Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics

Deciphering glycosylation-driven prognostic insights and therapeutic prospects in glioblastoma through a comprehensive regulatory model

The oncogenesis and development of glioblastoma multiforme have been linked to glycosylation modifications, which are common post-translational protein modifications. Abnormal glycosyltransferase development leads to irregular glycosylation patterns, which hold clinical significance for GB prognosis. By utilizing both single-cell and bulk data, we developed a scoring system to assess glycosylation levels in GB. Moreover, a glycosylation-based signature was created to predict GB outcomes and therapy responsiveness. The study led to the development of an glyco-model incorporating nine key genes. This risk assessment tool effectively stratified GB patients into two distinct groups. Extensive validation through ROC analysis, RMST, and Kaplan-Meier (KM) survival analysis emphasized the model's robust predictive capabilities. Additionally, a nomogram was constructed to predict survival rates at specific time intervals. The research revealed substantial disparities in immune cell infiltration between low-risk and high-risk groups, characterized by differences in immune cell abundance and elevated immune scores. Notably, the glyco-model predicted diverse responses to immune checkpoint inhibitors and drug therapies, with high-risk groups exhibiting a preference for immune checkpoint inhibitors and demonstrated superior responses to drug treatments. Furthermore, the study identified two potential drug targets and utilized Connectivity Map analysis to pinpoint promising therapeutic agents. Clofarabine and YM155 were identified as potent candidates for the treatment of high-risk GB. Our well-crafted glyco-model effectively discriminates patients by calculating the risk score, accurately predicting GB outcomes, and significantly enhancing prognostic assessment while identifying novel immunotherapeutic and chemotherapeutic strategies for GB treatment.

Tumor-associated carbohydrate antigens of MUC1 - Implication in cancer development

Glycosylation of cancerous epithelial MUC1 protein is specifically altered in comparison to that which is presented by healthy cells. One of such changes is appearing tumor-associated carbohydrate antigens (TACAs) which are rare in normal tissues and are highly correlated with poor clinical outcomes and cancer progression. This review summarizes and describes the role of Tn, T antigens, their sialylated forms as well as fucosylated Lewis epitopes in different aspects of tumor development, progression, and metastasis. Finally, applications of MUC1 glycan epitopes as potential targets for therapeutic strategy of cancers are notified. One of the novelties of this review is presentation of TACAs as inherently connected with MUC1 mucin.

Integrating the analysis of human biopsies using post-translational modifications proteomics

Proteome diversities and their biological functions are significantly amplified by post-translational modifications (PTMs) of proteins. Shotgun proteomics, which does not typically survey PTMs, provides an incomplete picture of the complexity of human biopsies in health and disease. Recent advances in mass spectrometry-based proteomic techniques that enrich and study PTMs are helping to uncover molecular detail from the cellular level to system-wide functions, including how the microbiome impacts human diseases. Protein heterogeneity and disease complexity are challenging factors that make it difficult to characterize and treat disease. The search for clinical biomarkers to characterize disease mechanisms and complexity related to patient diagnoses and treatment has proven challenging. Knowledge of PTMs is fundamentally lacking. Characterization of complex human samples that clarify the role of PTMs and the microbiome in human diseases will result in new discoveries. This review highlights the key role of proteomic techniques used to characterize unknown biological functions of PTMs derived from complex human biopsies. Through the integration of diverse methods used to profile PTMs, this review explores the genetic regulation of proteoforms, cells of origin expressing specific proteins, and several bioactive PTMs and their subsequent analyses by liquid chromatography and tandem mass spectrometry.

Decoding the glycoproteome: a new frontier for biomarker discovery in cancer

Cancer early detection and treatment response prediction continue to pose significant challenges. Cancer liquid biopsies focusing on detecting circulating tumor cells (CTCs) and DNA (ctDNA) have shown enormous potential due to their non-invasive nature and the implications in precision cancer management. Recently, liquid biopsy has been further expanded to profile glycoproteins, which are the products of post-translational modifications of proteins and play key roles in both normal and pathological processes, including cancers. The advancements in chemical and mass spectrometry-based technologies and artificial intelligence-based platforms have enabled extensive studies of cancer and organ-specific changes in glycans and glycoproteins through glycomics and glycoproteomics. Glycoproteomic analysis has emerged as a promising tool for biomarker discovery and development in early detection of cancers and prediction of treatment efficacy including response to immunotherapies. These biomarkers could play a crucial role in aiding in early intervention and personalized therapy decisions. In this review, we summarize the significant advance in cancer glycoproteomic biomarker studies and the promise and challenges in integration into clinical practice to improve cancer patient care.

Profiling of aberrant sialylated N-glycans in hepatocellular carcinoma by liquid chromatography mass spectrometry

BACKGROUND

Aberrant sialylation is closely associated with the tumorigenesis, progression, and metastasis, and may be of importance for disease diagnosis. However, the analysis of altered expression of sialylated glycans (SGs) in blood is particularly challenging due to the low content and poor ionization efficiency of sialylated glycans in mass spectrometry.

METHODS

An analytical strategy based on enrichment of SGs, liquid chromatography-high resolution mass spectrometric detection, and automatic glycan annotation was developed to profile the sialylated N-glycome in serum. The enrichment of sialylated glycans was accomplished using cationic cotton via electrostatic and hydrogen interaction. Using partial least squares-discriminant analysis (PLS-DA), the approach was applied for nontarget screening and profiling of aberrant sialylated N-glycans in hepatocellular carcinoma (HCC).

RESULTS

55 SGs were identified in human serum, and three important SGs (SG35, SG45, and SG46) were screened to have good diagnostic specificity for HCC. Their areas under the receiver operating characteristic (ROC) curve (AUC) were higher than α-fetoprotein (AFP)'s (AUC = 0.85), at 0.88, 0.87, and 0.91, respectively. When three SGs are combined, the diagnostic specificity for HCC may increase to 94 %. The fact that SGs biomarkers are sensitive to AFP-Negative HCC is very noteworthy.

CONCLUSIONS

The method significantly advanced the search for sialylated glycan-based cancer biomarkers. In comparison to traditional indicators like AFP and imaging tools, SGs showed a higher diagnostic sensitivity for HCC.

Robust Glycoproteomics Platform Reveals a Tetra-Antennary Site-Specific Glycan Capping with Sialyl-Lewis Antigen for Early Detection of Gastric Cancer

The lack of efficient biomarkers for the early detection of gastric cancer (GC) contributes to its high mortality rate, so it is crucial to discover novel diagnostic targets for GC. Recent studies have implicated the potential of site-specific glycans in cancer diagnosis, yet it is challenging to perform highly reproducible and sensitive glycoproteomics analysis on large cohorts of samples. Here, a highly robust N-glycoproteomics (HRN) platform comprising an automated enrichment method, a stable microflow LC-MS/MS system, and a sensitive glycopeptide-spectra-deciphering tool is developed for large-scale quantitative N-glycoproteome analysis. The HRN platform is applied to analyze serum N-glycoproteomes of 278 subjects from three cohorts to investigate glycosylation changes of GC. It identifies over 20 000 unique site-specific glycans from discovery and validation cohorts, and determines four site-specific glycans as biomarker candidates. One candidate has branched tetra-antennary structure capping with sialyl-Lewis antigen, and it significantly outperforms serum CEA with AUC values > 0.89 compared against < 0.67 for diagnosing early-stage GC. The four-marker panel can provide improved diagnostic performances. Besides, discrimination powers of four candidates are also testified with a verification cohort using PRM strategy. This findings highlight the value of this strong tool in analyzing aberrant site-specific glycans for cancer detection.

