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Plasma lipidomics profiling in predicting the chemo-immunotherapy response in advanced non-small cell lung cancer.
Jiang, Hui; Li, Xu-Shuo; Yang, Ying; Qi, Rui-Xue.
Afiliación
  • Jiang H; Department of Ultrasound, Jinshan Hospital, Fudan University, Shanghai, China.
  • Li XS; Department of Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, China.
  • Yang Y; Department of Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, China.
  • Qi RX; Department of Center for Tumor Diagnosis & Therapy, Jinshan Hospital, Fudan University, Shanghai, China.
Front Oncol ; 14: 1348164, 2024.
Article en En | MEDLINE | ID: mdl-39040440
ABSTRACT

Background:

Advanced 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.

Methods:

A 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.

Results:

Six lipids were identified as the key lipids. The expression levels of PC(160/182), PC(160/181), PC(160/180), CE(201), and PC(140/181) were significantly up-regulated. While the expression level of TAG567-FA182 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.

Conclusion:

Lipidomic 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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Oncol Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Oncol Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza