Identification of serum glycobiomarkers for Hepatocellular Carcinoma using lectin microarrays.

Objective: Hepatocellular carcinoma (HCC) is the sixth most commonly occurring cancer and ranks third in mortality among all malignant tumors; as a result, HCC represents a major human health issue. Although aberrant glycosylation is clearly implicated in HCC, changes in serum immunoglobulin (Ig)G and IgM glycosylation have not been comprehensively characterized. In this study, we used lectin microarrays to evaluate differences in serum IgG and IgM glycosylation among patients with HCC, hepatitis B cirrhosis (HBC), or chronic hepatitis B (CHB), and healthy normal controls (NC) and aimed to establish a model to improve the diagnostic accuracy of HCC. Methods: In total, 207 serum samples collected in 2019-2020 were used for lectin microarray analyses, including 97 cases of HCC, 50 cases of HBC, 30 cases of CHB, and 30 cases of NC. Samples were randomly divided into training and validation groups at a 2:1 ratio. Training group data were used to investigate the diagnostic value of the relative signal intensity for the lectin probe combined with alpha-fetoprotein (AFP). The efficacy of models for HCC diagnosis were analyzed by receiver operating characteristic (ROC) curves. Results: In terms of IgG, a model combining three lectins and AFP had good diagnostic accuracy for HCC. The area under the ROC curve was 0.96 (P < 0.05), the sensitivity was 82.54%, and the specificity was 100%. In terms of IgM, a model including one lectin combined with AFP had an area under the curve of 0.90 (P < 0.05), sensitivity of 75.41%, and specificity of 100%. Conclusion: Estimation of serum IgG and IgM glycosylation could act as complementary techniques to improve diagnosis and shed light on the occurrence and development of the HCC.