Improvement of Prostate Cancer Diagnosis by Detecting PSA Glycosylation-Specific Changes

Elevated serum levels of GPX4, NDUFS4, PRDX5, and TXNRD2 as predictive biomarkers for castration resistance in prostate cancer patients: an exploratory study

BACKGROUND

Prostate cancer (PCa) is a heterogeneous disease affecting over 14% of the male population worldwide. Although patients often respond positively to initial treatments within the first 2-3 years, many eventually develop a more lethal form of the disease known as castration-resistant PCa (CRPC). At present, no biomarkers that predict the onset of CRPC are available. This study aims to provide insights into the diagnosis and prediction of CRPC emergence.

METHODS

Protein expression dynamics were analysed in drug (androgen receptor inhibitor)-tolerant persister (DTP) and drug withdrawal cells using proteomics to identify potential biomarkers. These biomarkers were subsequently validated using a mouse model, 180-paired carcinoma/benign tissues, and 482 serum samples. Five machine learning algorithms were employed to build clinical prediction models, wherein the SHapley Additive exPlanation (SHAP) framework was used to interpret the best-performing model. Moreover, three regression models were developed to determine the Time from initial PCa diagnosis to CRPC development (TPC) in patients.

RESULTS

We identified that the protein expression levels of GPX4, NDUFS4, PRDX5, and TXNRD2 were significantly upregulated in PCa patients, particularly in those with CRPC. Among the tested machine learning models, the random forest and extreme gradient boosting models performed best on tissue and serum cohorts, achieving AUCs of 0.958 and 0.988, respectively. In addition, a significant inverse correlation was observed between TPC and serum levels of these four biomarkers. This correlation was formulated in three regression models, which achieved the smallest mean absolute error of 1.903 on independent datasets for predicting CRPC emergence.

CONCLUSION

Our study provides new insights into the role of DTP cells in CRPC development. The quad protein panel identified in our study, along with the post hoc and intrinsically explainable prediction models, may serve as a convenient and real-time prognostic tool, addressing the current lack of clinical biomarkers for CRPC.

A comprehensive view of N-glycosylation as clinical biomarker in prostate cancer

Alterations in the prostate cancer (PCa) N-glycome have gained attention as a potential biomarker. This comprehensive review explores the diversity of N-glycosylation patterns observed in PCa-related cell lines, tissue, serum and urine, focusing on prostate-specific antigen (PSA) and the total pool of glycoproteins. Within the context of PCa, altered N-glycosylation patterns are a mechanism of immune escape and a disruption in normal glycoprotein distribution and trafficking. Glycoproteins with PCa-induced N-glycosylation patterns tend to accumulate in prostate tissue and the bloodstream, thereby diminishing N-glycan proportions in urine. Based on literary observations, aberrations in N-glycan branching are probably a characteristic of metabolic reprogramming and (chronic) inflammation. Changes in (core) fucosylation, specific N-glycosylation structures (such as N,N'-diacetyllactosamine) and high-mannose glycans otherwise are more likely indicators of cancer development and progression. Further investigation into these PCa-specific alterations holds promise in the discovery of new diagnostic, prognostic and response prediction biomarkers in PCa.

Liquid Biomarkers in Prostate Cancer Diagnosis: Current Status and Emerging Prospects

Prostate cancer (PCa) is a major health concern that necessitates appropriate diagnostic approaches for timely intervention. This review critically evaluates the role of liquid biopsy techniques, focusing on blood- and urine-based biomarkers, in overcoming the limitations of conventional diagnostic methods. The 4Kscore test and Prostate Health Index have demonstrated efficacy in distinguishing PCa from benign conditions. Urinary biomarker tests such as PCa antigen 3, MyProstateScore, SelectMDx, and ExoDx Prostate IntelliScore test have revolutionized risk stratification and minimized unnecessary biopsies. Emerging biomarkers, including non-coding RNAs, circulating tumor DNA, and prostate-specific antigen (PSA) glycosylation, offer valuable insights into PCa biology, enabling personalized treatment strategies. Advancements in non-invasive liquid biomarkers for PCa diagnosis may facilitate the stratification of patients and avoid unnecessary biopsies, particularly when PSA is in the gray area of 4 to 10 ng/mL.

Liquid-Biopsy Glycan Score Biomarker Accurately Indicates and Stratifies Primary and Metastatic Prostate Cancers

Prostate cancer (PCa) is the most commonly diagnosed cancer in males. Early PCa usually shows no clinical symptoms and its primary diagnosis is currently guided by liquid-biopsy testing of serum prostate-specific antigen (PSA). This testing suffers from high false-positive and false-negative rates. Identifying new biomarkers for precise liquid-biopsy detection of PCa is, thus, an acute clinical request. Here, by using an advanced dual-functional aptamer assay, we quantified the extent of glycosylation of PSA circulating in cancer patients' serum, linked it to cancer-related breakage of PSA complexes with serum-circulating proteins, and proved its facility for stratification of primary and metastatic PCa. PSA's "Glycan Score" 100% accurately informed about PCa status in a 30-patient cohort, while serum PSA's concentration correctly classified only 53% of PCa patients and did not inform about their PCa status. The Glycan Score liquid-biopsy test thus has a huge potential for accurate diagnosis and staging of PCa, enabling mass-screening program progress and advanced PCa treatment monitoring.

Fingerprint Profiling of Glycans on Extracellular Vesicles via Lectin-Induced Aggregation Strategy for Precise Cancer Diagnostics

Extracellular vesicles (EVs) harbor abundant glycans that mediate various functions, such as intercellular communication and disease advancement, which play significant roles in disease progression. However, the presence of EV heterogeneity in body fluids and the complex nature of the glycan structures have posed challenges for the detection of EV glycans. In this study, we provide a streamlined method integrated, membrane-specific separation with lectin-induced aggregation strategy (MESSAGE), for multiplexed profiling of EV glycans. By leveraging a rationally designed lectin-induced aggregation strategy, the expression of EV glycans is converted to size-based signals. With the assistance learning machine algorithms, the MESSAGE strategy with high sensitivity, specificity, and simplicity can be used for early cancer diagnosis and classification, as well as monitoring cancer metastasis via 20 μL plasma sample within 2 h. Furthermore, our platform holds promise for advancing the field of EV-based liquid biopsy for clinical applications, opening new possibilities for the profiling of EV glycan signatures in various disease states.

Development of a first-in-class antibody and a specific assay for α-1,6-fucosylated prostate-specific antigen

Prostate-specific antigen (PSA) levels are widely used to screen for prostate cancer, yet the test has poor sensitivity, specificity and predictive value, which leads to overdiagnosis and overtreatment. Alterations in the glycosylation status of PSA, including fucosylation, may offer scope for an improved biomarker. We sought to generate a monoclonal antibody (mAb) targeting α-1,6-fucosylated PSA (fuc-PSA) and to develop a tissue-based immunological assay for fuc-PSA detection. Immunogens representing fuc-PSA were used for immunisation and resultant mAbs were extensively characterised. The mAbs reacted specifically with fuc-PSA-specific glycopeptide, but not with aglycosylated PSA or glycan without the PSA peptide. Reactivity was confirmed using high-throughput surface plasmon resonance spectroscopy. X-ray crystallography investigations showed that the mAbs bound to an α-helical form of the peptide, whereas the native PSA epitope is linear. Protein unfolding was required for detection of fuc-PSA in patient samples. Peptide inhibition of fuc-PSA mAbs was observed with positive screening reagents, and target epitope specificity was observed in formalin-fixed, paraffin-embedded tissue samples. This research introduces a well-characterised, first-in-class antibody targeting fuc-PSA and presents the first crystal structure of an antibody demonstrating glycosylation-specific binding to a peptide.

