Abstract

Influence of widely targeted quantitative lipidomics on plasma lipid predictors and pathway dysregulation for nasopharyngeal carcinoma.

Author
person Xi Chen Sun Yat-sen University Cancer Center, Guangzhou, China info_outline Xi Chen, Xiang Guo, Xing Lv
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Authors person Xi Chen Sun Yat-sen University Cancer Center, Guangzhou, China info_outline Xi Chen, Xiang Guo, Xing Lv Organizations Sun Yat-sen University Cancer Center, Guangzhou, China Abstract Disclosures Research Funding Other Foundation The National Natural Science Foundation of China; the Natural Science Foundation of Guangdong Province, China Background: Dysregulation of lipid metabolism is closely associated with cancer progression. We aimed to establish a prognostic model to predict distant metastasis-free survival (DMFS) in patients with locoregionally advanced nasopharyngeal carcinoma (NPC), based on widely targeted quantitative lipidomics. Methods: We measured and quantified the plasma lipid profiles of 179 patients with NPC 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). We employed a deep survival method called DeepSurv to develop our proposed model based on significant lipid species ( p < 0.01) and clinical biomarkers to predict DMFS. Concordance index and receiver operating curve analyses were performed to assess model effectiveness. We also explored the potential role of lipid alterations in the prognosis of NPC. Results: A total of 665 plasma endogenous lipid species consisting of 27 lipid classes and subclasses from 179 patients with NPC were annotated in lipidomics analysis. Forty lipids were recognized as distant metastasis-associated ( p < 0.05) by univariate Cox regression. The concordance indices of our proposed model were 0.764 (95% confidence interval (CI), 0.682–0.846) and 0.760 (95% CI, 0.649–0.871) in the training and validation sets, respectively. We also calculated the C-index values of the baseline survival model based only on clinical biomarkers, with 0.718 (95% CI, 0.591–0.845) and 0.672 (95% CI, 0.511–0.833) being detected in the training and validation sets, respectively, indicating the outstanding predictive performance of lipid biomarkers. High-risk patients had poorer 5-year DMFS compared with low-risk patients (Hazard ratio, 26.18; 95% CI, 3.52–194.80; p < 0.0001). Moreover, the six lipids were significantly correlated with immunity- and inflammation-associated biomarkers and were mainly enriched in metabolic pathways. Conclusions: Widely targeted quantitative lipidomics reveals plasma lipid predictors and pathway dysregulation for locoregionally advanced NPC, the prognostic model based on that demonstrated superior performance in predicting metastasis in NPC patients.

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