Lung cancer is the most common malignancy worldwide. Thus, there is a critical need for diagnostic biomarkers with adequate sensitivity and specificity for lung cancer detection. Glycans in glycoproteins are significantly altered in cancer, and may serve as a tool for identifying potential diagnostic biomarkers. Recent studies have reported changes in α-1-antitrypsin (A1AT) glycosylation in lung cancer serum, tissue and cell lines. In this study, a lectin microarray was used to detect glycosylation changes in serum A1AT from patients with lung adenocarcinoma (ADC), squamous cell lung cancer, small-cell lung cancer (SCLC) and benign pulmonary diseases. Differentially expressed glycosylated patterns of A1AT were identified by lectin arrays and were confirmed by lectin-based enzyme-linked immunosorbent assay (ELISA). We found that galactosylated A1AT could distinguish non-small-cell lung cancer (NSCLC) from benign pulmonary diseases (AUC = 0.834); fucosylated A1AT showed exceptional capability in distinguishing ADC from benign diseases (AUC = 0.919) or other lung cancer subtypes (AUC = 0.844), and A1AT containing poly-LacNAc could detect SCLC from benign diseases (AUC = 0.905) or NSCLC (AUC = 0.707). The present study indicates that glycosylated patterns of A1AT may serve as potential biomarkers for detection of lung cancer. Further studies in larger sample sizes are necessary to validate the clinical utility of these markers.

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Background: Chronic infection with HBV (CHB) or HCV (CHC) is the most common chronic viral hepatitis that can lead to cirrhosis and hepatocellular carcinoma in humans, their infections have distinct pathogenic processes, however, little is known about the difference of glycoprotein glycopatterns in serum between hepatitis B virus (HBV)- and hepatitis C virus (HCV)-infected patients.Methods: A method combining the lectin microarrays, letin-mediated affinity capture glycoproteins, and MALDI-TOF/TOF-MS was employed to analyze serum protein glycopatterns and identify the glycan structures from patients with CHB (n = 54) or CHC(n = 47), and healthy volunteers (HV, n = 35). Lectin blotting was further utilized to validate and assess the expression levels of their serum glycopatterns. Finally, the differences of the glycoprotein glycopatterns were systematically compared between CHB and CHC patients.Conclusions: As a result, there were 11 lectins (e.g., HHL, GSL-II, and EEL) exhibited significantly increased expression levels, and three lectins (LCA, VVA, and ACA) exhibited significantly decreased expression levels of serum protein glycopatterns only in the CHB patients. However, DBA exhibited significantly decreased expression levels, and two lectins (WGA and SNA) exhibited significantly increased expression levels of serum glycopatterns only in the CHC patients. Furthermore, LEL and MAL-I showed a coincidentally increasing trend in both CHC and CHB patients compared with the HV. The individual analysis demonstrated that eight lectins (MPL, GSL-I, PTL-II, UEA-I, WGA, LEL, VVA, and MAL-I) exhibited a high degree of consistency with the pooled serum samples of HV, CHB, and CHC patients. Besides, a complex-type N-glycans binder PHA-E+L exhibited significantly decreased NFIs in the CHB compared with HV and CHC subjects (p < 0.01). The MALDI-TOF/TOF-MS results of N-linked glycans from the serum glycoproteins isolated by PHA-E+L-magnetic particle conjugates showed that there was an overlap of 23 N-glycan peaks (e.g., m/z 1419.743, 1663.734, and 1743.581) between CHB, and CHC patients, 5 glycan peaks (e.g., m/z 1850.878, 1866.661, and 2037.750) were presented in virus-infected hepatitis patients compared with HV, 3 glycan peaks (1460.659, 2069.740, and 2174.772) were observed only in CHC patients. Our data provide useful information to find new biomarkers for distinguishing CHB and CHC patients based on the precision alteration of their serum glycopatterns.