ArticleLipids in health and disease2021
Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics.
Article in Lipids in health and disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 14 citations in OpenAlex.
- Lipidomic and transcriptomic analysis and its therapeutic implications in Chinese Kazakh patients with esophageal squamous cell carcinoma.BMC cancer · 2025Article
- Targeting Metabolic Reprogramming in Bladder Cancer Immunotherapy: A Precision Medicine Approach.Biomedicines · 2025Review
- Circulating bile acid profiles characteristics and the potential predictive role in clear cell renal cell carcinoma progression.BMC nephrology · 2025Article
- Metabolic signature of renal cell carcinoma tumours and its correlation with the urinary metabolome.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- HADH suppresses clear cell renal cell carcinoma progression through reduced NRF2-dependent glutathione synthesis.Translational oncology · 2024Article
- PI3K/AKT/mTOR Dysregulation and Reprogramming Metabolic Pathways in Renal Cancer: Crosstalk with the VHL/HIF Axis.International journal of molecular sciences · 2023Review
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7 authors at 4 institutions in 1 country.
Funding
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.
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