MALDI Mass Spectrometry Imaging of Early- and Late-Stage Serous Ovarian Cancer Tissue Reveals Stage-Specific N-Glycans

Mass spectrometry for metabolomics analysis: Applications in neonatal and cancer screening

Chemical analysis by analytical instrumentation has played a major role in disease diagnosis, which is a necessary step for disease treatment. While the treatment process often targets specific organs or compounds, the diagnostic step can occur through various means, including physical or chemical examination. Chemically, the genome may be evaluated to give information about potential genetic outcomes, the transcriptome to provide information about expression actively occurring, the proteome to offer insight on functions causing metabolite expression, or the metabolome to provide a picture of both past and ongoing physiological function in the body. Mass spectrometry (MS) has been elevated among other analytical instrumentation because it can be used to evaluate all four biological machineries of the body. In addition, MS provides enhanced sensitivity, selectivity, versatility, and speed for rapid turnaround time, qualities that are important for instance in clinical procedures involving the diagnosis of a pediatric patient in intensive care or a cancer patient undergoing surgery. In this review, we provide a summary of the use of MS to evaluate biomarkers for newborn screening and cancer diagnosis. As many reviews have recently appeared focusing on MS methods and instrumentation for metabolite analysis, we sought to describe the biological basis for many metabolomic and additional omics biomarkers used in newborn screening and how tandem MS methods have recently been applied, in comparison to traditional methods. Similar comparison is done for cancer screening, with emphasis on emerging MS approaches that allow biological fluids, tissues, and breath to be analyzed for the presence of diagnostic metabolites yielding insight for treatment options based on the understanding of prior and current physiological functions of the body.

Mass spectrometry imaging methods for visualizing tumor heterogeneity

Profiling spatial distributions of lipids, metabolites, and proteins in tumors can reveal unique cellular microenvironments and provide molecular evidence for cancer cell dysfunction and proliferation. Mass spectrometry imaging (MSI) is a label-free technique that can be used to map biomolecules in tumors in situ. Here, we discuss current progress in applying MSI to uncover molecular heterogeneity in tumors. First, the analytical strategies to profile small molecules and proteins are outlined, and current methods for multimodal imaging to maximize biological information are highlighted. Second, we present and summarize biological insights obtained by MSI of tumor tissue. Finally, we discuss important considerations for designing MSI experiments and several current analytical challenges.

Advancements in protein glycosylation biomarkers for ovarian cancer through mass spectrometry-based approaches

INTRODUCTION

Ovarian cancer, characterized by metastasis and reduced 5-year survival rates, stands as a substantial factor in the mortality of gynecological malignancies worldwide. The challenge of delayed diagnosis originates from vague early symptoms and the absence of efficient screening and diagnostic biomarkers for early cancer detection. Recent studies have explored the intricate interplay between ovarian cancer and protein glycosylation, unveiling the potential significance of glycosylation-oriented biomarkers.

AREAS COVERED

This review examines the progress in glycosylation biomarker research, with particular emphasis on advances driven by mass spectrometry-based technologies. We document milestones achieved, discuss encountered limitations, and also highlight potential areas for future research and development of protein glycosylation biomarkers for ovarian cancer.

EXPERT OPINION

The association of glycosylation in ovarian cancer is well known, but current research lacks desired sensitivity and specificity for early detection. Notably, investigations into protein-specific and site-specific glycoproteomics have the potential to significantly enhance our understanding of ovarian cancer and facilitate the identification of glycosylation-based biomarkers. Furthermore, the integration of advanced mass spectrometry techniques with AI-driven analysis and glycome databases holds the promise for revolutionizing biomarker discovery for ovarian cancer, ultimately transforming diagnosis and improving patient outcomes.

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.

Noninvasive serum N-glycans associated with ovarian cancer diagnosis and precancerous lesion prediction

BACKGROUND

Ovarian cancer (OC) is one of the most common gynecological tumors with high morbidity and mortality. Altered serum N-glycome has been observed in many diseases, while the association between serum protein N-glycosylation and OC progression remains unclear, particularly for the onset of carcinogenesis from benign neoplasms to cancer.

METHODS

Herein, a mass spectrometry based high-throughput technique was applied to characterize serum N-glycome profile in individuals with healthy controls, benign neoplasms and different stages of OC. To elucidate the alterations of glycan features in OC progression, an orthogonal strategy with lectin-based ELISA was performed.