Probing Blood Plasma Protein Glycosylation with Infrared Spectroscopy

The health state of an individual is closely linked to the glycosylation patterns of his or her blood plasma proteins. However, obtaining this information requires cost- and time-efficient analytical methods. We put forward infrared spectroscopy, which allows label-free analysis of protein glycosylation but so far has only been applied to analysis of individual proteins. Although spectral information does not directly provide the molecular structure of the glycans, it is sensitive to changes therein and covers all types of glycosidic linkages. Combining single-step ion exchange chromatography with infrared spectroscopy, we developed a workflow that enables the separation and analysis of major protein classes in blood plasma. Our results demonstrate that infrared spectroscopy can identify different patterns and global levels of glycosylation of intact plasma proteins. To showcase the strengths and limitations of the proposed approach, we compare the glycoforms of human and bovine alpha-1-acid glycoproteins, which exhibit highly variable global levels of glycosylation. To independently evaluate our conclusions, the glycan moieties of human alpha-1-acid glycoprotein were further analyzed using an established glycomics workflow. Importantly, the chromatographic separation of blood plasma improves the detection of aberrant glycoforms of a given protein as compared to infrared spectroscopy of bulk plasma. The presented approach allows a time-efficient comparison of glycosylation patterns of multiple plasma proteins, opening new avenues for biomedical probing.

CA19-9 and CEA biosensors in pancreatic cancer

Cancer is a complex pathophysiological condition causing millions of deaths each year. Early diagnosis is essential especially for pancreatic cancer. Existing diagnostic tools rely on circulating biomarkers such as Carbohydrate Antigen 19-9 (CA19-9) and Carcinoembryonic Antigen (CEA). Unfortunately, these markers are nonspecific and may be increased in a variety of disorders. Accordingly, diagnosis of pancreatic cancer generally involves more invasive approaches such as biopsy as well as imaging studies. Recent advances in biosensor technology have allowed the development of precise diagnostic tools having enhanced analytical sensitivity and specificity. Herein we examine these advances in the detection of cancer in general and in pancreatic cancer specifically. Furthermore, we highlight novel technologies in the measurement of CA19-9 and CEA and explore their future application in the early detection of pancreatic cancer.

Interdigitated impedimetric-based Maackia amurensis lectin biosensor for prostate cancer biomarker

Highly specific detection of tumor-associated biomarkers remains a challenge in the diagnosis of prostate cancer. In this research, Maackia amurensis (MAA) was used as a recognition element in the functionalization of an electrochemical impedance-spectroscopy biosensor without a label to identify cancer-associated aberrant glycosylation prostate-specific antigen (PSA). The lectin was immobilized on gold-interdigitated microelectrodes. Furthermore, the biosensor's impedance response was used to assess the establishment of a complex binding between MAA and PSA-containing glycans. With a small sample volume, the functionalized interdigitated impedimetric-based (IIB) biosensor exhibited high sensitivity, rapid response, and repeatability. PSA glycoprotein detection was performed by measuring electron transfer resistance values within a concentration range 0.01-100 ng/mL, with a detection limit of 3.574 pg/mL. In this study, the ability of MAA to preferentially recognize α2,3-linked sialic acid in serum PSA was proven, suggesting a potential platform for the development of lectin-based, miniaturized, and cost effective IIB biosensors for future disease detection.

Development of a predictive model to distinguish prostate cancer from benign prostatic hyperplasia by integrating serum glycoproteomics and clinical variables

BACKGROUND

Prostate Cancer (PCa) represents the second leading cause of cancer-related death in men. Prostate-specific antigen (PSA) serum testing, currently used for PCa screening, lacks the necessary sensitivity and specificity. New non-invasive diagnostic tools able to discriminate tumoral from benign conditions and aggressive (AG-PCa) from indolent forms of PCa (NAG-PCa) are required to avoid unnecessary biopsies.

METHODS

In this work, 32 formerly N-glycosylated peptides were quantified by PRM (parallel reaction monitoring) in 163 serum samples (79 from PCa patients and 84 from individuals affected by benign prostatic hyperplasia (BPH)) in two technical replicates. These potential biomarker candidates were prioritized through a multi-stage biomarker discovery pipeline articulated in: discovery, LC-PRM assay development and verification phases. Because of the well-established involvement of glycoproteins in cancer development and progression, the proteomic analysis was focused on glycoproteins enriched by TiO2 (titanium dioxide) strategy.

RESULTS

Machine learning algorithms have been applied to the combined matrix comprising proteomic and clinical variables, resulting in a predictive model based on six proteomic variables (RNASE1, LAMP2, LUM, MASP1, NCAM1, GPLD1) and five clinical variables (prostate dimension, proPSA, free-PSA, total-PSA, free/total-PSA) able to distinguish PCa from BPH with an area under the Receiver Operating Characteristic (ROC) curve of 0.93. This model outperformed PSA alone which, on the same sample set, was able to discriminate PCa from BPH with an AUC of 0.79. To improve the clinical managing of PCa patients, an explorative small-scale analysis (79 samples) aimed at distinguishing AG-PCa from NAG-PCa was conducted. A predictor of PCa aggressiveness based on the combination of 7 proteomic variables (FCN3, LGALS3BP, AZU1, C6, LAMB1, CHL1, POSTN) and proPSA was developed (AUC of 0.69).

CONCLUSIONS

To address the impelling need of more sensitive and specific serum diagnostic tests, a predictive model combining proteomic and clinical variables was developed. A preliminary evaluation to build a new tool able to discriminate aggressive presentations of PCa from tumors with benign behavior was exploited. This predictor displayed moderate performances, but no conclusions can be drawn due to the limited number of the sample cohort. Data are available via ProteomeXchange with identifier PXD035935.

Development of lectin-based lateral flow assay for fucosylated alpha-fetoprotein

Fucosylated alpha-fetoprotein (AFP-L3) is a more specific and sensitive biomarker for early diagnosis of hepatocellular carcinoma (HCC) than only the alpha-fetoprotein (AFP) level. Rapid and simple detection of AFP-L3 level greatly facilitates the early detection as well as the treatment of HCC, resulting in the reduction of mortality. Here, we developed a rapid and sensitive lateral flow assay (LFA) using lectin Lens culinaris agglutinin (LCA), which has a specific affinity to AFP-L3 fraction of AFP, as a biorecognition element for determination of the fucosylation of AFP. The assay is based on a sandwich format performed on a lateral flow test strip. LCA was immobilized on the membrane as a test line (T). Quantitative detection of AFP-L3 was achieved by measuring the green color intensity of captured gold nanoparticle conjugates on the T and control line (C) utilizing an in-house test strip reader. The calculated absorbance obtained by the green color intensity signals proportionally increased with AFP concentrations. The developed lectin-based LFA provided a detection limit of 0.8 ng/mL for AFP with a linear range between 1.5 and 160.0 ng/mL within an assay time of 10 min. Recoveries between 74.5% and 113.2% with relative standard deviations of 5.2%-8.7% for measuring spiked human serum were also achieved. The results reveal that the proposed assay offers a rapid, sensitive, and specific method, which is useful for development in point-of-care testing for early detection and treatment of HCC.

