Serum uric acid levels and health outcomes in CKD: a prospective cohort study.

BACKGROUND: Hyperuricemia is prevalent in individuals with chronic kidney disease (CKD). Elevated serum uric acid (SUA) concentrations have been considered an independent risk factor for the onset of CKD. However, the relationship between SUA concentrations and long-term health outcomes among patients with CKD remains unclear. METHODS: We performed a prospective cohort study with nationally representative sample to investigate the relationship between SUA concentrations and mortality risk including all-cause, cardiovascular disease (CVD) and cancer mortality, among patients with CKD. The weighted restricted cubic spline analyses combined with the multivariate-adjusted Cox proportional hazard models were used to test the nonlinearity of relationship. RESULTS: The 6642 patients participating in National Health and Nutrition Examination Survey 1999-2018 were enrolled. During 656 885 person-months of follow-up time, 2619 all-cause deaths were recorded, including 1030 CVD deaths and 458 cancer deaths. Our study presented J-shaped non-linear relationships between SUA concentrations and all-cause and CVD mortality with inflection points at 311.65 µmol/L and 392.34 µmol/L, respectively. When SUA concentration was higher than those inflection points, every increase of 50 µmol/L SUA was associated with 11.7% and 17.0% greater multivariable-adjusted hazard ratio of all-cause and CVD mortality, respectively. In addition, a negative linear correlation with cancer mortality was detected. CONCLUSION: These findings suggested that maintaining appropriate SUA concentrations may improve long-term health outcomes among CKD patients. The corresponding inflection points of J-shaped non-linear relationships were 311.65 and 392.34 µmol/L for all-cause and CVD mortality. Further clinical trials are required to investigate uric acid-lowering targets.

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.

Antidiabetic activity of Tartary buckwheat protein-derived peptide AFYRW and its effects on protein glycosylation of pancreas in mice.

Diabetes Mellitus (DM) is one of the most important public health problems, and new antidiabetic drugs with fewer side effects are urgently needed. Here, we measured the antidiabetic effects of an antioxidant peptide (Ala-Phe-Tyr-Arg-Trp, AFYRW) from Tartary Buckwheat Albumin (TBA) in a high-fat diet/streptozotocin (HFD/STZ)-induced diabetic mouse model. The data showed that AFYRW suppressed hepatocyte steatosis and triglycerides while ameliorating insulin resistance in mice. Successively, the influence of AFYRW on aberrant protein glycosylation in diabetic mice was further investigated by lectin microarrays. The results suggested AFYRW could restore the expression of GalNAc, GalNAcα1-3Gal and GalNAcα1-3Galß1-3/4Glc recognized by PTL-I, Siaα2-3Galß1-4Glc(NAc)/Glc, Siaα2-3Gal, Siaα2-3 and Siaα2-3GalNAc recognized by MAL-II, terminating in GalNAcα/ß1-3/6Gal recognized by WFA and αGalNAc, αGal, anti-A and B recognized by GSI-I to normal levels in the pancreas of HFD-STZ-induced diabetic mice. This work may provide new targets for the future discovery of potential biomarkers to evaluate the efficacy of food-derived antidiabetic drugs based on precise alterations of glycopatterns in DM.

Joint Application of Multiple Inflammatory Cytokines in Diagnosis of Gout Flare.

Purpose: This study aimed to explore the accuracy for joint application of inflammatory cytokines in diagnosis of gout flare by comparison with peripheral blood cells. Methods: We collected the clinical data of 96 acute gout patients and 144 remission gout patients, and compared the levels of peripheral blood cells, inflammatory cytokines and blood biochemistry indexes between acute and remission gout. We respectively assessed the area under curves (AUCs) for single and multiple inflammatory cytokines including C-reactive protein (CRP), interleukin-1ß (IL-1ß), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α), and single and multiple peripheral blood cells including platelet (PLT), white blood cell (WBC), percentages of neutrophils (N%), lymphocytes (L%), eosinophils (E%), basophils (B%) in diagnosis of acute gout by receiver operating characteristic (ROC) curve analysis. Results: By contrast with remission gout, the levels of PLT, WBC, N%, CRP, IL-1ß, IL-6 and TNF-α increased, and the levels of L%, E% and B% decreased in acute gout. The AUCs of PLT, WBC, N%, L%, E% and B% in diagnosis of acute gout were respectively 0.591, 0.601, 0.581, 0.567, 0.608 and 0.635, while the AUC for joint application of these peripheral blood cells was 0.674. Moreover, the AUCs of CRP, IL-1ß, IL-6 and TNF-α in diagnosis of acute gout were respectively 0.814, 0.683, 0.622 and 0.746, while the AUC for joint application of these inflammatory cytokines was 0.883, reflecting significantly higher levels than peripheral blood cells. Conclusion: The joint application of multiple inflammatory cytokines can better distinguish acute gout from remission gout compared with peripheral blood cells.

