Journal
CLINICA CHIMICA ACTA
Volume 400, Issue 1-2, Pages 63-69Publisher
ELSEVIER
DOI: 10.1016/j.cca.2008.10.014
Keywords
Metabolomics; Breast cancer; Ovarian cancer; Cervical cancer; PLS-DA
Categories
Funding
- National RD program
- Korea Ministry of Science and Technology (MOST)
- Korea Research Council of Fundamental Science and Technology (KRCF)
- National Research Foundation of Korea [2004-2002160, 2004-2002145] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Ask authors/readers for more resources
Background: The metabolomic approaches for mining biomarkers of women's cancers based on gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry combined with partial least squares-discriminant analysis are described. Methods: To identify urinary potential biomarkers, the qualitative and quantitative analyses were introduced with 10 breast, 9 ovarian and 12 cervical cancer patients as well as 22 normal controls, which were considered with their ages and menopausal state. Results: For comprehensive metabolomic approaches, the non-targeted qualitative profiling was first achieved to get metabolic patterns of collected samples and the targeted quantitative analysis focused on hormonal metabolism was also conducted. Two known biomarkers, i.e., 5-hydroxymethyl-2-deoxyuridine and 8-hydroxy-2-deoxyguanosine, in breast cancer were also confirmed using the present methods. In addition, 3 potential biomarkers for ovarian cancer i.e. 1-methyladenosine, 3-methyluridine, and 4-androstene-3,17-dione, which were categorized in significantly increased level using one way of variance analysis (p<0.05), were identified as quantitatively targeted metabolites with pattern analysis. The cancer markers identified in this study are highly related to metabolites which are responsible for oxidative DNA damage and DNA methylation process. Conclusion: The present metabolomic approaches are not only useful for diagnostic tools and patient stratification, but may be mapped on metabolic network to reflect disease states. (C) 2008 Published by Elsevier B.V.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available