Lectins as potential tools for cancer biomarker discovery from extracellular vesicles

Extracellular vesicles (EVs) have considerable potential as diagnostic, prognostic, and therapeutic agents, in large part because molecular patterns on the EV surface betray the cell of origin and may also be used to "target" EVs to specific cells. Cancer is associated with alterations to cellular and EV glycosylation patterns, and the surface of EVs is enriched with glycan moieties. Glycoconjugates of EVs play versatile roles in cancer including modulating immune response, affecting tumor cell behavior and site of metastasis and as such, paving the way for the development of innovative diagnostic tools and novel therapies. Entities that recognize specific glycans, such as lectins, may thus be powerful tools to discover and detect novel cancer biomarkers. Indeed, the past decade has seen a constant increase in the number of published articles on lectin-based strategies for the detection of EV glycans. This review explores the roles of EV glycosylation in cancer and cancer-related applications. Furthermore, this review summarizes the potential of lectins and lectin-based methods for screening, targeting, separation, and possible identification of improved biomarkers from the surface of EVs.

Tumor Markers and Their Diagnostic Significance in Ovarian Cancer

Ovarian cancer (OC) is characterized by silent progression and late-stage diagnosis. It is critical to detect and accurately diagnose the disease early to improve survival rates. Tumor markers have emerged as valuable tools in the diagnosis and management of OC, offering non-invasive and cost-effective options for screening, monitoring, and prognosis.

PURPOSE

This paper explores the diagnostic importance of various tumor markers including CA-125, CA15-3, CA 19-9, HE4,hCG, inhibin, AFP, and LDH, and their impact on disease monitoring and treatment response assessment.

METHODS

Article searches were performed on PubMed, Scopus, and Google Scholar. Keywords used for the searching process were "Ovarian cancer", "Cancer biomarkers", "Early detection", "Cancer diagnosis", "CA-125","CA 15-3","CA 19-9", "HE4","hCG", "inhibin", "AFP", "LDH", and others.

RESULTS

HE4, when combined with CA-125, shows improved sensitivity and specificity, particularly in early-stage detection. Additionally, hCG holds promise as a prognostic marker, aiding treatment response prediction and outcome assessment. Novel markers like microRNAs, DNA methylation patterns, and circulating tumor cells offer potential for enhanced diagnostic accuracy and personalized management. Integrating these markers into a comprehensive panel may improve sensitivity and specificity in ovarian cancer diagnosis. However, careful interpretation of tumor marker results is necessary, considering factors such as age, menopausal status, and comorbidities. Further research is needed to validate and refine diagnostic algorithms, optimizing the clinical significance of tumor markers in ovarian cancer management. In conclusion, tumor markers such as CA-125, CA15-3, CA 19-9, HE4, and hCG provide valuable insights into ovarian cancer diagnosis, monitoring, and prognosis, with the potential to enhance early detection.

Capitalizing glycomic changes for improved biomarker-based cancer diagnostics

Cancer serum biomarkers are valuable or even indispensable for cancer diagnostics and/or monitoring and, currently, many cancer serum markers are routinely used in the clinic. Most of those markers are glycoproteins, carrying cancer-specific glycan structures that can provide extra-information for cancer monitoring. Nonetheless, in the majority of cases, this differential feature is not exploited and the corresponding analytical assays detect only the protein amount, disregarding the analysis of the aberrant glycoform. Two exceptions to this trend are the biomarkers α-fetoprotein (AFP) and cancer antigen 19-9 (CA19-9), which are clinically monitored for their cancer-related glycan changes, and only the AFP assay includes quantification of both the protein amount and the altered glycoform. This narrative review demonstrates, through several examples, the advantages of the combined quantification of protein cancer biomarkers and the respective glycoform analysis, which enable to yield the maximum information and overcome the weaknesses of each individual analysis. This strategy allows to achieve higher sensitivity and specificity in the detection of cancer, enhancing the diagnostic power of biomarker-based cancer detection tests.

N-glycolylneuraminic acid as a carbohydrate cancer biomarker

One of the forms of aberrant glycosylation in human tumors is the expression of N-glycolylneuraminic acid (Neu5Gc). The only known enzyme to biosynthesize Neu5Gc in mammals, cytidine-5'-monophosphate-N-acetylneuraminic acid (CMAH), appears to be genetically inactivated in humans. Regardless, low levels of Neu5Gc have been detected in healthy humans. Therefore, it is proposed that the presence of Neu5Gc in humans is from dietary acquisition, such as red meat. Notably, detection of elevated Neu5Gc levels has been repeatedly found in cancer tissues, cells and serum samples, thereby Neu5Gc-containing antigens may be exploited as a class of cancer biomarkers. Here we review the findings to date on using Neu5Gc-containing tumor glycoconjugates as a class of cancer biomarkers for cancer detection, surveillance, prognosis and therapeutic targets. We review the evidence that supports an emerging hypothesis of de novo Neu5Gc biosynthesis in human cancer cells as a source of Neu5Gc in human tumors, generated under certain metabolic conditions.

Molecular genetics of early-onset colorectal cancer

Early-onset colorectal cancer (EOCRC) has been rising in global prevalence and incidence over the past several decades. Environmental influences, including generational lifestyle changes and rising obesity, contribute to these increased rates. While the rise in EOCRC is best documented in western countries, it is seen throughout the world, although EOCRC may have distinct genetic mutations in patients of different ethnic backgrounds. Pathological and molecular characterizations show that EOCRC has a distinct presentation compared with later-onset colorectal cancer (LOCRC). Recent studies have identified DNA, RNA, and protein-level alterations unique to EOCRC, revealing much-needed biomarkers and potential novel therapeutic targets. Many molecular EOCRC studies have been performed with Caucasian and Asian EOCRC cohorts, however, studies of other ethnic backgrounds are limited. In addition, certain molecular characterizations that have been conducted for LOCRC have not yet been repeated in EOCRC, including high-throughput analyses of histone modifications, mRNA splicing, and proteomics on large cohorts. We propose that the complex relationship between cancer and aging should be considered when studying the molecular underpinnings of EOCRC. In this review, we summarize current EOCRC literature, focusing on sporadic molecular alterations in tumors, and their clinical implications. We conclude by discussing current challenges and future directions of EOCRC research efforts.

Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples

Alterations of protein glycosylation can serve as sensitive and specific disease biomarkers. Labeling procedures for improved separation and detectability of oligosaccharides have several drawbacks, including incomplete derivatization, side-products, noticeable desialylation/defucosylation, sample loss, and interference with downstream analyses. Here, we develop a label-free workflow based on high sensitivity capillary zone electrophoresis-mass spectrometry (CZE-MS) for profiling of native underivatized released N-glycans. Our workflow provides a >45-fold increase in signal intensity compared to the conventional CZE-MS approaches used for N-glycan analysis. Qualitative and quantitative N-glycan profiling of purified human serum IgG, bovine serum fetuin, bovine pancreas ribonuclease B, blood-derived extracellular vesicle isolates, and total plasma results in the detection of >250, >400, >150, >310, and >520 N-glycans, respectively, using injected amounts equivalent to <25 ng of model protein and nL-levels of plasma-derived samples. Compared to reported results for biological samples of similar amounts and complexity, the number of identified N-glycans is increased up to ~15-fold, enabling highly sensitive analysis of sample amounts as low as sub-0.2 nL of plasma volume equivalents. Furthermore, highly sialylated N-glycans are identified and structurally characterized, and untreated sialic acid-linkage isomers are resolved in a single CZE-MS analysis.