RESULTS

It was observed that the initiation and development of OC was associated with increased high-mannosylationand agalactosylation, concurrently with decreased total sialylation of serum, each of which gained at least moderately accurate merits. The most important individual N-glycans in each glycan group was H7N2, H3N5 and H5N4S2F1, respectively. Notably, serum N-glycome could be used to accurately discriminate OC patients from benign cohorts, with a comparable or even higher diagnostic score compared to CA125 and HE4. Furthermore, bioinformatics analysis based discriminative model verified the diagnostic performance of serum N-glycome for OC in two independent sets.

CONCLUSIONS

These findings demonstrated the great potential of serum N-glycome for OC diagnosis and precancerous lesion prediction, paving a new way for OC screening and monitoring.

Influence of glycosylation on the immunogenicity and antigenicity of viral immunogens

A key aspect of successful viral vaccine design is the elicitation of neutralizing antibodies targeting viral attachment and fusion glycoproteins that embellish viral particles. This observation has catalyzed the development of numerous viral glycoprotein mimetics as vaccines. Glycans can dominate the surface of viral glycoproteins and as such, the viral glycome can influence the antigenicity and immunogenicity of a candidate vaccine. In one extreme, glycans can form an integral part of epitopes targeted by neutralizing antibodies and are therefore considered to be an important feature of key immunogens within an immunization regimen. In the other extreme, the existence of peptide and bacterially expressed protein vaccines shows that viral glycosylation can be dispensable in some cases. However, native-like glycosylation can indicate native-like protein folding and the presence of conformational epitopes. Furthermore, going beyond native glycan mimicry, in either occupancy of glycosylation sites or the glycan processing state, may offer opportunities for enhancing the immunogenicity and associated protection elicited by an immunogen. Here, we review key determinants of viral glycosylation and how recombinant immunogens can recapitulate these signatures across a range of enveloped viruses, including HIV-1, Ebola virus, SARS-CoV-2, Influenza and Lassa virus. The emerging understanding of immunogen glycosylation and its control will help guide the development of future vaccines in both recombinant protein- and nucleic acid-based vaccine technologies.

A Guide to MALDI Imaging Mass Spectrometry for Tissues

Imaging mass spectrometry is a well-established technology that can easily and succinctly communicate the spatial localization of molecules within samples. This review communicates the recent advances in the field, with a specific focus on matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) applied on tissues. The general sample preparation strategies for different analyte classes are explored, including special considerations for sample types (fresh frozen or formalin-fixed,) strategies for various analytes (lipids, metabolites, proteins, peptides, and glycans) and how multimodal imaging strategies can leverage the strengths of each approach is mentioned. This work explores appropriate experimental design approaches and standardization of processes needed for successful studies, as well as the various data analysis platforms available to analyze data and their strengths. The review concludes with applications of imaging mass spectrometry in various fields, with a focus on medical research, and some examples from plant biology and microbe metabolism are mentioned, to illustrate the breadth and depth 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.

Complex-Type N-Glycans Are Associated with Cartilage Degeneration within Different Loading Sites of the Tibial Plateau for Knee Osteoarthritis Patients

Abnormal N-glycosylation has been shown to play an important role in the pathogenesis of multiple diseases. However, little is known about the relationship between N-glycosylation and knee osteoarthritis (KOA) progression at the tissue level. Thus, the aim of this study was to quantify the cartilage histomorphometric changes in formalin-fixed paraffin-embedded (FFPE) tissue collected from the lateral and medial compartments of the tibial plateau KOA patients (n = 8). Subsequently, N-glycans were analyzed by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) followed by in situ MS/MS fragmentation. Overall, the Osteoarthritis Research Society International (OARSI) histological grade and cartilage surface fibrillation index were significantly higher, and chondrocyte size in the superficial zone was much larger, for the medial high-loaded cartilage compared to the lateral less-loaded cartilage. Among 92 putative N-glycans observed by MALDI-MSI, 3 complex-type N-glycans, (Hex)4(HexNAc)3, (Hex)4(HexNAc)4, and (Hex)5(HexNAc)4, and 1 oligomannose-type N-glycan, (Hex)9(HexNAc)2, were significantly higher in intensity in the medial cartilage compared to the lateral cartilage, whereas 2 tetra-antennary fucosylated-type N-glycans, (Hex)3(HexNAc)6(Fuc)2 and (Hex)3(HexNAc)6(Fuc)3, were significantly higher in intensity in the lateral cartilage than the medial cartilage. Our findings indicate that complex-type N-glycans are associated with higher severity of cartilage degeneration and may influence the cellular processes of KOA.

