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Plasma lipidomics profiling in predicting the chemo-immunotherapy response in advanced non-small cell lung cancer

Authors :
Hui Jiang
Xu-Shuo Li
Ying Yang
Rui-Xue Qi
Source :
Frontiers in Oncology, Vol 14 (2024)
Publication Year :
2024
Publisher :
Frontiers Media S.A., 2024.

Abstract

BackgroundAdvanced non-small cell lung cancer (NSCLC) presents significant treatment challenges, with chemo-immunotherapy emerging as a promising approach. This study explores the potential of lipidomic biomarkers to predict responses to chemo-immunotherapy in advanced non-small cell lung cancer (NSCLC) patients.MethodsA prospective analysis was conducted on 68 NSCLC patients undergoing chemo-immunotherapy, divided into disease control (DC) and progressive disease (PD) groups based on treatment response. Pre-treatment serum samples were subjected to lipidomic profiling using liquid chromatography-mass spectrometry (LC-MS). Key predictive lipids (biomarkers) were identified through projection to latent structures discriminant analysis. A biomarker combined model and a clinical combined model were developed to enhance the prediction accuracy. The predictive performances of the clinical combined model in different histological subtypes were also performed.ResultsSix lipids were identified as the key lipids. The expression levels of PC(16:0/18:2), PC(16:0/18:1), PC(16:0/18:0), CE(20:1), and PC(14:0/18:1) were significantly up-regulated. While the expression level of TAG56:7-FA18:2 was significantly down-regulated. The biomarker combined model demonstrated a receiver operating characteristic (ROC) curve of 0.85 (95% CI: 0.75–0.95) in differentiating the PD from the DC. The clinical combined model exhibited an AUC of 0.87 (95% CI: 0.79–0.96) in differentiating the PD from the DC. The clinical combined model demonstrated good discriminability in DC and PD patients in different histological subtypes with the AUC of 0.78 (95% CI: 0.62–0.96), 0.79 (95% CI: 0.64–0.94), and 0.86 (95% CI: 0.52–1.00) in squamous cell carcinoma, large cell carcinoma, and adenocarcinoma subtype, respectively. Pathway analysis revealed the metabolisms of linoleic acid, alpha-linolenic acid, glycerolipid, arachidonic acid, glycerophospholipid, and steroid were implicated in the chemo-immunotherapy response in advanced NSCLC.ConclusionLipidomic profiling presents a highly accurate method for predicting responses to chemo-immunotherapy in patients with advanced NSCLC, offering a potential avenue for personalized treatment strategies.

Details

Language :
English
ISSN :
2234943X
Volume :
14
Database :
Directory of Open Access Journals
Journal :
Frontiers in Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.63015a9ac674cf5b026aaae3e76e281
Document Type :
article
Full Text :
https://doi.org/10.3389/fonc.2024.1348164