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01.04.2015 | Original Article – Clinical Oncology | Ausgabe 4/2015

Journal of Cancer Research and Clinical Oncology 4/2015

Metabolomic profiling of human serum in lung cancer patients using liquid chromatography/hybrid quadrupole time-of-flight mass spectrometry and gas chromatography/mass spectrometry

Zeitschrift:
Journal of Cancer Research and Clinical Oncology > Ausgabe 4/2015
Autoren:
Yingrong Chen, Zhihong Ma, Aiying Li, Hongwei Li, Bin Wang, Jing Zhong, Lishan Min, Licheng Dai

Abstract

Purpose

Lung cancer is one of the most common causes of death from cancer. Serum markers that enable diagnosis of the disease in the early stage have not been found.

Methods

Serum samples were collected from 30 healthy volunteers and from 30 lung cancer patients preoperatively and postoperatively. Samples were subjected to metabolomic analysis using liquid chromatography/hybrid quadrupole time-of-flight mass spectrometry and gas chromatography/mass spectrometry. Differences in metabolomic profiles among the three groups were characterized by multivariate statistical techniques such as principal components analysis and partial least squares discriminant analysis (PLS-DA). An independent t test was used to determine whether levels of biomarker candidates identified using PLS-DA modeling were significantly different among groups at the univariate analysis level (p < 0.05).

Results

Based on pattern recognition results and univariate analysis, we showed that levels of ten potential biomarkers in serum were significantly different in the preoperative lung cancer patients compared with healthy volunteers and/or the postoperative lung cancer patients. The levels of sphingosine, phosphorylcholine, glycerophospho-N-arachidonoyl ethanolamine, γ-linolenic acid, 9,12-octadecadienoic acid, oleic acid, and serine were significantly different in preoperative lung cancer patients compared to healthy volunteers and to postoperative lung cancer patients. For prasterone sulfate, α-hydroxyisobutyric acid, 2,3,4-trihydroxybutyric acid, the levels were statistically different in preoperative and postoperative lung cancer patients compared with the healthy volunteers.

Conclusions

Our study identified potential metabolic biomarkers for diagnosis of lung cancer.

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