安定同位体標識を用いたモデリング予測ベースのHPLC-MS/MS：肝細胞癌におけるスフィンゴ脂質変化の静的・動的プロファイリング戦略

Hepatocellular carcinoma (HCC) is the most common primary liver cancer. Its occurrence and development are closely related to abnormal lipid metabolism, especially the metabolic changes of sphingolipids. Stable isotopes are considered a powerful tool for studying complex lipid metabolism networks. However, due to the structural complexity of lipids, achieving comprehensive and targeted detection remains challenging. This study innovatively combined stable isotope labeling technology with "modeling-prediction" strategy to achieve high targeted coverage detection and accurate quantification of isotope peaks. Moreover, a combined "static-dynamic" analysis approach was employed in this study to investigate and compare the impacts of glucose and palmitic acid on sphingolipid level in HepG2 cells and LO2 cells. A total of 220 sphingolipids were detected, among which 95 showed significant differences in response to glucose, 86 to palmitic acid, and 85 to the combination of both. Notably, 35 sphingolipids were identified as common differentially expressed sphingolipids across all conditions. Stable isotope labeling revealed that sphingolipids synthesized with glucose as the substrate had a broader isotopic distribution and higher 13C labeling than those with palmitic acid, suggesting that glucose contributes more broadly to sphingolipid-associated carbon pools through multiple metabolic routes than exogenous palmitate under our conditions. By integrating static and dynamic analyses, sphingolipid alteration profiles in hepatocellular carcinoma were further characterized, enabling the prediction of trends in sphingolipid metabolite synthesis and consumption. In summary, this study is expected to provide new insights into the study of complex sphingolipid metabolic networks.