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.

Optimized protocol for MALDI MSI of N-glycans using an on-tissue digestion in fresh frozen tissue sections

Glycans play an important role in biology with multiple cellular functions ranging from cell signaling, mobility and growth to protein folding and localization. The N-glycosylation state within a tissue has been found to vary greatly between healthy and diseased patients and has proven to have an important clinical diagnostic value. Matrix assisted laser-desorption ionization (MALDI) mass spectrometry imaging (MSI) allows for untargeted analysis of biomolecules, including N-glycans, on a tissue section and provides a spatial context of the analyte. Until now, N-glycans have been predominantly analyzed using MALDI MSI on formalin-fixed paraffin embedded (FFPE) tissue sections, however this greatly reduces the clinical applicability, as the FFPE embedding process alters the biological environment of the tissue. Here we developed a protocol that allows for MALDI MSI of N-glycans from fresh frozen tissue that matches the current standard of FFPE analysis. By optimizing several steps in the sample preparation, we see orders of magnitude increase in signal intensity. Furthermore, this method limits delocalization of released N-glycans, thus improving the effective spatial resolution of the label-free molecular images. This protocol provides a novel perspective towards clinical application of MALDI MSI and capitalizes on the diagnostic value of N-glycan analysis.

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.

Limited N-Glycan Processing Impacts Chaperone Expression Patterns, Cell Growth and Cell Invasiveness in Neuroblastoma

Enhanced N-glycan branching is associated with cancer, but recent investigations supported the involvement of less processed N-glycans. Herein, we investigated how changes in N-glycosylation influence cellular properties in neuroblastoma (NB) using rat N-glycan mutant cell lines, NB_1(-Mgat1), NB_1(-Mgat2) and NB_1(-Mgat3), as well as the parental cell line NB_1. The two earlier mutant cells have compromised N-acetylglucosaminyltransferase-I (GnT-I) and GnT-II activities. Lectin blotting showed that NB_1(-Mgat3) cells had decreased activity of GnT-III compared to NB_1. ESI-MS profiles identified N-glycan structures in NB cells, supporting genetic edits. NB_1(-Mgat1) had the most oligomannose N-glycans and the greatest cell invasiveness, while NB_1(-Mgat2) had the fewest and least cell invasiveness. The proliferation rate of NB_1 was slightly slower than NB_1(-Mgat3), but faster than NB_1(-Mgat1) and NB_1(-Mgat2). Faster proliferation rates were due to the faster progression of those cells through the G1 phase of the cell cycle. Further higher levels of oligomannose with 6-9 Man residues indicated faster proliferating cells. Human NB cells with higher oligomannose N-glycans were more invasive and had slower proliferation rates. Both rat and human NB cells revealed modified levels of ER chaperones. Thus, our results support a role of oligomannose N-glycans in NB progression; furthermore, perturbations in the N-glycosylation pathway can impact chaperone systems.

Mass Spectrometry-Based Glycoproteomic Workflows for Cancer Biomarker Discovery

Glycosylation has a clear role in cancer initiation and progression, with numerous studies identifying distinct glycan features or specific glycoproteoforms associated with cancer. Common findings include that aggressive cancers tend to have higher expression levels of enzymes that regulate glycosylation as well as glycoproteins with greater levels of complexity, increased branching, and enhanced chain length1. Research in cancer glycoproteomics over the last 50-plus years has mainly focused on technology development used to observe global changes in glycosylation. Efforts have also been made to connect glycans to their protein carriers as well as to delineate the role of these modifications in intracellular signaling and subsequent cell function. This review discusses currently available techniques utilizing mass spectrometry-based technologies used to study glycosylation and highlights areas for future advancement.

