TY - JOUR
T1 - Metabolomics provide new insights on lung cancer staging and discrimination from chronic obstructive pulmonary disease
AU - Deja, Stanislaw
AU - Porebska, Irena
AU - Kowal, Aneta
AU - Zabek, Adam
AU - Barg, Wojciech
AU - Pawelczyk, Konrad
AU - Stanimirova, Ivana
AU - Daszykowski, Michal
AU - Korzeniewska, Anna
AU - Jankowska, Renata
AU - Mlynarz, Piotr
N1 - Funding Information:
This study was supported by National Science Centre Poland (grant no. N N 402515939 ). Stanislaw Deja was a recipient of PhD scholarship under a project funded by the European Social Fund.
Publisher Copyright:
© 2014 Elsevier B.V.
PY - 2014
Y1 - 2014
N2 - Chronic obstructive pulmonary disease (COPD) and lung cancer are widespread lung diseases. Cigarette smoking is a high risk factor for both the diseases. COPD may increase the risk of developing lung cancer. Thus, it is crucial to be able to distinguish between these two pathological states, especially considering the early stages of lung cancer. Novel diagnostic and monitoring tools are required to properly determine lung cancer progression because this information directly impacts the type of the treatment prescribed. In this study, serum samples collected from 22 COPD and 77 lung cancer (TNM stages I, II, III, and IV) patients were analyzed. Then, a collection of NMR metabolic fingerprints was modeled using discriminant orthogonal partial least squares regression (OPLS-DA) and further interpreted by univariate statistics. The constructed discriminant models helped to successfully distinguish between the metabolic fingerprints of COPD and lung cancer patients (AUC training=0.972, AUC test=0.993), COPD and early lung cancer patients (AUC training=1.000, AUC test=1.000), and COPD and advanced lung cancer patients (AUC training=0.983, AUC test=1.000). Decreased acetate, citrate, and methanol levels together with the increased N-acetylated glycoproteins, leucine, lysine, mannose, choline, and lipid (CH3(CH2)n) levels were observed in all lung cancer patients compared with the COPD group. The evaluation of lung cancer progression was also successful using OPLS-DA (AUC training=0.811, AUC test=0.904). Based on the results, the following metabolite biomarkers may prove useful in distinguishing lung cancer states: isoleucine, acetoacetate, and creatine as well as the two NMR signals of N-acetylated glycoproteins and glycerol.
AB - Chronic obstructive pulmonary disease (COPD) and lung cancer are widespread lung diseases. Cigarette smoking is a high risk factor for both the diseases. COPD may increase the risk of developing lung cancer. Thus, it is crucial to be able to distinguish between these two pathological states, especially considering the early stages of lung cancer. Novel diagnostic and monitoring tools are required to properly determine lung cancer progression because this information directly impacts the type of the treatment prescribed. In this study, serum samples collected from 22 COPD and 77 lung cancer (TNM stages I, II, III, and IV) patients were analyzed. Then, a collection of NMR metabolic fingerprints was modeled using discriminant orthogonal partial least squares regression (OPLS-DA) and further interpreted by univariate statistics. The constructed discriminant models helped to successfully distinguish between the metabolic fingerprints of COPD and lung cancer patients (AUC training=0.972, AUC test=0.993), COPD and early lung cancer patients (AUC training=1.000, AUC test=1.000), and COPD and advanced lung cancer patients (AUC training=0.983, AUC test=1.000). Decreased acetate, citrate, and methanol levels together with the increased N-acetylated glycoproteins, leucine, lysine, mannose, choline, and lipid (CH3(CH2)n) levels were observed in all lung cancer patients compared with the COPD group. The evaluation of lung cancer progression was also successful using OPLS-DA (AUC training=0.811, AUC test=0.904). Based on the results, the following metabolite biomarkers may prove useful in distinguishing lung cancer states: isoleucine, acetoacetate, and creatine as well as the two NMR signals of N-acetylated glycoproteins and glycerol.
KW - COPD-chronic obstructive pulmonary disease
KW - H NMR spectroscopy
KW - Lung cancer
KW - Metabolic fingerprinting
KW - Metabolomics
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U2 - 10.1016/j.jpba.2014.08.020
DO - 10.1016/j.jpba.2014.08.020
M3 - Article
C2 - 25213261
AN - SCOPUS:84908566336
SN - 0731-7085
VL - 100
SP - 369
EP - 380
JO - Journal of Pharmaceutical and Biomedical Analysis
JF - Journal of Pharmaceutical and Biomedical Analysis
ER -