with tumor cell percentage estimates from histopathology. The small sample sizes and large sample numbers accessible with this methodology make for a powerful analytical system that facilitates the identification of molecular markers for later use in intraoperative applications to guide precision surgeries and ultimately improve patient outcomes.

High sensitivity glycomics in biomedicine

Many analytical challenges in biomedicine arise from the generally high heterogeneity and complexity of glycan- and glycoconjugate-containing samples, which are often only available in minute amounts. Therefore, highly sensitive workflows and detection methods are required. In this review mass spectrometric workflows and detection methods are evaluated for glycans and glycoproteins. Furthermore, glycomic methodologies and innovations that are tailored for enzymatic treatments, chemical derivatization, purification, separation, and detection at high sensitivity are highlighted. The discussion is focused on the analysis of mammalian N-linked and GalNAc-type O-linked glycans.

Diagnosing, Typing, and Staging of Renal Cell Carcinoma by Designer Matrix-Based Urinary Metabolic Analysis

Molecular diagnosing, typing, and staging have been considered to be the ideal alternatives of imaging-based detection methods in clinics. Designer matrix-based analytical tools, with high speed, throughout, efficiency and low/noninvasiveness, have attracted much attention recently for in vitro metabolite detection. Herein, we develop an advanced metabolic analysis tool based on highly porous metal oxides derived from available metal-organic frameworks (MOFs), which elaborately inherit the morphology and porosity of MOFs and newly incorporate laser adsorption capacity of metal oxides. Through optimized conditions, direct high-quality fingerprinting spectra in 0.5 μL of urine are acquired. Using these fingerprinting spectra, we can discriminate the renal cell carcinoma (RCC) from healthy controls with higher than 0.99 of area under the curve (AUC) values (R²Y(cum) = 0.744, Q² (cum) = 0.880), as well, from patients with other tumors (R²Y(cum) = 0.748, Q²(cum) = 0.871). We also realize the typing of three RCC subtypes, including clear cell RCC, chromophobe RCC (R²Y(cum) = 0.620, Q²(cum) = 0.656), and the staging of RCC (R²Y(cum) = 0.755, Q²(cum) = 0.857). Moreover, the tumor sizes (threshold value is 3 cm) can be remarkably recognized by this advanced metabolic analysis tool (R²Y(cum) = 0.710, Q²(cum) = 0.787). Our work brings a bright prospect for designer matrix-based analytical tools in disease diagnosis, typing and staging.

Mass spectrometry-based N-glycosylation analysis in kidney disease

Kidney disease is a global health concern with an enormous expense. It is estimated that more than 10% of the population worldwide is affected by kidney disease and millions of patients would progress to death prematurely and unnecessarily. Although creatinine detection and renal biopsy are well-established tools for kidney disease diagnosis, they are limited by several inevitable defects. Therefore, diagnostic tools need to be upgraded, especially for the early stage of the disease and possible progression. As one of the most common post-translational modifications of proteins, N-glycosylation plays a vital role in renal structure and function. Deepening research on N-glycosylation in kidney disease provides new insights into the pathophysiology and paves the way for clinical application. In this study, we reviewed recent N-glycosylation studies on several kidney diseases. We also summarized the development of mass spectrometric methods in the field of N-glycoproteomics and N-glycomics.

Controlled Humidity Levels for Fine Spatial Detail Information in Enzyme-Assisted N-Glycan MALDI MSI

Investigation of the spatial distribution of N-glycans in tissue specimens has emerged as a powerful tool in clinical research, in part, because altered N-glycans are often a hallmark of disease progression. Mass spectrometry imaging of N-glycans relies on peptide N-glycanase spraying and tissue incubation for efficient in situ release of N-glycans from their carrier proteins. Unstandardized and uncontrolled incubation steps often cause significant delocalization of released N-glycans, resulting in the inability to link given N-glycan composition to a specific microanatomical region in the tissue. Herein, we optimized the incubation step to provide accurate and sensitive MALDI-MSI of N-glycans. Specifically, we tested saturated solutions of various salts that maintain constant relative humidity in the incubation chamber. We showed that the best performance was achieved using a saturated solution of KNO₃ that maintains an 89% RH. Under these conditions, near maximal sensitivity was achieved with the minutest ion delocalization, which we demonstrated at a 35 μm spatial resolution, where we observed six distinct spatial patterns that colocalize to distinct microanatomical compartments in a kidney nephrectomy tissue section.