Mass spectrometry imaging in gynecological cancers: the best is yet to come

Mass spectrometry imaging (MSI) enables obtaining multidimensional results simultaneously in a single run, including regiospecificity and m/z values corresponding with specific proteins, peptides, lipids, etc. The knowledge obtained in this way allows for a multifaceted analysis of the studied issue, e.g., the specificity of the neoplastic process and the search for new therapeutic targets. Despite the enormous possibilities, this relatively new technique in many aspects still requires the development or standardization of analytical protocols (from collecting biological material, through sample preparation, analysis, and data collection, to data processing). The introduction of standardized protocols for MSI studies, with its current potential to extend diagnostic and prognostic capabilities, can revolutionize clinical pathology. As far as identifying ovarian cancer subtypes can be challenging, especially in poorly differentiated tumors, developing MSI-based algorithms may enhance determining prognosis and tumor staging without the need for extensive surgery and optimize the choice of subsequent therapy. MSI might bring new solutions in predicting response to treatment in patients with endometrial cancer. Therefore, MSI may help to revolutionize the future of gynecological oncology in terms of diagnostics, treatment, and predicting the response to therapy. This review will encompass several aspects, e.g., contemporary discoveries in gynecological cancer research utilizing MSI, indicates current challenges, and future perspectives on MSI.

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 Protocol for the Acquisition of Comprehensive Proteomics Data from Single Cases Using Formalin-Fixed Paraffin Embedded Sections

The molecular analysis of small or rare patient tissue samples is challenging and often limited by available technologies and resources, such as reliable antibodies against a protein of interest. Although targeted approaches provide some insight, here, we describe the workflow of two complementary mass spectrometry approaches, which provide a more comprehensive and non-biased analysis of the molecular features of the tissue of interest. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) generates spatial intensity maps of molecular features, which can be easily correlated with histology. Additionally, liquid chromatography tandem mass spectrometry (LC-MS/MS) can identify and quantify proteins of interest from a consecutive section of the same tissue. Here, we present data from concurrent precancerous lesions from the endometrium and fallopian tube of a single patient. Using this complementary approach, we monitored the abundance of hundreds of proteins within the precancerous and neighboring healthy regions. The method described here represents a useful tool to maximize the number of molecular data acquired from small sample sizes or even from a single case. Our initial data are indicative of a migratory phenotype in these lesions and warrant further research into their malignant capabilities.

In Situ N-glycosylation Signatures of Epithelial Ovarian Cancer Tissue as Defined by MALDI Mass Spectrometry Imaging

The particularly high mortality of epithelial ovarian cancer (EOC) is in part linked to limited understanding of its molecular signatures. Although there are data available on in situ N-glycosylation in EOC tissue, previous studies focused primarily on neutral N-glycan species and, hence, still little is known regarding EOC tissue-specific sialylation. In this proof-of-concept study, we implemented MALDI mass spectrometry imaging (MALDI-MSI) in combination with sialic acid derivatization to simultaneously investigate neutral and sialylated N-glycans in formalin-fixed paraffin-embedded tissue microarray specimens of less common EOC histotypes and non-malignant borderline ovarian tumor (BOT). The applied protocol allowed detecting over 50 m/z species, many of which showed differential tissue distribution. Most importantly, it could be demonstrated that α2,6- and α2,3-sialylated N-glycans are enriched in tissue regions corresponding to tumor and adjacent tumor-stroma, respectively. Interestingly, analogous N-glycosylation patterns were observed in tissue cores of BOT, suggesting that regio-specific N-glycan distribution might occur already in non-malignant ovarian pathologies. All in all, our data provide proof that the combination of MALDI-MSI and sialic acid derivatization is suitable for delineating regio-specific N-glycan distribution in EOC and BOT tissues and might serve as a promising strategy for future glycosylation-based biomarker discovery studies.

Recent advances and trends in sample preparation and chemical modification for glycan analysis

Growing significance of glycosylation in protein functions has accelerated the development of methodologies for detection, identification, and characterization of protein glycosylation. In the past decade, glycobiology research has been advanced by innovative techniques with further progression in the post-genome era. Although significant technical progress has been made in terms of analytical throughput, comprehensiveness, and sensitivity, most methods for glycosylation analysis still require laborious and time-consuming sample preparation tasks. Additionally, sample preparation methods that are focused on specific glycan(s) require an in-depth understanding of various issues in glycobiology. In this review, modern sample preparation and chemical modification methods for the structural and quantitative glycan analyses together with the challenges and advantages of recent sample preparation methods are summarized. The techniques presented herein can facilitate the exploration of biomarkers, understanding of unknown glycan functions, and development of biopharmaceuticals.