Mutual regulation between glycosylation and transforming growth factor-ß isoforms signaling pathway.

Transforming growth factor-beta (TGF-ß) superfamily members orchestrate a wide breadth of biological processes. Through Sma and Mad (Smad)-related dependent or noncanonical pathways, TGF-ß members involve in the occurrence and development of many diseases such as cancers, fibrosis, autoimmune diseases, cardiovascular diseases and brain diseases. Glycosylation is one kind of the most common posttranslational modifications on proteins or lipids. Abnormal protein glycosylation can lead to protein malfunction and biological process disorder, thereby causing serious diseases. Previously, researchers commonly make comprehensive systematic overviews on the roles of TGF-ß signaling in a specific disease or biological process. In recent years, more and more evidences associate glycosylation modification with TGF-ß signaling pathway, and we can no longer disengage and ignore the roles of glycosylation from TGF-ß signaling to make investigation. In this review, we provide an overview of current findings involved in glycosylation within TGF-ßs and theirs receptors, and the interaction effects between glycosylation and TGF-ß subfamily signaling, concluding that there is an intricate mutual regulation between glycosylation and TGF-ß signaling, hoping to present the glycosylation regulatory patterns that concealed in TGF-ßs signaling pathways.

[Glycosphingolipid-mediated apoptosis and tumor therapy: a review].

Glycosphingolipids (GSLs) are widely distributed in the phospholipid bilayer of various cell membranes, which play an important role in maintaining cell membrane stability, and regulate various cellular processes including adhesion, proliferation, apoptosis and recognition, as well as participate in various cellular activities. In addition, GSLs are not only involved in the process of apoptosis, but also regulate multiple signals in tumorigenesis and tumor development. The tumor-associated GSLs are expected to be used as diagnostic markers and immunotherapeutic targets for malignant tumors. These findings have important implications for the study of apoptosis and provide the new direction of tumor therapy. This review summarized the latest research progress of GSLs-mediated apoptosis and its effect on the genesis, development and metastasis of tumor cells. Moreover, we discussed the metabolic pathway of GSLs-mediated apoptosis and its application in tumor therapy, as well as the development prospect of targeted therapy strategies based on GSLs.

Diagnosis of hepatocellular carcinoma based on salivary protein glycopatterns and machine learning algorithms.

OBJECTIVES: Hepatocellular carcinoma (HCC) is difficult to diagnose early and progresses rapidly, making it one of the most deadly malignancies worldwide. This study aimed to evaluate whether salivary glycopattern changes combined with machine learning algorithms could help in the accurate diagnosis of HCC. METHODS: Firstly, we detected the alteration of salivary glycopatterns by lectin microarrays in 118 saliva samples. Subsequently, we constructed diagnostic models for hepatic cirrhosis (HC) and HCC using three machine learning algorithms: Least Absolute Shrinkage and Selector Operation, Support Vector Machine (SVM), and Random Forest (RF). Finally, the performance of the diagnostic models was assessed in an independent validation cohort of 85 saliva samples by a series of evaluation metrics, including area under the receiver operator curve (AUC), accuracy, specificity, and sensitivity. RESULTS: We identified alterations in the expression levels of salivary glycopatterns in patients with HC and HCC. The results revealed that the glycopatterns recognized by 22 lectins showed significant differences in the saliva of HC and HCC patients and healthy volunteers. In addition, after Boruta feature selection, the best predictive performance was obtained with the RF algorithm for the construction of models for HC and HCC. The AUCs of the RF-HC model and RF-HCC model in the validation cohort were 0.857 (95% confidence interval [CI]: 0.780-0.935) and 0.886 (95% CI: 0.814-0.957), respectively. CONCLUSIONS: Detecting alterations in salivary protein glycopatterns with lectin microarrays combined with machine learning algorithms could be an effective strategy for diagnosing HCC in the future.

Identification of CD8+ T Cell Related Biomarkers in Ovarian Cancer.