Metabolic Links to Socioeconomic Stresses Uniquely Affecting Ancestry in Normal Breast Tissue at Risk for Breast Cancer

A primary difference between black women (BW) and white women (WW) diagnosed with breast cancer is aggressiveness of the tumor. Black women have higher mortalities with similar incidence of breast cancer compared to other race/ethnicities, and they are diagnosed at a younger age with more advanced tumors with double the rate of lethal, triple negative breast cancers. One hypothesis is that chronic social and economic stressors result in ancestry-dependent molecular responses that create a tumor permissive tissue microenvironment in normal breast tissue. Altered regulation of N-glycosylation of proteins, a glucose metabolism-linked post-translational modification attached to an asparagine (N) residue, has been associated with two strong independent risk factors for breast cancer: increased breast density and body mass index (BMI). Interestingly, high body mass index (BMI) levels have been reported to associate with increases of cancer-associated N-glycan signatures. In this study, we used matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) to investigate molecular pattern changes of N-glycosylation in ancestry defined normal breast tissue from BW and WW with significant 5-year risk of breast cancer by Gail score. N-glycosylation was tested against social stressors including marital status, single, education, economic status (income), personal reproductive history, the risk factors BMI and age. Normal breast tissue microarrays from the Susan G. Komen tissue bank (BW=43; WW= 43) were used to evaluate glycosylation against socioeconomic stress and risk factors. One specific N-glycan (2158 m/z) appeared dependent on ancestry with high sensitivity and specificity (AUC 0.77, Brown/Wilson p-value<0.0001). Application of a linear regression model with ancestry as group variable and socioeconomic covariates as predictors identified a specific N-glycan signature associated with different socioeconomic stresses. For WW, household income was strongly associated to certain N-glycans, while for BW, marital status (married and single) was strongly associated with the same N-glycan signature. Current work focuses on understanding if combined N-glycan biosignatures can further help understand normal breast tissue at risk. This study lays the foundation for understanding the complexities linking socioeconomic stresses and molecular factors to their role in ancestry dependent breast cancer risk.

Application of Mass Spectrometry Imaging in Uro-Oncology: Discovering Potential Biomarkers

A growing need is emerging worldwide for new molecular markers which could enhance the accuracy of diagnostic and therapeutic methods for detecting urogenital cancers. Mass spectrometry imaging (MSI) is a very promising tool in this regard. In this review, we attempt to provide a subjective summary of the latest publications on potential biomarkers of renal, bladder, prostate, and testicular malignancies detected with MSI through the eyes of a clinical urologist.

GlycoFibroTyper: A Novel Method for the Glycan Analysis of IgG and the Development of a Biomarker Signature of Liver Fibrosis

Our group has recently developed the GlycoTyper assay which is a streamlined antibody capture slide array approach to directly profile N-glycans of captured serum glycoproteins including immunoglobulin G (IgG). This method needs only a few microliters of serum and utilizes a simplified processing protocol that requires no purification or sugar modifications prior to analysis. In this method, antibody captured glycoproteins are treated with peptide N-glycosidase F (PNGase F) to release N-glycans for detection by MALDI imaging mass spectrometry (IMS). As alterations in N-linked glycans have been reported for IgG from large patient cohorts with fibrosis and cirrhosis, we utilized this novel method to examine the glycosylation of total IgG, as well as IgG1, IgG2, IgG3 and IgG4, which have never been examined before, in a cohort of 106 patients with biopsy confirmed liver fibrosis. Patients were classified as either having no evidence of fibrosis (41 patients with no liver disease or stage 0 fibrosis), early stage fibrosis (10 METAVIR stage 1 and 18 METAVIR stage 2) or late stage fibrosis (6 patients with METAVIR stage 3 fibrosis and 37 patients with METAVIR stage 4 fibrosis (cirrhosis)). Several major alterations in glycosylation were observed that classify patients as having no fibrosis (sensitivity of 92% and a specificity of 90%), early fibrosis (sensitivity of 84% with 90% specificity) or significant fibrosis (sensitivity of 94% with 90% specificity).