Molecular Histology Analysis of Cryopreserved Tissue Using Peptide/Protein MALDI-TOF Imaging Mass Spectrometry (MALDI-IMS)

Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) has emerged as a powerful tool for analyzing the spatial distribution of peptides, small proteins, and other molecules within biological tissues. The obtained signals can be correlated with underlying tissue architecture, without any geometrical distortion, enabling the so-called molecular histology. Here, we analyzed cryopreserved tissue samples employing the MALDI-IMS for proteins and peptides. We used a nonstandard OCT-free cryo-slicing protocol, followed by Carnoy delipidation. Automated matrix spray was utilized to circumvent some of MALDI-IMS technology drawbacks in protein and peptide analysis.

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.

Molecular tissue profiling by MALDI imaging: recent progress and applications in cancer research

Matrix-assisted laser desorption/ionization (MALDI) imaging is an emergent technology that has been increasingly adopted in cancer research. MALDI imaging is capable of providing global molecular mapping of the abundance and spatial information of biomolecules directly in the tissues without labeling. It enables the characterization of a wide spectrum of analytes, including proteins, peptides, glycans, lipids, drugs, and metabolites and is well suited for both discovery and targeted analysis. An advantage of MALDI imaging is that it maintains tissue integrity, which allows correlation with histological features. It has proven to be a valuable tool for probing tumor heterogeneity and has been increasingly applied to interrogate molecular events associated with cancer. It provides unique insights into both the molecular content and spatial details that are not accessible by other techniques, and it has allowed considerable progress in the field of cancer research. In this review, we first provide an overview of the MALDI imaging workflow and approach. We then highlight some useful applications in various niches of cancer research, followed by a discussion of the challenges, recent developments and future prospect of this technique in the field.

Advances in mass spectrometry-based glycomics-An update covering the period 2017-2021

The wide variety of chemical properties and biological functions found in proteins is attained via post-translational modifications like glycosylation. Covalently bonded to proteins, glycans play a critical role in cell activity. Complex structures with microheterogeneity, the glycan structures that are associated with proteins are difficult to analyze comprehensively. Recent advances in sample preparation methods, separation techniques, and MS have facilitated the quantitation and structural elucidation of glycans. This review focuses on highlighting advances in MS-based techniques for glycomic analysis that occurred over the last 5 years (2017-2021) as an update to the previous review on the subject. The topics of discussion will include progress in glycomic workflow such as glycan release, purification, derivatization, and separation as well as the topics of ionization, tandem MS, and separation techniques that can be coupled with MS. Additionally, bioinformatics tools used for the analysis of glycans will be described.

In-House Packed Porous Graphitic Carbon Columns for Liquid Chromatography-Mass Spectrometry Analysis of N-Glycans

Protein glycosylation is a common post-translational modification that modulates biological processes such as the immune response and protein trafficking. Altered glycosylation profiles are associated with cancer and inflammatory diseases, as well as impacting the efficacy of therapeutic monoclonal antibodies. Consisting of oligosaccharides attached to asparagine residues, enzymatically released N-linked glycans are analytically challenging due to the diversity of isomeric structures that exist. A commonly used technique for quantitative N-glycan analysis is liquid chromatography-mass spectrometry (LC-MS), which performs glycan separation and characterization. Although many reversed and normal stationary phases have been utilized for the separation of N-glycans, porous graphitic carbon (PGC) chromatography has become desirable because of its higher resolving capability, but is difficult to implement in a robust and reproducible manner. Herein, we demonstrate the analytical properties of a 15 cm fused silica capillary (75 µm i.d., 360 µm o.d.) packed in-house with Hypercarb PGC (3 µm) coupled to an Agilent 6550 Q-TOF mass spectrometer for N-glycan analysis in positive ion mode. In repeatability and intermediate precision measurements conducted on released N-glycans from a glycoprotein standard mixture, the majority of N-glycans reported low coefficients of variation with respect to retention times (≤4.2%) and peak areas (≤14.4%). N-glycans released from complex samples were also examined by PGC LC-MS. A total of 120 N-glycan structural and compositional isomers were obtained from formalin-fixed paraffin-embedded ovarian cancer tissue sections. Finally, a comparison between early- and late-stage formalin-fixed paraffin-embedded ovarian cancer tissues revealed qualitative changes in the α2,3- and α2,6-sialic acid linkage of a fucosylated bi-antennary complex N-glycan. Although the α2,3-linkage was predominant in late-stage ovarian cancer, the alternate α2,6-linkage was more prevalent in early-stage ovarian cancer. This study establishes the utility of in-house packed PGC columns for the robust and reproducible LC-MS analysis of N-glycans.