[Applications of chromatography in glycomics]

Glycomics, an emerging "omics" technology that was developed after genomics and proteomics, is a discipline that studies the composition, structure, and functions of glycomes in cells, tissues, and organisms. Glycomics plays key roles in understanding the laws of major life activities, disease prevention and treatment, and drug quality control and development. At present, the structural analysis of glycans relies mainly on mass spectrometry. However, glycans have low abundance in biological samples. In addition, factors such as variable monosaccharide compositions, differences in glycosidic bond positions and modes, diverse branching structures, contribute to the complexity of the compositions and structures of glycans, posing great challenges to glycomics research. Liquid chromatography can effectively remove matrix interferences and enhance glycan separation to improve the mass spectrometric response of glycans. Thus, liquid chromatography and liquid chromatography coupled with mass spectrometry are important technical tools that have been actively applied to solve these problems; these technologies play indispensable roles in glycomics research. Different studies have highlighted similarities and differences in the applications of various types of liquid chromatography, which also reflects the versatility and flexibility of this technology. In this review, we first discuss the enrichment methods for glycans and their applications in glycomics research from the perspective of chromatographic separation mechanisms. We then compare the advantages and disadvantages of these methods. Some glycan-enrichment modes include affinity, hydrophilic interactions, size exclusion, and porous graphitized carbon adsorption. A number of newly developed materials exhibit excellent glycan-enrichment ability. We enumerate the separation mechanisms of reversed-phase high performance liquid chromatography (RP-HPLC), high performance anion-exchange chromatography (HPAEC), hydrophilic interaction chromatography (HILIC), and porous graphitic carbon (PGC) chromatography in the separation and analysis of glycans, and describe the applications of these methods in the separation of glycans, glycoconjugates, and glyco-derivatives. Among these methods, HILIC and PGC chromatography are the most widely used, whereas HPAEC and RP-HPLC are less commonly used. The HILIC and RP-HPLC modes are often used for the separation of derived glycans. The ionization efficiency and detectability of glycans are significantly improved after derivatization. However, the derivatization process is relatively cumbersome, and byproducts inevitably affect the accuracy and completeness of the detection results. HPAEC and PGC chromatography exhibit good separation effects on nonderivative glycans, but issues related to the detection integrity of low-abundance glycans owing to their poor detection effect continue to persist. Therefore, the appropriate analytical method for a specific sample or target analyte or mutual verification must be selected. Finally, we highlight the research progress in various chromatographic methods coupled with mass spectrometry for glycomics analysis. Significant progress has been made in glycomics research in recent years owing to advancements in the development of chromatographic separation techniques. However, several significant challenges remain. As the development of novel separation materials and methods continues, chromatographic techniques may be expected to play a critical role in future glycomics research.

Lectin-nanoparticle concept for free PSA glycovariant providing superior cancer specificity

BACKGROUND

Using lectins to target cancer-associated modifications of PSA glycostructure for identification of clinically significant prostate cancers, e.g., Gleason score (GS) ≥ 7, from benign and indolent cancers (GS 6), is highly promising yet technically challenging. From previous findings to quantify increased PSA fucosylation in urine, we set out to construct a robust, specific test concept suitable for plasma samples.

METHODS

Macrophage galactose-binding lectin (MGL) coupled to 100 nm Eu3 + -nanoparticles was used to probe PSA captured from cancer cell lines, seminal plasma, and plasma samples from 249 patients with a clinical suspicion of prostate cancer onto 3 mm dense spots of free PSA antibody fab fragments. Results were compared to four kallikrein tests: tPSA, fPSA, iPSA and hK2.

RESULTS

The fPSAMGLglycovariant provided superior discrimination of the GS ≥ 7 and benign + GS 6 groups (p 0.0003) compared to fPSA (NS). The corresponding AUC in ROC analysis was 0.70 compared to 0.66 for tPSA. In contrast to all four kallikrein tests, the fPSAMGLGV was independent of prostate gland volume. Using a logistic regression analysis the fPSAMGLGV significantly improved on the four-kallikrein model.

CONCLUSIONS

Due to Eu-nanoparticles and a dense fPSA capture spot, the fPSAMGL glycovariant identifies an fPSA subform with the highest cancer specificity compared to the four conventional kallikreins.

The glycosylation landscape of prostate cancer tissues and biofluids

An overview of the role of glycosylation in prostate cancer (PCa) development and progression is presented, focusing on recent advancements in defining the N-glycome through glycomic profiling and glycoproteomic methodologies. Glycosylation is a common post-translational modification typified by oligosaccharides attached N-linked to asparagine or O-linked to serine or threonine on carrier proteins. These attached sugars have crucial roles in protein folding and cellular recognition processes, such that altered glycosylation is a hallmark of cancer pathogenesis and progression. In the past decade, advancements in N-glycan profiling workflows using Matrix Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) technology have been applied to define the spatial distribution of glycans in PCa tissues. Multiple studies applying N-glycan MALDI-MSI to pathology-defined PCa tissues have identified significant alterations in N-glycan profiles associated with PCa progression. N-glycan compositions progressively increase in number, and structural complexity due to increased fucosylation and sialylation. Additionally, significant progress has been made in defining the glycan and glycopeptide compositions of prostatic-derived glycoproteins like prostate-specific antigen in tissues and biofluids. The glycosyltransferases involved in these changes are potential drug targets for PCa, and new approaches in this area are summarized. These advancements will be discussed in the context of the further development of clinical diagnostics and therapeutics targeting glycans and glycoproteins associated with PCa progression. Integration of large scale spatial glycomic data for PCa with other spatial-omic methodologies is now feasible at the tissue and single-cell levels.

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.

Identification and characterization of intact glycopeptides in human urine

Glycoproteins in urine have the potential to provide a rich class of informative molecules for studying human health and disease. Despite this promise, the urine glycoproteome has been largely uncharacterized. Here, we present the analysis of glycoproteins in human urine using LC-MS/MS-based intact glycopeptide analysis, providing both the identification of protein glycosites and characterization of the glycan composition at specific glycosites. Gene enrichment analysis reveals differences in biological processes, cellular components, and molecular functions in the urine glycoproteome versus the urine proteome, as well as differences based on the major glycan class observed on proteins. Meta-heterogeneity of glycosylation is examined on proteins to determine the variation in glycosylation across multiple sites of a given protein with specific examples of individual sites differing from the glycosylation trends in the overall protein. Taken together, this dataset represents a potentially valuable resource as a baseline characterization of glycoproteins in human urine for future urine glycoproteomics studies.

