Serum lipid profiling analysis and potential marker discovery for ovarian cancer based on liquid chromatography-Mass spectrometry

Low early diagnosis rate and unclear pathogenesis are the primary reasons for the high mortality of epithelial ovarian cancer (EOC). Lipidomics is a powerful tool for marker discovery and mechanism explanation. Hence, a ultra high-performance liquid chromatography-mass spectrometry based non-targeted lipidomics analysis was performed to acquire lipid profiling of 153 serum samples including healthy control (HC, n = 50), benign ovarian tumor (BOT, n = 41), and EOC (n = 62) to reveal lipid disturbance, then differential lipids were verified in another sample set including 187 sera. Significant lipid disturbance occurred in BOT and EOC, fatty acid, lyso-phosphatidylcholine, and lyso-phosphatidylethanolamine were observed to be increased in BOT and EOC subjects, while phosphatidylcoline, ether phosphatidylcoline (PC-O), ether phosphatidylethanolamine (PE-O), and sphingomyelin significantly decreased. Compared with BOT, PC-Os and PE-Os presented a greater reduction in EOC, and serum ceramide increased only in EOC. Moreover, potential markers consisting of 4 lipids were defined and validated for EOC diagnosis. High areas under the curve (0.854-0.865 and 0.903-0.923 for distinguishing EOC and early EOC from non-cancer, respectively) as well as good specificity and sensitivity were obtained. This study not only revealed the characteristics of lipid metabolism in EOC, but also provided a potential marker pattern for aiding EOC diagnosis.& nbsp; (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

The study identified lipid disturbances in the serum of patients with epithelial ovarian cancer (EOC) and established 4 lipids as potential markers for aiding EOC diagnosis. These markers showed high accuracy in distinguishing EOC and early EOC from non-cancer, with good specificity and sensitivity. The research not only revealed the characteristics of lipid metabolism in EOC, but also provided a potential marker pattern for aiding EOC diagnosis.