Wang Haoyue, Luo Yanbo, Chen Huan, Hou Hongwei, Hu Qingyuan, Ji Min
Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.
Science Island Branch, Graduate School of University of Science and Technology of China, Hefei 230026, China.
Metabolites. 2022 Nov 9;12(11):1087. doi: 10.3390/metabo12111087.
Laryngeal cancer is a common head and neck malignant cancer type. However, effective biomarkers for diagnosis are lacking and pathogenesis is unclear. Lipidomics is a powerful tool for identifying biomarkers and explaining disease mechanisms. Hence, in this study, non-targeted lipidomics based on ultra-performance liquid chromatography-quadrupole time of flight-mass spectrometry (UHPLC-QTOF-MS) were applied to screen the differential lipid metabolites in serum and allowed for exploration of the remodeled lipid metabolism of laryngeal cancer, laryngeal benign tumor patients, and healthy crowds. Multivariate analysis and univariate analysis were combined to screen for differential lipid metabolites among the three groups. The results showed that, across a total of 57 lipid metabolic markers that were screened, the regulation of the lipid metabolism network occurred mainly in phosphatidylcholine (PC), lysophosphatidylcholine (LPC), and sphingomyelin (SM) metabolism. Of note, the concentration levels of sphingolipids 42:2 (SM 42:2) and sphingolipids 42:3 (SM 42:3) correlated with laryngeal cancer progression and were both significantly different among the three groups. Both of them could be considered as potential biomarkers for diagnosis and indicators for monitoring the progression of laryngeal cancer. From the perspective of lipidomics, this study not only revealed the regulatory changes in the lipid metabolism network, but also provided a new possibility for screening biomarkers in laryngeal cancer.
喉癌是一种常见的头颈部恶性肿瘤类型。然而，目前缺乏有效的诊断生物标志物，其发病机制也尚不清楚。脂质组学是一种用于识别生物标志物和解释疾病机制的强大工具。因此，在本研究中，基于超高效液相色谱-四极杆飞行时间质谱（UHPLC-QTOF-MS）的非靶向脂质组学技术被应用于筛选血清中的差异脂质代谢物，以探索喉癌、喉良性肿瘤患者和健康人群脂质代谢的重塑情况。通过多变量分析和单变量分析相结合的方法，筛选出三组之间的差异脂质代谢物。结果显示，在总共筛选出的57种脂质代谢标志物中，脂质代谢网络的调节主要发生在磷脂酰胆碱（PC）、溶血磷脂酰胆碱（LPC）和鞘磷脂（SM）代谢中。值得注意的是，鞘脂42:2（SM 42:2）和鞘脂42:3（SM 42:3）的浓度水平与喉癌进展相关，且在三组之间均有显著差异。它们均可被视为喉癌诊断的潜在生物标志物和监测喉癌进展的指标。从脂质组学的角度来看，本研究不仅揭示了脂质代谢网络的调节变化，还为喉癌生物标志物的筛选提供了新的可能性。