Lectin-Mimicking Aptamer as a Generic Glycan Receptor for Sensitive Detection of Glycoproteins Associated with Cancer

The shortage of specific glycan recognition reagents has proven a significant hurdle in the development of assays to detect altered glycoforms associated with cancer. Here, a carbohydrate-binding aptamer originally selected against the glycan moiety of prostate-specific antigen (PSA) is used as a lectin-mimicking reagent. As a first proof-of-principle, this aptamer has been applied to develop a sandwich-type electrochemical biosensor for the detection of the serum amyloid P (SAP) component, a glycosylated protein whose increased sialylation has been associated with pancreatic cancer. The assay combines a specific antibody for this potential tumor biomarker and the aptamer as capture and detection receptors, respectively. Two oriented antibody immobilization approaches, protein A-based and boronic ester-based attachment to self-assembled monolayers built onto gold surfaces, were comparatively evaluated, the latter being able to circumvent the unwanted interaction between the aptamer and the glycans on the electrode-attached antibody. The resulting biosensing platform allows the detection of the SAP glycoprotein at levels of nanograms per milliliter with a reproducibility value lower than 20%, both in aqueous buffer and in serum. This work represents a proof-of-concept of a promiscuous ligand of proteins with high levels of sialylated glycans typically produced by cancer cells.

Deep learning enhanced the diagnostic merit of serum glycome for multiple cancers

Protein glycosylation is associated with the pathogenesis of various cancers. The utilization of certain glycans in cancer diagnosis models holds promise, yet their accuracy is not always guaranteed. Here, we investigated the utility of deep learning techniques, specifically random forests combined with transfer learning, in enhancing serum glycome's discriminative power for cancer diagnosis (including ovarian cancer, non-small cell lung cancer, gastric cancer, and esophageal cancer). We started with ovarian cancer and demonstrated that transfer learning can achieve superior performance in data-disadvantaged cohorts (AUROC >0.9), outperforming the approach of PLS-DA. We identified a serum glycan-biomarker panel including 18 serum N-glycans and 4 glycan derived traits, most of which were featured with sialylation. Furthermore, we validated advantage of the transfer learning scheme across other cancer groups. These findings highlighted the superiority of transfer learning in improving the performance of glycans-based cancer diagnosis model and identifying cancer biomarkers, providing a new high-fidelity cancer diagnosis venue.

Serum-based Comprehensive N-Glycans Profiling Analysis in Different Gastric Disease Stages by Porous Graphitic Carbon Liquid Chromatography-Mass Spectrometry Associated With Potential Marker Discovery

BACKGROUND/AIM

N-glycans are potential serum biomarkers due to their aberrant structure and abundance alteration during disease progression. Few studies have been associated with relative quantitative N-glycans profiling during different gastric disease stages. In this study, we conducted an investigation on the profiling of N-glycans in patients with gastric disease, as well as in healthy controls.

MATERIALS AND METHODS

In this study, the porous graphitization carbon chromatography-high resolution Fourier transform mass spectrometry (PGC-FTMS) method was applied to assess comprehensive N-glycans profiling in patients at different stages of gastric disease, including gastritis, atrophic gastritis, gastric ulcer, gastric polyps, and gastric cancer.

RESULTS

A total of 45 N-glycans (relative abundance >0.1%) were detected, and 9 N-glycans were found to be potential biomarkers for gastric disease detection. Along with the progression of gastric disease, the abundance of sialylated N-glycans increased, while that of core-fucosylated N-glycans decreased. Multivariate statistical analysis demonstrated that N-glycans profiling between gastritis and healthy controls had significant differences. The characteristic N-glycans distinguished gastric cancer from healthy controls, which had strong clinical diagnostic value.

CONCLUSION

The relative quantitative profile of N-glycans in different gastric disease stages was revealed and serum N-glycans are proposed for distinguishing gastric disease stages in clinical application.

Structural insights into the role of N-terminal integrity in PhoSL for core-fucosylated N-glycan recognition

PhoSL (Pholiota squarrosa Lectin) has an exceptional binding affinity for biomolecules with core-fucosylated N-glycans. This modification involves the addition of fucose to the inner N-acetylglucosamine within the N-glycan structure and is known to influence many physiological processes. Nevertheless, the molecular interactions underlying high-affinity binding of native PhoSL to core-fucosylated N-glycans remain largely unknown. In this study, we devised a strategy to produce PhoSL with the essential structural characteristics of the native protein (n-PhoSL). To do so, a fusion protein was expressed in E. coli and purified. Then, enzymatic cleavage and incubation with glutathione were utilized to recapitulate the native primary structure and disulfide bonding pattern. Subsequently, we identified the residues crucial for n-PhoSL binding to core-fucosylated chitobiose (N2F) via NMR spectroscopy. Additionally, crystal structures were solved for both apo n-PhoSL and its N2F complex. These analyses suggested a pivotal role of the N-terminal amine in maintaining the integrity of the binding pocket and actively contributing to core-fucose recognition. In support of this idea, the inclusion of additional residues at the N-terminus considerably reduced binding affinity and PhoSL cytotoxicity toward breast cancer cells. Taken together, these findings can facilitate the utilization of PhoSL in basic research, diagnostics and therapeutic strategies.

Absolute Affinities from Quantitative Shotgun Glycomics Using Concentration-Independent (COIN) Native Mass Spectrometry

Native mass spectrometry (nMS) screening of natural glycan libraries against glycan-binding proteins (GBPs) is a powerful tool for ligand discovery. However, as the glycan concentrations are unknown, affinities cannot be measured directly from natural libraries. Here, we introduce Concentration-Independent (COIN)-nMS, which enables quantitative screening of natural glycan libraries by exploiting slow mixing of solutions inside a nanoflow electrospray ionization emitter. The affinities (K_d) of detected GBP-glycan interactions are determined, simultaneously, from nMS analysis of their time-dependent relative abundance changes. We establish the reliability of COIN-nMS using interactions between purified glycans and GBPs with known K_d values. We also demonstrate the implementation of COIN-nMS using the catch-and-release (CaR)-nMS assay for glycosylated GBPs. The COIN-CaR-nMS results obtained for plant, fungal, viral, and human lectins with natural libraries containing hundreds of N-glycans and glycopeptides highlight the assay's versatility for discovering new ligands, precisely measuring their affinities, and uncovering "fine" specificities. Notably, the COIN-CaR-nMS results clarify the sialoglycan binding properties of the SARS-CoV-2 receptor binding domain and establish the recognition of monosialylated hybrid and biantennary N-glycans. Moreover, pharmacological depletion of host complex N-glycans reduces both pseudotyped virions and SARS-CoV-2 cell entry, suggesting that complex N-glycans may serve as attachment factors.

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.

Aberrant protein glycosylation: Implications on diagnosis and Immunotherapy

Glycosylation-mediated post-translational modification is critical for regulating many fundamental processes like cell division, differentiation, immune response, and cell-to-cell interaction. Alterations in the N-linked or O-linked glycosylation pattern of regulatory proteins like transcription factors or cellular receptors lead to many diseases, including cancer. These alterations give rise to micro- and macro-heterogeneity in tumor cells. Here, we review the role of O- and N-linked glycosylation and its regulatory function in autoimmunity and aberrant glycosylation in cancer. The change in cellular glycome could result from a change in the expression of glycosidases or glycosyltransferases like N-acetyl-glucosaminyl transferase V, FUT8, ST6Gal-I, DPAGT1, etc., impact the glycosylation of target proteins leading to transformation. Moreover, the mutations in glycogenes affect glycosylation patterns on immune cells leading to other related manifestations like pro- or anti-inflammatory effects. In recent years, understanding the glycome to cancer indicates that it can be utilized for both diagnosis/prognosis as well as immunotherapy. Studies involving mass spectrometry of proteome, site- and structure-specific glycoproteomics, or transcriptomics/genomics of patient samples and cancer models revealed the importance of glycosylation homeostasis in cancer biology. The development of emerging technologies, such as the lectin microarray, has facilitated research on the structure and function of glycans and glycosylation. Newly developed devices allow for high-throughput, high-speed, and precise research on aberrant glycosylation. This paper also discusses emerging technologies and clinical applications of glycosylation.