Reduced Hemoglobin Signal and Improved Detection of Endogenous Proteins in Blood-Rich Tissues for MALDI Mass Spectrometry Imaging

Mass spectrometry imaging provides a powerful approach for the direct analysis and spatial visualization of molecules in tissue sections. Using matrix-assisted laser desorption/ionization mass spectrometry, intact protein imaging has been widely investigated for biomarker analysis and diagnosis in a variety of tissue types and diseases. However, blood-rich or highly vascular tissues present a challenge in molecular imaging due to the high ionization efficiency of hemoglobin, which leads to ion suppression of endogenous proteins. Here, we describe a protocol to selectively reduce hemoglobin signal in blood-rich tissues that can easily be integrated into mass spectrometry imaging workflows.

Fucosylation in Urological Cancers

Fucosylation is an oligosaccharide modification that plays an important role in immune response and malignancy, and specific fucosyltransferases (FUTs) catalyze the three types of fucosylations: core-type, Lewis type, and H type. FUTs regulate cancer proliferation, invasiveness, and resistance to chemotherapy by modifying the glycosylation of signaling receptors. Oligosaccharides on PD-1/PD-L1 proteins are specifically fucosylated, leading to functional modifications. Expression of FUTs is upregulated in renal cell carcinoma, bladder cancer, and prostate cancer. Aberrant fucosylation in prostate-specific antigen (PSA) could be used as a novel biomarker for prostate cancer. Furthermore, elucidation of the biological function of fucosylation could result in the development of novel therapeutic targets. Further studies are needed in the field of fucosylation glycobiology in urological malignancies.

Trends in oligomannosylation and α1,2-mannosidase expression in human cancers

Aberrant protein glycosylation is a prominent cancer feature. While many tumour-associated glycoepitopes have been reported, advances in glycoanalytics continue to uncover new associations between glycosylation and cancer. Guided by a comprehensive literature survey suggesting that oligomannosylation (Man_5–9 GlcNAc₂) is a widespread and often regulated glycosignature in human cancers, we here revisit a valuable compilation of nearly 500 porous graphitized carbon LC-MS/MS N-glycomics datasets acquired across 11 human cancer types to systematically test for oligomannose-cancer associations. Firstly, the quantitative glycomics data obtained across 34 cancerous cell lines demonstrated that oligomannosylation is a pan-cancer feature spanning in a wide abundance range. In keeping with literature, our quantitative glycomics data of tumour and matching control tissues and new MALDI-MS imaging data of tissue microarrays showed a strong cancer-associated elevation of oligomannosylation in both basal cell (p = 1.78 × 10^–12) and squamous cell (p = 1.23 × 10^–11) skin cancer and colorectal cancer (p = 8.0 × 10^–4). The glycomics data also indicated that some cancer types including gastric and liver cancer exhibit unchanged or reduced oligomannose levels, observations also supported by literature and MALDI-MS imaging data. Finally, expression data from public cancer repositories indicated that several α1,2-mannosidases are regulated in tumour tissues suggesting that these glycan-processing enzymes may contribute to the cancer-associated modulation of oligomannosylation. This omics-centric study has compiled robust glycomics and enzyme expression data revealing interesting molecular trends that open avenues to better understand the role of oligomannosylation in human cancers.

