The Abnormal Glycopatterns of Salivary Glycoproteins in Esophageal Squamous Cell Carcinoma Patients

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.

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022

The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.

Latest insights into the global epidemiological features, screening, early diagnosis and prognosis prediction of esophageal squamous cell carcinoma

As a highly invasive carcinoma, esophageal cancer (EC) was the eighth most prevalent malignancy and the sixth leading cause of cancer-related death worldwide in 2020. Esophageal squamous cell carcinoma (ESCC) is the major histological subtype of EC, and its incidence and mortality rates are decreasing globally. Due to the lack of specific early symptoms, ESCC patients are usually diagnosed with advanced-stage disease with a poor prognosis, and the incidence and mortality rates are still high in many countries, especially in China. Therefore, enormous challenges still exist in the management of ESCC, and novel strategies are urgently needed to further decrease the incidence and mortality rates of ESCC. Although the key molecular mechanisms underlying ESCC pathogenesis have not been fully elucidated, certain promising biomarkers are being investigated to facilitate clinical decision-making. With the advent and advancement of high-throughput technologies, such as genomics, proteomics and metabolomics, valuable biomarkers with high sensitivity, specificity and stability could be identified for ESCC. Herein, we aimed to determine the epidemiological features of ESCC in different regions of the world, especially in China, and focused on novel molecular biomarkers associated with ESCC screening, early diagnosis and prognosis prediction.

N-Glycan Profiles of Neuraminidase from Avian Influenza Viruses

The cleavage of sialic acids by neuraminidase (NA) facilitates the spread of influenza A virus (IV) descendants. Understanding the enzymatic activity of NA aids research into the transmission of IVs. An effective method for purifying NA was developed using p-aminophenyloxamic acid-modified functionalized hydroxylated magnetic particles (AAMPs), and from 0.299 to 0.401 mg of NA from eight IV strains was isolated by 1 mg AAMP. A combination of lectin microarrays and MALDI-TOF/TOF-MS was employed to investigate the N-glycans of isolated NAs. We found that more than 20 N-glycans were identified, and 16 glycan peaks were identical in the strains derived from chicken embryo cultivation. Multi-antennae, bisected, or core-fucosylated N-glycans are common in all the NAs. The terminal residues of N-glycans are predominantly composed of galactose and N-acetylglucosamine residues. Meanwhile, sialic acid residue was uncommon in these N-glycans. Further computational docking analysis predicted the interaction mechanism between NA and p-aminophenyloxamic acid.

The glycopatterns of Pseudomonas aeruginosa as a potential biomarker for its carbapenem resistance

IMPORTANCE

Bacterial surface glycans are an attractive therapeutic target in response to antibiotics; however, current knowledge of the corresponding mechanisms is rather limited. Antimicrobial susceptibility testing, genome sequencing, and MALDI-TOF MS, commonly used in recent years to analyze bacterial resistance, are unable to rapidly and efficiently establish associations between glycans and resistance. The discovery of new antimicrobial strategies still requires the introduction of promising analytical methods. In this study, we applied lectin microarray technology and a machine-learning model to screen for important glycan structures associated with carbapenem-resistant P. aeruginosa. This work highlights that specific glycopatterns can be important biomarkers associated with bacterial antibiotic resistance, which promises to provide a rapid entry point for exploring new resistance mechanisms in pathogens.

Beneficial or detrimental: Recruiting more types of benign cases for cancer diagnosis based on salivary glycopatterns

With the advantages of convenient, painless and non-invasive collection, saliva holds great promise as a valuable biomarker source for cancer detection, pathological assessment and therapeutic monitoring. Salivary glycopatterns have shown significant potential for cancer screening in recent years. However, the understanding of benign lesions at non-cancerous sites in cancer diagnosis has been overlooked. Clarifying the influence of benign lesions on salivary glycopatterns and cancer screening is crucial for advancing the development of salivary glycopattern-based diagnostics. In this study, 2885 samples were analyzed using lectin microarrays to identify variations in salivary glycopatterns according to the number, location, and type of lesions. By utilizing our previously published data of tumor-associated salivary glycopatterns, the performance of machine learning algorithm for cancer screening was investigated to evaluate the effect of adding benign disease cases to the control group. The results demonstrated that both the location and number of lesions had discernible effects on salivary glycopatterns. And it was also revealed that incorporating a broad range of benign diseases into the controls improved the classifier's performance in distinguishing cancer cases from controls. This finding holds guiding significance for enhancing salivary glycopattern-based cancer screening and facilitates their practical implementation in clinical settings.

Site-specific, covalent immobilization of PNGase F on magnetic particles mediated by microbial transglutaminase

In the workflow of global N-glycosylation analysis, endoglycosidase-mediated removal of glycans from glycoproteins is an essential and rate-limiting step. Peptide-N-glycosidase F (PNGase F) is the most appropriate and efficient endoglycosidase for the removal of N-glycans from glycoproteins prior to analysis. Due to the high demand for PNGase F in both basic and industrial research, convenient and efficient methods are urgently needed to generate PNGase F, preferably in the immobilized form to solid phases. However, there is no integrated approach to implement both efficient expression, and site-specific immobilization of PNGase F. Herein, efficient production of PNGase F with a glutamine tag in Escherichia coli and site-specific covalent immobilization of PNGase F with this special tag via microbial transglutaminase (MTG) is described. PNGase F was fused with a glutamine tag to facilitate the co-expression of proteins in the supernatant. The glutamine tag was covalently and site-specifically transformed to primary amine-containing magnetic particles, mediated by MTG, to immobilize PNGase F. Immobilized PNGase F could deglycosylate substrates with identical enzymatic performance to that of the soluble counterpart, and exhibit good reusability and thermal stability. Moreover, the immobilized PNGase F could also be applied to clinical samples, including serum and saliva.