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.

Establishment and validation of a plasma oncofetal chondroitin sulfated proteoglycan for pan-cancer detection

Various biomarkers targeting cell-free DNA (cfDNA) and circulating proteins have been tested for pan-cancer detection. Oncofetal chondroitin sulfate (ofCS), which distinctively modifies proteoglycans (PGs) of most cancer cells and binds specifically to the recombinant Plasmodium falciparum VAR2CSA proteins (rVAR2), is explored for its potential as a plasma biomarker in pan-cancer detection. To quantitate the plasma ofCS/ofCSPGs, we optimized an ELISA using different capture/detection pairs (rVAR2/anti-CD44, -SDC1, and -CSPG4) in a case-control study with six cancer types. We show that the plasma levels of ofCS/ofCSPGs are significantly higher in cancer patients (P values, 1.2 × 10^-2 to 4.4 × 10^-10). Validation studies are performed with two independent cohorts covering 11 malignant tumors. The individuals in the top decile of ofCS-CD44 have more than 27-fold cancer risk (OR = 27.8, 95%CI = 18.8-41.4, P = 2.72 × 10^-62) compared with the lowest 20%. Moreover, the elevated plasma ofCS-CD44 could be detected at the early stage of pan-cancer with strong dose-dependent odds risk prediction.

Proceedings of workshop: "Neuroglycoproteins in health and disease", INNOGLY cost action

The Cost Action "Innovation with glycans: new frontiers from synthesis to new biological targets" (INNOGLY) hosted the Workshop "Neuroglycoproteins in health and disease", in Alicante, Spain, on March 2022. This event brought together an european group of scientists that presented novel insights into changes in glycosylation in diseases of the central nervous system and cancer, as well as new techniques to study protein glycosylation. Herein we provide the abstracts of all the presentations.

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.

Advances in glycopeptide enrichment methods for the analysis of protein glycosylation over the past decade

Advances in bioanalytical technology have accelerated the analysis of complex protein glycosylation, which is beneficial to understanding glycosylation in drug discovery and disease diagnosis. Due to its biological uniqueness in the course of disease occurrence and development, disease-specific glycosylation requires quantitative characterization of protein glycosylation. We provide a comprehensive review of recent advances in glycosylation analysis, including workflows for glycoprotein digestion, glycopeptide separation and enrichment, and mass-spectrometry sequencing. We specifically focus on different strategies for glycopeptide enrichment through physical interaction, chemical oxidation, or metabolic labeling of intact glycopeptides. The recent advances and challenges of O-glycosylation analysis are presented, and the development of improved enrichment methods combining different proteases to analyze O-glycosylation is also proposed. This article is protected by copyright. All rights reserved.

Glycoforms of human prostate-specific membrane antigen (PSMA) in human cells and prostate tissue

INTRODUCTION

N-glycosylation is a ubiquitous and variable posttranslational modification that regulates physiological functions of secretory and membrane-associated proteins and the dysregulation of glycosylation pathways is often associated with cancer growth and metastasis. Prostate-specific membrane antigen (PSMA) is an established biomarker for prostate cancer imaging and therapy.

METHODS

Mass spectrometry was used to analyze the distribution of the site-specific glycoforms of PSMA in insect, human embryonic kidney, and prostate cancer cells, and in prostate tissue upon immunoaffinity enrichment.

RESULTS

While recombinant PSMA expressed in insect cells was decorated mainly by paucimannose and high mannose glycans, complex, hybrid, and high mannose glycans were detected in samples from human cells and tissue. We noted an interesting spatial distribution of the glycoforms on the PSMA surface-high mannose glycans were the dominant glycoforms at the N459, N476, and N638 sequons facing the plasma membrane, while the N121, N195, and N336 sites, located at the exposed apical PSMA domain, carried primarily complex glycans. The presence of high mannose glycoforms at the former sequons likely results from the limited access of enzymes of the glycosynthetic pathway required for the synthesis of the complex structures. In line with the limited accessibility of membrane-proximal sites, no glycosylation was observed at the N51 site positioned closest to the membrane.

CONCLUSIONS

Our study presents initial descriptive analysis of the glycoforms of PSMA observed in cell lines and in prostate tissue. It will hopefully stimulate further research into PSMA glycoforms in the context of tumor staging, noninvasive detection of prostate tumors, and the impact of glycoforms on physicochemical and enzymatic characteristics of PSMA in a tissue-specific manner.

Glycosylation Changes in Prostate Cancer Progression

Prostate Cancer (PCa) is the most commonly diagnosed malignancy and second leading cause of cancer-related mortality in men. With the use of next generation sequencing and proteomic platforms, new biomarkers are constantly being developed to both improve diagnostic sensitivity and specificity and help stratify patients into different risk groups for optimal management. In recent years, it has become well accepted that altered glycosylation is a hallmark of cancer progression and that the glycan structures resulting from these mechanisms show tremendous promise as both diagnostic and prognostic biomarkers. In PCa, a wide range of structural alterations to glycans have been reported such as variations in sialylation and fucosylation, changes in branching, altered levels of Lewis and sialyl Lewis antigens, as well as the emergence of high mannose "cryptic" structures, which may be immunogenic and therapeutically relevant. Furthermore, aberrant expression of galectins, glycolipids, and proteoglycans have also been reported and associated with PCa cell survival and metastasis. In this review, we discuss the findings from various studies that have explored altered N- and O-linked glycosylation in PCa tissue and body fluids. We further discuss changes in O-GlcNAcylation as well as altered expression of galectins and glycoconjugates and their effects on PCa progression. Finally, we emphasize the clinical utility and potential impact of exploiting glycans as both biomarkers and therapeutic targets to improve our ability to diagnose clinically relevant tumors as well as expand treatment options for patients with advanced disease.

Abnormal sialylation and fucosylation of saliva glycoproteins: Characteristics of lung cancer-specific biomarkers

Dysregulated surface glycoproteins play an important role in tumor cell proliferation and progression. Abnormal glycosylation of these glycoproteins may activate tumor signal transduction and lead to tumor development. The tumor microenvironment alters its molecular composition, some of which regulate protein glycosylation biosynthesis. The glycosylation of saliva proteins in lung cancer patients is different from healthy controls, in which the glycans of cancer patients are highly sialylated and hyperfucosylated. Most studies have shown that O-glycans from cancer are truncated O-glycans, while N-glycans contain fucoses and sialic acids. Because glycosylation analysis is challenging, there are few reports on how glycosylation of saliva proteins is related to the occurrence or progression of lung cancer. In this review, we discussed glycoenzymes involved in protein glycosylation, their changes in tumor microenvironment, potential tumor biomarkers present in body fluids, and abnormal glycosylation of saliva or lung glycoproteins. We further explored the effect of glycosylation changes on tumor signal transduction, and emphasized the role of receptor tyrosine kinases in tumorigenesis and metastasis.