MASS SPECTROMETRY TECHNOLOGIES TO ADVANCE CARE FOR CANCER PATIENTS IN CLINICAL AND INTRAOPERATIVE USE

Developments in mass spectrometry technologies have driven a widespread interest and expanded their use in cancer-related research and clinical applications. In this review, we highlight the developments in mass spectrometry methods and instrumentation applied to direct tissue analysis that have been tailored at enhancing performance in clinical research as well as facilitating translation and implementation of mass spectrometry in clinical settings, with a focus on cancer-related studies. Notable studies demonstrating the capabilities of direct mass spectrometry analysis in biomarker discovery, cancer diagnosis and prognosis, tissue analysis during oncologic surgeries, and other clinically relevant problems that have the potential to substantially advance cancer patient care are discussed. Key challenges that need to be addressed before routine clinical implementation including regulatory efforts are also discussed. Overall, the studies highlighted in this review demonstrate the transformative potential of mass spectrometry technologies to advance clinical research and care for cancer patients. © 2020 Wiley Periodicals, Inc. Mass Spec Rev.

Glycan-specific antibodies as potential cancer biomarkers: a focus on microarray applications

Glycosylation is one of the most common posttranslational modifications of proteins and lipids. In the case of tumors, cell transformation accompanied by aberrant glycosylation results in the expression of tumor-associated glycans that promote tumor invasion. As part of the innate immunity, anti-glycan antibodies recognize tumor-associated glycans, and these antibodies can be present in the bloodstream in the early stages of cancer. Recently, anti-glycan antibody profiles have been of interest in various cancer studies. Novel advantages in the field of analytical techniques have simplified the analysis of anti-glycan antibodies and made it easier to have more comprehensive knowledge about their functions. One of the robust approaches for studying anti-glycan antibodies engages in microarray technology. The analysis of glycan microarrays can provide more expanded information to simultaneously specify or suggest the role of antibodies to a wide variety of glycans in the progression of different diseases, therefore making it possible to identify new biomarkers for diagnosing cancer and/or the state of the disease. Thus, in this review, we discuss antibodies to various glycans, their application for diagnosing cancer and one of the most promising tools for the investigation of these molecules, microarrays.

Glycan Imaging Mass Spectrometry: Progress in Developing Clinical Diagnostic Assays for Tissues, Biofluids, and Cells

N-glycan imaging mass spectrometry (IMS) can rapidly and reproducibly identify changes in disease-associated N-linked glycosylation that are linked with histopathology features in standard formalin-fixed paraffin-embedded tissue samples. It can detect multiple N-glycans simultaneously and has been used to identify specific N-glycans and carbohydrate structural motifs as possible cancer biomarkers. Recent advancements in instrumentation and sample preparation are also discussed. The tissue N-glycan IMS workflow has been adapted to new glass slide-based assays for effective and rapid analysis of clinical biofluids, cultured cells, and immunoarray-captured glycoproteins for detection of changes in glycosylation associated with disease.

Optimization of Multiple Glycosidase and Chemical Stabilization Strategies for N-Glycan Isomer Detection by Mass Spectrometry Imaging in Formalin-Fixed, Paraffin-Embedded Tissues

The analysis of N-glycan distributions in formalin-fixed, paraffin-embedded (FFPE) tissues by matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is an effective approach for characterization of many disease states. As the workflow has matured and new technology emerged, approaches are needed to more efficiently characterize the isomeric structures of these N-glycans to expand on the specificity of their localization within tissue. Sialic acid chemical derivatization can be used to determine the isomeric linkage (α2,3 or α2,6) of sialic acids attached to N-glycans, while endoglycosidase F3 (Endo F3) can be enzymatically applied to preferentially release α1,6-linked core fucosylated glycans, further describing the linkage of fucose on N-glycans. Here we describe workflows where N-glycans are chemically derivatized to reveal sialic acid isomeric linkages, combined with a dual-enzymatic approach of endoglycosidase F3 and PNGase F to further elucidate fucosylation isomers on the same tissue section.

