Τίτλος:
1H NMR metabonomic analysis in renal cell carcinoma: A possible diagnostic tool
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
1H NMR based metabonomic approach was applied in order to monitor the alterations of plasma metabolic profile in Renal Cell Carcinoma (RCC) patients and controls. 1H NMR spectra of plasma samples from 32 RCC patients and 13 controls (patients exhibiting benign urologic disease) were recorded and analyzed using multivariate statistical techniques. Alterations in the levels of LDL/VLDL, NAC, lactate, and choline were observed between RCC patients and controls discriminating these groups in Principal Component Analysis (PCA) plots. Post OSC PLS-DA presented a satisfactory clustering between T1 with T3 RCC patients. Decrease in plasma lipid concentrations in RCC patients was verified using conventional clinical chemistry analysis. The results suggest that combination of 1H NMR spectroscopy with PCA has potential in cancer diagnosis; however, a limitation of the method to monitor RCC is that major biomarkers revealed (lipoproteins and choline) in this metabolic profile are not unique to RCC but may be the result of the presence of any malignancy. © 2010 American Chemical Society.
Συγγραφείς:
Zira, A.N.
Theocharis, S.E.
Mitropoulos, D.
Migdalis, V.
Mikros, E.
Περιοδικό:
Journal of Proteome Research
Λέξεις-κλειδιά:
acetic acid; acetoacetic acid; alanine; cholesterol; choline; glucose; glycoprotein; lactic acid; low density lipoprotein cholesterol; pyruvic acid; triacylglycerol; very low density lipoprotein cholesterol, adult; aged; article; cancer diagnosis; cancer patient; cholesterol blood level; clinical article; controlled study; glucose blood level; human; kidney carcinoma; lactate blood level; lipid blood level; lipoprotein blood level; multivariate analysis; principal component analysis; priority journal; protein blood level; proton nuclear magnetic resonance; triacylglycerol blood level, Aged; Blood Chemical Analysis; Carcinoma, Renal Cell; Case-Control Studies; Humans; Kidney Neoplasms; Metabolomics; Middle Aged; Nuclear Magnetic Resonance, Biomolecular; Principal Component Analysis