Lectins applied to diagnosis and treatment of prostate cancer and benign hyperplasia: A review

Environmental factors, as well as genetic factors, contribute to the increase in prostate cancer cases (PCa), the second leading cause of cancer death in men. This fact calls for the development of more reliable, quick and low-cost early detection tests to distinguish between malignant and benign cases. Abnormal cell glycosylation pattern is a promising PCa marker for this purpose. Proteins, such as lectins can decode the information contained in the glycosylation patterns. Several studies have reported on applications of plant lectins as diagnostic tools for PCa considering the ability to differentiate it from benign cases. In addition, they can be used to detect, separate and differentiate the glycosylation patterns of cells or proteins present in serum, urine and semen. Herein, we present an overview of these studies, showing the lectins that map glycans differentially expressed in PCa, as well as benign hyperplasia (BPH). We further review their applications in biosensors, histochemical tests, immunoassays, chromatography, arrays and, finally, their therapeutic potential. This is the first study to review vegetable lectins applied specifically to PCa.

Glycosylated biomarker sensors: advancements in prostate cancer diagnosis

Prostate cancer is currently diagnosed using the conventional gold standard methods using prostate-specific antigen (PSA) as the selective biomarker. However, lack of precision in PSA screening has resulted in needless biopsies and delays the treatment of potentially fatal prostate cancer. Thus, identification of glycans as novel biomarkers for the early detection of prostate cancer has attracted considerable attention due to their reliable diagnostic platform compared with the current PSA systems. Therefore, biosensing technologies that provide point-of-care diagnostics have demonstrated the ability to detect various analytes, including glycosylated micro- and macro-molecules, thereby enabling versatile detection methodologies. This highlight article discusses recent advances in the biosensor-based detection of prostate cancer glycan biomarkers and the innovative strategies for the conjugation of nanomaterials adapted to biosensing platforms. Finally, the article is concluded with prospects and challenges of prostate cancer biosensors and recommendations to overcome the issues associated with prostate cancer diagnosis.

Associations Between Genetically Predicted Plasma N-Glycans and Prostate Cancer Risk: Analysis of Over 140,000 European Descendants

BACKGROUND

Previous studies suggest a potential link between glycosylation and prostate cancer. To better characterize the relationship between the two, we performed a study to comprehensively evaluate the associations between genetically predicted blood plasma N-glycan levels and prostate cancer risk.

METHODS

Using genetic variants associated with N-glycan levels as instruments, we evaluated the associations between levels of 138 plasma N-glycans and prostate cancer risk. We analyzed data of 79,194 cases and 61,112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL.

RESULTS

We identified three N-glycans with genetically predicted levels in plasma to be associated with prostate cancer risk after Bonferroni correction. The estimated odds ratios (95% confidence intervals) were 1.29 (1.20-1.40), 0.80 (0.74-0.88), and 0.79 (0.72-0.87) for PGP18, PGP33, and PGP109, respectively, per every one standard deviation increase in genetically predicted levels of N-glycan. However, the instruments for these N-glycans only involved one to two variants. The proportions of variations that can be explained by the instruments range from 1.58% to 2.95% for these three N-glycans.

CONCLUSION

We observed associations between genetically predicted levels of three N-glycans PGP18, PGP33, and PGP109 and prostate cancer risk. Given the correlated nature of the N-glycans and that many N-glycans share genetic loci, pleiotropy is a major concern. Future work is warranted to better characterize the relationship between N-glycans and prostate cancer.

Inflammatory metabolic profile of South African patients with prostate cancer

Background

Men with African ancestry are more likely to develop aggressive prostate cancer (PCa) and to die from this disease. The study of PCa in the South African population represents an opportunity for biomedical research due to the high prevalence of aggressive PCa. While inflammation is known to play a significant role in PCa progression, its association with tumor stage in populations of African descent has not been explored in detail. Identification of new metabolic biomarkers of inflammation may improve diagnosis of patients with aggressive PCa.

Methods

Plasma samples were profiled from 41 South African men with PCa using nuclear magnetic resonance (NMR) spectroscopy. A total of 41 features, including metabolites, lipid classes, total protein, and the inflammatory NMR markers, GlycA, and GlycB, were quantified from each NMR spectrum. The Bruker’s B.I.-LISA protocols were used to characterize 114 parameters related to the lipoproteins. The unsupervised KODAMA method was used to stratify the patients of our cohort based on their metabolic profile.

Results

We found that the plasma of patients with very high risk, aggressive PCa and high level of C-reactive protein have a peculiar metabolic phenotype (metabotype) characterized by extremely high levels of GlycA and GlycB. The inflammatory processes linked to the higher level of GlycA and GlycB are characterized by a deep change of the plasma metabolome that may be used to improve the stratification of patients with PCa. We also identified a not previously known relationship between high values of VLDL and low level of GlycB in a different metabotype of patients characterized by lower-risk PCa.

Conclusions

For the first time, a portrait of the metabolic changes in African men with PCa has been delineated indicating a strong association between inflammation and metabolic profiles. Our findings indicate how the metabolic profile could be used to identify those patients with high level of inflammation, characterized by aggressive PCa and short life expectancy. Integrating a metabolomic analysis as a tool for patient stratification could be important for opening the door to the development of new therapies. Further investigations are needed to understand the prevalence of an inflammatory metabotype in patients with aggressive PCa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40170-021-00265-6.

Systematic Optimisation of Microtiter Plate Lectin Assay to Improve Sialic Acid Linkage Detection

AIMS

We aimed to develop a high-throughput lectin assay with minimized background signals to investigate the interactions of lectins and sialic acid glycans, focusing on prostate-specific antigen (PSA).

BACKGROUND

High background signals resulting from nonspecific binding are a significant concern for microtiter plate-based enzyme-linked lectin sorbent assays (ELLSAs), as they can mask specific binding signals and cause false-positive results.

METHODS

In this study, we constructed an ELLSA based on different washing step parameters, including the number of washing cycles, NaCl and Tween-20 concentrations, and the type of blocking agent and evaluated the effects on both specific and nonspecific binding signals. Furthermore, we performed a PSA binding assay using the optimized ELLSA.

RESULTS

The optimal washing parameters based on the highest specific binding signal proposed four cycles of washing steps using a washing buffer containing a high salt concentration (0.5 M NaCl) and mild detergent (0.05% Tween-20). The utilization of the optimized washing parameters in this assay was shown to be sufficient to obtain the optimal binding signals without the use of any blocking agent. Binding assays performed using the optimized ELLSA revealed that the glycan of the PSA sample used in this study mainly consists of terminal α2,6-linked sialic acid, as strongly recognized by Sambucus nigra agglutinin (SNA) with a KD value of 12.38 nM.

CONCLUSION

The ELLSA reported in this study provides a simple yet sensitive assay for sialic acid linkage recognition.

