biostudies-literatureChen XNatural Science Foundation of Guangdong Province, ChinaNational Natural Science Foundation of China81https://www.ebi.ac.uk/biostudies/studies/S-EPMC10294458biostudies-literatureUnknown22(1)<h4>Background</h4>Dysregulation of lipid metabolism is closely associated with cancer progression. The study aimed to establish a prognostic model to predict distant metastasis-free survival (DMFS) in patients with nasopharyngeal carcinoma (NPC), based on lipidomics.<h4>Methods</h4>The plasma lipid profiles of 179 patients with locoregionally advanced NPC (LANPC) were measured and quantified using widely targeted quantitative lipidomics. Then, patients were randomly split into the training (125 patients, 69.8%) and validation (54 patients, 30.2%) sets. To identify distant metastasis-associated lipids, univariate Cox regression was applied to the training set (P < 0.05). A deep survival method called DeepSurv was employed to develop a proposed model based on significant lipid species (P < Lipids in health and diseaseWidely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma.PMC102944588187237582172863319004612021A1515010118Zhou JYZhang LLHuang YYKe LRCai ZCGuo XLv XZhan ZJLi XLiang CXCao XHuang HYMei JXie GTChen XQiang MYLi YXDeng YfalseWidely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma.<h4>Background</h4>Dysregulation of lipid metabolism is closely associated with cancer progression. The study aimed to establish a prognostic model to predict distant metastasis-free survival (DMFS) in patients with nasopharyngeal carcinoma (NPC), based on lipidomics.<h4>Methods</h4>The plasma lipid profiles of 179 patients with locoregionally advanced NPC (LANPC) were measured and quantified using widely targeted quantitative lipidomics. Then, patients were randomly split into the training (125 patients, 69.8%) and validation (54 patients, 30.2%) sets. To identify distant metastasis-associated lipids, univariate Cox regression was applied to the training set (P < 0.05). A deep survival method called DeepSurv was employed to develop a proposed model based on significant lipid species (P < 2023-01-01T00:00:00Z2023 Jun2025-04-26T04:49:02Z2025-04-06T11:14:02.108ZS-EPMC102944583736563710.1186/s12944-023-01830-2