The hidden potential of glycomarkers: Glycosylation studies in the service of cancer diagnosis and treatment

Changes in the glycosylation process appear early in carcinogenesis and evolve with the growth and spread of cancer. The correlation of the characteristic glycosylation signature with the tumor stage and the appropriate therapy choice is an important issue in translational medicine. Oncologists also pay attention to extracellular vesicles as reservoirs of new cancer glycomarkers that can be potent for cancer diagnosis/prognosis. In this review, we recall glycomarkers used in oncology and show their new glycoforms of improved clinical relevance. We summarize current knowledge on the biological functions of glycoepitopes in cancer-derived extracellular vesicles and their potential use in clinical practice. Is glycomics a future of cancer diagnosis? It may be, but in combination with other omics analyses than alone.

In-depth investigation of altered glycosylation in human haptoglobin associated cancer by mass spectrometry

Serum haptoglobin (Hp), a highly sialylated biomolecule with four N-glycosylation sites, is a positive acute-phase response glycoprotein that acts as an immunomodulator. Hp has gained considerable attention due to its potential as a signature molecule that exhibits aberrant glycosylation in inflammatory disorders and malignancies. Its glycosylation can be analyzed qualitatively and quantitatively by various methods using mass spectrometry. In this review, we have provided a brief overview of Hp structure and biological function and described mass spectrometry-based techniques for analyzing glycosylation ranging from macroheterogeneity to microheterogeneity of Hp in diseases and cancer. The sugars on haptoglobin can be a sweet bridge to link the potential of cancer-specific biomarkers to clinically relevant applications.

Systematic characterization of extracellular glycoproteins using mass spectrometry

Surface and secreted glycoproteins are essential to cells and regulate many extracellular events. Because of the diversity of glycans, the low abundance of many glycoproteins, and the complexity of biological samples, a system-wide investigation of extracellular glycoproteins is a daunting task. With the development of modern mass spectrometry (MS)-based proteomics, comprehensive analysis of different protein modifications including glycosylation has advanced dramatically. This review focuses on the investigation of extracellular glycoproteins using MS-based proteomics. We first discuss the methods for selectively enriching surface glycoproteins and investigating protein interactions on the cell surface, followed by the application of MS-based proteomics for surface glycoprotein dynamics analysis and biomarker discovery. We then summarize the methods to comprehensively study secreted glycoproteins by integrating various enrichment approaches with MS-based proteomics and their applications for global analysis of secreted glycoproteins in different biological samples. Collectively, MS significantly expands our knowledge of extracellular glycoproteins and enables us to identify extracellular glycoproteins as potential biomarkers for disease detection and drug targets for disease treatment.

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.

Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy

BACKGROUND

Gliomas are the most common brain tumours with the high-grade glioblastoma representing the most aggressive and lethal form. Currently, there is a lack of specific glioma biomarkers that would aid tumour subtyping and minimally invasive early diagnosis. Aberrant glycosylation is an important post-translational modification in cancer and is implicated in glioma progression. Raman spectroscopy (RS), a vibrational spectroscopic label-free technique, has already shown promise in cancer diagnostics.

METHODS

RS was combined with machine learning to discriminate glioma grades. Raman spectral signatures of glycosylation patterns were used in serum samples and fixed tissue biopsy samples, as well as in single cells and spheroids.

RESULTS

Glioma grades in fixed tissue patient samples and serum were discriminated with high accuracy. Discrimination between higher malignant glioma grades (III and IV) was achieved with high accuracy in tissue, serum, and cellular models using single cells and spheroids. Biomolecular changes were assigned to alterations in glycosylation corroborated by analysing glycan standards and other changes such as carotenoid antioxidant content.

CONCLUSION

RS combined with machine learning could pave the way for more objective and less invasive grading of glioma patients, serving as a useful tool to facilitate glioma diagnosis and delineate biomolecular glioma progression changes.

Targeting galectin-driven regulatory circuits in cancer and fibrosis

Galectins are a family of endogenous glycan-binding proteins that have crucial roles in a broad range of physiological and pathological processes. As a group, these proteins use both extracellular and intracellular mechanisms as well as glycan-dependent and independent pathways to reprogramme the fate and function of numerous cell types. Given their multifunctional roles in both tissue fibrosis and cancer, galectins have been identified as potential therapeutic targets for these disorders. Here, we focus on the therapeutic relevance of galectins, particularly galectin 1 (GAL1), GAL3 and GAL9 to tumour progression and fibrotic diseases. We consider an array of galectin-targeted strategies, including small-molecule carbohydrate inhibitors, natural polysaccharides and their derivatives, peptides, peptidomimetics and biological agents (notably, neutralizing monoclonal antibodies and truncated galectins) and discuss their mechanisms of action, selectivity and therapeutic potential in preclinical models of fibrosis and cancer. We also review the results of clinical trials that aim to evaluate the efficacy of galectin inhibitors in patients with idiopathic pulmonary fibrosis, nonalcoholic steatohepatitis and cancer. The rapid pace of glycobiology research, combined with the acute need for drugs to alleviate fibrotic inflammation and overcome resistance to anticancer therapies, will accelerate the translation of anti-galectin therapeutics into clinical practice.

Beyond glyco-proteomics-Understanding the role of genetics in cancer biomarkers

The development of robust cancer biomarkers is the most effective way to improve overall survival, as early detection and treatment leads to significantly better clinical outcomes. Many of the cancer biomarkers that have been identified and are clinically utilized are glycoproteins, oftentimes a specific glycoform. Aberrant glycosylation is a common theme in cancer, with dysregulated glycosylation driving tumor initiation and metastasis, and abnormal glycosylation can be detection both on the tissue surface and in serum. However, most cancer types are heterogeneous in regard to tumor genomics, and this heterogeneity extends to cancer glycomics. This limits the sensitivity of standalone glycan-based biomarkers, which has slowed their implementation clinically. However, if targeted biomarker development can take into account genomic tumor information, the development of complementary biomarkers that target unique cancer subgroups can be accomplished. This idea suggests the need for algorithm-based cancer biomarkers, which can utilize multiple biomarkers along with relevant demographic information. This concept has already been established in the detection of hepatocellular carcinoma with the GALAD score, and an algorithm-based approach would likely be effective in improving biomarker sensitivity for additional cancer types. In order to increase cancer diagnostic biomarker sensitivity, there must be more targeted biomarker development that considers tumor genomic, proteomic, metabolomic, and clinical data while identifying tumor biomarkers.

