Glycoprofiling of early non-small cell lung cancer using lectin microarray technology

Abstract

Abstract Objectives Non-small cell lung cancer (NSCLC) is one of the most common malignancies in the world with a high incidence and it lacks effective biomarkers for early-stage detection. In this investigation, we aimed to investigate the alterations in plasma glycans related to NSCLC and assess the possibility of plasma glycopatterns as potential biomarkers for the diagnosis of NSCLC. Methods First, plasma samples from 16 patients with early-stage lung adenocarcinoma (LUAD), 16 patients with early-stage Lung squamous cell carcinoma (LUSC), and 16 healthy volunteers, were selected for inclusion in this study to probe the difference in plasma glycopatterns using lectin microarrays. Then, the diagnostic effectiveness of the candidate lectins was evaluated using ROC. Results In contrast to the NL group, seven candidate lectins offered potential diagnostic utility in the NSCLC (LUAD and LUSC) group. F17AG was significantly altered in LUSC with an AUC of 0.818 (adj.P.Val<0.05) compared to NL samples. There were 20 differentially expressed lectins in the LUAD group compared to the NL group. Based on the AUC values (AUC>0.800) and the normalized fluorescence intensities of the lectins, we selected eight lectins, GAL2, PTL-1, GNA, SSA, LENTIL, CA, PHA-E, and MAA to perform logistic regression analysis, and found that the combination of these eight candidate lectins had high diagnostic potential. Conclusions The results of this study should help to distinguish between NSCLC and NL based on changes in plasma glycopatterns, which have a great deal of potential to be biomarkers for diagnosing NSCLC.