Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma
Abstract Background 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. Methods The plasma lipid profi...
| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-06-01
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| Series: | Lipids in Health and Disease |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12944-023-01830-2 |
| _version_ | 1797789603857432576 |
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| author | Xi Chen Ying-xue Li Xun Cao Meng-yun Qiang Chi-xiong Liang Liang-ru Ke Zhuo-chen Cai Ying-ying Huang Ze-jiang Zhan Jia-yu Zhou Ying Deng Lu-lu Zhang Hao-yang Huang Xiang Li Jing Mei Guo-tong Xie Xiang Guo Xing Lv |
| author_facet | Xi Chen Ying-xue Li Xun Cao Meng-yun Qiang Chi-xiong Liang Liang-ru Ke Zhuo-chen Cai Ying-ying Huang Ze-jiang Zhan Jia-yu Zhou Ying Deng Lu-lu Zhang Hao-yang Huang Xiang Li Jing Mei Guo-tong Xie Xiang Guo Xing Lv |
| author_sort | Xi Chen |
| collection | DOAJ |
| description | Abstract Background 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. Methods 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 < 0.01) and clinical biomarkers to predict DMFS. Concordance index and receiver operating curve analyses were performed to assess model effectiveness. The study also explored the potential role of lipid alterations in the prognosis of NPC. Results Forty lipids were recognized as distant metastasis-associated (P < 0.05) by univariate Cox regression. The concordance indices of the 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. 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 for LANPC, the prognostic model based on that demonstrated superior performance in predicting metastasis in LANPC patients. |
| first_indexed | 2024-03-13T01:53:02Z |
| format | Article |
| id | doaj.art-ee63bbf351264abb9cff062a2210848b |
| institution | Directory Open Access Journal |
| issn | 1476-511X |
| language | English |
| last_indexed | 2024-03-13T01:53:02Z |
| publishDate | 2023-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Lipids in Health and Disease |
| spelling | doaj.art-ee63bbf351264abb9cff062a2210848b2023-07-02T11:25:45ZengBMCLipids in Health and Disease1476-511X2023-06-0122111310.1186/s12944-023-01830-2Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinomaXi Chen0Ying-xue Li1Xun Cao2Meng-yun Qiang3Chi-xiong Liang4Liang-ru Ke5Zhuo-chen Cai6Ying-ying Huang7Ze-jiang Zhan8Jia-yu Zhou9Ying Deng10Lu-lu Zhang11Hao-yang Huang12Xiang Li13Jing Mei14Guo-tong Xie15Xiang Guo16Xing Lv17State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterPing An TechnologyState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterDepartment of Head and Neck Radiotherapy, the Cancer Hospitalof the, University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer, Chinese Academy of Sciences State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterPing An TechnologyPing An TechnologyPing An TechnologyState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterAbstract Background 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. Methods 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 < 0.01) and clinical biomarkers to predict DMFS. Concordance index and receiver operating curve analyses were performed to assess model effectiveness. The study also explored the potential role of lipid alterations in the prognosis of NPC. Results Forty lipids were recognized as distant metastasis-associated (P < 0.05) by univariate Cox regression. The concordance indices of the 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. 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 for LANPC, the prognostic model based on that demonstrated superior performance in predicting metastasis in LANPC patients.https://doi.org/10.1186/s12944-023-01830-2LipidomicsSurvival modelLipid biomarkersImmune and metabolic dysregulationNasopharyngeal carcinoma |
| spellingShingle | Xi Chen Ying-xue Li Xun Cao Meng-yun Qiang Chi-xiong Liang Liang-ru Ke Zhuo-chen Cai Ying-ying Huang Ze-jiang Zhan Jia-yu Zhou Ying Deng Lu-lu Zhang Hao-yang Huang Xiang Li Jing Mei Guo-tong Xie Xiang Guo Xing Lv Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma Lipids in Health and Disease Lipidomics Survival model Lipid biomarkers Immune and metabolic dysregulation Nasopharyngeal carcinoma |
| title | Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma |
| title_full | Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma |
| title_fullStr | Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma |
| title_full_unstemmed | Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma |
| title_short | Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma |
| title_sort | widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma |
| topic | Lipidomics Survival model Lipid biomarkers Immune and metabolic dysregulation Nasopharyngeal carcinoma |
| url | https://doi.org/10.1186/s12944-023-01830-2 |
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