Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma
© 2023. The Author(s)..
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.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:22 |
|---|---|
| Enthalten in: |
Lipids in health and disease - 22(2023), 1 vom: 26. Juni, Seite 81 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Chen, Xi [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Immune and metabolic dysregulation |
|---|
| Anmerkungen: |
Date Completed 28.06.2023 Date Revised 01.07.2023 published: Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1186/s12944-023-01830-2 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM35866991X |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM35866991X | ||
| 003 | DE-627 | ||
| 005 | 20231226075234.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1186/s12944-023-01830-2 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1195.xml |
| 035 | |a (DE-627)NLM35866991X | ||
| 035 | |a (NLM)37365637 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Chen, Xi |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 28.06.2023 | ||
| 500 | |a Date Revised 01.07.2023 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2023. The Author(s). | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Immune and metabolic dysregulation | |
| 650 | 4 | |a Lipid biomarkers | |
| 650 | 4 | |a Lipidomics | |
| 650 | 4 | |a Nasopharyngeal carcinoma | |
| 650 | 4 | |a Survival model | |
| 650 | 7 | |a Lipids |2 NLM | |
| 700 | 1 | |a Li, Ying-Xue |e verfasserin |4 aut | |
| 700 | 1 | |a Cao, Xun |e verfasserin |4 aut | |
| 700 | 1 | |a Qiang, Meng-Yun |e verfasserin |4 aut | |
| 700 | 1 | |a Liang, Chi-Xiong |e verfasserin |4 aut | |
| 700 | 1 | |a Ke, Liang-Ru |e verfasserin |4 aut | |
| 700 | 1 | |a Cai, Zhuo-Chen |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Ying-Ying |e verfasserin |4 aut | |
| 700 | 1 | |a Zhan, Ze-Jiang |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Jia-Yu |e verfasserin |4 aut | |
| 700 | 1 | |a Deng, Ying |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Lu-Lu |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Hao-Yang |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Xiang |e verfasserin |4 aut | |
| 700 | 1 | |a Mei, Jing |e verfasserin |4 aut | |
| 700 | 1 | |a Xie, Guo-Tong |e verfasserin |4 aut | |
| 700 | 1 | |a Guo, Xiang |e verfasserin |4 aut | |
| 700 | 1 | |a Lv, Xing |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Lipids in health and disease |d 2002 |g 22(2023), 1 vom: 26. Juni, Seite 81 |w (DE-627)NLM123930782 |x 1476-511X |7 nnns |
| 773 | 1 | 8 | |g volume:22 |g year:2023 |g number:1 |g day:26 |g month:06 |g pages:81 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1186/s12944-023-01830-2 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 22 |j 2023 |e 1 |b 26 |c 06 |h 81 | ||