Glycosylation: Rising Potential for Prostate Cancer Evaluation

Simple Summary

Aberrant protein glycosylation is a well-known hallmark of cancer and is associated with differential expression of enzymes such as glycosyltransferases and glycosidases. The altered expression of the enzymes triggers cancer cells to produce glycoproteins with specific cancer-related aberrations in glycan structures. Increasing number of data indicate that glycosylation patterns of PSA and other prostate-originated proteins exert a potential to distinguish between benign prostate disease and cancer as well as among different stages of prostate cancer development and aggressiveness. This review summarizes the alterations in glycan sialylation, fucosylation, truncated O-glycans, and LacdiNAc groups outlining their potential applications in non-invasive diagnostic procedures of prostate diseases. Further research is desired to develop more general algorithms exploiting glycobiology data for the improvement of prostate diseases evaluation.

Abstract

Prostate cancer is the second most commonly diagnosed cancer among men. Alterations in protein glycosylation are confirmed to be a reliable hallmark of cancer. Prostate-specific antigen is the biomarker that is used most frequently for prostate cancer detection, although its lack of sensitivity and specificity results in many unnecessary biopsies. A wide range of glycosylation alterations in prostate cancer cells, including increased sialylation and fucosylation, can modify protein function and play a crucial role in many important biological processes in cancer, including cell signalling, adhesion, migration, and cellular metabolism. In this review, we summarize studies evaluating the prostate cancer associated glycosylation related alterations in sialylation, mainly α2,3-sialylation, core fucosylation, branched N-glycans, LacdiNAc group and presence of truncated O-glycans (sTn, sT antigen). Finally, we discuss the great potential to make use of glycans as diagnostic and prognostic biomarkers for prostate cancer.

Tissue- and Liquid-Based Biomarkers in Prostate Cancer Precision Medicine

Worldwide, prostate cancer (PC) is the second-most-frequently diagnosed male cancer and the fifth-most-common cause of all cancer-related deaths. Suspicion of PC in a patient is largely based upon clinical signs and the use of prostate-specific antigen (PSA) levels. Although PSA levels have been criticised for a lack of specificity, leading to PC over-diagnosis, it is still the most commonly used biomarker in PC management. Unfortunately, PC is extremely heterogeneous, and it can be difficult to stratify patients whose tumours are unlikely to progress from those that are aggressive and require treatment intensification. Although PC-specific biomarker research has previously focused on disease diagnosis, there is an unmet clinical need for novel prognostic, predictive and treatment response biomarkers that can be used to provide a precision medicine approach to PC management. In particular, the identification of biomarkers at the time of screening/diagnosis that can provide an indication of disease aggressiveness is perhaps the greatest current unmet clinical need in PC management. Largely through advances in genomic and proteomic techniques, exciting pre-clinical and clinical research is continuing to identify potential tissue, blood and urine-based PC-specific biomarkers that may in the future supplement or replace current standard practices. In this review, we describe how PC-specific biomarker research is progressing, including the evolution of PSA-based tests and those novel assays that have gained clinical approval. We also describe alternative diagnostic biomarkers to PSA, in addition to biomarkers that can predict PC aggressiveness and biomarkers that can predict response to certain therapies. We believe that novel biomarker research has the potential to make significant improvements to the clinical management of this disease in the near future.

Serum core-type fucosylated prostate-specific antigen index for the detection of high-risk prostate cancer

It is known that core-type fucosylation is higher in prostate cancer cells than in other cancer cell types and is associated with high-risk prostate cancer. Here, we developed an automated microcapillary electrophoresis-based immunoassay system for measuring serum core-type fucosylated prostate-specific antigen (PSA) and evaluated whether the serum fucosylated PSA index (FPI) can detect high-risk prostate cancer. Core-type fucosylated-free PSA was measured by our automated microcapillary electrophoresis-based immunoassay system with Pholiota squarrosa lectin. The FPI was calculated from total PSA and the percentage of fucosylated-free PSA. The optimum model to predict Gleason grade (GG) ≥2 was constructed by multivariate logistic regression analysis. Discrimination was assessed by determining the area under the receiver operator characteristic curve (AUC). The study included 252 men who underwent prostate needle biopsy due to elevated serum PSA levels (4-20 ng/mL), including 138 with GG ≥2. A higher FPI was significantly associated with GG (P < .0001). Multivariate logistic regression analysis showed that age, prostate volume and FPI were significant predictors of GG ≥2. The AUC of FPI and the model were 0.729 (95% confidence interval [CI]: 0.668-0.790) and 0.837 (95% CI: 0.788-0.886), respectively, compared to 0.629 (95% CI: 0.561-0.698) for PSA. Decision curve analysis showed the superior benefit of FPI and the model when compared to PSA. In a cohort with serum PSA levels <20 ng/mL, FPI could differentiate high-risk prostate cancer from biopsy-negative or low-risk prostate cancer. Therefore, FPI could be a useful adjunct in prostate biopsy counseling for men with abnormal PSA levels.

A panel of selected serum protein biomarkers for the detection of aggressive prostate cancer

Background: Current PSA-based tests used to detect prostate cancer (PCa) lack sufficient specificity, leading to significant overdetection and overtreatment. Our previous studies showed that serum fucosylated PSA (Fuc-PSA) and soluble TEK receptor tyrosine kinase (Tie-2) had the ability to predict aggressive (AG) PCa. Additional biomarkers are needed to address this significant clinical problem. Methods: A comprehensive Pubmed search followed by multiplex immunoassays identified candidate biomarkers associated with AG PCa. Subsequently, multiplex and lectin-based immunoassays were applied to a case-control set of sera from subjects with AG PCa, low risk PCa, and non-PCa (biopsy negative). These candidate biomarkers were further evaluated for their ability as panels to complement the prostate health index (phi) in detecting AG PCa. Results: When combined through logistic regression, two panel of biomarkers achieved the best performance: 1) phi, Fuc-PSA, SDC1, and GDF-15 for the detection of AG from low risk PCa and 2) phi, Fuc-PSA, SDC1, and Tie-2 for the detection of AG from low risk PCa and non-PCa, with noticeable improvements in ROC analysis over phi alone (AUCs: 0.942 vs 0.872, and 0.934 vs 0.898, respectively). At a fixed sensitivity of 95%, the panels improved specificity with statistical significance in detecting AG from low risk PCa (76.0% vs 56%, p=0.029), and from low risk PCa and non-PCa (78.2% vs 65.5%, p=0.010). Conclusions: Multivariate panels of serum biomarkers identified in this study demonstrated clinically meaningful improvement over the performance of phi, and warrant further clinical validation, which may contribute to the management of PCa.

Tissue N-linked glycosylation as potential prognostic biomarker for biochemical recurrence-free survival

PURPOSE

Only few biomarkers have been evaluated for their prognostic value following radical prostatectomy. We explored if tissue N-glycosylation shows prognostic properties for biochemical recurrence (BCR)-free survival.

MATERIALS AND METHODS

Tissue N-glycosylation profile was determined from 82 prostate cancer (PCa) patients and prognostic features were compared to clinical and biochemical parameters for BCR-free survival.

RESULTS

Majority presented with Gleason score 3 + 4 (41%), extensive local disease (62%) and without pelvic lymph nodes invasion (83%). Several parameters (low T stage, low Gleason score, low EAU risk groups for BCR, absence of positive surgical margins, high ratio of fucosylated triantennary structures on total of multiantennary structures [3AFc/MA], low ratio of fucosylated biantennary with core-branched N-acetylglucosamine on total of biantennary structures, and high ratio of triantennary structures on total of multiantennary structures) proved to have a univariate beneficial effect on BCR-free survival. Multivariate analysis proved positive surgical margins and 3AFc/MA to be independent prognosticators.