Current and emerging biomarkers in ovarian cancer diagnosis; CA125 and beyond

Ovarian cancer (OC) is one of the most common causes of cancer-related death in women worldwide. Its five-year survival rates are worse than the two most common gynecological cancers, cervical and endometrial. This is because it is asymptomatic in the early stages and usually detected in the advanced metastasized stage. Thus, survival is increasingly dependent on timely diagnosis. The delay in detection is contributed partly by the occurrence of non-specific clinical symptoms in the early stages and the lack of effective biomarkers and detection approaches. This underlines the need for biomarker identification and clinical validation, enabling earlier diagnosis, effective prognosis, and response to therapy. Apart from the traditional diagnostic biomarkers for OC, several new biomarkers have been delineated using advanced high-throughput molecular approaches in recent years. They are currently being clinically evaluated for their true diagnostic potential. In this chapter, we document the commonly utilized traditional screening markers and recently identified emerging biomarkers in OC diagnosis, focusing on secretory and protein biomarkers. We also briefly reviewed the recent advances and prospects in OC diagnosis.

Aberrant N-glycosylation in cancer: MGAT5 and β1,6-GlcNAc branched N-glycans as critical regulators of tumor development and progression

BACKGROUND

Changes in protein glycosylation are widely observed in tumor cells. N-glycan branching through adding β1,6-linked N-acetylglucosamine (β1,6-GlcNAc) to an α1,6-linked mannose, which is catalyzed by the N-acetylglucosaminyltransferase V (MGAT5 or GnT-V), is one of the most frequently observed tumor-associated glycan structure formed. Increased levels of this branching structure play a pro-tumoral role in various ways, for example, through the stabilization of growth factor receptors, the destabilization of intercellular adhesion, or the acquisition of a migratory phenotype.

CONCLUSION

In this review, we provide an updated and comprehensive summary of the physiological and pathophysiological roles of MGAT5 and β1,6-GlcNAc branched N-glycans, including their regulatory mechanisms. Specific emphasis is given to the role of MGAT5 and β1,6-GlcNAc branched N-glycans in cellular mechanisms that contribute to the development and progression of solid tumors. We also provide insight into possible future clinical implications, such as the use of MGAT5 as a prognostic biomarker.

Terminal fucosylation of haptoglobin in cancer-derived exosomes during cholangiocarcinoma progression

Background

Cholangiocarcinoma (CCA) is a silent tumor with a high mortality rate due to the difficulty of early diagnosis and prediction of recurrence even after timely surgery. Serologic cancer biomarkers have been used in clinical practice, but their low specificity and sensitivity have been problematic. In this study, we aimed to identify CCA-specific glycan epitopes that can be used for diagnosis and to elucidate the mechanisms by which glycosylation is altered with tumor progression.

Methods

The serum of patients with various cancers was fractioned into membrane-bound and soluble components using serial ultracentrifugation. Lectin blotting was conducted to evaluate glycosylation. Proteins having altered glycosylation were identified using proteomic analysis and further confirmed using immunoblotting analysis. We performed HPLC, gene analysis, real-time cargo tracking, and immunohistochemistry to determine the origin of CCA glycosylation and its underlying mechanisms. Extracellular vesicles (EV) were isolated from the sera of 62 patients with CCA at different clinical stages and inflammatory conditions and used for glycan analysis to assess their clinical significance.

Results

The results reveal that glycosylation patterns between soluble and membrane-bound fractions differ significantly even when obtained from the same donor. Notably, glycans with α1-3/4 fucose and β1-6GlcNAc branched structures increase specifically in membrane-bound fractions of CCA. Mechanically, it is primarily due to β-haptoglobin (β-Hp) originating from CCA expressing fucosyltransferase-3/4 (FUT 3/4) and N-acetylglucosaminyltransferase-V (MGAT5). Newly synthesized β-Hp is loaded into EVs in early endosomes via a KFERQ-like motif and then secreted from CCA cells to induce tumor progression. In contrast, β-Hp expressed by hepatocytes is secreted in a soluble form that does not affect CCA progression. Moreover, evaluation of EV glycosylation in CCA patients shows that fucosylation level of EV-Hp gradually increases with tumor progression and decreases markedly when the tumors are eliminated by surgery.

Conclusion

This study suggests that terminal fucosylation of Hp in cancer-derived exosomes can be a novel glycan marker for diagnosis and prognosis of CCA. These findings highlight the potential of glycan analysis in different fractions of serum for biomarker discover for other diseases. Further research is needed to understand the role of fucosylated EVs on CCA progression.

Glycobiology of cellular expiry: Decrypting the role of glycan-lectin regulatory complex and therapeutic strategies focusing on cancer

Often the outer leaflets of living cells bear a coat of glycosylated proteins, which primarily regulates cellular processes. Glycosylation of such proteins occurs as part of their post-translational modification. Within the endoplasmic reticulum, glycosylation enables the attachment of specific oligosaccharide moieties such as, 'glycan' to the transmembrane receptor proteins which confers precise biological information for governing the cell fate. The nature and degree of glycosylation of cell surface receptors are regulated by a bunch of glycosyl transferases and glycosidases which fine-tune attachment or detachment of glycan moieties. In classical death receptors, upregulation of glycosylation by glycosyl transferases is capable of inducing cell death in T cells, tumor cells, etc. Thus, any deregulated alternation at surface glycosylation of these death receptors can result in life-threatening disorder like cancer. In addition, transmembrane glycoproteins and lectin receptors can transduce intracellular signals for cell death execution. Exogenous interaction of lectins with glycan containing death receptors signals for cell death initiation by modulating downstream signalings. Subsequently, endogenous glycan-lectin interplay aids in the customization and implementation of the cell death program. Lastly, the glycan-lectin recognition system dictates the removal of apoptotic cells by sending accurate signals to the extracellular milieu. Since glycosylation has proven to be a biomarker of cellular death and disease progression; glycans serve as specific therapeutic targets of cancers. In this context, we are reviewing the molecular mechanisms of the glycan-lectin regulatory network as an integral part of cell death machinery in cancer to target them for successful therapeutic and clinical approaches.

Post-Translational Modifications in Tumor-Associated Antigens as a Platform for Novel Immuno-Oncology Therapies

Post-translational modifications (PTMs) are generated by adding small chemical groups to amino acid residues after the translation of proteins. Many PTMs have been reported to correlate with tumor progression, growth, and survival by modifying the normal functions of the protein in tumor cells. PTMs can also elicit humoral and cellular immune responses, making them attractive targets for cancer immunotherapy. This review will discuss how the acetylation, citrullination, and phosphorylation of proteins expressed by tumor cells render the corresponding tumor-associated antigen more antigenic and affect the immune response in multiple cancers. In addition, the role of glycosylated protein mucins in anti-cancer immunotherapy will be considered. Mucin peptides in combination with stimulating adjuvants have, in fact, been utilized to produce anti-tumor antibodies and vaccines. Finally, we will also outline the results of the clinical trial exploiting glycosylated-MUC1 as a vaccine in different cancers. Overall, PTMs in TAAs could be considered in future therapies to result in lasting anti-tumor responses.

