Identification of serum glycobiomarkers for Hepatocellular Carcinoma using lectin microarrays

Glycoproteomics of Gastrointestinal Cancers and Its Use in Clinical Diagnostics

Cancer is a leading cause of death worldwide, resulting in substantial economic costs. Because cancer is a complex, heterogeneous group of diseases affecting a variety of cells, its detection may sometimes be difficult. Herein we review a large group of the gastrointestinal cancers (oral, esophageal, stomach, pancreatic, liver, and bowel cancers) and the possibility of using glycans conjugated to protein backbones for less-invasive diagnoses than the commonly used endoscopic approaches. The reality of bacterial N-glycosylation and the effect of epithelial mucosa on gut microbiota are discussed. Current advantages, barriers, and advantages in the prospective use of selected glycomic approaches in clinical practice are also detailed.

Association between serum IgM and all-cause mortality risk in Chinese centenarians: a prospective cohort study

BACKGROUND

We investigated the associations between IgM, IgG, IgA, and IgE levels and all-cause mortality risk in Chinese centenarians.

METHODS

All participants were from the China Hainan Centenarian Cohort Study. Eligible participants were divided into quartiles based on their IgM, IgG, IgA, and IgE levels. We used restricted cubic spline analyses, Cox regression analyses, and Kaplan-Meier survival curves to analyze associations between IgM, IgG, IgA, and IgE and all-cause mortality risk.

RESULTS

A total of 906 centenarian participants were included in this study (81.2% female; median age, 102 years). During a median follow-up of 30.1 months, 838 (92.5%) participants died. Restricted cubic spline analysis revealed a nonlinear relationship ("L" type) between serum IgM level and all-cause mortality. Compared with the higher three quartiles of serum IgM level, the lowest quartile was associated with a higher risk of death (Q1 versus Q2-Q4: HR, 1.365; 95% CI, 1.166-1.598; P < 0.001). Among individuals for whom IgM < 0.708 g/L (Q1), the risk of all-cause mortality was 36.5% higher. Kaplan-Meier analyses showed that centenarians with lower serum IgM levels had significantly shorter median survival time (Q1 versus Q2-Q4: 26 months versus 32 months, log-rank P = 0.001).

CONCLUSION

Serum IgM levels in centenarians significantly correlated with the risk of death, suggesting that they are suitable for predicting the overall risk of death in centenarians and can be used as an independent predictor of death.

Glycosylation in cancer as a source of biomarkers

INTRODUCTION

Glycosylation, the process of glycan synthesis and attachment to target molecules, is a crucial and common post-translational modification (PTM) in mammalian cells. It affects the protein's hydrophilicity, charge, solubility, structure, localization, function, and protection from proteolysis. Aberrant glycosylation in proteins can reveal new detection and therapeutic Glyco-biomarkers, which help to improve accurate early diagnosis and personalized treatment. This review underscores the pivotal role of glycans and glycoproteins as a source of biomarkers in human diseases, particularly cancer.

AREAS COVERED

This review delves into the implications of glycosylation, shedding light on its intricate roles in cancer-related cellular processes influencing biomarkers. It is underpinned by a thorough examination of literature up to June 2024 in PubMed, Scopus, and Google Scholar; concentrating on the terms: (Glycosylation[Title/Abstract]) OR (Glycan[Title/Abstract]) OR (glycoproteomics[Title/Abstract]) OR (Proteoglycans[Title/Abstract]) OR (Glycomarkers[Title/Abstract]) AND (Cancer[Title/Abstract]) AND ((Diagno*[Title/Abstract]) OR (Progno*[Title/Abstract])).

EXPERT OPINION

Glyco-biomarkers enhance early cancer detection, allow early intervention, and improve patient prognoses. However, the abundance and complex dynamic glycan structure may make their scientific and clinical application difficult. This exploration of glycosylation signatures in cancer biomarkers can provide a detailed view of cancer etiology and instill hope in the potential of glycosylation to revolutionize cancer research.

Deciphering disease through glycan codes: leveraging lectin microarrays for clinical insights

Glycosylation, a crucial posttranslational modification, plays a significant role in numerous physiological and pathological processes. Lectin microarrays, which leverage the high specificity of lectins for sugar binding, are ideally suited for profiling the glycan spectra of diverse and complex biological samples. In this review, we explore the evolution of lectin detection technologies, as well as the applications and challenges of lectin microarrays in analyzing the glycome profiles of various clinical samples, including serum, saliva, tissues, sperm, and urine. This review not only emphasizes significant advancements in the high-throughput analysis of polysaccharides but also provides insight into the potential of lectin microarrays for diagnosing and managing diseases such as tumors, autoimmune diseases, and chronic inflammation. We aim to provide a clear, concise, and comprehensive overview of the use of lectin microarrays in clinical settings, thereby assisting researchers in conducting clinical studies in glycobiology.