Background: Immunotherapy is a promising strategy for ovarian cancer (OC), and this study aims to identify biomarkers related to CD8+ T cell infiltration to further discover the potential therapeutic target. Methods: Three datasets with OC transcriptomic data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Two immunotherapy treated cohorts were obtained from the Single Cell Portal and Mariathasan's study. The infiltration fraction of immune cells was quantified using three different algorithms, Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), and microenvironment cell populations counter (MCPcounter), and single-sample GSEA (ssGSEA). Weighted gene co-expression network analysis (WGCNA) was applied to identify the co-expression modules and related genes. The nonnegative matrix factorization (NMF) method was proposed for sample classification. The mutation analysis was conducted using the "maftools" R package. Key molecular markers with implications for prognosis were screened by univariate COX regression analysis and K-M survival analysis, which were further determined by the receiver operating characteristic (ROC) curve. Results: A total of 313 candidate CD8+ T cell-related genes were identified by taking the intersection from the TCGA-OV and GSE140082 cohorts. The NMF clustering analysis suggested that patients in the TCGA-OV cohort were divided into two clusters and the Cluster 1 group showed a worse prognosis. In contrast, Cluster 2 had higher amounts of immune cell infiltration, elevated ssGSEA scores in immunotherapy, and a higher mutation burden. CSMD3, MACF1, PDE4DIP, and OBSCN were more frequently mutated in Cluster 1, while SYNE2 was more frequently mutated in Cluster 2. CD38 and CXCL13 were identified by univariate COX regression analysis and K-M survival analysis in the TCGA-OV cohort, which were further externally validated in GSE140082 and GSE32062. Of note, patients with lower CXCL13 expression showed a worse prognosis and the CR/PR group had a higher expression of CXCL13 in two immunotherapy treated cohorts. Conclusion: OC patients with different CD8+ T cell infiltration had distinct clinical prognoses. CXCL13 might be a potential therapeutic target for the treatment of OC.

Machine learning reveals salivary glycopatterns as potential biomarkers for the diagnosis and prognosis of papillary thyroid cancer.

The diagnosis of thyroid cancer, especially papillary thyroid cancer (PTC), is increasing rapidly worldwide. In this study, we aimed to study the glycosylation of salivary proteins associated with PTC and assess the likelihood that salivary glycopatterns may be a potential biomarker of PTC diagnosis. Firstly, 22 benign thyroid nodule (BTN) samples, 27 PTC samples, and 30 healthy volunteers (HV) samples were collected to probe the difference of salivary glycopatterns associated with PTC using lectin microarrays. Then, five machine learning models including K-Nearest Neighbor (KNN), Multilayer Perceptron (MLP), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) were established to distinguish HV, BTN and PTC based on the changes of salivary glycopatterns. As a result, SVM had the best diagnostic effect with an accuracy rate of 92 % in testing set. Besides, lectin microarrays were used to explore the differences in salivary glycopatterns of 26 paired salivary samples of PTC patients before and after operation in order to probe into salivary glycopatterns as potential biomarkers for prognosis of PTC patients. The results showed that the levels of salivary glycopatterns recognized by 6 different lectins in patients after the operation almost convergenced with HVs. This study could help to screen and assess patients with PTC and their prognosis based on precise changes of salivary glycopatterns.

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.

Elevation of α-1,3 fucosylation promotes the binding ability of TNFR1 to TNF-α and contributes to osteoarthritic cartilage destruction and apoptosis.

BACKGROUND: Osteoarthritis (OA) is the most common form of arthritis and is characterized by the degradation of articular cartilage and inflammation of the synovial membrane. Fucosylation is an important feature of protein N/O-glycosylation and is involved in a variety of pathological processes, including inflammation and cancer. However, whether fucosylation impacts the OA pathological process is unknown. METHODS: Total proteins were extracted from cartilage samples obtained from patients with OA (n = 11) and OA rabbit models at different time points (n = 12). OA-associated abnormal glycopatterns were evaluated by lectin microarrays and lectin blots. The expression of fucosyltransferases involved in the synthesis of α-1,3 fucosylation was assessed by semi-qPCR. The synthesis of α-1,3 fucosylation mediated by FUT10 was interrupted by the transfection of siRNA, and the effect of α-1,3 fucosylation on OA-associated events was assessed. Then, immunoprecipitation and lectin blotting were used to investigate the relationship between the α-1,3 fucosylation level of tumor necrosis factor receptor superfamily member 1A (TNFR1) and OA. Finally, a TNFR1 antibody microarray was fabricated to evaluate the effect of α-1,3 fucosylation on the ability of TNFR1 to bind to tumor necrosis factor-α (TNF-α). RESULTS: Elevated α-1,3 fucosylation was observed in cartilage from OA patients, rabbit models, and chondrocytes induced by TNF-α (fold change> 2, p< 0.01). Our results and the GEO database indicated that the overexpression of FUT10 contributed to this alteration. Silencing the expression of FUT10 impaired the ability of TNFR1 to bind to TNF-α, impeded activation of the NF-κB and P38/JNK-MAPK pathways, and eventually retarded extracellular matrix (ECM) degradation, senescence, and apoptosis in chondrocytes exposed to TNF-α. CONCLUSION: The elevation of α-1,3 fucosylation is not only a characteristic of OA but also impacts the OA pathological process. Our work provides a new positive feedback loop of "inflammation conditions/TNF-α/FUT10/α-1,3 fucosylation of TNFR1/NF-κB and P38/JNK-MAPK pathways/proinflammatory processes" that contributes to ECM degradation and chondrocyte apoptosis.

