Comprehensive profiling of serum glycosphingolipids to discover the diagnostic biomarkers of lung cancer and uncover the variation of glycosphingolipid networks in different lung cancer subtypes.

Abstract

Glycosphingolipids are glycolipid complexes formed by an oligosaccharide chain covalently linked to a ceramide backbone and play important roles in the occurrence and metastasis of lung cancer. In this study, an UHPLC-HRMS method was developed for the comprehensive profiling of glycosphingolipids, with an in-house library constructed for data interpretation. Serum glycosphingolipids were profiled in 31 healthy controls (HCs) and 92 lung cancer patients with different pathologic subtypes. Over 1700 glycosphingolipids were detected in human serum based on the novel method. A total of 567 differential glycosphingolipids (adjusted P < 0.05, and fold change > 2) were found between lung cancer patients and HCs. Glycosphingolipids can be used as potential biomarkers for lung cancer diagnosis, with sensitivity much higher than that of traditional serum tumor markers. The levels of most glycosphingolipids in squamous cell carcinoma (Squa) were significantly lower than those in small cell lung cancer (SCLC) and adenocarcinoma (Aden). The highest Cer1P abundance in SCLC patients among the three different subtypes of lung cancer was thought to be related to the high malignancy and metastasis of SCLC. An artificial neural network (ANN) model was constructed for the discrimination of the three different subtypes of lung cancer, with accuracy higher than 93%. Beyond providing biomarkers and statistical models for the diagnosis of lung cancer and discrimination of lung cancer subtypes, this study uncovered the variation of glycosphingolipid networks in different subtypes of lung cancer and thereby provided a novel insight to study the pathogenesis of lung cancer and explore therapeutic targets.