Machine Learning Reveals Serum Glycopatterns as Potential Biomarkers for the Diagnosis of Nonalcoholic Fatty Liver Disease (NAFLD)

Nonalcoholic fatty liver disease (NAFLD) has emerged as the predominant chronic liver condition globally, and underdiagnosis is common, particularly in mild cases, attributed to the asymptomatic nature and traditional ultrasonography's limited sensitivity to detect early-stage steatosis. Consequently, patients may experience progressive liver pathology. The objective of this research is to ascertain the efficacy of serum glycan glycopatterns as a potential diagnostic biomarker, with a particular focus on the disease's early stages. We collected a total of 170 serum samples from volunteers with mild-NAFLD (Mild), severe-NAFLD (Severe), and non-NAFLD (None). Examination via lectin microarrays has uncovered pronounced disparities in serum glycopatterns identified by 19 distinct lectins. Following this, we employed four distinct machine learning algorithms to categorize the None, Mild, and Severe groups, drawing on the alterations observed in serum glycopatterns. The gradient boosting decision tree (GBDT) algorithm outperformed other models in diagnostic accuracy within the validation set, achieving an accuracy rate of 95% in differentiating the None group from the Mild group. Our research indicates that employing lectin microarrays to identify alterations in serum glycopatterns, when integrated with advanced machine learning algorithms, could constitute a promising approach for the diagnosis of NAFLD, with a special emphasis on its early detection.

Medical Relevance, State-of-the-Art and Perspectives of "Sweet Metacode" in Liquid Biopsy Approaches

This review briefly introduces readers to an area where glycomics meets modern oncodiagnostics with a focus on the analysis of sialic acid (Neu5Ac)-terminated structures. We present the biochemical perspective of aberrant sialylation during tumourigenesis and its significance, as well as an analytical perspective on the detection of these structures using different approaches for diagnostic and therapeutic purposes. We also provide a comparison to other established liquid biopsy approaches, and we mathematically define an early-stage cancer based on the overall prognosis and effect of these approaches on the patient's quality of life. Finally, some barriers including regulations and quality of clinical validations data are discussed, and a perspective and major challenges in this area are summarised.

Differential Glycoform Analysis of MUC1 Derived from Biological Specimens Using an Antibody-Overlay Lectin Microarray

The association between altered glycosylation of MUC1 and various disease events has sparked significant interest. However, analytical technologies to investigate the disease-related glycoforms of endogenous MUC1 in blood and tissue specimens are limited. Therefore, we devised a reliable technique for differential analysis of endogenous MUC1 glycoforms based on an antibody-assisted lectin microarray. Its highly sensitive detection aids in analyzing soluble MUC1 from relatively small amounts of serum via a simple enrichment process. Micro-/macro-dissection of the MUC1-positive region is combined with glycoform analysis of the membrane-tethered MUC1. Thus, we have optimized the protocol for sample qualification using immunohistochemistry, sample pretreatment for tissue sections, protein extraction, purification via immunoprecipitation, and the antibody-overlay lectin microarray, which are sequentially essential for differential glycoform analysis of endogenous MUC1.

Bittersweet Sugars: How Unusual Glycan Structures May Connect Epithelial-to-Mesenchymal Transition and Multidrug Resistance in Cancer

Cancer cells are characterized by metabolic reprogramming, which enables their survival in of-ten inhospitable conditions. A very well-documented example that has gained attraction in re-cent years and is already considered a hallmark of transformed cells is the reprogramming of carbohydrate metabolism. Such a feature, in association with the differential expression of en-zymes involved in the biosynthesis of glycoconjugates, generically known as glycosyltransfer-ases, contributes to the expression of structurally atypical glycans when compared to those ex-pressed in healthy tissues. The latest studies have demonstrated that glycophenotypic alterations are capable of modulating multifactorial events essential for the development and/or progres-sion of the disease. Herein, we will address the importance of glycobiology in modern medi-cine, focusing on the ability of unusual/truncated O-linked glycans to modulate two complex and essential phenomena for cancer progression: the acquisition of the multidrug resistance (MDR) phenotype and the activation of molecular pathways associated with the epithelial-mesenchymal transition (EMT) process, an event deeply linked with cancer metastasis.

FNBP4 is a Potential Biomarker Associated with Cuproptosis and Promotes Tumor Progression in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that lacks an efficient therapeutic approach because of its elusive molecular mechanisms. This study aimed to investigate the biological function and potential mechanism of formin-binding protein 4 (FNBP4) in HCC.

Methods

FNBP4 expression in tissues and cells were detected by quantitative real-time PCR (qRT‒PCR), Western blot, and immunohistochemistry (IHC). The Kaplan-Meier method was used to explore the correlation between the FNBP4 expression and clinical survival. MTT, EdU incorporation, colony formation, and Transwell assays were performed to evaluate the function of FNBP4 in cell proliferation and migration in vitro. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to explore the potential mechanism of FNBP4. The prognostic risk signature and nomogram were constructed to demonstrate the prognostic value of FNBP4.

Results

We found that FNBP4 was upregulated in patients with HCC and associated with poor overall survival (OS). Furthermore, knockdown of FNBP4 inhibited the proliferation and migration in HCC cells. Then, we performed a KEGG pathway analysis of the coexpressed genes associated with FNBP4 and found that FNBP4 may be associated with tumor-related signaling pathways and cuproptosis. We verified that FNBP4 could cause cell cycle progression and inactivation of the hippo signaling pathway. A prognostic risk signature containing three FNBP4-related differentially expressed cuproptosis regulators (DECRs) was established and can be used as an independent risk factor to evaluate the prognosis of patients with HCC. In addition, a nomogram including a risk score and clinicopathological factors was used to predict patient survival probabilities.

Conclusion

FNBP4, as a potential biomarker associated with cuproptosis, promotes HCC cell proliferation and metastasis. We provide a new potential strategy for HCC treatment by targeting FNBP4.