An Edaravone-Guided Design of a Rhodamine-Based Turn-on Fluorescent Probe for Detecting Hydroxyl Radicals in Living Systems.

The hydroxyl radical (·OH), one of the reactive oxygen species (ROS) in biosystems, is found to be involved in many physiological and pathological processes. However, specifically detecting endogenous ·OH remains an outstanding challenge owing to the high reactivity and short lifetime of this radical. Herein, inspired by the scavenging mechanism of a neuroprotective drug edaravone toward ·OH, we developed a new ·OH-specific fluorescent probe RH-EDA. RH-EDA is a hybrid of rhodamine and edaravone and exploits a ·OH-specific 3-methyl-pyrazolone moiety to control its fluorescence behavior. RH-EDA itself is almost nonfluorescent in physiological conditions, which was attributed to the formation of a twisted intramolecular charge transfer (TICT) state upon photoexcitation and the acylation of its rhodamine nitrogen at the 3' position. However, upon a treatment with ·OH, its edaravone subunit was converted to the corresponding 2-oxo-3-(phenylhydrazono)-butanoic acid (OPB) derivative (to afford RH-OPB), thus leading to a significant fluorescence increase (ca. 195-fold). RH-EDA shows a high sensitivity and selectivity to ·OH without interference from other ROS. RH-EDA has been utilized for imaging endogenous ·OH production in living cells and zebrafishes under different stimuli. Moreover, RH-EDA allows a high-contrast discrimination of cancer cells from normal ones by monitoring their different ·OH levels upon stimulation with ß-Lapachone (ß-Lap), an effective ROS-generating anticancer therapeutic agent. The present study provides a promising methodology for the construction of probes through a drug-guided approach.

Alternations of N-glycans recognized by Phaseolus vulgaris leucoagglutinin in the saliva of patients with breast cancer.

Breast cancer is the most frequently diagnosed cancer in most countries. Early diagnosis of breast disease is necessary for its prognosis and treatment. Altered protein glycosylation has been shown to be expressed in precursor lesions of breast cancer, making them powerful early diagnostic biomarkers. The present study validated alterations of the N-glycan profiles of their salivary glycoproteins isolated by the Phaseolus vulgaris leucoagglutinin (PHA-E+L)-magnetic particle conjugates from 141 female subjects (66 healthy volunteers (HV), and 75 patients with breast disease including breast benign cyst (BB) or breast cancer in stage I/II (BC-I/II)) were analyzed and annotated by MALDI-TOF/TOF-MS. The results showed that there were 11, 20, 16, and 17 N-glycans recognized by PHA-E+L identified and annotated from the pooled salivary samples of HV, BB, BC-I, and BC-II, respectively. There were 3 N-glycans peaks (m/z 2459.8799, 2507.9139, and 2954.0547), 2 N-glycans peaks (m/z 1957.7265 and 2794.0427), and 2 N-glycans peaks (m/z 1866.6608 and 2240.8056) recognized by PHA-E+L that existed only in BB, BC-I, and BC-II, respectively. The present study compared the alternations of N-glycans from the salivary proteins isolated by PHA-E+L-magnetic particle conjugates among HV, BB, BC-I, and BC-II, which could provide information on N-glycans during the development of breast cancer in saliva to promote the study of its biomarkers.

Comprehensive analysis of glycosphingolipid glycans by lectin microarrays and MALDI-TOF mass spectrometry.

