A novel in-depth “static- dynamic” lipidomics workflow to reveal lipids reprogramming in hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths globally, and with current treatments proving less effective, there is an urgent need for specific biomarkers and therapeutic targets. Lipid metabolism reprogramming is a crucial cancer hallmark, yet comprehensive studies on lipid metabolic fluxes remain limited. In this study, combined with non-targeted lipidomics, a comprehensive workflow for stable isotope tracing lipidomics was established to analyze changes in lipid levels of HepG2 cells and LO2 cells from both static and dynamic perspectives. Through the screening of differential metabolites and the enrichment analysis of lipid metabolic pathways, the most significant differential metabolic pathways were found. Finally, the TCGA and CPTAC databases were utilized to analyze the gene expression levels and protein expression levels of pivotal enzymes in the differential metabolic pathways, and these findings were verified by Western Blotting experiments. The results demonstrated that the lipid metabolism of HCC was disordered, and the metabolic pathways that caused lipid changes in HCC were mainly glycerophospholipid metabolism and sphingolipid signaling pathway. LPCAT1 and SMPD1 played a crucial role in the reprogramming of lipid metabolism in HCC. The established "static-dynamic" lipidomics workflow improves the coverage and accuracy of dynamic lipid monitoring, elucidating the roles of lipids in physiological and pathological processes, providing tools for studying lipid function, and offering new perspectives on the pathogenesis of HCC as well as the identification of drug targets.