Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics

作者：Wen Li, Xiaobin Wang, Xianbin Zhang, Peng Gong, Degang Ding, Ning Wang, Zhifeng Wang · 发表于：Lipids in Health and Disease · 年份：2021 · DOI：10.1186/s12944-021-01572-z · 被引用次数：15 · 研究领域：Cancer, Lipids, and Metabolism、Metabolomics and Mass Spectrometry Studies、Lipid metabolism and biosynthesis

BACKGROUND: The high drug resistance and metabolic reprogramming of clear cell renal cell carcinoma (ccRCC) are considered responsible for poor prognosis. In-depth research at multiple levels is urgently warranted to illustrate the lipid composition, distribution, and metabolic pathways of clinical ccRCC specimens. METHODS: In this project, a leading-edge targeted quantitative lipidomic study was conducted using 10 pairs of cancerous and adjacent normal tissues obtained from ccRCC patients. Accurate lipid quantification was performed according to a linear equation calculated using internal standards. Qualitative and quantitative analyses of lipids were performed with multiple reaction monitoring analysis based on ultra-performance liquid chromatography (UPLC) and mass spectrometry (MS). Additionally, a multivariate statistical analysis was performed using data obtained on lipids. RESULTS: A total of 28 lipid classes were identified. Among them, the most abundant were triacylglycerol (TG), diacylglycerol (DG), phosphatidylcholine (PC), and phosphatidylethanolamine (PE). Cholesteryl ester (CE) was the lipid exhibiting the most considerable difference between normal samples and tumor samples. Lipid content, chain length, and chain unsaturation of acylcarnitine (CAR), CE, and DG were found to be significantly increased. Based on screening for variable importance in projection scores ≥1, as well as fold change limits between 0.5 and 2, 160 differentially expressed lipids were iden...