Protein Glycosylation as Biomarkers in Gynecologic Cancers

Gynecologic cancers are the leading cause of death in women. Endometrial, ovarian, and cervical cancer are the three main types of gynecologic cancers. Poor prognoses and high mortality rates of advanced-stage cancer are still challenges of all three types. Diagnostic tools for early cancer detection could be the cornerstone for further cancer treatment and prevention. Glycosylation plays a vital role in cell proliferation, adhesion, motility, and angiogenesis, and is aberrantly expressed in cancer cells. Alterations of glycosylation may represent promising biomarkers with potential diagnostic and monitoring applications, as well as disease prognosis. Many glycosylated biomarkers, including glycoprotein, glycan, and enzyme, were discovered and well-studied for application in gynecologic cancers. Some of them have been developed as targets for cancer treatment. The use of certain biomarkers for diagnostics and monitoring of gynecologic cancers has clinical advantages, as it is quantitative, comparable, convenient, and inexpensive. However, one of the single markers have sufficient sensitivity for the screening of gynecologic cancers. In this review, we introduced the details of glycosylation and the current application of glycosylated biomarkers in these three cancers. Moreover, we also reviewed the different roles of each biomarker in other cancers and aimed to understand these glycosylated biomarkers comprehensively.

First bioelectronic immunoplatform for quantitative secretomic analysis of total and metastasis-driven glycosylated haptoglobin

The glycosylation status of proteins is increasingly used as biomarker to improve the reliability in the diagnosis and prognosis of diseases as relevant as cancer. This feeds the need for tools that allow its simple and reliable analysis and are compatible with applicability in the clinic. With this objective in mind, this work reports the first bioelectronic immunoplatforms described to date for the determination of glycosylated haptoglobin (Hp) and the simultaneous determination of total and glycosylated Hp. The bioelectronic immunoplatform is based on the implementation of non-competitive bioassays using two different antibodies or an antibody and a lectin on the surface of commercial magnetic microcarriers. The resulting bioconjugates are labeled with the horseradish peroxidase (HRP) enzyme, and after their magnetic capture on disposable electroplatforms, the amperometric transduction using the H2O2/hydroquinone (HQ) system allows the single or multiple detection. The developed immunoplatform achieves limits of detection (LODs) of 0.07 and 0.46 ng mL−1 for total and glycosylated Hp in buffer solution, respectively. The immunoplatform allows accurate determination using simple and relatively short protocols (approx. 75 min) of total and glycosylated Hp in the secretomes of in vitro–cultured colorectal cancer (CRC) cells with different metastatic potentials, which is not feasible, due to lack of sensitivity, by means of some commercial ELISA kits and Western blot methodology.

Graphical abstract

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.

Alteration of rhesus macaque serum N-glycome during infection with the human parasitic filarial nematode Brugia malayi

Serum N-glycan profiling studies during the past decades have shown robust associations between N-glycan changes and various biological conditions, including infections, in humans. Similar studies are scarcer for other mammals, despite the tremendous potential of serum N-glycans as biomarkers for infectious diseases in animal models of human disease and in the veterinary context. To expand the knowledge of serum N-glycan profiles in important mammalian model systems, in this study, we combined MALDI-TOF-MS analysis and HILIC-UPLC profiling of released N-glycans together with glycosidase treatments to characterize the glycan structures present in rhesus macaque serum. We used this baseline to monitor changes in serum N-glycans during infection with Brugia malayi, a parasitic nematode of humans responsible for lymphatic filariasis, in a longitudinal cohort of infected rhesus macaques. Alterations of the HILIC-UPLC profile, notably of abundant structures, became evident as early as 5 weeks post-infection. Given its prominent role in the immune response, contribution of immunoglobulin G to serum N-glycans was investigated. Finally, comparison with similar N-glycan profiling performed during infection with the dog heartworm Dirofilaria immitis suggests that many changes observed in rhesus macaque serum N-glycans are specific for lymphatic filariasis.

Mass spectrometry imaging spatially identifies complex-type N-glycans as putative cartilage degradation markers in human knee osteoarthritis tissue

N-Glycan alterations contribute to the pathophysiology and progression of various diseases. However, the involvement of N-glycans in knee osteoarthritis (KOA) progression at the tissue level, especially within articular cartilage, is still poorly understood. Thus, the aim of this study was to spatially map and identify KOA-specific N-glycans from formalin-fixed paraffin-embedded (FFPE) osteochondral tissue of the tibial plateau relative to cadaveric control (CTL) tissues. Human FFPE osteochondral tissues from end-stage KOA patients (n=3) and CTL individuals (n=3), aged >55 years old, were analyzed by matrix‐assisted laser desorption/ionization mass spectrometry imaging (MALDI‐MSI) and liquid chromatography–tandem mass spectrometry (LC-MS/MS). Overall, it was revealed that 22 N-glycans were found in the cartilage region of KOA and CTL tissue. Of those, 15 N-glycans were more prominent in KOA cartilage than CTL cartilage. We then compared sub-regions of KOA and CTL tissues based on the Osteoarthritis Research Society International (OARSI) histopathological grade (1 to 6), where 1 is an intact cartilage surface and 6 is cartilage surface deformation. Interestingly, three specific complex-type N-glycans, (Hex)₄(HexNAc)₃, (Hex)₄(HexNAc)₄, and (Hex)₅(HexNAc)₄, were found to be localized to the superficial fibrillated zone of degraded cartilage (KOA OARSI 2.5-4), compared to adjacent cartilage with less degradation (KOA OARSI 1-2) or relatively healthy cartilage (CTL OARSI 1-2). Our results demonstrate that N-glycans specific to degraded cartilage in KOA patients have been identified at the tissue level for the first time. The presence of these N-glycans could further be evaluated as potential diagnostic and prognostic biomarkers.

Characterization of Mesothelin Glycosylation in Pancreatic Cancer: Decreased Core Fucosylated Glycoforms in Pancreatic Cancer Patients’ Sera

Currently, there are no reliable biomarkers for the diagnosis of pancreatic cancer (PaC). Glycoproteomic approaches that analyze the glycan determinants on specific glycoproteins have proven useful to develop more specific cancer biomarkers than the corresponding protein levels. In PaC, mesothelin (MSLN) is a neo-expressed glycoprotein. MSLN glycosylation has not been described and could be altered in PaC. In this work, we aimed to characterize MSLN glycans from PaC cells and serum samples to assess their potential usefulness as PaC biomarkers. First, we analyzed MSLN glycans from PaC cell lines and then we developed an enzyme-linked lectin assay to measure core fucosylated-MSLN (Cf-MSLN) glycoforms. MSLN glycans from PaC cells were analyzed by glycan sequencing and through Western blotting with lectins. All of the cell lines secreted MSLN, with its three N-glycosylation sites occupied by complex-type N-glycans, which were mainly α2,3-sialylated, core fucosylated and highly branched. The Cf-MSLN glycoforms were quantified on PaC serum samples, and compared with MSLN protein levels. The Cf-MSLN was significantly decreased in PaC patients compared to control sera, while no differences were detected by using MSLN protein levels. In conclusion, Cf-MSLN glycoforms were differently expressed in PaC, which opens the way to further investigate their usefulness as PaC biomarkers.