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.

Implementation of Mass Spectrometry Imaging in Pathology: Advances and Challenges

Mass spectrometry imaging (MSI) combines the excellence in molecular characterization of mass spectrometry with microscopic imaging capabilities of hematoxylin- and eosin-stained samples, enabling the precise location of several analytes in the tissue. Especially in the field of pathology, MSI may have an impactful role in tumor diagnosis, biomarker identification, prognostic prediction, and characterization of tumor margins during tumor resection procedures. This article discusses the recent developments in the field that are paving the way for this technology to become accepted as an analytical tool in the clinical setting, its current limitations, and future directions.

The matrix in cancer

The extracellular matrix is a fundamental, core component of all tissues and organs, and is essential for the existence of multicellular organisms. From the earliest stages of organism development until death, it regulates and fine-tunes every cellular process in the body. In cancer, the extracellular matrix is altered at the biochemical, biomechanical, architectural and topographical levels, and recent years have seen an exponential increase in the study and recognition of the importance of the matrix in solid tumours. Coupled with the advancement of new technologies to study various elements of the matrix and cell-matrix interactions, we are also beginning to see the deployment of matrix-centric, stromal targeting cancer therapies. This Review touches on many of the facets of matrix biology in solid cancers, including breast, pancreatic and lung cancer, with the aim of highlighting some of the emerging interactions of the matrix and influences that the matrix has on tumour onset, progression and metastatic dissemination, before summarizing the ongoing work in the field aimed at developing therapies to co-target the matrix in cancer and cancer metastasis.

The Complexity and Dynamics of the Tissue Glycoproteome Associated With Prostate Cancer Progression

The complexity and dynamics of the immensely heterogeneous glycoproteome of the prostate cancer (PCa) tumor microenvironment remain incompletely mapped, a knowledge gap that impedes our molecular-level understanding of the disease. To this end, we have used sensitive glycomics and glycoproteomics to map the protein-, cell-, and tumor grade-specific N- and O-glycosylation in surgically removed PCa tissues spanning five histological grades (n = 10/grade) and tissues from patients with benign prostatic hyperplasia (n = 5). Quantitative glycomics revealed PCa grade-specific alterations of the oligomannosidic-, paucimannosidic-, and branched sialylated complex-type N-glycans, and dynamic remodeling of the sialylated core 1- and core 2-type O-glycome. Deep quantitative glycoproteomics identified ∼7400 unique N-glycopeptides from 500 N-glycoproteins and ∼500 unique O-glycopeptides from nearly 200 O-glycoproteins. With reference to a recent Tissue and Blood Atlas, our data indicate that paucimannosidic glycans of the PCa tissues arise mainly from immune cell-derived glycoproteins. Furthermore, the grade-specific PCa glycosylation arises primarily from dynamics in the cellular makeup of the PCa tumor microenvironment across grades involving increased oligomannosylation of prostate-derived glycoproteins and decreased bisecting GlcNAcylation of N-glycans carried by the extracellular matrix proteins. Furthermore, elevated expression of several oligosaccharyltransferase subunits and enhanced N-glycoprotein site occupancy were observed associated with PCa progression. Finally, correlations between the protein-specific glycosylation and PCa progression were observed including increased site-specific core 2-type O-glycosylation of collagen VI. In conclusion, integrated glycomics and glycoproteomics have enabled new insight into the complexity and dynamics of the tissue glycoproteome associated with PCa progression generating an important resource to explore the underpinning disease mechanisms.

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.