Glycosphingolipids (GSLs) are ubiquitous glycoconjugates present on the cell membrane; they play significant roles in many bioprocesses such as cell adhesion, embryonic development, signal transduction and carcinogenesis. Analyzing such amphiphilic molecules is a major challenge in the field of glycosphingolipidomics. We provide a step-by-step protocol that uses a lectin microarray to analyze GSL glycans from cultured cells. The procedure describes (i) extraction of GSLs from cell pellets, (ii) N-monodeacylation using sphingolipid ceramide N-deacylase digestion to form lyso-GSLs, (iii) fluorescence labeling at the newly exposed amine group, (iv) preparation of a lectin microarray, (v) GSL-glycan analysis by a lectin microarray, (vi) complementary mass spectrometry analysis and (vii) data acquisition and analysis. This method is high-throughput, low cost and easy to conduct, and it provides detailed information about glycan linkages. This protocol takes ~10 d.

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

Glycosylation is one of the most crucial posttranslational modifications of proteins, containing a remarkable amount of biological information. The alteration of glycosylation is closely associated with certain diseases. Exploring glyco-code in the development of diseases is a hot topic in recent years. Esophageal squamous cell carcinoma (ESCC) is the primary pathological histology in developing countries and a severe threat to human health. Although the glycan profiles in the blood samples of ESCC patients were analyzed using glycomic and glycoproteomic methods, the difference of salivary glycopatterns between healthy subjects and ESCC patients is not explicit yet. In the present study, ESCC patients (n = 16) and healthy volunteers (HVs, n = 25) were enrolled. The glycomic strategy combining lectin microarray and lectin blotting was employed to investigate and confirm the altered salivary glycopatterns. Datura stramonium (DSA) was selected to isolate the GlcNAc or Galß1-4GlcNA-containing glycoproteins due to the distinct difference between ESCC patients and HVs. The N-glycans from DSA-enriched glycoproteins were released by PNGase F and further identified by MALDI-TOF/TOF-MS to obtain the precise structural information of the altered glycans. As a result, the glycopatterns recognized by 13 lectins (e.g., ECA, RCA120, and DSA) showed significant alterations in ESCC patients' saliva. The ESCC patients showed higher levels of GalNAc and Gal, sialic acid, and GlcNAc expression profiles and lower levels of mannose and fucose expression profiles. The MALDI-TOF/TOF-MS results indicated that the proportion of the GlcNAc or Galß1-4GlcNAc-containing N-glycans was increased in ESCC patients (79.04%) compared with HV (63.20%), which was consistent with the results of lectin microarrays. Our findings provide comprehensive information to understand the complex physiological changes in ESCC patients. And the altered salivary glycopatterns such as GlcNAc or Galß1-4GlcNAc-containing N-glycans recognized by DSA might serve as potential biomarkers for the diagnosis of ESCC patients.

Abnormal Galactosylated-Glycans recognized by Bandeiraea Simplicifolia Lectin I in saliva of patients with breast Cancer.

Currently, the definitive diagnosis in breast cancer requires biopsy and histopathology, such the most effective markers are tissue-based. However, the advantages of saliva in collection and storage make it possible for assessing human pathology and contributing to the development of cancer-related biomarkers for clinical application. The present study validated alteration of salivary protein glycopatterns recognized by Bandeiraea simplicifolia lectin I (BS-I) in the saliva of patients with breast diseases using saliva microarrays, and the N/O-glycan profiles of their salivary glycoproteins isolated by the BS-I-magnetic particle conjugates from 259 female subjects (66 healthy volunteers (HV), 65 benign breast cyst or tumor patients (BB), 66 patients with breast cancer in stage I (BC-I) and 62 patients with breast cancer in stage II (BC-II)) were analyzed by MALDI-TOF/TOF-MS. The results showed that the expression level of galactosylated glycans recognized by BS-I was significantly increased in patients with breast cancer compared with HV (p < 0.05). Totally, there were 11/10, 10/19, 7/24 and 7/9 galactosylated N-/O-linked glycans were identified and annotated from the pooled salivary samples of HV, BB, BC-I and BC-II, respectively. One galactosylated N-glycan peak (m/z 2773.977), and 4 galactosylated O-glycan peaks (m/z 868.295, 882.243, 884.270 and 1030.348) were found only in BC-I. These findings could provide pivotal information on galactosylated N/O-linked glycans related to breast cancer, and promote the study of biomarkers for early-stage breast cancer based on precise alterations of galactosylated N/O-glycans in saliva.

Lectin microarrays for glycoproteomics: an overview of their use and potential.