CONCLUSIONS

Tissue N-glycans are a powerful prognostic tool and can be an asset in PCa as the ratio of 3AFc/MA is independently associated with BCR-free survival. This could be of clinical use in guiding patients following radical prostatectomy, e.g. referral to adjuvant radiotherapy. Further elaboration of this biomarker is warranted.

Post-Translational Modifications That Drive Prostate Cancer Progression

While a protein primary structure is determined by genetic code, its specific functional form is mostly achieved in a dynamic interplay that includes actions of many enzymes involved in post-translational modifications. This versatile repertoire is widely used by cells to direct their response to external stimuli, regulate transcription and protein localization and to keep proteostasis. Herein, post-translational modifications with evident potency to drive prostate cancer are explored. A comprehensive list of proteome-wide and single protein post-translational modifications and their involvement in phenotypic outcomes is presented. Specifically, the data on phosphorylation, glycosylation, ubiquitination, SUMOylation, acetylation, and lipidation in prostate cancer and the enzymes involved are collected. This type of knowledge is especially valuable in cases when cancer cells do not differ in the expression or mutational status of a protein, but its differential activity is regulated on the level of post-translational modifications. Since their driving roles in prostate cancer, post-translational modifications are widely studied in attempts to advance prostate cancer treatment. Current strategies that exploit the potential of post-translational modifications in prostate cancer therapy are presented.

Enhancing Comprehensive Analysis of Secreted Glycoproteins from Cultured Cells without Serum Starvation

Glycoproteins secreted by cells play essential roles in the regulation of extracellular activities. Secreted glycoproteins are often reflective of cellular status, and thus glycoproteins from easily accessible bodily fluids can serve as excellent biomarkers for disease detection. Cultured cells have been extensively employed as models in the research fields of biology and biomedicine, and global analysis of glycoproteins secreted from these cells provides insights into cellular activities and glycoprotein functions. However, comprehensive identification and quantification of secreted glycoproteins is a daunting task because of their low abundances compared with the high-abundance serum proteins required for cell growth and proliferation. Several studies employed serum-free media to analyze secreted proteins, but it has been shown that serum starvation, even for a short period of time, can alter protein secretion. To overcome these issues, we developed a method to globally characterize secreted glycoproteins and their N-glycosylation sites from cultured cells by combining selective enrichment of secreted glycoproteins with a boosting approach. The results demonstrated the importance of the boosting sample selection and the boosting-to-sample ratio for improving the coverage of secreted glycoproteins. The method was applied to globally quantify secreted glycoproteins from THP-1 monocytes and macrophages in response to lipopolysaccharides (LPS) and from Hep G2 cells treated with TGF-β without serum starvation. We found differentially secreted glycoproteins in these model systems that showed the cellular response to the immune activation or the epithelial-to-mesenchymal transition. Benefiting from the selective enrichment and the signal enhancement of low-abundance secreted glycoproteins, this method can be extensively applied to study secreted glycoproteins without serum starvation, which will provide a better understanding of protein secretion and cellular activity.

Glycoproteogenomics: Setting the Course for Next-generation Cancer Neoantigen Discovery for Cancer Vaccines

Molecular-assisted precision oncology gained tremendous ground with high-throughput next-generation sequencing (NGS), supported by robust bioinformatics. The quest for genomics-based cancer medicine set the foundations for improved patient stratification, while unveiling a wide array of neoantigens for immunotherapy. Upfront pre-clinical and clinical studies have successfully used tumor-specific peptides in vaccines with minimal off-target effects. However, the low mutational burden presented by many lesions challenges the generalization of these solutions, requiring the diversification of neoantigen sources. Oncoproteogenomics utilizing customized databases for protein annotation by mass spectrometry (MS) is a powerful tool toward this end. Expanding the concept toward exploring proteoforms originated from post-translational modifications (PTMs) will be decisive to improve molecular subtyping and provide potentially targetable functional nodes with increased cancer specificity. Walking through the path of systems biology, we highlight that alterations in protein glycosylation at the cell surface not only have functional impact on cancer progression and dissemination but also originate unique molecular fingerprints for targeted therapeutics. Moreover, we discuss the outstanding challenges required to accommodate glycoproteomics in oncoproteogenomics platforms. We envisage that such rationale may flag a rather neglected research field, generating novel paradigms for precision oncology and immunotherapy.

Impedimetric aptamer-based glycan PSA score for discrimination of prostate cancer from other prostate diseases

Prostate specific antigen (PSA) is the common biomarker for prostate cancer (PCa). However, its lack of specificity to differentiate PCa from benign prostate disorders stimulates the search for alternative cancer biomarkers to improve the clinical management of the patients. Different studies have described changes in the core-fucosylation level of PSA between PCa patients and healthy controls. To exploit these findings, we have adapted an impedimetric aptamer-based sensor to the dual recognition of PSA. Two different aptamers, PSAG-1 and anti-PSA, are immobilized onto two adjacent nanostructured gold electrodes. The direct binding from diluted serum samples of specific glycosylated-PSA to the first sensor and total PSA to the second one leads to changes in the charge transfer resistance, which correlate to the amount of glycosylated and total PSA in the sample. The sensors are able to measure PSA in serum with a dynamic range between 0.26 and 62.5 ng/mL (PSAG-1) and from 0.64 to 62.5 ng/mL (anti-PSA), with a reproducibility of 5.4 %. The final output of the proposed platform is the ratio between PSAG-1 reactive PSA and total PSA, defined as the glycan score. The glycan score was tested in serum samples from patients with different pathologies, showing excellent correlation between the measured score and the known diagnosis of the patients. Hence this dual aptamer-based impedimetric biosensor could be used as a minimally invasive method for the diagnosis of prostate cancer.

Separation based characterization methods for the N-glycosylation analysis of prostate-specific antigen

Prostate cancer has the highest malignancy rate diagnosed in men worldwide. Albeit, the gold standard serum prostate-specific antigen (PSA) assays reduced the mortality rate of the disease, the number of false positive diagnoses steeply increased. Therefore, there is an urgent need for complementary biomarkers to enhance the specificity and selectivity of current diagnostic methods. Information about PSA glycosylation can help to fulfill this gap as alterations of its carbohydrate moieties due to cancerous transformation may represent additional markers to distinguish malignant from benign tumors. However, development of suitable methods and instrumentations to investigate the N-glycosylation profile of PSA represents a challenge. In this paper, we critically review the current bioanalytical trends and strategies in the field of PSA glycobiomarker research focusing on separation based characterization methods.