Altered N-linked glycosylation in endometrial cancer

It is well established that cell surface glycans play a vital role in biological processes and their altered form can lead to carcinogenesis. Mass spectrometry-based techniques have become prominent for analysing N-linked glycans, for example using matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). Additionally, MALDI MS can be used to spatially map N-linked glycans directly from cancer tissue using a technique termed MALDI MS imaging (MALDI MSI). This powerful technique combines mass spectrometry and histology to visualise the spatial distribution of N-linked glycans on a single tissue section. Here, we performed N-glycan MALDI MSI on six endometrial cancer (EC) formalin-fixed paraffin-embedded (FFPE) tissue sections and tissue microarrays (TMA) consisting of eight EC patients with lymph node metastasis (LNM) and twenty without LNM. By doing so, several putative N-linked glycan compositions were detected that could significantly distinguish normal from cancerous endometrium. Furthermore, a complex core-fucosylated N-linked glycan was detected that could discriminate a primary tumour with and without LNM. Structural identification of these putative N-linked glycans was performed using porous graphitized carbon liquid chromatography tandem mass spectrometry (PGC-LC-MS/MS). Overall, we observed higher abundance of oligomannose glycans in tumour compared to normal regions with AUC ranging from 0.85-0.99, and lower abundance of complex N-linked glycans with AUC ranges from 0.03-0.28. A comparison of N-linked glycans between primary tumours with and without LNM indicated a reduced abundance of a complex core-fucosylated N-glycan (Hex)₂(HexNAc)₂(Deoxyhexose)₁+(Man)₃(GlcNAc)₂, in primary tumour with associated lymph node metastasis. In summary, N-linked glycan MALDI MSI can be used to differentiate cancerous endometrium from normal, and endometrial cancer with LNM from endometrial cancer without.

MALDI-MSI-A Step Forward in Overcoming the Diagnostic Challenges in Ovarian Tumors

This study presents the use of matrix-assisted laser desorption and ionization mass spectrometry imaging (MALDI-MSI) directly on the tissue of two ovarian tumors that often present a diagnostic challenge, a low-grade serous borderline ovarian tumor and ovarian fibrothecoma. Different spatial distribution of m/z values within the tissue samples was observed, and regiospecific peaks were identified. Among the 106 peaks in the borderline ovarian tumor five, regiospecific peaks (m/z: 2861.35; 2775.79; 3368.34; 3438.43; 4936.37) were selected using FlexImaging software. Subsequently, the distribution of those selected peaks was visualized on the fibrothecoma tissue section, which demonstrated the differences in the tissue homo-/heterogeneous structure of both tumors. The comparison with the histopathological staining of the ovarian borderline tumor tissue section, obtained during serial sectioning, showed a close correlation of the molecular map with the morphological and histopathological features of the tissue and allowed the identification of different tissue types within the sample. This study highlights the potential significance of MSI in enabling morphological characterization of ovarian tumors as well as correct diagnosis and further prognosis than thus far seen in the literature. Osteopontin, tropomyosin and orosomucoid are only a couple of the molecules investigated using MALDI-MSI in ovarian cancer research. This study, in line with the available literature, proves the potential of MALDI-MSI to overcome the current limitations of classic histopathological examination giving a more in-depth insight into the tissue structure and thus lead to the more accurate differential diagnosis of ovarian tumors, especially in the most challenging cases.

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.

N-Glycome changes reflecting resistance to platinum-based chemotherapy in ovarian cancer

A number of studies have reported aberrant glycosylation in connection with malignancy. Our investigation further expands on this topic through the examination of N-glycans, which could be associated with the resistance of advanced stage, high-grade non-mucinous ovarian cancer to platinum/taxane based chemotherapy. We used tissue samples of 83 ovarian cancer patients, randomly divided into two independent cohorts (basic and validation). Both groups involved either cases with/without postoperative tumor residue or the cases determined either resistant or sensitive to this chemotherapy. In the validation cohort, preoperative serum samples were also available. N-glycans released from tumors and sera were permethylated and analyzed by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The MS analysis yielded a consecutive detection of 68 (tissue) and 63 (serum) N-glycan spectral signals. Eight of these were found to be differentially abundant in tissues of both independent cohorts including the cases with a postoperative cancer residue. One of these glycans was detected as differentially abundant in sera of the validation cohort. No statistically significant differences in intensities due to the same N-glycans were found in the cases without postoperative macroscopic residues in either the basic or validation cohort. From the biochemical point of view, the statistically significant N-glycans correspond to the structures carrying bisecting (terminal) GlcNAc residue and tetra-antennary structures with sialic acid and/or fucose residues. Among them, six tissue N-glycans could be considered potential markers connected with a resistance to chemotherapy in ovarian cancer patients. The prediction of primary resistance to standard chemotherapy may identify the group of patients suitable for alternative treatment strategies. SIGNIFICANCE: Drug resistance has become a major impediment to a successful treatment of patients with advanced ovarian cancer. The glycomic measurements related to cancer are becoming increasingly popular in identification of the key molecules as potential diagnostic and prognostic indicators. Our report deals with identification of differences in N-glycosylation of proteins in tissue and serum samples from the individuals showing sensitivity or resistance to platinum/taxane-based chemotherapy. The detection sensitivity to chemotherapy is vitally important for these patients.

