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

Abstract 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 c...

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Autores principales:	Wen Li, Xiaobin Wang, Xianbin Zhang, Peng Gong, Degang Ding, Ning Wang, Zhifeng Wang
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Clear cell renal cell carcinoma Lipids Lipidomics Lipid metabolite Lipid biomarker Lipid quantification Nutritional diseases. Deficiency diseases RC620-627
Acceso en línea:	https://doaj.org/article/ff711bc81dd846acba3809596fd5516d
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spelling	oai:doaj.org-article:ff711bc81dd846acba3809596fd5516d2021-11-14T12:39:53ZRevealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics10.1186/s12944-021-01572-z1476-511Xhttps://doaj.org/article/ff711bc81dd846acba3809596fd5516d2021-11-01T00:00:00Zhttps://doi.org/10.1186/s12944-021-01572-zhttps://doaj.org/toc/1476-511XAbstract 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 identified. CE was found to be the most significantly upregulated lipid, while TG was observed to be the most significantly downregulated lipid. Conclusion Based 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.Wen LiXiaobin WangXianbin ZhangPeng GongDegang DingNing WangZhifeng WangBMCarticleClear cell renal cell carcinomaLipidsLipidomicsLipid metaboliteLipid biomarkerLipid quantificationNutritional diseases. Deficiency diseasesRC620-627ENLipids in Health and Disease, Vol 20, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Clear cell renal cell carcinoma Lipids Lipidomics Lipid metabolite Lipid biomarker Lipid quantification Nutritional diseases. Deficiency diseases RC620-627
spellingShingle	Clear cell renal cell carcinoma Lipids Lipidomics Lipid metabolite Lipid biomarker Lipid quantification Nutritional diseases. Deficiency diseases RC620-627 Wen Li Xiaobin Wang Xianbin Zhang Peng Gong Degang Ding Ning Wang Zhifeng Wang Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics
description	Abstract 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 identified. CE was found to be the most significantly upregulated lipid, while TG was observed to be the most significantly downregulated lipid. Conclusion Based 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.
format	article
author	Wen Li Xiaobin Wang Xianbin Zhang Peng Gong Degang Ding Ning Wang Zhifeng Wang
author_facet	Wen Li Xiaobin Wang Xianbin Zhang Peng Gong Degang Ding Ning Wang Zhifeng Wang
author_sort	Wen Li
title	Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics
title_short	Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics
title_full	Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics
title_fullStr	Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics
title_full_unstemmed	Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics
title_sort	revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics
publisher	BMC
publishDate	2021
url	https://doaj.org/article/ff711bc81dd846acba3809596fd5516d
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_version_	1718429145911787520

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

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