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.
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 cancerpatients 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.
Authors: Franca Podo; Lutgarde M C Buydens; Hadassa Degani; Riet Hilhorst; Edda Klipp; Ingrid S Gribbestad; Sabine Van Huffel; Hanneke W M van Laarhoven; Jan Luts; Daniel Monleon; Geert J Postma; Nicole Schneiderhan-Marra; Filippo Santoro; Hans Wouters; Hege G Russnes; Therese Sørlie; Elda Tagliabue; Anne-Lise Børresen-Dale Journal: Mol Oncol Date: 2010-04-24 Impact factor: 6.603
Authors: David B Liesenfeld; Nina Habermann; Robert W Owen; Augustin Scalbert; Cornelia M Ulrich Journal: Cancer Epidemiol Biomarkers Prev Date: 2013-10-04 Impact factor: 4.254
Authors: Gunjal Garg; Ali Yilmaz; Praveen Kumar; Onur Turkoglu; David G Mutch; Matthew A Powell; Barry Rosen; Ray O Bahado-Singh; Stewart F Graham Journal: Metabolomics Date: 2018-11-24 Impact factor: 4.290
Authors: Habtom W Ressom; Jun Feng Xiao; Leepika Tuli; Rency S Varghese; Bin Zhou; Tsung-Heng Tsai; Mohammad R Nezami Ranjbar; Yi Zhao; Jinlian Wang; Cristina Di Poto; Amrita K Cheema; Mahlet G Tadesse; Radoslav Goldman; Kirti Shetty Journal: Anal Chim Acta Date: 2012-07-20 Impact factor: 6.558