Introduction: Glycoproteomics is an important subdiscipline of proteomics, focusing on the role of protein glycosylation in various biological processes. Protein glycosylation is the enzymatic addition of sugars or oligosaccharides to proteins. Altered glycosylation often occurs in the early stages of disease development, for example, certain tumor-associated glycans have been shown to be expressed in precursor lesions of different types of cancer, making them powerful early diagnostic markers. Lectin microarrays have become a powerful tool for both the study of glycosylation and the diagnosis of various diseases including cancer.Areas covered: This review will discuss the most useful features of lectin microarrays, such as their technological advances, their capability for parallel/high-throughput analysis for the important glycopatterns of glycoprotein, and an overview of their use for glycosylation analysis of various complex protein samples, as well as their diagnostic potential in various diseases.Expert opinion: Lectin microarrays have proved to be useful in studying multiple lectin-glycan interactions in a single experiment and, with the advances made in the field, hold a promise of enabling glycopatterns of diseases in a fast and efficient manner. Lectin microarrays will become increasingly powerful early diagnostic tool for a variety of conditions.

Protein Glycopatterns in Bronchoalveolar Lavage Fluid as Novel Potential Biomarkers for Diagnosis of Lung Cancer.

Lung cancer is one of the most prevalent and life-threatening neoplasias worldwide due to the deficiency of ideal diagnostic biomarkers. Although aberrant glycosylation has been observed in human serum and tissue, little is known about the alterations in bronchoalveolar lavage fluid (BALF) that are extremely associated with lung cancer. In this study, our aim was to systematically investigate and assess the alterations of protein glycopatterns in BALF and possibility as biomarkers for diagnosis of lung cancer. Here, lectin microarrays and blotting analysis were utilized to detect the differential expression of BALF glycoproteins from patients with 80 adenocarcinomas (ADC), 77 squamous carcinomas (SCC), 51 small cell lung cancer (SCLC), and 73 benign pulmonary diseases (BPD). These 281 specimens were then randomly divided into a training cohort and validation cohort for constructing and verifying the diagnostic models based on the glycopattern abundances. Moreover, an independent test was performed with 120 newly collected BALF samples enrolled in the double-blind cohort to further assess the clinical application potential of the diagnostic models. According to the results, there were 15 (e.g., PHA-E, EEL, and BPL) and 14 lectins (e.g., PTL-II, LCA, and SJA) that individually showed significant variations in different types and stages of lung cancer compared to BPD. Notably, the diagnostic models achieved better discriminate power in the validation cohort and exhibited high accuracies of 0.917, 0.864, 0.712, 0.671, and 0.781 in the double-blind cohort for the diagnosis of lung cancer, early stage lung cancer, ADC, SCC, and SCLC, respectively. Taken together, the present study revealed that the abnormally altered protein glycopatterns in BALF are expected to be novel potential biomarkers for the identification and early diagnosis of lung cancer, which will contribute to explain the mechanism of the development of lung cancer from the perspective of glycobiology.

Alterations in serum protein glycopatterns related to small cell lung cancer, adenocarcinoma and squamous carcinoma of the lung.

Background: The main reason why lung cancer has maintained a high rate of morbidity and mortality is that its early diagnosis is difficult. No current lung cancer screening is recommended by any major medical organization due to the lack of sensitive and specific screening technologies. Thus, this study aimed to systematically investigate the correlation between the alterations in serum glycosylation and three main types of lung cancers (SCLC, ADC and SqCC). Materials and methods: We investigated the protein glycopatterns in sera from 333 subjects (65 healthy volunteers, 38 benign lung disease patients, 49 small cell lung cancer patients, and 181 NSCLC patients) using a lectin microarray. A serum microarray was produced to evaluate and verify the terminal carbohydrate moieties of the glycoproteins in individual serum samples from 30 cases simultaneously. Results: There were 16 lectins (e.g., RCA120, BS-I, and UEA-I), 24 lectins (e.g., HHL, PTL-I, and MAL-II), and 18 lectins (e.g., GSL-I, LEL, and ACA) that exhibited significant differences in serum protein glycopatterns in the patients with SCLC, ADC and SqCC compared with the controls (HV and BPD). There were 6 lectins (e.g., EEL, NPA, and LEL) that exhibited significantly increased NFIs in ADC and SqCC compared with SCLC. Also, there were 5 lectins (e.g., Jacalin, BS-I, and UEA-I) that exhibited significantly decreased NFIs in ADC compared with SCLC and SqCC. Conclusions: This study can facilitate the discovery of potential biomarkers for the differential diagnosis of lung cancer based on the precise alteration in serum protein glycopatterns.