4.7 Article

Liquid Chromatography-Mass Spectrometry-Based Tissue Metabolic Profiling Reveals Major Metabolic Pathway Alterations and Potential Biomarkers of Lung Cancer

期刊

JOURNAL OF PROTEOME RESEARCH
卷 19, 期 9, 页码 3750-3760

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.0c00285

关键词

non-small-cell lung cancer; metabolomics; metabolic reprogramming; biomarkers

资金

  1. key foundation of Dalian City [2019J11CY018]
  2. National Natural Science Foundation of China [21934006, 21705147, 81700274, 21130001]
  3. DICP, CAS [DICP ZZBS201804]

向作者/读者索取更多资源

Unclarified molecular mechanism and lack of practical diagnosis biomarkers hinder the effective treatment of non-small-cell lung cancer. Herein, we performed liquid chromatography-mass spectrometry-based nontargeted metabolomics analysis in 131 patients with their lung tissue pairs to study the metabolic characteristics and disordered metabolic pathways in lung tumor. A total of 339 metabolites were identified in metabolic profiling. Also, 241 differential metabolites were found between lung carcinoma tissues (LCTs) and paired distal noncancerous tissues; amino acids, purine metabolites, fatty acids, phospholipids, and most of lysophospholipids significantly increased in LCTs, while 3-phosphoglyceric acid, phosphoenolpyruvate, 6-phosphogluconate, and citrate decreased. Additionally, pathway enrichment analysis revealed that energy, purine, amino acid, lipid, and glutathione metabolism are markedly disturbed in lung cancer (LCa). Using binary logistic regression, we further defined candidate biomarkers for different subtypes of lung tumor. Xanthine and PC 35:2 were selected as combinational biomarkers for distinguishing benign from malignant lung tumors with a 0.886 area under curve (AUC) value, and creatine, myoinositol and LPE 16:0 were defined as combinational biomarkers for discriminating adenocarcinoma from squamous cell lung carcinoma with a 0.934 AUC value. Overall, metabolic characterization and pathway disturbance demonstrated apparent metabolic reprogramming in LCa. The defined candidate metabolite marker panels are useful for subtyping of lung tumors to assist clinical diagnosis.

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