Abstract
BackgroundThe 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.MethodsIn 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.ResultsA 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 identified. CE was found to be the most significantly upregulated lipid, while TG was observed to be the most significantly downregulated lipid.ConclusionBased on the absolute quantitative analysis of lipids in ccRCC specimens, it was observed that the content and change trends varied in different lipid classes. Upregulation of CAR, CE, and DG was observed, and analysis of changes in the distribution helped clarify the causes of lipid accumulation in ccRCC and possible carcinogenic molecular mechanisms. The results and methods described herein provide a comprehensive analysis of ccRCC lipid metabolism and lay a theoretical foundation for cancer treatment.
Highlights
The high drug resistance and metabolic reprogramming of clear cell renal cell carcinoma are considered responsible for poor prognosis
Loss of the Von Hippel Lindau (VHL) gene and deletion of a part of chromosome 3p are involved in the initial steps, and vascular endothelial growth factor, PI3K, mTOR, and carbonic anhydrase IX have been defined as therapeutic targets [3]
Metabolomics based on nuclear magnetic resonance (NMR), chromatography, and mass spectrometry (MS) can be considered to systematically analyze the variations under different physiological conditions using a combination of genomics and proteomics [6]
Summary
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. Clear cell renal cell carcinoma (ccRCC) accounts for 70% of all renal cell carcinoma patients and is the main pathological feature of lipid accumulation [2]. Owing to poor prognosis attributable to drug resistance and immune escape, it is suggested that the discovery of more potential molecular mechanisms holds considerable promise [4, 5]. As an independent branch of metabolomics, lipidomics helps to comprehensively and systematically identify and quantify lipids to reveal key drivers of disease pathology. Apart from acting as constituents of biological structural components and participating in signal transduction, lipids bind proteins to enable expansion of the metabolic regulatory network [10]
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