Imaging Mass Spectrometry and Lectin Analysis of N-Linked Glycans in Carbohydrate Antigen-Defined Pancreatic Cancer Tissues

The early detection of pancreatic ductal adenocarcinoma (PDAC) is a complex clinical obstacle yet is key to improving the overall likelihood of patient survival. Current and prospective carbohydrate biomarkers carbohydrate antigen 19-9 (CA19-9) and sialylated tumor-related antigen (sTRA) are sufficient for surveilling disease progression yet are not approved for delineating PDAC from other abdominal cancers and noncancerous pancreatic pathologies. To further understand these glycan epitopes, an imaging mass spectrometry (IMS) approach was used to assess the N-glycome of the human pancreas and pancreatic cancer in a cohort of patients with PDAC represented by tissue microarrays and whole-tissue sections. Orthogonally, these same tissues were characterized by multiround immunofluorescence that defined expression of CA19-9 and sTRA as well as other lectins toward carbohydrate epitopes with the potential to improve PDAC diagnosis. These analyses revealed distinct differences not only in N-glycan spatial localization across both healthy and diseased tissues but importantly between different biomarker-categorized tissue samples. Unique sulfated biantennary N-glycans were detected specifically in normal pancreatic islets. N-glycans from CA19-9-expressing tissues tended to be biantennary, triantennary, and tetra-antennary structures with both core and terminal fucose residues and bisecting GlcNAc. These N-glycans were detected in less abundance in sTRA-expressing tumor tissues, which favored triantennary and tetra-antennary structures with polylactosamine extensions. Increased sialylation of N-glycans was detected in all tumor tissues. A candidate new biomarker derived from IMS was further explored by fluorescence staining with selected lectins on the same tissues. The lectins confirmed the expression of the epitopes in cancer cells and revealed different tumor-associated staining patterns between glycans with bisecting GlcNAc and those with terminal GlcNAc. Thus, the combination of lectin-immunohistochemistry and lectin-IMS techniques produces more complete information for tumor classification than the individual analyses alone. These findings potentiate the development of early assessment technologies to rapidly and specifically identify PDAC in the clinic that may directly impact patient outcomes.

Rapid N-Glycan Profiling of Serum and Plasma by a Novel Slide-Based Imaging Mass Spectrometry Workflow

Changes in the levels and compositions of N-glycans released from serum and plasma glycoproteins have been assessed in many diseases across many large clinical sample cohorts. Assays used for N-glycan profiling in these fluids currently require multiple processing steps and have limited throughput, thus diminishing their potential for use as standard clinical diagnostic assays. A novel slide-based N-glycan profiling method was evaluated for sensitivity and reproducibility using a pooled serum standard. Serum was spotted on to an amine-reactive slide, delipidated and desalted with a series of washes, sprayed with peptide N-glycosidase F and matrix, and analyzed by MALDI-FTICR or MALDI-Q-TOF mass spectrometry. Routinely, over 75 N-glycan species can be detected from one microliter of serum in less than 6.5 h. Additionally, endoglycosidase F3 was applied to this workflow to identify core-fucosylated N-glycans and displayed the adaptability of this method for the determination of structural information. This method was applied to a small pooled serum set from either obese or nonobese patients that had breast cancer or a benign lesion. This study confirms the reproducibility, sensitivity, and adaptability of a novel method for N-glycan profiling of serum and plasma for potential application to clinical diagnostics.

MALDI-2 for the Enhanced Analysis of N-Linked Glycans by Mass Spectrometry Imaging

N-glycans are important players in a variety of pathologies including different types of cancer, (auto)immune diseases, and also viral infections. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is an important tool for high-throughput N-glycan profiling and, upon use of tandem MS, for structure determination. By use of MALDI-MS imaging (MSI) in combination with PNGase F treatment, also spatially correlated N-glycan profiling from tissue sections becomes possible. Here we coupled laser-induced postionization, or MALDI-2, to a trapped ion mobility quadrupole time-of-flight mass spectrometer (timsTOF fleX MALDI-2, Bruker Daltonics). We demonstrate that with MALDI-2 the sensitivity for the detection of molecular [M – H]⁻ species of N-glycans increased by about 3 orders of magnitude. Compared to the current gold standard, the positive ion mode analysis of [M + Na]⁺ adducts, a sensitivity increase by about a factor of 10 is achieved. By exploiting the advantageous fragmentation behavior of [M – H]⁻ ions, exceedingly rich structural information on the composition of complex N-glycans was moreover obtained directly from thin tissue sections of human cerebellum and upon use of low-energy collision-induced dissociation tandem MS. In another set of experiments, in this case by use of a modified Synapt G2-S QTOF mass spectrometer (Waters), we investigated the influence of relevant input parameters, in particular pressure of the N₂ cooling gas in the ion source, delay between the two laser pulses, and that of their pulse energies. In this way, analytical conditions were identified at which molecular ion abundances were maximized and fragmentation reactions minimized. The use of negative ion mode MALDI-2-MSI could constitute a valuable tool in glycobiology research.