Artificial Intelligence to Decode Cancer Mechanism: Beyond Patient Stratification for Precision Oncology

The multitude of multi-omics data generated cost-effectively using advanced high-throughput technologies has imposed challenging domain for research in Artificial Intelligence (AI). Data curation poses a significant challenge as different parameters, instruments, and sample preparations approaches are employed for generating these big data sets. AI could reduce the fuzziness and randomness in data handling and build a platform for the data ecosystem, and thus serve as the primary choice for data mining and big data analysis to make informed decisions. However, AI implication remains intricate for researchers/clinicians lacking specific training in computational tools and informatics. Cancer is a major cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018. Certain cancers, such as pancreatic and gastric cancers, are detected only after they have reached their advanced stages with frequent relapses. Cancer is one of the most complex diseases affecting a range of organs with diverse disease progression mechanisms and the effectors ranging from gene-epigenetics to a wide array of metabolites. Hence a comprehensive study, including genomics, epi-genomics, transcriptomics, proteomics, and metabolomics, along with the medical/mass-spectrometry imaging, patient clinical history, treatments provided, genetics, and disease endemicity, is essential. Cancer Moonshot℠ Research Initiatives by NIH National Cancer Institute aims to collect as much information as possible from different regions of the world and make a cancer data repository. AI could play an immense role in (a) analysis of complex and heterogeneous data sets (multi-omics and/or inter-omics), (b) data integration to provide a holistic disease molecular mechanism, (c) identification of diagnostic and prognostic markers, and (d) monitor patient's response to drugs/treatments and recovery. AI enables precision disease management well beyond the prevalent disease stratification patterns, such as differential expression and supervised classification. This review highlights critical advances and challenges in omics data analysis, dealing with data variability from lab-to-lab, and data integration. We also describe methods used in data mining and AI methods to obtain robust results for precision medicine from "big" data. In the future, AI could be expanded to achieve ground-breaking progress in disease management.

Aberrant sialylation in ovarian cancers

Sialylation (the covalent addition of sialic acid to the terminal end of glycoproteins or glycans), tightly regulated cell- and microenvironment-specific process and orchestrated by sialyltransferases and sialidases (neuraminidases) family, is one of the posttranslational modifications, which plays an important biological role in the maintenance of normal physiology and involves many pathological dysfunctions. Glycans have roles in all the cancer hallmarks, referring to capabilities acquired during all steps of cancer development to initiate malignant transformation (a driver of a malignant genotype), enable cancer cells to survive, proliferate, and metastasize (a consequence of a malignant phenotype), which includes sustaining proliferative signaling, evading growth suppressor, resisting cell apoptosis, enabling replicative immortality, inducing angiogenesis, reprogramming of energy metabolism, evading tumor destruction, accumulating inflammatory microenvironment, and activating invasion and accelerating metastases. Regarding the important role of altered sialylation of cancers, further knowledge about the initiation and the consequences of altered sialylation pattern in tumor cells is needed, because all may offer a better chance for developing novel therapeutic strategy. In this review, we would like to update alteration of sialylation in ovarian cancers.

Mass spectrometry imaging to detect lipid biomarkers and disease signatures in cancer

BACKGROUND

Current methods to identify, classify, and predict tumor behavior mostly rely on histology, immunohistochemistry, and molecular determinants. However, better predictive markers are required for tumor diagnosis and evaluation. Due, in part, to recent technological advancements, metabolomics and lipid biomarkers have become a promising area in cancer research. Therefore, there is a necessity for novel and complementary techniques to identify and visualize these molecular markers within tumors and surrounding tissue.

RECENT FINDINGS

Since its introduction, mass spectrometry imaging (MSI) has proven to be a powerful tool for mapping analytes in biological tissues. By adding the label-free specificity of mass spectrometry to the detailed spatial information of traditional histology, hundreds of lipids can be imaged simultaneously within a tumor. MSI provides highly detailed lipid maps for comparing intra-tumor, tumor margin, and healthy regions to identify biomarkers, patterns of disease, and potential therapeutic targets. In this manuscript, recent advancement in sample preparation and MSI technologies are discussed with special emphasis on cancer lipid research to identify tumor biomarkers.

CONCLUSION

MSI offers a unique approach for biomolecular characterization of tumor tissues and provides valuable complementary information to histology for lipid biomarker discovery and tumor classification in clinical and research cancer applications.