Evaluation of CSTB and DMBT1 expression in saliva of gastric cancer patients and controls

Background

Gastric cancer (GC) is the fifth most common cancer and the third cause of cancer deaths globally, with late diagnosis, low survival rate, and poor prognosis. This case-control study aimed to evaluate the expression of cystatin B (CSTB) and deleted in malignant brain tumor 1 (DMBT1) in the saliva of GC patients with healthy individuals to construct diagnostic algorithms using statistical analysis and machine learning methods.

Methods

Demographic data, clinical characteristics, and food intake habits of the case and control group were gathered through a standard checklist. Unstimulated whole saliva samples were taken from 31 healthy individuals and 31 GC patients. Through ELISA test and statistical analysis, the expression of salivary CSTB and DMBT1 proteins was evaluated. To construct diagnostic algorithms, we used the machine learning method.

Results

The mean salivary expression of CSTB in GC patients was significantly lower (115.55 ± 7.06, p = 0.001), and the mean salivary expression of DMBT1 in GC patients was significantly higher (171.88 ± 39.67, p = 0.002) than the control.

Multiple linear regression analysis demonstrated that GC was significantly correlated with high levels of DMBT1 after controlling the effects of age of participants (R² = 0.20, p < 0.001).

Considering salivary CSTB greater than 119.06 ng/mL as an optimal cut-off value, the sensitivity and specificity of CSTB in the diagnosis of GC were 83.87 and 70.97%, respectively. The area under the ROC curve was calculated as 0.728. The optimal cut-off value of DMBT1 for differentiating GC patients from controls was greater than 146.33 ng/mL (sensitivity = 80.65% and specificity = 64.52%). The area under the ROC curve was up to 0.741.

As a result of the machine learning method, the area under the receiver-operating characteristic curve for the diagnostic ability of CSTB, DMBT1, demographic data, clinical characteristics, and food intake habits was 0.95. The machine learning model’s sensitivity, specificity, and accuracy were 100, 70.8, and 80.5%, respectively.

Conclusion

Salivary levels of DMBT1 and CSTB may be accurate in diagnosing GCs. Machine learning analyses using salivary biomarkers, demographic, clinical, and nutrition habits data simultaneously could provide affordability models with acceptable accuracy for differentiation of GC by a cost-effective and non-invasive method.

Role of salivary glycopatterns for oral microbiota associated with gastric cancer

Microbiota in the oral cavity plays an important role in maintaining human health. Our previous studies have revealed significant alterations of salivary glycopatterns in gastric cancer (GC) patients, but it is unclear whether these altered salivary glycopatterns can cause the dysbiosis of oral microbiota. In this study, the oral microbiome of healthy volunteers (HVs) and GC patients were detected. The neoglycoproteins were then synthesized according to the altered glycopatterns in GC patients and used to explore the effects of specific salivary glycopattern against oral microbiota. The results showed that five species were significantly increased (p < 0.05) while two species were significantly decreased (p < 0.01) in the saliva of GC patients compared with that of HVs. And the fucose-neoglycoproteins (30-100 μg/mL) could reduce the adhesion and toxicity of Aggregatibacter segnis (A. segnis) to oral cells (HOEC and CAL-27), change the glycan structures of lipopolysaccharide on the surface of A. segnis, and enhance the capacity of A. segnis to trigger innate immune responses. This study revealed that the changes of salivary protein glycopatterns in GC patients might contribute to the dysbiosis of oral microbiota, and had important implications in developing new carbohydrate drugs to maintain a balanced microbiota in the oral.

Glycan characteristics of human heart constituent cells maintaining organ function: relatively stable glycan profiles in cellular senescence

Cell surface glycoproteins, which are good indicators of cellular types and biological function; are suited for cell evaluation. Tissue remodeling using various cells is a key feature of regenerative therapy. For artificial heart remodeling, a mixture of heart constituent cells has been investigated for organ assembly, however, the cellular characteristics remain unclear. In this study, the glycan profiles of human cardiomyocytes (HCMs), human cardiac fibroblasts (HCFs), and human vascular endothelial cells (ECs) were analyzed using evanescent-field lectin microarray analysis, a tool of glycan profiling, to clarify the required cellular characteristics. We found that ECs had more “α1-2fucose” and “core α1-6fucose” residues than other cells, and that “α2-6sialic acid” residue was more abundant in ECs and HCMs than in HCFs. HCFs showed higher abundance of “β-galactose” and “β-N-acetylgalactosamine” residues on N-glycan and O-glycan, respectively, compared to other cells. Interestingly, cardiac glycan profiles were insignificantly changed with cellular senescence. The residues identified in this study may participate in organ maintenance by contributing to the preservation of glycan components. Therefore, future studies should investigate the roles of glycans in optimal tissue remodeling since identifying cellular characteristics is important for the development of regenerative therapies.