On-Tissue Derivatization with Girard's Reagent P Enhances N-Glycan Signals for Formalin-Fixed Paraffin-Embedded Tissue Sections in MALDI Mass Spectrometry Imaging

Glycosylation is a major protein post-translational modification whose dysregulation has been associated with many diseases. Herein, an on-tissue chemical derivatization strategy based on positively charged hydrazine reagent (Girard's reagent P) coupled with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) was developed for analysis of N-glycans from FFPE treated tissue sections. The performance of the proposed approach was evaluated by analysis of monosaccharides, oligosaccharides, N-glycans released from glycoproteins, as well as MS imaging of N-glycans from human cancer tissue sections. The results demonstrated that the signal-to-noise ratios for target saccharides were notably improved after chemical derivatization, in which signals were enhanced by 230-fold for glucose and over 28-fold for maltooctaose. Improved glycome coverage was obtained for N-glycans derived from glycoproteins and tissue samples after chemical derivatization. Furthermore, on-tissue derivatization was applied for MALDI-MSI of N-glycans from human laryngeal cancer and ovarian cancer tissues. Differentially expressed N-glycans among the tumor region, adjacent normal tissue region, and tumor proximal collagen stroma region were imaged, revealing that high-mannose type N-glycans were predominantly expressed in the tumor region. Overall, our results indicate that the on-tissue labeling strategy coupled with MALDI-MSI shows great potential to spatially characterize N-glycan expression within heterogeneous tissue samples with enhanced sensitivity. This study provides a promising approach to better understand the pathogenesis of cancer related aberrant glycosylation, which is beneficial to the design of improved clinical diagnosis and therapeutic strategies.

Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective

The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME.

Robustness in glycosylation systems: effect of modified monosaccharides, acceptor decoys and azido sugars on cellular nucleotide-sugar levels and pattern of N-linked glycosylation

Small molecule monosaccharide analogs (e.g. 4F-GlcNAc, 4F-GalNAc) and acceptor decoys (e.g. ONAP, SNAP) are commonly used as metabolic glycoengineering tools to perturb molecular and cellular recognition processes. Azido-derivatized sugars (e.g. ManNAz, GlcNAz, GalNAz) are also used as bioorthogonal probes to assay the glycosylation status of cells and tissue. With the goal of obtaining a systems-level understanding of how these compounds work, we cultured cells with these molecules and systematically evaluated their impact on: (i) cellular nucleotide-sugar levels, and (ii) N-linked glycosylation. To this end, we developed a streamlined, simple workflow to quantify nucleotide-sugar levels using amide-based hydrophilic interaction liquid chromatography (HILIC) separation followed by negative-mode electrospray ionization mass spectrometry (ESI-MS/MS) using an Orbitrap detector. N-Glycans released from cells were also procainamide functionalized and quantified using positive-mode ESI-MS/MS. Results show that all tested compounds changed the baseline nucleotide-sugar levels, with the effect being most pronounced for the fluoro-HexNAc compounds. These molecules depressed UDP-HexNAc levels in cells by up to 80%, while concomitantly elevating UDP-4F-GalNAc and UDP-4F-GlcNAc. While the measured changes in nucleotide-sugar concentration were substantial in many cases, their impact on N-linked glycosylation was relatively small. This may be due to the high nucleotide-sugar concentrations in the Golgi, which far exceed the K_M values of the glycosylating enzymes. Thus, the glycosylation system output exhibits 'robustness' even in the face of significant changes in cellular nucleotide-sugar concentrations.