Phaseolus vulgaris Erythroagglutinin (PHA-E)-Positive Ceruloplasmin Acts as a Potential Biomarker in Pancreatic Cancer Diagnosis

Pancreatic cancer (PC) remains one of the top 10 causes of cancer-related death in recent years. Approximately 80% of PC patients are diagnosed at the middle or advanced stage and miss the opportunity for surgery. The demand for early diagnostic methods and reliable biomarkers is increasing, although a number of tumor markers such as CA19-9 and CEA have already been utilized in clinics. In this study, we analyzed the alteration of N-glycan of serum glycoproteins by mass spectrometry and lectin blotting. The results showed that bisecting GlcNAc structures of glycoproteins are significantly increased in PC patients' sera. With Phaseolus vulgaris Erythroagglutinin (PHA-E) lectin that specifically recognizes bisecting GlcNAc N-glycans, the serum glycoproteins bearing bisecting GlcNAc in PC patients' sera were pulled down and identified by nano-LC-MS/MS. Among them, ceruloplasmin (Cp) was screened out with a satisfied sensitivity and specificity in identifying PC from acute pancreatitis patients (AUC: 0.757) and normal healthy persons (AUC: 0.972), suggesting a close association between Cp and PC development and diagnosis. To prove that, the Cp expression in tumor tissues of PC patients was examined. The results showed that Cp was significantly upregulated in PC tissues compared to that in adjacent normal tissues. All these results suggested that PHA-E-positive Cp could be a potential PC-specific glycoprotein marker to distinguish PC patients from acute pancreatitis patients and normal persons.

Concerted Regulation of Glycosylation Factors Sustains Tissue Identity and Function

Glycosylation is a fundamental cellular process affecting human development and health. Complex machinery establishes the glycan structures whose heterogeneity provides greater structural diversity than other post-translational modifications. Although known to present spatial and temporal diversity, the evolution of glycosylation and its role at the tissue-specific level is poorly understood. In this study, we combined genome and transcriptome profiles of healthy and diseased tissues to uncover novel insights into the complex role of glycosylation in humans. We constructed a catalogue of human glycosylation factors, including transferases, hydrolases and other genes directly involved in glycosylation. These were categorized as involved in N-, O- and lipid-linked glycosylation, glypiation, and glycosaminoglycan synthesis. Our data showed that these glycosylation factors constitute an ancient family of genes, where evolutionary constraints suppressed large gene duplications, except for genes involved in O-linked and lipid glycosylation. The transcriptome profiles of 30 healthy human tissues revealed tissue-specific expression patterns preserved across mammals. In addition, clusters of tightly co-expressed genes suggest a glycosylation code underlying tissue identity. Interestingly, several glycosylation factors showed tissue-specific profiles varying with age, suggesting a role in ageing-related disorders. In cancer, our analysis revealed that glycosylation factors are highly perturbed, at the genome and transcriptome levels, with a strong predominance of copy number alterations. Moreover, glycosylation factor dysregulation was associated with distinct cellular compositions of the tumor microenvironment, reinforcing the impact of glycosylation in modulating the immune system. Overall, this work provides genome-wide evidence that the glycosylation machinery is tightly regulated in healthy tissues and impaired in ageing and tumorigenesis, unveiling novel potential roles as prognostic biomarkers or therapeutic targets.

Biomarkers for Early Diagnosis of Ovarian Carcinoma

The leading cause of gynecological cancer-related morbidity and mortality is ovarian cancer (OC), which is dubbed a silent killer. Currently, OC is a target of intense biomarker research, because it is often not discovered until the disease is advanced. The goal of OC research is to develop effective tests using biomarkers that can detect the disease at the earliest stages, which would eventually decrease the mortality, thereby preventing recurrence. Therefore, there is a pressing need to revisit the existing biomarkers to recognize the potential biomarkers that can lead to efficient predictors for the OC diagnosis. This Perspective covers an update on the currently available biomarkers used in the triaging of OC to gain certain insights into the potential role of these biomarkers and their estimation that are crucial to the understanding of neoplasm progression, diagnostics, and therapy.

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.

Differentiation of Sialyl Linkages Using a Combination of Alkyl Esterification and Phenylhydrazine Derivatization: Application for N-Glycan Profiling in the Sera of Patients with Lung Cancer

Alterations in oligosaccharides and types of sialic acid (SA) attachments have been associated with different pathological states. Matrix-assisted laser desorption mass spectrometry (MS) is commonly used for glycosylation studies. However, native sialylated glycans are suppressed or not detected during MS experiments. Consequently, different approaches have been employed to neutralize the negative charge of the carboxyl group. In this study, we present the advantage of phenylhydrazine (PHN) labeling for the detection and efficient discrimination of SA linkages when this derivatization follows alkyl esterification. As expected, PHN-labeled sialylated oligosaccharides with the 2,6-linkage type can be easily recognized according to the additional shift in mass corresponding to the presence of a methyl or ethyl group. Surprisingly, oligosaccharides with the 2,3-linked SA residue instead of a lactone were detected carrying the second PHN unit. This was beneficial as no further processing after esterification was needed to stabilize the lactone form. Moreover, during tandem mass experiments, all modified glycans produced favorable fragmentation patterns with a coherent recognition of SA linkages. Although both types of esterification, herein called the EST-PHN approach, provided comparable results, methylation exhibited marginally higher linkage specificity than ethyl esterification. The simplicity and effectiveness of the methodology are demonstrated on the model compound, sialyllactose, and its applicability for biological studies is presented on N-glycan profiling in the sera of lung cancer patients.

TMT-Based Multiplexed Quantitation of N-Glycopeptides Reveals Glycoproteome Remodeling Induced by Oncogenic Mutations

Glycoproteomics, or the simultaneous characterization of glycans and their attached peptides, is increasingly being employed to generate catalogs of glycopeptides on a large scale. Nevertheless, quantitative glycoproteomics remains challenging even though isobaric tagging reagents such as tandem mass tags (TMT) are routinely used for quantitative proteomics. Here, we present a workflow that combines the enrichment or fractionation of TMT-labeled glycopeptides with size-exclusion chromatography (SEC) for an in-depth and quantitative analysis of the glycoproteome. We applied this workflow to study the cellular glycoproteome of an isogenic mammary epithelial cell system that recapitulated oncogenic mutations in the PIK3CA gene, which codes for the phosphatidylinositol-3-kinase catalytic subunit. As compared to the parental cells, cells with mutations in exon 9 (E545K) or exon 20 (H1047R) of the PIK3CA gene exhibited site-specific glycosylation alterations in 464 of the 1999 glycopeptides quantified. Our strategy led to the discovery of site-specific glycosylation changes in PIK3CA mutant cells in several important receptors, including cell adhesion proteins such as integrin β-6 and CD166. This study demonstrates that the SEC-based enrichment of glycopeptides is a simple and robust method with minimal sample processing that can easily be coupled with TMT-labeling for the global quantitation of glycopeptides.

