Carson International Cancer Centre, Shenzhen University General Hospital and Shenzhen University Clinical Medical Academy Centre, Shenzhen University, 1098 Xueyuan Road, Shenzhen, 518000, Guangdong, China.
Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.
Lipids Health Dis. 2021 Nov 13;20(1):160. doi: 10.1186/s12944-021-01572-z.
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.
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.
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.
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.
透明细胞肾细胞癌（ccRCC）的高耐药性和代谢重编程被认为是导致预后不良的原因。迫切需要在多个层面进行深入研究，以阐明临床 ccRCC 标本的脂质组成、分布和代谢途径。
在本项目中，对 10 对来自 ccRCC 患者的癌组织和相邻正常组织进行了前沿的靶向定量脂质组学研究。根据使用内部标准计算的线性方程进行准确的脂质定量。使用基于超高效液相色谱（UPLC）和质谱（MS）的多重反应监测分析进行脂质的定性和定量分析。此外，还使用脂质数据进行了多变量统计分析。
共鉴定出 28 种脂质类别。其中，含量最丰富的是三酰甘油（TG）、二酰甘油（DG）、磷脂酰胆碱（PC）和磷脂酰乙醇胺（PE）。胆固醇酯（CE）是正常样本和肿瘤样本之间差异最显著的脂质。酰基肉碱（CAR）、CE 和 DG 的脂质含量、链长和链不饱和度均显著增加。基于筛选变量重要性投影得分≥1 以及 0.5 到 2 之间的倍数变化限制，鉴定出 160 种差异表达的脂质。CE 是上调最显著的脂质，而 TG 是下调最显著的脂质。
基于 ccRCC 标本中脂质的绝对定量分析，观察到不同脂质类别中的含量和变化趋势存在差异。观察到 CAR、CE 和 DG 的上调，并分析分布变化有助于阐明 ccRCC 中脂质积累的原因和可能的致癌分子机制。本文所述的结果和方法提供了对 ccRCC 脂质代谢的全面分析，为癌症治疗奠定了理论基础。
