NDLI: Serum proton NMR metabolomics analysis of human lung cancer following microwave ablation

Content Provider	Springer Nature : BioMed Central
Author	Hu, Jian-Ming Sun, Huang-Tao
Abstract	Background To find potential serum biomarkers of microwave ablation (MWA) for treatment of human lung cancer by 1H nuclear magnetic resonance (NMR)-based metabolomics analysis. Methods Serum specimens collected from 43 healthy individuals, 39 patients with advanced non-small cell lung cancer (NSCLC) and 38 NSCLC patients treated with MWA, were subjected to 1H NMR-based metabolomics analysis. Partial least squares discriminant analysis was used to analyze the data. Results Compared with healthy controls, NSCLC patients showed significantly elevated serum levels of lactate, alanine, glutamate, proline, glycoprotein, phenylalanine, tyrosine and tryptophan, and markedly decreased serum levels of glucose, taurine, glutamine, glycine, phosphocreatine and threonine (p < 0.05). MWA treatment reversed the metabolic profiles of NSCLC patients towards the control group. Conclusions 1H NMR-based metabolomics analysis enhanced the current understanding of the mechanisms involved in NSCLC, and uncovered the therapeutic potential of MWA for treatment of NSCLC. The above disturbed serum metabolites were proposed to be the potential biomarkers that may help to predict NSCLC and to evaluate the efficacy of MWA in the treatment of NSCLC.
Related Links	https://ro-journal.biomedcentral.com/counter/pdf/10.1186/s13014-018-0982-5.pdf
Ending Page	10
Page Count	10
Starting Page	1
File Format	HTM / HTML
DOI	10.1186/s13014-018-0982-5
Journal	Radiation Oncology
Issue Number	1
Volume Number	13
Language	English
Publisher	BioMed Central
Publisher Date	2018-03-12
Access Restriction	Open
Subject Keyword	Cancer Research Oncology Radiotherapy Imaging Radiology Non-small cell lung cancer Microwave ablation Nuclear magnetic resonance Metabolomics PLS-DA
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Oncology
Journal Impact Factor	3.3/2023
5-Year Journal Impact Factor	3.6/2023

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