Characterisation of the main PSA glycoforms in aggressive prostate cancer

Serum levels of prostate specific antigen (PSA) are commonly used for prostate cancer (PCa) detection. However, their lack of specificity to distinguish benign prostate pathologies from PCa, or indolent from aggressive PCa have prompted the study of new non-invasive PCa biomarkers. Aberrant glycosylation is involved in neoplastic progression and specific changes in PSA glycosylation pattern, as the reduction in the percentage of α2,6-sialic acid (SA) are associated with PCa aggressiveness. In this study, we have characterised the main sialylated PSA glycoforms from blood serum of aggressive PCa patients and have compared with those of standard PSA from healthy individuals’ seminal plasma. PSA was immunoprecipitated and α2,6-SA were separated from α2,3-SA glycoforms using SNA affinity chromatography. PSA N-glycans were released, labelled and analysed by hydrophilic interaction liquid chromatography combined with exoglycosidase digestions. The results showed that blood serum PSA sialylated glycoforms containing GalNAc residues were largely increased in aggressive PCa patients, whereas the disialylated core fucosylated biantennary structures with α2,6-SA, which are the major PSA glycoforms in standard PSA from healthy individuals, were markedly reduced in aggressive PCa. The identification of these main PSA glycoforms altered in aggressive PCa opens the way to design specific strategies to target them, which will be useful to improve PCa risk stratification.

Mass spectrometry in clinical glycomics: The path from biomarker identification to clinical implementation

Over the past decades, the genome and proteome have been widely explored for biomarker discovery and personalized medicine. However, there is still a large need for improved diagnostics and stratification strategies for a wide range of diseases. Post-translational modification of proteins by glycosylation affects protein structure and function, and glycosylation has been implicated in many prevalent human diseases. Numerous proteins for which the plasma levels are nowadays evaluated in clinical practice are glycoproteins. While the glycosylation of these proteins often changes with disease, their glycosylation status is largely ignored in the clinical setting. Hence, the implementation of glycomic markers in the clinic is still in its infancy. This is for a large part caused by the high complexity of protein glycosylation itself and of the analytical techniques required for their robust quantification. Mass spectrometry-based workflows are particularly suitable for the quantification of glycans and glycoproteins, but still require advances for their transformation from a biomedical research setting to a clinical laboratory. In this review, we describe why and how glycomics is expected to find its role in clinical tests and the status of current mass spectrometry-based methods for clinical glycomics.

Analysis of serum glycome by lectin microarrays for prostate cancer patients - a search for aberrant glycoforms

This is the first work focused on glycoprofiling of whole N- and O- glycome using lectins in an array format applied for analysis of serum samples from healthy individuals, benign prostate hyperplasia (BPH) patients, and prostate cancer (PCa) patients. Lectin microarray was prepared using traditional lectins with the incorporation of 2 recombinant bacterial lectins and 3 human lectins (17 lectins in total). Clinical validation of glycans as biomarkers was done in two studies: discrimination of healthy individuals with BPH patients vs. PCa patients (C vs. PCa) and discrimination of healthy individuals vs. BPH and PCa patients (H vs. PCond). Single lectins (17 lectins) and a combination of two lectins (136 binary lectin combinations) were applied in the clinical validation of glycan biomarkers providing 153 AUC values from ROC curves for both studies (C vs. PCa and H vs. PCond). Potential N- and O-glycans as biomarkers were identified and possible carriers of these glycans are shortly discussed.

Validating fPSA Glycoprofile as a Prostate Cancer Biomarker to Avoid Unnecessary Biopsies and Re-Biopsies

BACKGROUND

To compare the clinical performance of a new PCa serum biomarker based on fPSA glycoprofiling to fPSA% and PHI.

METHODS

Serum samples from men who underwent prostate biopsy due to increased PSA were used. A comparison between two equal groups (with histologically confirmed PCa or benign, non-cancer condition) was used for the clinical validation of a new glycan-based PCa oncomarker. SPSS and R software packages were used for the multiparametric analyses of the receiver operating curve (ROC) and for genetic algorithm metaheuristics.

RESULTS

When comparing the non-cancer and PCa cohorts, the combination of four fPSA glycoforms with two clinical parameters (PGI, prostate glycan index (PGI)) showed an area under receiver operating curve (AUC) value of 0.821 (95% CI 0.754-0.890). AUC values were 0.517 for PSA, 0.683 for fPSA%, and 0.737 for PHI. A glycan analysis was also applied to discriminate low-grade tumors (GS = 6) from significant tumors (GS ≥ 7).

CONCLUSIONS

Compared to PSA on its own, or fPSA% and the PHI, PGI showed improved discrimination between presence and absence of PCa and in predicting clinically significant PCa. In addition, the use of PGI would help practitioners avoid 63.5% of unnecessary biopsies, while the use of fPSA% and PHI would help avoid 17.5% and 33.3% of biopsies, respectively, while missing four significant tumors (9.5%).

Microfibril associated protein 4 (MFAP4) is a carrier of the tumor associated carbohydrate sialyl-Lewis x (sLex) in pancreatic adenocarcinoma

Late diagnosis of pancreatic ductal adenocarcinoma (PDA) is one of the reasons of its low 5-year survival rate and it is due to its unspecific symptoms during the first stages of the disease and the lack of reliable serological markers. Since PDA shows an altered glycan expression, here we have focused on finding novel potential biomarkers, namely glycoproteins that express the tumor associated carbohydrate structure sialyl-Lewis x (sLe^x), which is described in PDA. Through a glycoproteomic approach, we have analyzed target proteins containing sLe^x from PDA tissues by 2DE and immunodetection techniques, and have identified by mass spectrometry the protein MFAP4 as a carrier of sLe^x in PDA. MFAP4 showed a higher expression in PDA tissues compared with pancreatic control tissues. In addition, the colocalization of sLe^x over MFAP4 was found only in PDA and not in control pancreatic tissues. The analysis of MFAP4 expression in PDA cell lines and their secretome, in combination with immunohistochemistry of pancreatic tissues, revealed that MFAP4 was not produced by PDA cells, but it was found in the pancreatic extracellular matrix. The specificity of MFAP4 glycoform containing sLe^x in PDA tissues shows its relevance as a potential PDA biomarker. SIGNIFICANCE: Despite advances in the field of cancer research, pancreatic ductal adenocarcinoma (PDA) lacks of a specific and sensitive biomarker for its early detection, when curative resection is still possible before metastases arise. Thus, efforts to discover new PDA biomarkers represent the first line in the fight against the increase of its incidence reported in recent years. Glycan alterations on glycoconjugates, such as glycoproteins have emerged as a rich source for the identification of novel cancer markers. In the present work, we aimed to shed light on novel biomarkers based on altered glycosylation in PDA, in particular those glycoproteins of PDA tissues carrying the tumor carbohydrate antigen sialyl-Lewis x (sLe^x). Through a glycoproteomic approach, we have shown that the glycoprotein MFAP4 carries sLe^x in PDA tissues and not in control pancreatic tissues. MFAP4 is found in the extracellular matrix in PDA and although its role in cancer progression is unclear, its sLe^x glycoform could be a potential biomarker in pancreatic ductal adenocarcinoma.

Advances in the discovery of novel biomarkers for cancer: spotlight on protein N-glycosylation

Progress on glycosylation and tumor markers has not been extensively reported. Glycosylation plays an important part in post-translational modification. Previous research on glycosylation-modified biomarkers has lagged behind due to insufficient understanding of glycosylation-related regulations. However, some new methods and ideas illustrated in recent research may provide new inspirations in the field. This article aims to review current advances in revealing relationship between tumors and abnormal N-glycosylation and discuss leading-edge applications of N-glycosylation in developing novel tumor biomarkers.