Analysis of Tumor Glycosylation Characteristics and Implications for Immune Checkpoint Inhibitor’s Efficacy for Breast Cancer

The alterations of glycosylation, which is a common post-translational modification of proteins, have been acknowledged as key events in breast cancer (BC) oncogenesis and progression. The aberrant expression of glycosyltransferases leads to aberrant glycosylation patterns, posing the diagnostic potential in BC outcomes. The present study aims to establish a glycosyltransferase-based signature to predict BC prognosis and response to immune checkpoint inhibitors. We firstly screened 9 glycosyltransferase genes from The Cancer Genome Atlas (TCGA) database and accordingly established a glyco-signature for predicting the prognosis in BC patients. Patients with BC were successfully divided into high-risk and low-risk groups based on the median cutoff point for risk scores in this signature. Next, the combinational analyses of univariate and multivariate Cox regression, Kaplan–Meier, and receiver operating characteristic (ROC) curves were used to prove that this glyco-signature possessed excellent predictive performance for prognosis of BC patients, as the high-risk group possessed worse outcomes, in comparison to the low-risk group. Additionally, the Gene Set Enrichment Analysis (GSEA) and immunologic infiltration analysis were adopted and indicated that there was a more immunosuppressive state in the high-risk group than that in the low-risk group. The clinical sample validation verified that glycosyltransferase genes were differentially expressed in patients in the low- and high-risk groups, while the biomarkers of antitumor M1 macrophages were increased and N-glycosyltransferase STT3A decreased in the low-risk group. The final in vitro assay showed that the silencing of STT3A suppressed the proliferation and migration of BC cells. Collectively, our well-constructed glyco-signature is able to distinguish the high- and low-risk groups and accordingly predict BC prognosis, which will synergistically promote the prognosis evaluation and provide new immunotherapeutic targets for combating BC.

Pathological implication of protein post-translational modifications in cancer

Protein post-translational modifications (PTMs) profoundly influence protein functions and play crucial roles in essentially all cell biological processes. The diverse realm of PTMs and their crosstalk is linked to many critical signaling events involved in neoplastic transformation, carcinogenesis and metastasis. The pathological roles of various PTMs are implicated in all aspects of cancer hallmark functions, cancer metabolism and regulation of tumor microenvironment. Study of PTMs has become an important area in cancer research to understand cancer biology and discover novel biomarkers and therapeutic targets. With a limited scope, this review attempts to discuss some PTMs of high frequency with recognized importance in cancer biology, including phosphorylation, acetylation, glycosylation, palmitoylation and ubiquitination, as well as their implications in clinical applications. These protein modifications are among the most abundant PTMs and profoundly implicated in carcinogenesis.

Advances in High Throughput Proteomics Profiling in Establishing Potential Biomarkers for Gastrointestinal Cancer

Gastrointestinal cancers (GICs) remain the most diagnosed cancers and accounted for the highest cancer-related death globally. The prognosis and treatment outcomes of many GICs are poor because most of the cases are diagnosed in advanced metastatic stages. This is primarily attributed to the deficiency of effective and reliable early diagnostic biomarkers. The existing biomarkers for GICs diagnosis exhibited inadequate specificity and sensitivity. To improve the early diagnosis of GICs, biomarkers with higher specificity and sensitivity are warranted. Proteomics study and its functional analysis focus on elucidating physiological and biological functions of unknown or annotated proteins and deciphering cellular mechanisms at molecular levels. In addition, quantitative analysis of translational proteomics is a promising approach in enhancing the early identification and proper management of GICs. In this review, we focus on the advances in mass spectrometry along with the quantitative and functional analysis of proteomics data that contributes to the establishment of biomarkers for GICs including, colorectal, gastric, hepatocellular, pancreatic, and esophageal cancer. We also discuss the future challenges in the validation of proteomics-based biomarkers for their translation into clinics.

Applications of artificial intelligence (AI) in ovarian cancer, pancreatic cancer, and image biomarker discovery

BACKGROUND

Artificial intelligence (AI), including machine learning (ML) and deep learning, has the potential to revolutionize biomedical research. Defined as the ability to "mimic" human intelligence by machines executing trained algorithms, AI methods are deployed for biomarker discovery.

OBJECTIVE

We detail the advancements and challenges in the use of AI for biomarker discovery in ovarian and pancreatic cancer. We also provide an overview of associated regulatory and ethical considerations.

METHODS

We conducted a literature review using PubMed and Google Scholar to survey the published findings on the use of AI in ovarian cancer, pancreatic cancer, and cancer biomarkers.

RESULTS

Most AI models associated with ovarian and pancreatic cancer have yet to be applied in clinical settings, and imaging data in many studies are not publicly available. Low disease prevalence and asymptomatic disease limits data availability required for AI models. The FDA has yet to qualify imaging biomarkers as effective diagnostic tools for these cancers.

CONCLUSIONS

Challenges associated with data availability, quality, bias, as well as AI transparency and explainability, will likely persist. Explainable and trustworthy AI efforts will need to continue so that the research community can better understand and construct effective models for biomarker discovery in rare cancers.

Emerging Roles of Post-Translational Modifications in Skin Diseases: Current Knowledge, Challenges and Future Perspectives

Post-translational modifications (PTMs) of proteins represent as a key step in regulating their biological functions and dynamic interaction with other players. This process is fine-tuned by a myriad of enzymes named “writers, readers and erasers” whose actions are precisely controlled. Either the mutation, aberration in the expression of the aforementioned enzymes or their substrates have shown to participate in the pathogenesis of various skin diseases such as melanoma, vitiligo, psoriasis, eczema, atopic dermatitis and inherited dermatological diseases. It is becoming increasingly clear that key transcriptional factors, inflammation-related molecules are prone to PTMs. Despite their importance in regulating key processes including inflammation, keratinocyte apoptosis, proliferation and differentiation, PTMs have received less attention due to the challenges involved. Here in this review we summarize the role of the most common types and the newly discovered PTMs, including acetylation, glycosylation, citrullination, PARylation and sumoylation in dermatoses and surveys the recent progress in PTM-based therapeutic approaches in skin diseases.

Construction of InstantPC derivatized glycan GU database: A foundation work for high-throughput and high-sensitivity glycomic analysis

Glycosylation is well-recognized as a critical quality attribute of biotherapeutics being routinely monitored to ensure desired product quality, safety, and efficacy. Additionally, as one of the most prominent and complex post-translational modifications, glycosylation plays a key role in disease manifestation. Changes in glycosylation may serve as a specific and sensitive biomarker for disease diagnostics and prognostics. However, the conventional 2-aminobenzamide based N-glycosylation analysis procedure is time-consuming and insensitive, with poor reproducibility. We have evaluated an innovative streamlined 96-well-plate-based platform utilizing InstantPC label for high-throughput, high-sensitivity glycan profiling, which is user-friendly, robust, and ready for automation. However, the limited availability of InstantPC labelled glycan standards has significantly hampered the applicability and transferability of this platform for expedited glycan structural profiling. To address this challenge, we have constructed a detailed InstantPC labelled glycan glucose unit database through analysis of human serum and a variety of other glycoproteins from various sources. Following preliminary hydrophilic interaction liquid chromatography with fluorescence detection separation and analysis, glycoproteins with complex glycan profiles were subjected to further fractionation by weak anion exchange hydrophilic interaction liquid chromatography and exoglycosidase sequential digestion for cross-validation of the glycan assignment. Hydrophilic interaction ultra-performance liquid chromatography coupled with electrospray ionization mass spectrometry was subsequently utilised for glycan fragmentation and accurate glycan mass confirmation. The constructed InstantPC glycan GU database is accurate and robust. It is believed that this database will enhance the application of the developed platform for high-throughput, high-sensitivity glycan profiling, and eventually advance glycan-based biopharmaceutical production and disease biomarker discovery.